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Brewer, Tom David (2013) Social determinants of the
exploitation and management of coral reef resources in
Solomon Islands. PhD thesis, James Cook University.
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SOCIAL DETERMINANTS OF THE EXPLOITATION AND
MANAGEMENT OF CORAL REEF RESOURCES IN
SOLOMON ISLANDS
Thesis submitted by
Tom David Brewer
B.Sc. (Hons) University of Queensland
in 2013
for the degree of Doctor of Philosophy
at the Australian Research Council Centre of Excellence for Coral Reef Studies
James Cook University
ii
STATEMENT OF ACCESS
I, the undersigned author of this work, understand that James Cook University will
make this thesis available for use within the University Library, via the Australian
Theses Network, or by other means allow access to users in other approved libraries.
I understand that as an unpublished work, a thesis has significant protection under the
Copyright Act but beyond this protection, I do not wish to place any access restrictions
to this thesis.
16th January, 2013
Tom David Brewer
Date of submission
iii
iv
STATEMENT OF SOURCES DECLARATION
I declare that this thesis is my own work and has not been submitted in any form for
another degree or diploma at any university or other institution of tertiary education.
Information derived from the published or unpublished work of others has been duly
acknowledged in the text and a list of references is given.
______________________
16th January, 2013
Tom David Brewer
Date of submission
v
vi
STATEMENT OF CONTRIBUTION OF OTHERS
Research funding:
Australian Research Council Centre of Excellence for Coral Reef Studies
Stipend:
Australian Postgraduate Award
Supervisory Committee:
Principle supervisor:
Assoc. Prof. Joshua Cinner, ARC Centre of Excellence for Coral Reef Studies, James
Cook University
Associate supervisors:
Distinguished Prof. Bob Pressey, ARC Centre of Excellence for Coral Reef Studies,
James Cook University
Distinguished Prof. Terry Hughes, ARC Centre of Excellence for Coral Reef Studies,
James Cook University
Dr Simon Foale, ARC Centre of Excellence for Coral Reef Studies, James Cook
University.
Survey design and data collection:
Assoc. Prof. Joshua Cinner assisted with survey design (chapter 4)
Dr Simon Foale assisted with survey design (chapter 4)
Freda Paiva assisted with survey translation (chapter 4)
Joe Gynegele assisted with the field surveys (chapter 4)
Statistical and analytical support:
Assoc. Prof. Joshua Cinner (whole thesis)
Dr Johnathan Kool (chapter 3)
Dr M. Aaron MacNeil (chapter 2A)
Dr Nick Graham (chapter 2B)
vii
Dr Rebecca Fisher (chapter 2B)
Editorial assistance:
Assoc. Prof. Joshua Cinner (whole thesis)
Distinguished Prof. Bob Pressey (chapter 2A, Introduction, Discussion)
Distinguished Prof. Terry Hughes (chapters 2A, 2B)
Dr Simon Foale (chapters 3, 4)
Dr Katie Moon (whole thesis)
Christina Hicks (chapters 2A, 2B)
Dr Alison Green (chapters 2A, 2B)
Dr Shaun Wilson (chapter 2B)
Dr Rebecca Fisher (chapter 2B)
Permits
Field work for this thesis complies with the current laws of Australia, and permits
necessary for the project were obtained from James Cook University Human Ethics
under ethics code H3596.
Preferred citation:
Brewer, T.D. 2013. Social determinants of the exploitation and management of coral
reef resources in Solomon Islands. Ph.D. thesis.
viii
For Molly,
my future.
ix
x
ACKNOWLEDGEMENTS
First and foremost, thank you to my supervisors. This thesis began as a literature
review of a problem that was too expansive for me to articulate; identifying traits of
human societies that explain variation in the state of natural resources. My supervisors
provided me with support, some tough love, and backed my capacity to engage with the
challenge. For this, I thank them all. In particular, Josh, for his patience, sharing of
similar experience, giving me many opportunities, supporting my work, and keeping me
focused on the core tasks. Thank you to Terry, for his sage advice, lessons in critical
thinking and education on the workings of the scientific institution. Thank you to Bob,
for his relaxed nature, willingness to let me explore, open-mindedness, and inspiring
dedication to the conservation of biodiversity. Thank you to Simon, for his honest
appraisal of my work and the work of others, and for long discussions on scientific
debate of the functioning of human societies and their interaction with the natural
world.
Second, thank you to the academic staff and students at the Australian Research Council
Centre of Excellence for Coral Reef Studies for; the many friendships, the many
esoteric discussions on the future state of the planet and for the sometimes fierce
debates on all things social and ecological. Particular gratitude to my friends who most
changed the way I interpret the world; Toby Elmhirst, Johnathan Kool, Piero Visconti,
Duan Biggs, Christina Graham, Sylvain Foret.
Third, thank you to the support staff at the Australian Research Council Centre of
Excellence for Coral Reef Studies; David Yellowlees, Jenny Lappin, Olga Bazaka,
Janet Swanson, Rose-Marie Vasiljuk and Louise Lennon for your friendship, endless
patience with my often-convoluted paperwork and your realism.
Fourth, thank you to Chris Fulton of Australian National University for hosting me as a
visiting fellow, and to Deborah Blackman of University of Canberra for providing me
with desk space for the writing phase of the thesis.
xi
Fifth, thank you to the people and government of, and my friends in, Solomon Islands,
for being so welcoming, for supporting me in my research, and for teaching me so
much.
Sixth, thank you to those that shared their data with me to ensure the aims of this thesis
could be realised. Particularly, thank you to Nick Gagahe of the Solomon Islands
statistics office for providing me with the necessary social data, and thank you to The
Nature Conservancy for allowing me access to your exceptional ecological database.
Seventh, thank you to my family: Jeannie, David, Sam and Farley, for unquestioning
support of my passion, for enduring my often nonsensical rants about my research, and
for putting on a brave face when I ask you to read my papers. Particular thanks to Mum
and Dad for teaching me to pursue what I believe in, and Mum for caring for Molly
whilst I wrote.
Last, thank you to Katie, my love. Over the course of writing this thesis she has taught
me so much about the English language; about brevity, clarity, and argument
construction. She has given me unwavering support and without her this thesis might
never have seen the light of day.
I acknowledge openly, that from the outset of this thesis I have had an agenda beyond
knowledge for knowledge sake. That agenda was, and remains, to better understand the
interaction between people and natural resources for improved human welfare. I do not,
however, believe that this agenda generated a priori bias within the thesis, but rather
enhanced the accuracy of the content.
xii
ABSTRACT
Globally, natural resources are declining due primarily to unsustainable human
consumption. Resource scarcity and associated problems therefore arise fundamentally
from social processes. This thesis compares and contrasts the relative merit of the three
dominant environmental sociology perspectives for their respective ability to explain
the effect of human societies on natural resources. First is the perspective of population
pressure driving resource scarcity; a perspective commonly known, and referred to
herein, as ‘Malthusian overpopulation’. Second is the perspective of free market
capitalism and associated market expansion driving resource scarcity; a perspective
commonly cited as the ‘treadmill of production’ in environmental sociology (herein
referred to as ‘market expansion’). Third is the perspective of modernization driving
resource scarcity at low levels of modernization and resource abundance at high levels
of modernization; a perspective commonly known as ‘ecological modernization’ in
environmental sociology and the ‘environmental Kuznets curve’ in ecological
economics (herein referred to as ‘modernization’). Each perspective is supported by
many scholars, and has a significant literature to substantiate the respective claims of
the key social processes that cause change in the state of natural resource. Critical
comparison of the three perspectives will likely offer greater insight into interactions
between societies and natural resources than examining one perspective alone, and may
therefore offer more appropriate solutions to the challenges posed by resource scarcity.
There are gaps in our understanding of society’s effects on natural resources that are
apparent from a review of comparative studies on the three dominant perspectives.
First, most studies that compare and contrast the relative merit of the three perspectives
correlate proxy variables for each of the perspectives [e.g. human population density
(for ‘Malthusian overpopulation’), and Gross Domestic Product (for ‘market
expansion’)] with environmental indicators (e.g. fishery biomass) without explicitly
considering mechanisms such as resource exploitation intensity or resource
management institution efficacy. Second, few of the comparative analyses that have
been undertaken to date, explicitly compare and contrast the three perspectives at the
local-level. Most studies have instead focused on the national-level. Yet interactions
xiii
between societies and resources vary significantly across social-political levels, and one
could argue that most decisions to exploit and manage resources do occur at the locallevel, particularly in less affluent societies where there is comparatively limited
centralised management and vast reserves of natural resources. Third, there is
inadequate attention paid to the developing country context. Most studies that compare
the perspectives are either global or focused on affluent nations. Few studies have
focused analyses on poorer, economically peripheral nations where much of the world’s
biodiversity and other natural resources exist. This is critical for two reasons; first,
affluent and poor societies represent very different social contexts so conclusions drawn
from global or affluent-nation analyses are unlikely to be transferrable to developing
countries; second world systems theory suggests that affluent societies import resources
and export pollutants to poorer societies and vice-versa, and therefore opportunities to
modernize as per the modernization perspective might be difficult to realize. Fourth, no
comparative analyses of the perspectives have included research on local perceptions of
society’s effects on natural resources. Understanding local perceptions, however, is
useful to confirm (or refute) hypothesis-driven research and potentially useful to
increase the likelihood of implementation of research recommendations in applied
research.
The aim of this thesis is to fill these research gaps by 1) explaining society’s effects on
natural resources, at the local-level in an economically peripheral nation, using
dominant environmental sociology perspectives (research gaps 1-3), and to 2) determine
whether local perceptions, support or refute the scientific explanation (research gap 4).
These broad aims are achieved by completing the following research objectives:
1. Determine which dominant environmental sociology perspectives, of
societies effects on natural resources, best explains the effects of exploitation
on;
a) Coral reef fish that are vulnerable to extinction by overfishing;
b) Function and diversity of coral reef fish;
2. Determine which of the perspectives explain the occurrence of coral reef
resource management institutions; and
xiv
3. Determine whether local perceptions support, or refute, the findings, as
identified in objectives 1 and 2, of society’s effects on the exploitation and
management of coral reef fish.
To achieve research objective 1, I collected secondary social (census) and ecological
(survey) data from 25 local-level sites spanning Solomon Islands. I then analysed the
data using structural equation models to explain how proxy variables, which represent
each of the dominant perspectives, affect fishing pressure to, in turn, affect the
distributions of a) biomass of coral reef fish that are vulnerable to overfishing and b)
coral reef fish functional group biomass and diversity. The key aspects of fish
distributions I examined were explained by fishing pressure. Specifically, there was
lower biomass of coral reef fish that are vulnerable to overfishing, lower biomass of key
functional groups of fishes, and lower fish species diversity where there was higher
fishing pressure. The key finding, which addresses research objective 1 is that fishing
pressure was, in turn, driven by high human population density and greater access to
markets; proxy variables for the Malthusian overpopulation and market expansion
perspectives, respectively. Modernization had no discernable effect on fishing pressure.
To achieve research objective 2, I collected data for proxy variables of each of the
dominant perspectives and on coral reef resource management institutions (gear
restrictions, species restrictions, and spatial closures) from ≥723 local-level sites
spanning Solomon Islands (I developed some of the survey instrument on management
institutions but the data were collected by the national government and other agencies).
I then tested the effects of each set of proxy variables, which represent each of the
perspectives, on the occurrence of management institutions using a range of statistical
analyses. I found that the presence of management institutions was negatively
correlated with human population density and positively correlated with modernization
and the presence of fish markets, lending support to the Malthusian overpopulation
perspective, and simultaneously detracting from the market expansion perspective. The
results neither clearly supported nor refuted the modernization perspective.
xv
To achieve research objective 3, I conducted interviews, using a survey instrument, with
119 fishers and fish traders in the major urban centres of Solomon Islands to identify
which factors they perceive can increase and decrease coral reef fish stocks. The
qualitative responses were coded, and analysed using Principal Components Analysis to
derive the dominant perceptions. The interviewed fishers and middlemen perceived an
extensive range of factors to be causing fish decline, and also stated a diverse range of
management interventions that they perceived would increase fish stocks. Respondents
identified fishing as a major cause of fish decline driven by income-related needs,
among other factors, which is concordant with the findings of objectives 1 and 2.
In this thesis I compared the three dominant perspectives of society’s effects on natural
resources using a novel model in an economically peripheral nation at the local-level.
In doing so, I found greatest support for both the Malthusian overpopulation and market
expansion perspectives. This finding was concordant with local perceptions, adding
further weight of evidence. Given these findings, it can be expected that, with predicted
population growth and continued resource commoditization and aspirations of
affluence, coral reef resources will likely continue to be depleted in Solomon Islands,
and other locations with comparable context (economically peripheral). Policy
prescriptions that aim to slow this depletion must consider local population pressure and
markets as dominant driving forces.
xvi
TABLE OF CONTENTS
STATEMENT OF ACCESS .......................................................................................................................... III
STATEMENT OF SOURCES DECLARATION .................................................................................................. V
STATEMENT OF CONTRIBUTION OF OTHERS............................................................................................VII
ACKNOWLEDGEMENTS ....................................................................................................................XI
ABSTRACT...........................................................................................................................................XIII
TABLE OF CONTENTS ................................................................................................................... XVII
LIST OF TABLES ................................................................................................................................ XXI
LIST OF FIGURES ...........................................................................................................................XXIII
CHAPTER 1: INTRODUCTION ............................................................................................................. 1
1.1 DECLINING NATURAL RESOURCES...................................................................................................... 1
1.2 SOCIAL CAUSES OF NATURAL RESOURCE DECLINE ............................................................................. 2
1.2.1 Dominant perspectives .............................................................................................................. 3
1.2.2 Synthesis of the dominant perspectives ................................................................................... 16
1.2.3 General conclusion about perspectives from the literature review ......................................... 20
1.3 RESEARCH GAPS ............................................................................................................................... 21
1.4 RESEARCH OBJECTIVES .................................................................................................................... 31
1.5 THESIS OUTLINE .............................................................................................................................. 31
1.6 SUMMARY OF THESIS CHAPTERS: ..................................................................................................... 32
CHAPTER 2: SOCIAL DETERMINANTS OF CORAL REEF RESOURCE DISTRIBUTIONS . 37
CHAPTER 2A: SOCIAL DETERMINANTS OF THE EXPLOITATION OF CORAL REEF
FISHES THAT ARE VULNERABLE TO FISHING .......................................................................... 39
ABSTRACT ............................................................................................................................................. 39
2A.1 INTRODUCTION.............................................................................................................................. 40
2A.1.1 Dominant perspectives .......................................................................................................... 40
2A.2 METHODS ...................................................................................................................................... 43
2A.2.1 Fish Biomass and Vulnerability ............................................................................................ 43
2A.2.2 Social and Economic Data .................................................................................................... 46
2A.2.3 Linking Fish Data to Social and Economic Data ................................................................. 49
2A.2.4 Analysis ................................................................................................................................. 50
2A.3 RESULTS ....................................................................................................................................... 51
2A.3.1 Data Reduction ..................................................................................................................... 51
2A.3.2 Effects of distal drivers on proximate drivers and habitat .................................................... 52
2A.3.3 Distal and proximate drivers of total fish biomass ............................................................... 53
2A.3.4 Distal and proximate drivers of fish biomass in vulnerability categories ............................. 53
2A.4 DISCUSSION .................................................................................................................................. 55
CHAPTER 2B: SOCIAL DETERMINANTS OF THE DIVERSITY AND FUNCTION OF CORAL
REEF FISH ASSEMBLAGES................................................................................................................ 59
ABSTRACT ............................................................................................................................................. 59
2B.1 INTRODUCTION .............................................................................................................................. 60
2B.2 METHODS ...................................................................................................................................... 63
2B.2.1 Site Selection and Delineation .............................................................................................. 63
2B.2.2 Ecological Response Variables ............................................................................................. 64
2B.2.3 Proximate Drivers ................................................................................................................. 65
2B.2.4 Distal Drivers ....................................................................................................................... 65
xvii
2B.2.5 Model Construction ............................................................................................................... 65
2B.3 RESULTS ........................................................................................................................................ 66
2B.3.1 Effects of Proximate Drivers on Fish Function and Diversity .............................................. 66
2B.3.2 Effects of Distal Drivers on Fish Function and Diversity ..................................................... 68
2B.4 DISCUSSION ................................................................................................................................... 68
2B.4.1 Explaining the effects of Proximate Drivers on Fish Function and Diversity....................... 69
2B.4.2 Explaining the effects of distal drivers on fish function and diversity ................................... 70
2B.4.3 Future model extensions ....................................................................................................... 71
2B.5 CONCLUSION ................................................................................................................................. 72
CHAPTER 3: SOCIAL DETERMINANTS OF CORAL REEF RESOURCE MANAGEMENT
INSTITUTION OCCURRENCE ........................................................................................................... 73
ABSTRACT ............................................................................................................................................. 73
3.1 INTRODUCTION ................................................................................................................................. 74
3.2 METHODS ......................................................................................................................................... 76
3.2.1 Data sources and reduction ..................................................................................................... 76
3.2.2 Social and economic drivers .................................................................................................... 77
3.2.3 Resource management institutions .......................................................................................... 78
3.2.4 Analysis ................................................................................................................................... 79
3.3 RESULTS AND DISCUSSION ............................................................................................................... 80
3.4 LIMITATIONS .................................................................................................................................... 86
3.5 CONCLUSIONS .................................................................................................................................. 87
CHAPTER 4: FISHER AND MIDDLEMEN PERCEPTIONS OF CORAL REEF FISH DECLINE
AND INCREASE ..................................................................................................................................... 89
ABSTRACT ............................................................................................................................................. 89
4.1 INTRODUCTION ................................................................................................................................. 91
4.2 METHODS ......................................................................................................................................... 94
4.2.1 Field interviews ....................................................................................................................... 94
4.2.2 Data Analysis........................................................................................................................... 99
4.3 RESULTS......................................................................................................................................... 100
4.3.1 Fish decline ........................................................................................................................... 100
4.3.2 Fish increase ......................................................................................................................... 104
4.3.3 Socio-demographic attributes................................................................................................ 108
4.4 DISCUSSION.................................................................................................................................... 110
4.4.1 Scientific and local explanations of coral reef fish distributions........................................... 110
4.4.2 Dominant discourses ............................................................................................................. 111
4.4.3 Socio-demographic attributes................................................................................................ 113
4.4.4 Limitations ............................................................................................................................. 114
4.5 CONCLUSIONS ................................................................................................................................ 115
CHAPTER 5: GENERAL DISCUSSION AND CONCLUSIONS .................................................... 117
5.1 REVIEW OF THE RESEARCH GAPS ADDRESSED IN THIS THESIS INCLUDING THEORETICAL
CONTRIBUTIONS ................................................................................................................................... 117
5.2 THE BROAD THEORETICAL CONTRIBUTION OF THIS THESIS: A UNIFIED NARRATIVE OF SOCIETY’S
EFFECTS ON CORAL REEF FISHERY RESOURCES IN SOLOMON ISLANDS. ................................................ 124
5.3 LIMITATIONS TO THE THESIS AND CONSEQUENT FUTURE RESEARCH .............................................. 129
5.3.1 The wrong method or missing variables in the general model? ............................................ 130
5.3.2 A missing link in the model .................................................................................................... 131
5.3.3 A modeled system of flows and feedbacks ............................................................................. 133
5.3.4 Linkages among and between levels in the social-political scale .......................................... 135
5.4 GENERAL CONCLUSIONS ................................................................................................................ 139
xviii
REFERENCES ...................................................................................................................................... 145
CHAPTER 6: APPENDICES ............................................................................................................... 173
APPENDIX 1: RESEARCH CONDUCTED, AND SYMPOSIA/CONFERENCES ATTENDED DURING DISSERTATION
PERIOD NOT INCLUDED WITHIN THE THESIS .......................................................................................... 174
Peer-reviewed Publications: ....................................................................................................................... 174
Other Publications (reports, book chapters, other): .................................................................................... 174
Symposia / Conference Presentations / Workshops / Guest lectures .......................................................... 175
APPENDIX 2: FISH SURVEY METHODS AND BIOMASS ESTIMATION ........................................................ 177
Fish survey methods................................................................................................................................... 177
Biomass Calculation .................................................................................................................................. 179
References .................................................................................................................................................. 179
APPENDIX 3: LIST OF FISH INCLUDING VULNERABILITY CATEGORY AND SCORE USED FOR CHAPTER 2A
............................................................................................................................................................ 180
APPENDIX 4: LIST OF FISH INCLUDING FUNCTIONAL GROUPING, AND WHETHER THEY ARE FISHERIES
SPECIES, USED IN CHAPTER 2B ............................................................................................................. 189
APPENDIX 5: X, Y PLOTS OF STANDARDISED A) PROXIMATE DRIVERS AND DIVERSITY AND FUNCTION,
AND B) DISTAL AND PROXIMATE DRIVERS ............................................................................................ 195
APPENDIX 6: SURVEY USED TO ELICIT FISHER AND MIDDLEMEN PERCEPTIONS .................................... 200
xix
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LIST OF TABLES
Table 1.1 Studies that quantitatively test the relative merit of all three dominant
perspectives. .................................................................................................................... 18
Table 1.2 Dominant perspective attributes of Countries and Territories in the Asia
Pacific region, including coral triangle initiative member countries. ............................. 29
Table 2A.1 Potential distal and proximate drivers, habitat, and resource state variables
used in models, including raw data, data sources, and pre-model transformations. ....... 44
Table 2B.1 Key environmental and human factors that explain in situ coral reef fish
diversity and functional group distributions at biogeographic scales relevant to this
study. ............................................................................................................................... 62
Table 3.1 Principal components analysis of modernization variables ........................... 78
Table 3.2 Effects of social and economic drivers, including components of
modernization, on community-level management institutions. ...................................... 82
Table 4.1 Distribution of respondent socio-demographic attributes across study sites. 98
Table 4.2 Proximate causes of fish decline as perceived by respondents across sites..101
Table 4.3 Principal Components Analysis of key proximate factors (P) and associated
distal factors (D), for fish stock decline.. ...................................................................... 103
Table 4.4 Proximate causes of fish stock increase as perceived by respondents across
sites. .............................................................................................................................. 105
Table 4.5 Principal Components Analysis of key proximate factors (P) and associated
distal factors (D), for increasing fish stocks.. ............................................................... 107
Table 4.6 Spearman’s Rank correlations between candidate socio-demographic
explanatory variables .................................................................................................... 108
Table 4.7 Effect of socio-demographic attributes on the dominant discourses (PC’s) of
both fish stock decline and fish stock increase ............................................................. 109
xxi
xxii
LIST OF FIGURES
Figure 1.1 Theorized effect of modernization (expressed as economic development
here) on environmental impact in affluent nations showing that, when externalities are
considered, environmental impacts do not diminish at high levels of modernization. ... 15
Figure 1.2 Model framework commonly used to test the merit of the three perspectives
in explaining the effect of ‘drivers’ (D) on the ‘state’ (S) of natural resources. ............ 22
Figure 1.3 Model framework, derived from Driver, Pressure, State theory. ................ 25
Figure 1.4 Thesis chapter outline ................................................................................... 32
Figure 1.5 Generalised model used in this thesis to test the relative merit of each of the
three dominant perspectives for explaining natural resource state. ................................ 33
Figure 2A.1 a The main islands of Solomon Islands showing study site locations, and b.
a generalized image of a study site including marine site boundary, ecological sampling
location, coral reef area, and villages. ............................................................................ 42
Figure 2A.2 Schematic structural equation model of the social and economic
determinants of coral reef fish biomass distributions. .................................................... 51
Figure 2A.3 Density of variables comprising basic gear fishing and efficient gear
fishing, across sites. ........................................................................................................ 52
Figure 2A.4 Structural equation modeling results (SEM) of the total effect size
(determined by multiplication of path coefficients (β) along each distinct path, prior to
summing of distinct paths) for the different distal and proximate drivers for each of the
resource state variables based on the general model (Fig. 2A.2). .................................. 54
Fig. 2B.1 Structural equation modeling results (SEM) showing (a) general model used
including distal and proximate drivers and (b-i) the total effect size (determined by
multiplication of β coefficients along each distinct path, prior to summing of distinct
paths) of the different distal and proximate drivers for each of the ecological response
variables. ......................................................................................................................... 67
Figure 3.1 Effect of (A) human population size, (B) human population density, (C)
modernization, and (D) market access, on the probability of management institution
occurrence (± 95% C.I. for A, B, C). .............................................................................. 83
Figure 4.1 Main island chain of Solomon Islands with provinces denoted in uppercase,
and survey sites denoted in lower case. .......................................................................... 95
Figure 5.1 Local-level process-based model (which could also be considered a
narrative) of society’s effects on coral reef resources in Solomon Islands derived from
chapters 2 and 3 of this thesis.+/- = direction (slope) of effects; a-f = see text above and
below. ............................................................................................................................ 125
Figure 5.2 A heuristic model of the effect of world systems trade on modernization
trajectories for core and peripheral nations................................................................... 129
xxiii
Figure 5.3 Generalised model used in this thesis. ....................................................... 132
Figure 5.4 Proposed generalised model of the dominant sociological perspectives of
society’s effects on natural resources at the local-level embedded within a socialecological framework. .................................................................................................. 134
Figure 5.5 Heuristic model showing hypothetical lag effects between model variables,
driven by increasing population density....................................................................... 134
Figure 5.6 Nested social-political levels that interact to effect the local-level
exploitation and management (institutions) of coral reef resources in Solomon Islands.
...................................................................................................................................... 138
xxiv
LIST OF PHOTOS
Photo 2A.1 Fishers in traditional wooden paddle canoes in Roviana lagoon, heading out
to the reef edge for fishing at dusk. ................................................................................ 48
Photo 2A.2 A typical fibreglass boat used for fishing and transport throughout Solomon
Islands ............................................................................................................................. 48
Photo 2A.3 A very kind fish seller, ‘Buss’, who introduced me to fish sellers at the
Honiara market. .............................................................................................................. 49
Photo 2A.4 The fish section in the Honiara fish market. ............................................... 57
Photo 4.1 Fera island with Buala township in the background. ..................................... 96
Photo 4.2 A typical catch from a night spearfishing trip in Roviana lagoon, Western
Province. ....................................................................................................................... 100
Photo 4.3 The provincial market in Gizo, Western Province, with local fishers selling
their catch, primarily caught by night spearfishing using torches and sling spears ...... 104
xxv
CHAPTER 1: INTRODUCTION
1.1 DECLINING NATURAL RESOURCES
The interaction between people, as individuals and societies, and the natural
environment has attracted increasing attention from both the public and scientific
community in recent years. Increased attention is likely attributable to our growing
acknowledgement of the role of human agency in the depletion of finite natural
resources (Frank 1925; Brueckheimer 1956; Machlis 1992; Grossman & Krueger 1995;
Ehrlich & Ehrlich 2013), and the resulting decrease in biological diversity and collapse
of ecological systems (e.g. Hughes 1994; Scheffer et al. 2001; Sanderson et al. 2002;
Rockstrom et al. 2009; Barnosky et al. 2012; Nyström et al. 2012; Ehrlich & Ehrlich
2013). More importantly for humanity, however, is our increasing awareness that
humans are dependent on functioning natural systems for our well-being (e.g. Catton Jr
& Dunlap 1978; Fuller et al. 2007; Cardinale et al. 2012) and probably for our survival
(for examples of localised collapse of societies see Diamond 2006).
Human understanding of both our dependency on the natural environment for our
welfare, and the clear negative effect we are having on natural systems, has catalyzed a
scientific effort to understand the causes of natural resource decline, particularly the
social causes, and prescribe means of changing individual and social behaviour to
enable a more sustainable environmental future (Schnaiberg 1980; York et al. 2003a;
Mol et al. 2010). The applied aspect of this research assumes that the better we
understand the social causes of resource decline, the more effectively we can prescribe
policy to improve the condition of natural resources.
1
1.2 SOCIAL CAUSES OF NATURAL RESOURCE DECLINE
Identifying the social causes1 of natural resource2 decline is somewhat challenging due
to the inherent dynamic complexity and contextual heterogeneity of social-ecological
systems 3. Both social and ecological systems are complex and dynamic, and processes
within each system operate across multiple scales (Cash et al. 2006). This dynamic
complexity is likely becoming more pronounced as societies become more globally
connected with ever-increasing flows of information, resources, and people (e.g.
Kramer et al. 2009). Both social and ecological systems also possess context-specific
traits (Luck 2007), such as localized ecosystem processes and societal customs.
Therefore, generalized theory cannot explain all ecological degradation or offer
approaches for addressing all ecological degradation (Ostrom 2007).
Out of the complexity of understanding the social causes of natural resource decline,
three dominant (i.e. pervasive in the literature) environmental sociology perspectives
have emerged that relate to the social causes of natural resource decline. These form the
theoretical foundation for this thesis. Each perspective arose at different periods in
history, in different contexts, by observation of changing social processes that resulted
in changing rates of resource exploitation. Such processes centre on for example,
population growth, economic production, institutional adaptation, and technological
innovation. Each perspective maintains a unique ideology of our relationship with
natural resources, and offers substantively different solutions to halting natural resource
decline. It is these differences between the perspectives, I think, that offer divergent
insights into the key structural properties of society that cause natural resource decline.
Therefore, they offer a fruitful set of perspectives to compare and contrast in this thesis.
In short, the perspectives are:
1. “Malthusian overpopulation”: Human population growth drives natural
resource scarcity.
1
Herein the term ‘social cause’ refers to any human characteristic, be it economic, demographic, cultural
etc., which explains the state of natural resources, correlative or causative.
2
Herein the term ‘natural resources’ refers to any ecological quality that has recognized human utility.
3
A social-ecological system is a system that acknowledges the interdependencies and feedbacks between
social and ecological systems – a relatively new paradigm in environmental sociology (Catton Jr &
Dunlap 1980).
2
2. “Market expansion”: Economic growth, by natural resource exploitation,
drives natural resource scarcity.
3. “Modernization”: Development and associated affluence and institutional
reform drive resource scarcity at low levels of modernization, and drive
resource abundance at high levels of modernization.
I proceed with a brief summary of the three perspectives; including the thesis
(theoretical foundation, narrative, and evidence) and the antithesis (limitations) of each.
1.2.1 DOMINANT PERSPECTIVES
Perspective 1: Malthusian overpopulation: Human population growth drives natural
resource scarcity (broadly considered a demographic theory).
Theoretical foundation
The most publicly and academically prominent perspective on human-environment
interactions is that human population growth and the associated pressure on natural
resources is responsible for declining resource conditions (Ehrlich & Holdren 1971;
Ehrlich et al. 1971; Pauly 1988; Cropper & Griffiths 1994; McKee et al. 2004). The
rationale of this perspective is that resources are finite and so continued increase of
human populations will inevitably lead to resource decline, potential species extinctions
and ecological collapse. The foundation of this work dates to Rev. Thomas Malthus
(1798), who proposed that increased productivity, enabled through linear increase of
technological innovation, would temporarily buffer people from resource scarcity, but
that human populations would eventually exceed innovation, due to geometric growth,
leading to resource scarcity and human suffering. Consequently, proponents of this
perspective argue that human population growth must be limited to avoid ‘Malthusian
overpopulation’ and human suffering.
3
Narrative
Human societies, as with populations of other species’, increase their total population to
environmental carrying capacity4. Assuming there is environmental variability (e.g.
droughts and floods), and inter-specific competition, there will be periods when the total
population increases, and times when the population decreases. The ability of humans
to increase their environmental carrying capacity through technological innovation (as
has occurred in agricultural (and aquaculture/fisheries revolutions during the 20th
Century) enables populations to grow. There are limits to innovation, however, and
therefore limits to human-modified environmental carrying capacity, and so human
populations are ultimately limited. Therefore, it is necessary to limit human populations
to within environmental carrying capacity to avoid significant natural resource decline
and consequent human suffering.
Evidence
There is no doubt that Malthusian overpopulation (frequently measured as
population/potential resources) will explain some of the variance of the state of natural
resources, including those resources that have direct utility such as fishes and forests,
and broader measures of resources, such as biological diversity and the condition of
functional groups (see Luck 2007 for a review). For example, there is substantial
support in the coral reef literature of the negative effect of human population density on
coral reef resources (Jennings & Polunin 1996, 1997; Dulvy et al. 2004a; Dulvy et al.
2004b; Newton et al. 2007; Mora 2008; Sandin et al. 2008; Williams et al. 2008; Cinner
et al. 2009b; Mora et al. 2011; Williams et al. 2011; Bellwood et al. 2012). Indeed a
popular term for overfishing caused by human population growth is ‘Malthusian
overfishing’ (Pauly 1988).
Population density and size are also likely to affect the efficacy of natural resource
management institutions5. When populations are adequately high that exploitation
exceeds rates of ecological replenishment, it is possible that resource management
4
‘Environmental carrying capacity’ is defined here as the maximum number of people an environment
can sustain indefinitely.
5
Herein the term ‘management institutions’ refers to any set of rules relating to the exploitation of natural
resources.
4
institutions, which are believed to mediate the effects of Malthusian overpopulation on
natural resource exploitation (Agrawal & Yadama 1997), will fail, particularly in the
context of common-pool resources (sensu Hardin 1968). There is also evidence that an
optimum community population size (neither too small nor too large) might lead to the
successful collective action such as natural resource management (Agrawal & Golyal
2001).
Limitations
There are five key limitations to the perspective that Malthusian overpopulation alone
can explain declining resources. First is a debate on causality. Malthusian perspective
proponents argue that increased means of production enables population growth, rather
than population growth as the driver of increased production, as argued by Boserup
(2005). The central tenet of Boserup’s argument is that necessity (i.e. inadequate food
supply) drives innovation as the means of production to prevent suffering and death,
and therefore human populations will not outpace the means of production. Boserups
thesis has given rise to the idea that rapid population growth, even in areas of marginal
productivity, might generate economies of scale in production, and more sophisticated
management institutions that ultimately reduce environmental footprints whilst
improving quality of life (e.g. Malakoff 2011). Indeed, early research in the Pacific by
Johannes (1978) suggests that resource management institutions emerge and evolve, as
required, as human population pressure increases and decreased, assuming negative
external influence, such as abolition of underlying access rights, is avoided. Second,
proponents of Malthusian overpopulation tend to assume that all people interact with
the natural environment in the same manner, and consume the same volume and types
of natural resource (however Malthus himself acknowledged differences in
consumption between individuals of different social class within societies) (see York &
Gossard 2004 for an example of context variability in resource consumption).
Therefore, human population size per potential available resources cannot accurately
predict the state of natural resources. Third, the role of technology tends to be ignored
(see Commoner 1972 for early debate on the relative importance of technology in
explaining environmental impacts) in explaining natural resource exploitation rates.
Yet technologies affect rates of exploitation and consumption, and different societies
have access to different technologies. Fourth, local human population size/density does
5
not account for trade of resources between social-ecological systems– relatively
wealthier societies are able to import goods and services and export pollutants, such as
those produced by heavy industry, and consequently maintain a population beyond local
carrying capacity (Ehrlich & Holdren 1971; Wallerstein 1976). Therefore, it is not
possible to conclude that any two societies, equal in population size and equal in net
primary productivity (e.g. fisheries or forestry) will have resources of equal condition
(e.g. number of trees, fishery biomass). Fifth, it has been observed that high population
density (measured as number of fishers per length of coastline) can correlate positively
with higher fish biomass (Pollnac et al. 2000). This result was explained by the mobility
of fishers, enabling them to migrate to areas of higher resource density. Therefore, the
relationship between density of people, and resource condition, should be considered
critically, and particularly where human populations are mobile, including nomadic
people. Further, a recent study by Pollnac et al. (2010) found stark differences in
correlations between human population density and differencess in fish biomass inside
and outside spatial closures among three regions; the Caribbean, the Philippines, and the
Western Indian Ocean. Specifically, only the Caribbean exhibited a negative correlation
between population density and differences in fish biomass, whilst the Western Indian
Ocean exhibited a positive correlation among the same variables. The authors explained
this as possible high exploitation outside spatial closures. Therefore, adherence to
spatial closure rules had a possible over-riding effect on fish biomass in this instance. In
essence, this perspective is crude and eco-centric, and does not take adequate account of
the modern complex social matrix of human societies6. And so, to explain the human
causes of resource decline it is necessary to explore beyond the simplistic narrative of
human population size and/or density.
6
While this perspective is ecologically centric, Malthus makes clear distinction between people and other
species with respect to limits to growth and the response to resource scarcity. Subsequently, scholars have
frequently ‘ecologised’ and consequently simplified Malthus’ work on the Principles of Population to
suggest that individuals within a human society will respond similarly to individuals within a population
of, for example, plant or other animal species. This simplification leads to a morally and ethically fraught
position of the need to limit human population size to ensure sustainable natural resource use for human
well-being.
6
Perspective 2: Market expansion: Economic growth, by natural resource exploitation,
drives natural resource scarcity (based on the political-economic theory ’neoMarxism’, and more recently the environmental sociology theory of the ‘treadmill of
production’).
Theoretical foundation
The underlying principle of this perspective, which is rooted in Marxist philosophy
(Marx 1887)7, is that of the social perception of the need for economic growth for
improved personal and social welfare, enabled through ‘free market’ innovation and
exploitation of natural resources. Proponents of this perspective argue that economic
growth, rather than environmental sustainability, dominates social and political
decision-making. Fundamentally, proponents of this perspective argue that problems
related to natural resource scarcity cannot be solved as long as the ideology of
dependence on economic growth persists, and that a radical restructuring of the political
economy and the elimination of the growth-dependent ideology is required to ensure a
sustainable future (Schnaiberg 1980). As stated by a proponent of this perspective
‘..economic growth remains the foundation of decision making with regards to the
design, performance and evaluation of production and consumption, dwarfing any
ecological concerns’(Schnaiberg et al. 2002, p1.).
The dominant thesis of this perspective is the treadmill of production (Schnaiberg
1980), which has been hailed ‘the single most influential framework of analysis within
environmental sociology in the United States’ (Foster 2005). The treadmill of
production thesis represents an addition to Marxist philosophy, by describing the
process of natural resource degradation by capitalist production (Kovel 2011).
However, as Foster states, the thesis is from the United States of America, and despite
making reference to market expansion and capitalism, generally, the focus is on the
7
The philosophy of Karl Marx; particularly in his work on the accumulation of Capital (Marx 1887),
relates more to the social effects of resource privatisation, rather than the effect of economic production
on natural resources discussed by Allan Schnaiberg as the treadmill of production. However, both theses
suggest that the accumulation of capital from natural resources through the ‘free market’ ideology (sensu
Smith 1843), is detrimental to human welfare (particularly equality of welfare distribution) and the
natural environment. Fundamentally, therefore, this thesis loosely examines the effects of social
adherence to the dominant western political philosophies of socialism and capitalism, on the state of
natural resources.
7
post-WWII United States of America model of production expansion. That is, the
purpose of Schnaiberg’s work was to explain monopolistic production – the type of
political-economic system promoted in the writings of Ayn Rand (2005), which was
based on industrial nations extracting natural resources both domestically and from
economically peripheral nations with cheap labour and limited environmental regulation
(Gould et al. 2004). Therefore, the treadmill of production is fraught when it is applied
to production systems owned and operated in economically peripheral nation contexts
void of significant industry, a well-functioning civil service, and a stable society
conducive to the development of a significant labour force. Yet, such nations, which
are economically marginalised, and peripheral to the global economy (Wallerstein
1976), are prone to significant environmental degradation by natural resource extraction
for local consumption, and for export to affluent nations (Singer 1975; FischerKowalski & Amann 2001; Gould et al. 2004). Hence, there is a need to adapt the
treadmill of production narrative to suit such contexts or to consider alternative
perspectives (see Bunker 2005 for further rationale of the need to consider global
position in treadmill of production analysis). Therefore, whilst acknowledging the
treadmill of production, and the many subsequent publications reviewing and analysing
it, the following narrative is generalised to suit broader contexts including less formal
production systems that are common in peripheral nations such as Solomon Islands,
which is context for this thesis.
Narrative8
Natural resources are exploited by producers (e.g. logging companies, fishers) to satisfy
market demand. Production is supported by governments and other public
administration entities because increases in production result in economic growth,
employment and material affluence. Producers aim to increase net production and
production efficiency to maximise profits (assuming the ideology of constant growth).
Production efficiency is increased by the use of technology rather than by an expanded
labour force. In the context of small-scale fisheries, fishers would be expected to
maximise harvest to maximise income. The use of increasingly efficient gears would
8
Note that this is a significantly simplified narrative to suit broader contexts than discussed by
Schnaiberg (1980). The purpose of the simplification is to maintain relevance to the production system
analysed in this thesis; a small-scale fishery in a peripheral nation. The next sections continue to refer to
the treadmill of production because it has had significant influence in the literature.
8
make fishers more competitive by increasing catch, and reducing labour expenses (e.g.
boat crew). Key to maximising profits is access to consumer markets (including
proximity). Desire for maximised profits drives the use of technology which results in
resource depletion. Thus, in the context of local-level social-ecological systems, this
perspective differs from the Malthusian overpopulation perspective primarily in that
resources are extracted for capital accumulation by exportation from the local socialecological system, rather than for consumption and/or barter within the socialecological system.
Evidence
There is a growing literature that supports the perspective that the economic growth
ideology, manifest as capitalism and presented as the treadmill of production, is driving
resource scarcity. Evidence exists in descriptive works and case studies such as a suite
of papers by Gould on industry pollution on the Great Lakes of the United States of
America (Gould 1991; Gould 1992, 1994), post-consumer recycling in the United States
of America (Weinberg et al. 2000), rainforest eco-tourism in Belize (Gould 1999), and
environmental injustice in electronic industries (Pellow & Park 2002; Pellow 2004), to
name a few. More recently, scholars have conducted quantitative comparative analysis,
using proxy, or manifest, variables [e.g. economic freedom, gross domestic product,
urbanization (York et al. 2003a; Özler & Obach 2009)], to amass a significant body of
evidence in support of treadmill of production perspective (e.g. Naidoo & Adamowicz
2001; York et al. 2003a; Hoffmann 2004; Clausen & York 2008b, a; Özler & Obach
2009; Bradshaw et al. 2010). In a coral reef context, distance to markets, which can be
considered a manifestation of market expansion, explains the condition of harvested fish
(Cinner & McClanahan 2006) and in situ fish stocks (Brewer et al. 2009; Cinner et al.
2012a; Cinner et al. 2012b). There is also substantial evidence to suggest that market
access erodes fishery management institutions which exist, by and large, to constrain
exploitation (e.g. Cinner 2005; McClanahan et al. 2006; Cinner et al. 2007).
Limitations
There are three clear limitations to the treadmill of production as a general theory for
explaining socially driven resource scarcity. First, as stated above, Schnaiberg derived
9
the treadmill of production from observations of the rapid rise of industry and corporate
enterprise in post-WWII America. Second, the treadmill of production assumes that the
producer privately owns natural resources, yet natural resources are often shared my
means of common property institutions, with all community members acting as
producers, the state (via institutions that set natural resource exploitation rules), and
consumers (Weitzman 1974; Wade 1987; Ostrom et al. 1994). That is, in many
societies, the members of society possess collective use-rights to resources, such as
fisheries or forestry (Gordon 1954; McKean & Ostrom 1995). Third, the complexity of
the treadmill of production narrative, which involves dynamic interaction of the state
(governance), the production system and the labour force as consumers and workers(see
Schnaiberg 1980) makes challenging, any attempts to comparatively and quantitatively
test the relevance of the perspective. Consequently, research has focused on contextual
descriptions or the use of proxy metrics such as gross domestic product (GDP), to test
the occurrence of the treadmill of production, resulting in, what I perceive, to be a
failure to produce substantive evidence to support this perspective. For example,
quantitative studies often correlate production proxies (e.g. GDP, urbanization) with
ecological indicators (e.g. fishery biomass), without considering how such proxies alter
production (exploitation) and natural resource management institutions (e.g. Naidoo &
Adamowicz 2001; York et al. 2003a; Hoffmann 2004; Clausen & York 2008b, a; Özler
& Obach 2009; Bradshaw et al. 2010). A better understanding of how such proxies
affect exploitation and management behaviours would improve understanding of the
treadmill of production as a social process that causes resource decline. Therefore,
while there is significant support for this perspective, there is a need to consider
peripheral nation contexts, collective ownership of resources, and behavioural changes
including resource exploitation and resource management.
Perspective 3: Modernization: Development and associated affluence and institutional
reform drive resource scarcity at low levels of modernization, and drive resource
abundance at high levels of modernization (referred to as ‘ecological modernization’ in
environmental sociology and the ‘environmental Kuznets curve’ in ecological
economics).
10
Theoretical foundation
The third and final perspective investigated in this thesis is that of ecological
modernization and the related environmental Kuznets curve theory. Ecological
modernization proponents believe there is a growing emancipation of politics and
economy from the environment (Mol 1996), and therefore directly challenge the
treadmill of production thesis - that deindustrialization and dramatic economic reform is
required to ensure future environmental sustainability (Mol & Spaargaren 2000).
Rather, ecological modernization proponents champion both increased efficiency by
technological innovation and public and private institutional reform as mechanisms for
ensuring a sustainable future (Fisher & Freudenburg 2001) without the need for
dramatic economic restructuring of the global economy. They argue that the process of
ecological modernization is an essential pre-condition to further development - a part of
which is taking inspiration from ecological systems in the design of social and
economic systems, to make them more compatible. In the words of a leading proponent
of ecological modernization theory:
“..the basic premise of the Ecological Modernization Theory is the centripetal movement
of ecological interests, ideas and considerations involved in social practices and
institution developments, which results in the constant ecological restructuring of modern
societies. Ecological restructuring refers to the ecologically-inspired and environment
induced processes of transformation and reform going on in the central institutions of
modern society.”
(Mol 2003, p59.)
The allied environmental Kuznets curve theory is an adaptation of the theory developed
by Simon Kuznets of non-linear (inverse U-shaped curve) income inequality with
increasing economic growth/production (Kuznets 1955; Grossman & Krueger 1991).
The theory is rooted in economics, rather than sociology, and therefore, provides an
economically rational explanation for the proposed improvement in natural resource
state with increasing affluence (York et al. 2003a).
11
Narrative
At low levels of modernization, societies exploit natural resources for improved shared
and personal welfare. Consequently, natural resources become scarce and pollution
levels increase. Once a certain level of modernization, and associated affluence, is
attained, societies have the luxury of being able to prioritize natural resource
considerations in decision-making. Consequently, at the given level of modernization
(which varies across different natural resources and pollutants), natural resources
replenish and pollutants diminish as modernization progresses. Ecological
modernization proponents suggest that this shift in the social-ecological trajectory is
primarily a consequence of institutional reform and technological innovation that is
driven by an awareness (largely in post-Industrial nations) of the limits to production
and consumption combined with an environmental consciousness and consideration of
the welfare of future generations (Mol 2003). Some environmental Kuznets curve
scholars suggest that increased modernization and associated affluence allow for import
of resources and export of pollutants ( a ‘scale effect’), transition from a primary
industry to a service-based economy and, through research and development (a
‘composition effect’), the application of technologies that have a reduced environmental
impact (a ‘technique effect’) (see Grossman & Krueger 1991 for theory development;
see Cinner et al. 2009b for testing of these effects).
Evidence
The modernization perspective is an attractive proposition: that institutions and
technology are transforming to ensure sustainable social-ecological systems in the
future. Consequently, there is a significant literature discussing the merits of, and
providing evidence for, the theory. Evidence of ecological modernization is often based
on case studies (e.g. Mol 1995; Mol & Sonnenfeld 2000). A classic example of
ecological modernization is the chemical industry in Europe. The industry was the cause
of severe environmental deterioration from prior to the Industrial Revolution until the
1980s, when widespread public concern triggered restructuring of the industry. The
restructuring included environmental management systems in chemical companies,
including environmental accounting, and the production of relatively environmentally
products, driven by consumer demand. The industry is now far more aligned with
environmental sustainability, and has a greatly diminished negative effect on ecological
12
systems (Mol 1995). Further, proponents also provide more general regional and global
evidence such as the proliferation of environmental non-government organizations (Mol
2000). The majority of quantitative research testing the merit of this perspective has
been labelled as the environmental Kuznets curve. The environmental Kuznets curve
has been observed in fish catch (Clausen & York 2008a), in situ fishery biomass
(Cinner et al. 2009b), the number of threatened bird species (Naidoo & Adamowicz
2001), CO2 emissions (Rosa et al. 2004), city air pollution and water quality (Grossman
& Krueger 1995), and deforestation (Ehrhardt-Martinez et al. 2002), to name a few.
Limitations
Despite the accumulation of supporting comparative and case study evidence, the
modernization perspective has received significant criticism from within the sociology
(particularly York & Rosa 2003) and ecological economics (Arrow et al. 1995; Stern et
al. 1996) fraternities. Criticisms of the perspective are numerous, so for brevity, I will
elaborate on those that have relevance to this thesis only.
York & Rosa (2003) identified four key challenges to the claims of ecological
modernization; 1) there is inadequate evidence that institutional modifications lead to
ecological improvements; 2) there is inadequate evidence of changes in production and
consumption patterns in the latter stages of modernity; 3) that ecological modernization
does not adequately show that decreased ecological impact by some entities (e.g. firms,
corporations, nations) does not result in increased negative ecological impact by other
entities (i.e. ecological modernization does not adequately account for externalities);
and 4) there is a need for ecological modernization to show, not only that economies are
becoming more resource-efficient, but also that increased efficiency exceeds the pace of
total production. Three of these apparent limitations are particularly relevant to this
thesis, and therefore elaborated on here.
The second limitation identified by York and Rosa (2003), and elaborated by York et al.
(2004), is one of evidence derived from variance (increased variability in context) rather
than central tendency (mean trend). That is, in later stages of modernity there exists
13
increased variability in environmental performance due to increased diversity in
production forms (e.g. processes, products and institution types), and therefore, it is
possible that outliers that support ecological modernization and the environmental
Kuznets curve are being over-reported whilst the mean trend remains one of declining
resources with increased affluence. Evidence of this limitation is that ecological
modernization and the environmental Kuznets curve are infrequently identified in
general cases, such as global analyses of the effects of modernization on environmental
footprints (York et al. 2003a; Bradshaw et al. 2010) (Table 1.1), but are more common
in context-specific cases in post-industrial nations (e.g. Mol 1995).
The third limitation identified by York and Rosa (2003) suggests that ecological
modernization and the environmental Kuznets curve might only apply in affluent
societies, such as post-industrial Europe (Fisher & Freudenburg 2001). Variability
within nation states is still largely unknown(but see Grossman & Krueger 1995;
M'henni et al. 2011), and whether this theory applies to any degree in economically
peripheral nations is still unknown. Arthur Mol, a leading author of ecological
modernization, acknowledges that a major shortcoming of the theory is that of its
Europe-centric nature, and poorer nations and societies might not be undergoing
ecological modernization (Mol 2003). This acknowledged limitation fits with world
systems theory and dependency theory, whereby the wealthier (core) nations (e.g.
United Kingdom, France, Germany, Japan, United States of America) maintain a
healthy natural environment by importing goods from, and exporting pollutants to, poor
(peripheral) nations (Wallerstein 1974; Singer 1975; Bruckner et al. 2012), and
therefore ecological modernization/environmental Kuznets curve trends in core nations
are spurious (Figure 1.1). If Wallerstein (1974) and Singer (1975) are correct, then
natural resources in relatively poor social-political areas (nations, regions,
communities) are being exploited, and consequently degraded, to support consumption
by people in relatively affluent social-political areas. Ultimately, there is a distinct need
for a better understanding of modernization theories as they apply to any potential
development policies in peripheral nations (Frank 1966; but see Hoffmann 2004;
Shandra et al. 2009 for evidence of the effect of world system position on natural
resources; McKinney et al. 2010). Both of these limitations (2 & 3) suggest there is a
14
need for comparative (as opposed to case-based) evidence in a peripheral nation context
to determine whether the critique offered by York and Rosa (2003) has merit.
Figure 1.1 Theorized effect of modernization (expressed as economic development here) on
environmental impact in affluent nations showing that, when externalities are considered, environmental
impacts do not diminish at high levels of modernization. Source: York et al. (2003a).
A final important limitation, which exists across perspectives, is one of causality. The
shared narrative of ecological modernization and the environmental Kuznets curve is
one of changing social behaviour, including reduced resource exploitation, at a given
level of modernization and associated affluence. Yet, there is scant evidence to suggest
that modernization causes changing behaviour that, in turn, explains improvements in
the state of natural resources. T hat is, the majority of studies correlate modernization
(using proxy variables such as GDP and urbanization) with natural resource indicators
(e.g. air pollution, species diversity, resource biomass), without explaining the
mechanisms by which the non-linear relationship occurs (Grossman & Krueger 1995;
York et al. 2003b). Such mechanisms include the scale, technique, and composition
effects outlined by Grossman & Krueger (1991). One recent exception is a local-level
multi-nation study by Cinner et al. (2009b) that explained increased coral reef fish
biomass, with increased modernization, to be caused by differing levels of engagement
in fishing (composition effect), differing fishing gears (technique effect), and better
transportation (scale effect). Therefore there is a distinct need to understand causality,
and in particular, how modernization drives improved resource management institutions
and decreased exploitation (Mills & Waite 2009).
15
1.2.2 SYNTHESIS OF THE DOMINANT PERSPECTIVES
Each of these three perspectives (Malthusian overpopulation, market expansion, and
modernization) has a vast literature of supporting evidence in different forms, including
qualitative and quantitative evidence from both case studies and comparative analyses.
Attempts to compare and contrast the different perspectives have taken different forms,
with the general trend of analysis type from descriptive case studies and basic modeling,
through to more recent comparative analyses using a combination of social and
ecological data.
Early attempts to understand human effects on natural resources began with models that
incorporated aspects of each perspective, without explicitly making reference to all
three perspectives. The most notable and enduring such model, developed by Barry
Commoner, Paul Ehrlich and John Holdren is the I PAT model (Impact = Population *
Affluence * Technology) that aimed to explain human impacts on the environment as
the effect of population, affluence and technology, such that the effect of all three
independent variables is greater than the sum of each in isolation (Ehrlich & Holdren
1971; Commoner 1972). The I PAT model was not an attempt to synthesise the three
perspectives, but inadvertently incorporated some of the different variables contained
within the three perspectives. Since this time, a number of refinements on this model
have been developed (see Chertow 2000 for a review; see York et al. 2003c for a
comparison of dominant models). This general model, and its refinements, is useful
because it accounts for interaction between dominant independent variables.
Conclusions from empirical investigations using I PAT based models vary, but
generally, population (P) and technology (T) have frequently explained impact (I),
whilst affluence (A) has mixed effects, depending on which indicator variables are used
(e.g. gross domestic product), but each variable is context-dependent (York et al. 2002).
This approach has generally lent weight to both the Malthusian overpopulation and
market expansion perspectives (likely due to the dominant role that technology plays in
market expansion) (e.g. York et al. 2003a; York et al. 2003c; Dietz et al. 2007).
Recently, with increased availability of large social and ecological data sets, and a more
nuanced understanding of the aforementioned perspectives, research has focused on
specifically comparing and contrasting the merit of the three perspectives, within single
16
analyses, and in different contexts (e.g. natural resource type) (Table 1.1). The results
vary, depending on response variables (measure of relative resource state) and predictor
variables (that represent the respective perspectives). It is not clear, however, which
resource types respond to which drivers (Table 1.1). For example, threatened species
are negatively affected by proxy variables for all three perspectives, but not consistently
across studies. However, natural resources would be expected to respond positively to,
for example, improved management or the elimination of markets, with speciesdependent variation in response (e.g. highly fecund species with a low age at maturity,
such as some fish, would be expected to respond more rapidly). The disparate modes of
analysis and data sources are also likely to affect the results. Generally, however, there
is greatest support for the Malthusian overpopulation and market expansion
perspectives.
As with the quantitative studies that address the merit of individual perspectives
discussed above, there are limitations to the syntheses that have been conducted. First,
the studies that have compared and contrasted all three perspectives (Table 1.1) were
conducted at the nation-level. Because social-ecological dynamics vary across socialpolitical levels, there is a distinct need to compare and contrast the three perspectives at
levels other than nation/country, such as at the local-level (community or village).
Second, quantitative comparisons rarely consider the perspectives as processes (but see
Cinner et al. 2009b), and instead directly test (correlate) the effects of, for example,
modernization on wild fish stocks (a limitation I earlier raised for each of the
perspectives). T here is a clear need to understand how, in this example; modernization
affects rates of exploitation and the efficacy of resource management institutions, to
explain the condition of the fishery. Making this link between the variables that
represent the different perspectives, and the human behaviour(s) associated with
exploitation and management of natural resources will allow us to understand better the
causal effects of abstract concepts like modernization on natural resources (Mills &
Waite 2009).
17
Table 1.1 Studies that quantitatively test the relative merit of all three dominant perspectives.
Study
Unit of analysis
Perspective
Explanatory variables
Response variable
Result
1
National
MO
Total Population
Ecological Footprint
+
Population Density
‘’
+
Nondependent population
+
Urbanization
‘’
‘’
‘’
‘’
‘’
Population Density
Mammal and Bird endangerment rates
NS
Annual population growth
NS
[GDP per capita growth rate]
‘’
‘’
‘’
‘’
‘’
‘’
‘’
Average annual population
Threatened marine and freshwater fish
+
NS
M
[GDP per capita]
2
[Urbanization]2
ME
2
National
MO
GDP per capita
Percent Urbanization
Annual Deforestation rates
M
log[GDP per capita]
2
[GDP per capita growth rate]
ME
3
4
National
National
MO
log[GDP per capita]
2
NS
+
+
+
NS
NS
+
NS
+
+
M
log[GDP per capita]
ME
log[GDP per capita]
‘’
‘’
MO
Total Population
Landed fish catch
+
Mean fish trophic level
+
Landed fish catch
-
Mean fish trophic level
-
[Urbanization]
2
Landed fish catch
+
[Urbanization]
2
Mean fish trophic level
-
GDP per capita
Landed fish catch
+
GDP per capita
Mean fish trophic level
+
Urbanization
Landed fish catch
-
Total Population
M
[GDP per capita]
2
[GDP per capita]2
ME
2
+
18
5
National
MO
Urbanization
Mean fish trophic level
-
log[Total Population]
Percent bird species threatened
+
log[Population density]
‘’
‘’
‘’
NS
M
Environmental treaties ratified
ME
log[GDP per capita]
+
NS
N.B. In some instances authors have generated multiple models. Summary results presented here are either for an optimized model (optimised by e.g. lowest Akieke
information criterion score) or a model specific to a particular perspective.
NS = Not significant. +/- = p < 0.05.
MO = Malthusian overpopulation; ME = market expansion; M = modernization.
Studies cited: 1. York et al. (2003a), 2. Hoffman (2004), 3. Clausen & York (2008b), 4. Clausen & York (2008a), 5. McKinney et al. (2009).
19
1.2.3 GENERAL CONCLUSION ABOUT PERSPECTIVES FROM THE LITERATURE REVIEW
Each of the three perspectives has strengths and limitations. Differences in the
conclusions drawn from the disparate studies are likely to result from differences in
scale including differing social-political levels of analysis (e.g. local, provincial,
national) and different contexts (e.g. resource type, levels of modernization, and
connectivity to other social-ecological systems by trade). Consideration of all three
perspectives, within any single context and scale, is likely to explain more of the
variance in ecological distributions, than any one perspective alone. This point is
illustrated by the following statement by Fisher & Freudberg with respect to ecological
modernization:
‘The mere accumulation of additional examples, accordingly, would seem highly unlikely
to prove that one side is “right,” while the other is “wrong.” Instead, both the theory’s
proponents and its critics have met the philosophical condition of existence proof—
anything that exists is possible—but it is equally clear that neither ecological
modernization nor the obverse [market expansion] could be considered universal. The
task that now faces the scientific community is thus to work toward greater rigor in
identifying conditions under which “ecological modernization” outcomes are more or less
likely.’
(Fisher & Freudenburg 2001, p704.)
This point is further illustrated by Arthur Mol, a leading author of the modernization
perspective:
‘At the same time we have to acknowledge that in the majority of situations the most
fruitful explanations are to be found somewhere along the continuum between the two
extremes [modernization and market expansion], albeit at different points for different
social practices, localities, and times.’
(Mol 2003, p70.)
Ultimately, there are two potential social-ecological futures. If some combination of
Malthusian overpopulation and market expansion dominate the future social-ecological
landscape, then human and ecological welfare will diminish. If ecological
modernization and the environmental Kuznets curve trends dominate the future social20
ecological landscape, then human and ecological welfare will have a higher probability
of flourishing.
‘Come what may, the twenty-first century will be the century of the environment – either
the century of ecological catastrophes or the century of ecological transformation.’
(Sachs et al. 1998, p8)
So far I have presented a review of the dominant perspectives of society’s effects on
natural resources including their respective theory, narratives, evidence, and limitations.
I have also reviewed studies that have synthesised the perspectives, and highlighted
limitations to the syntheses. Based on this review, and the limitations to current
perspectives, individually, and in synthesis, I now proceed by outlining the research
gaps that are addressed in this thesis.
1.3 RESEARCH GAPS
Reviewing the literature highlights four clear research gaps in the dominant humanenvironment perspectives (described in detail below). The first research gap is one of
causality. The second gap is one of scale. The third gap is one of context. The fourth
gap is one of triangulation of findings. I have focused on research gaps that are
ubiquitous across perspectives, and so contribute to general understanding of the effects
of society on natural resources, rather than attempting to refine any one particular
perspective. I have taken this approach because it is clear that each perspective has
strengths and limitations, and is therefore, by itself, insufficient for explaining the
effects of societies on natural systems.
Research gap 1: Limited understanding of causal links between social and
ecological systems.
The majority of quantitative studies directly test the effect of proxy variables that are
representative of the elements of the perspectives (e.g. population density, GDP,
urbanization) against indicators of the state of natural resource (e.g. species diversity,
fishery biomass), without considering the mechanisms by which these proxy variables
21
act on natural resources. That is, there is distinct paucity of research on the effect of
Malthusian overpopulation, market expansion or modernization, on resource
exploitation or the success of resource management institutions9 which more directly
explain the state of natural resources (Mills & Waite 2009). That is, most studies that
test the merit of the perspectives directly correlate, using regression techniques, the
effect of ‘driver’ (D) variables (proxy variables for the respective perspectives) on
‘state’ (S) variables (the state of the natural resource in question), without considering
the ‘pressure’ (P) variables that mediate the interaction between driver and state
variables (but see Clausen & York 2008a; McKinney et al. 2010) (Figure 1.2).
Figure 1.2 Model framework commonly used to test the merit of the three perspectives in explaining the
effect of ‘drivers’ (D) on the ‘state’ (S) of natural resources.
To illustrate further- in the context of small-scale fisheries, modernization does not
affect the biomass of targeted in situ fish stocks per se, but could result in increased
access to, and subsequent use of, more efficient fishing gears (exploitation) that might,
in turn, decrease fish stock biomass, or cause management institutions to fail (Cinner et
al. 2009b). The argument is summarized by Alier:
‘The environment does not care at all about GNP [a proxy variable for, or manifestation
of, modernization], it cares about absolute amounts of pollutants or extractions.’
(Alier 2003, p138)
9
Other causes of resource decline exist including the indirect impacts of exploitation such as habitat
degradation and runoff from logging, and atmospheric warming from burning fossil fuels. I argue here,
however, that these are consequences of exploitation as I have defined it.
22
I address this research gap by developing and testing a more nuanced model than that
presented in Figure 1.2. The model, based on a sound theoretical foundation that is
outlined below, includes proxy variables for each of the perspectives, measures of both
exploitation and management as mediating factors, and diverse measures of resource
state.
A widely accepted sociological theory is that broad social phenomena (e.g. population
growth, religious denomination, economic affluence), measured objectively, influence
human behaviour (e.g. fishing effort) (Durkheim 1897). The general theory posits that
individual actions (e.g. resource exploitation and management institution establishment
and adherence) are determined by broader social function and phenomena, and therefore
the behaviour of individuals and social sub-groups is constrained by the broader social
context. Inherently, this infers causality between the social phenomena and human
behaviour. The theory was first used to explain suicide rates in Europe (Durkheim
1897), but broadly applies to the behaviour of any sub-set of a human population.
This theory has facilitated the development of frameworks that link broad social
phenomena to natural systems, through human behaviour. For example, it has been
adapted as the driver, pressure, state (DPS) model wherein drivers are the broad social
phenomena, pressures are those factors which directly affect ecological systems, and the
state represents the measured condition of the ecological system (e.g. Pirrone et al.
2005; Mangi et al. 2007). The framework for analysing systems using this model is in
the form D → P → S10. It was also used in the Millennium Ecosystems Assessment
(2005). Similar frameworks have been adopted in contemporary research to explain
sequential cause and effect in social-ecological systems (Forester & Machlis 1996;
Agrawal & Yadama 1997; Geist & Lambin 2002; McKinney et al. 2010), whereby
10
Additions to the three part model include, sequentially “I” (impact on society), and “R” (social response to the
causes of changed environmental state which feeds back to “D” and “P”) such that: D→P→S→I→R (e.g.
Kristensen 2004).
23
broad social phenomena explain human activities which, in turn, explain environmental
variability, following Durkhiem (1897). Yet, none of these studies has been used
explicitly within the dominant perspectives. I argue, based on the work of Durkhiem
and many since, that using this model structure within the three different perspectives
will help inform our understanding of the cause and effect of societies on natural
resources. I therefore use Durkheim’s theory to generate a model structure that I use for
testing the three dominant perspectives of the society’s effects on natural resources.
In quantitative analysis, proxy variables are used to approximate each of the three
perspectives. Such variables are, in effect, the measured manifestations of the
underlying theory for each perspective. In the absence of reducing the complex
narratives into measureable variables, it would not be possible to test quantitatively the
perspectives, or any social-ecological phenomena for that matter. As reviewed above,
such variables include distance to markets, urbanization, and population density. In this
thesis, I maintain the use of proxy variables to represent each of the perspectives.
Within the D → P → S framework such variables would be ‘driver’ (D) variables.
Further, I argue that the primary social causes (pressures in the DPS model) of resource
decline are the utilization of natural resources (herein exploitation) by labour and
technology, and failure of resource management institutions to constrain
overexploitation. There is evidence of the negative effect of exploitation on natural
resources in all ecosystems where resources with some utility exist (see Jennings et al.
1995; Jennings & Polunin 1996 for contextually relevant examples; Friedlander &
Demartini 2002; DeMartini et al. 2008 ). There is also evidence that the presence of
effective resource management institutions contributes to sustaining natural resources
(see Russ & Alcala 1989 for contextually relevant examples; Cinner et al. 2012b). In
this thesis, I therefore define the ‘pressure’ (P) variables as those social characteristics
that represent natural resource exploitation, and suppression of exploitation, through
resource management institutions. Within the model, driver variables, that are
manifestations of each of the perspectives, act on the two key pressure variables,
exploitation and management institutions, to effect a change in the state of natural
resources. This approach provides a more nuanced understanding of each of the
24
perspectives, and allows greater inference of causality, commensurate with the processbased narratives of each perspective. In figure 1.3 for example, population growth (a)
causes increased exploitation of resources (b), and failure of management institutions to
limit exploitation (c), resulting in decreased natural resources (d).
Figure 1.3 Model framework, derived from Driver, Pressure, State theory. DPS theory is to be applied in
this thesis to explain the effects of society on natural resources. The purpose of this model is to synthesize
the direct effects of human behaviour on natural resources, and does not claim to account for indirect
effects such as variability related to climate change caused by the exploitation of tropical forests. Note
that double-headed arrows represent interaction effects; single-headed arrows assume unidirectional flow
of causality; institutions mediate the effects of exploitation on natural resources.
According to theory, each of the three perspectives would show different effects
within the above model (Figure 1.3). Malthusian overpopulation would lead to failure in
management institutions and increased exploitation intensity, including the use of more
efficient and destructive gears, with clear negative flow-on effects to natural resources.
Market expansion would lead to failure of institutions through factors such as rule
transgression driven by potential economic gains, and increased exploitation intensity,
including the use of more efficient gears, sourced through income generation.
Modernization would, at some point in development, lead to more sophisticated
management institutions able to cope with sustainable resource allocation issues, and
the successful elimination of destructive exploitation practises, such as dynamite fishing
and nylon nets with small mesh size. However, in early stages of development failure of
relatively simple management institutions and use of unsustainable exploitation
practises would be expected.
25
Research gap 2: Scale
There is bias toward national-level global analyses of the perspectives (York et al.
2003a, b; Hoffmann 2004; York & Gossard 2004; Clausen & York 2008b, a; McKinney
et al. 2009) (Table 1.1). Preference for nation/state level analyses is probably driven by
data availability and global relevance. Yet, it is clear that different factors drive
resource decline at different social-political levels (Kronen et al. 2010), and there is a
distinct paucity of comparative analyses at the local-level. Yet decisions to either
exploit or conserve resources often occur at the individual and local-level, such as in
coastal fishing communities, with limited influence from national-level policies. Also,
it is likely that people and ecosystems are more tightly coupled at the local-level than at
the nation/state level (Almany et al. 2013), and therefore feedbacks between society and
ecology are more direct and consequently likely to be observable. This is particularly
relevant to Solomon Islands coral reef social-ecological systems because, while there
are certainly exceptions (Foale & MacIntyre 2000), coral reef resources are frequently
exploited by the people living adjacent to the reef (Aswani 1999; Aswani 2002). Last,
there is less social-ecological complexity and diversity at the local-level (particularly
when comparing local-level sites within a nation/state), than at the nation/state level,
and therefore less ‘noise’ in data, and greater likelihood of accounting for variability.
The local-level, therefore, provides both a suitable and relatively novel level to compare
the merit of the three perspectives. This thesis addresses research gap 2 by conducting
the comparison of the perspectives using coastal communities in Solomon Islands as
replicates within the analyses.
Variables that are used to approximate each of the perspectives (proxy variables) at the
nation-level are not available at the local-level. For example, GDP, which is frequently
used as a proxy for both modernization and market expansion, is not measured at the
local-level. Therefore, in this thesis I use comparable proxy variables that are both
available at the local-level and relevant to coral reef resources.
26
Research gap 3: Geo-political context
As stated by Fisher & Freudenberg (2001), acknowledged by a key proponent of
ecological modernization (Mol 2003), and shown in table 1.1, the merit (explanatory
power) of each perspective will vary among different social and ecological contexts.
For the perspectives to develop therefore, it is essential to test them across a diverse set
of contexts. Yet, there exists bias towards studies focused on modernized and affluent
nations and societies (e.g. Schnaiberg 1980; Grossman & Krueger 1995; Mol 1995;
Weinberg et al. 2000; Luck 2007). The perspectives have not been compared and
contrasted within an economically disadvantaged, peripheral nation context. Yet, as
discussed in the perspectives’ limitations above, there is also strong evidence that the
position of a nation in the world system (Wallerstein 1974), be it peripheral, semiperipheral, or core, has a bearing on the state of its natural resources (Hoffmann 2004;
Bunker 2005; Shandra et al. 2009; McKinney et al. 2010). Therefore, there is a distinct
need to understand, better, the effects of societies on natural resources within a
peripheral nation context, where a large portion of global biodiversity exists (Myers et
al. 2000; Kramer et al. 2009). If, for example, there is no evidence of ecological
modernization in peripheral nations then it is possible that ecological modernization
observed in core nations and in global analyses is a result of core nations externalizing
their ecological footprints through resource importation and pollution exportation.
To address research gap 3, the social-political context for this thesis, as stated above, is
Solomon Islands, a peripheral nation that is highly dependent on marine resources
situated in the western Pacific. Compared to other countries and territories in the Asia
Pacific region, Solomon Islands is poor, has an average population density, and is
highly dependent on coastal resources for livelihoods (Table 1.2).Solomon Islands is
typical of a peripheral nation in that it has relied almost exclusively on resource
extraction, including logging and tuna fishing, for income. Round-log exports, for
example, accounted for between 50-68% of the country’s GDP between the years 19902000 (Central Bank of Solomon Islands 2000). On a smaller scale, a number of other
marine resources, including bêche-de-mer, trochus, and shark fin, have had a long
history of both legal and illegal export (Bennett 1987). And so, in contrast to core
nations, where the perspectives have been studied in greater detail, Solomon Islands is a
nation of net resource export and net pollution import (largely by environmental
degradation caused by logging and mining), and so is a contextually suitable location to
27
conduct this research. It could be argued that using a single nation would not present an
adequate range to test the merit of the modernization perspective (e.g. a large enough
range of modernization, relating to domestic inequality), however, our understanding of
what an adequate range might be is still limited, and non-linear effects of modernization
have been observed previously within single nations (Grossman & Krueger 1995;
M'henni et al. 2011).
Notably, several papers have begun addressing how these different perspectives explain
key aspects of coral reef conditions at the local-level in a coral reef context, including
study sites in peripheral nations. First, Cinner et al. (2009b) compared the Malthusian
overpopulation and modernization perspectives at the local-level, and found
modernization better explained much of the variance of the biomass of reef fish. The
same study also proposed and tested the effects modernization on a number of
mechanisms (akin to ‘pressures’, or proximate drivers, in this thesis) of fishery
exploitation; the aforementioned composition, technique and scale effects, and found
strong correlations between many of the indicator variables and modernization. Second,
Cinner et al. (2012a) compared the Malthusian overpopulation and market expansion
perspectives by meta-analysis on a global dataset. The results show that distance to
market, as a proxy for market expansion, better explained fish biomass than did
Malthusian overpopulation measured as human population density. Therefore, at the
local-level, within the ecological context of this thesis, there is strong support for both
the modernization and market expansion perspectives, which challenges the dogma of
Malthusian overpopulation. While very informative, neither of these studies tested all
three perspectives. Yet this is important in accounting for colinearity between the
perspectives and considering which perspective is dominant. Further, the first of these
studies was conducted in the western Indian Ocean, and the second was a global
analysis. Yet, there is evidence of regional variation in coupled coral reef socialecological systems (Pollnac et al. 2010). Therefore, Solomon Islands, situated in
Melanesia in the western Pacific Ocean, represents a spatially novel context in which to
test the merit of the perspectives.
28
Table 1.2 Dominant perspective attributes of Countries and Territories in the Asia Pacific region,
including coral triangle initiative member countries. Included here are key variables relating to each of
the three perspectives similar to those variables used in studies presented in Figure 1.1. GDP is a variable
commonly used at the nation-level to represent both the market expansion and ecological modernization
perspectives, and population density is commonly used to represent the Malthusian perspective. Further,
data on population employed in coastal fishing has been included to reveal both dependence on, and level
of market integration of, coastal fishing. Note that, for the region, Solomon Islands has a low GDP,
average population density, and high dependence on coastal fisheries.- = no data, * = Coral Triangle
member countries. Data on population size was derived from the World Bank (The World Bank Group
2004) and the United Nations Common Database (United Nations 2008) and the CIA World Fact book,
(CIA 2012). Coral reef area data was derived from the World Atlas of Coral Reefs (Spalding et al. 2001).
GDP data was sourced from the CIA World Fact Book (CIA 2008, 2013) and the United Nations (United
Nations 2008).
Countries and Territories in
the Asia Pacific region
Malaysia*
New Caledonia
French Polynesia
CNMI
Timor-Leste*
Palau
Indonesia*
Philippines*
Cook Islands
Fiji
Marshall Islands
Fed. States of Micronesia
Tonga
Vanuatu
Tuvalu
Samoa
Tokelau
Papua New Guinea*
Solomon Islands*
Kiribati
GDP per
capita (PPP)
(avg. 19902000)
$17,200
$16,606
$15,551
$10,950
$10,000
$5,657
$5,100
$4,500
$4,477
$2,259
$1,849
$1,807
$1,670
$1,286
$1,183
$1,078
$1,000
$932
$881
$499
Population
/ km2
coral reef
8230.11
39.16
42.61
1605.16
17.5
4922.78
4218.70
12.49
82.64
9.28
25.36
66.24
52.4
14.71
375.19
28.02
438.56
82.16
31.29
% Population
employed in
coastal
fisheries
14
25
30
32
14
10
45
79
34
33
60
69
29
Research gap 4: Triangulation using local perceptions.
None of the quantitative comparative studies relating to the dominant perspectives has
used local perceptions to triangulate conclusions. Understanding of local perceptions is
likely to contribute to both theory development and maturation. Local people within a
study system (e.g. fishers in a fishery) are likely to have knowledge that is not apparent
to system observers (e.g. scientists), and can therefore contribute additional knowledge
to understanding the social processes that lead to resource decline (e.g. Berkes et al.
2000; Johannes et al. 2000). Local perceptions are also likely to either support or refute
quantitative models, and therefore add weight to evidence, or force review of
conclusions drawn from quantitative models alone. Understanding of local perceptions
is also likely to aid in developing a realistic resource management agenda because, if
local perceptions are not aligned with scientific conclusions then the application of
scientific conclusions, for improved resource management will likely be untenable (see
Foale 2006 for a discussion on scientific and local knowledge relevant to the context of
this thesis).
I address research gap 4 by conducting interviews, using a survey, with fishers and
middlemen (fish traders) in Solomon Islands. The surveys were conducted in major fish
markets, where a large portion of the national reef fish catch is sold. A component of
the survey included a series of questions relating to the respondents’ perceptions of the
causes of coral reef fish abundance decline, and what they perceived would cause an
increase in coral reef fish abundance. The interviewer asked probing questions to
obtain the respondents’ perceptions beyond a single answer response. For example, if a
respondent perceived that fishing causes coral reef fish to decline, then the interviewer
would probe by asking what the respondent believed to be causing fishing to increase.
By doing so, qualitative responses were obtained that are comparable to the scientific
model presented in figure 1.3.
So far I have critically reviewed the dominant perspectives of the effects of society on
natural resources, individually, and in synthesis. I have also outlined four clear research
gaps and summarised how they are addressed in this thesis. I now proceed by outlining
30
the aim of this thesis including stated research objectives and an outline of the thesis
chapters.
1.4 RESEARCH OBJECTIVES
The aim of this thesis is to fill the aforementioned research gaps by 1) explaining
society’s effects on natural resources, at the local-level in an economically peripheral
nation, using dominant environmental sociology perspectives (research gaps 1-3), and
to 2) determine whether local perceptions, support or refute the scientific explanation
(research gap 4). These broad aims are achieved by completing the following research
objectives:
4. Determine which dominant environmental sociology perspectives, of
societies effects on natural resources, best explains the effects of exploitation
on;
a) Coral reef fish that are vulnerable to extinction by overfishing;
b) Function and diversity of coral reef fish;
5. Determine which of the perspectives explain the occurrence of coral reef
resource management institutions; and
6. Determine whether local perceptions support, or refute, the findings, as
identified in objectives 1 and 2, of society’s effects on the exploitation and
management of coral reef fish.
1.5 THESIS OUTLINE
The analytical component of this thesis is presented as three chapters, which comprise
four stand-alone manuscripts (two manuscripts in chapter 2, and one in each chapter’s 3
and 4; Figure 1.4). This section indicates the contribution of each chapter to the thesis
to filling the identified research gaps, by completing the thesis objectives.
31
Figure 1.4 Thesis chapter outline
1.6 SUMMARY OF THESIS CHAPTERS:
Chapter 1: General Introduction
This (i.e. current) chapter provided a review of the dominant perspectives on the social
causes of natural resource decline, and highlights limitations of each of the perspectives.
Research gaps were identified, including a brief overview of how the research gaps will
be filled in the thesis.
Chapter 2: Social determinants of coral reef resource distributions
In this chapter, I quantitatively test the relative merit of each of the three perspectives in
explaining the coral reef fish distributions using comparative methods (grey dashed line
32
in Figure 1.5). This chapter focuses on the relationships between proxy variables for
each of the perspectives and exploitation (fishing) pressure on coral reef ecology (the
next chapter focuses on the relationship between proxy variables for each of the
perspectives and resource management institutions). The analysis includes 25 sites
across Solomon Islands. The chapter is divided into two papers, with one focused on
how the dominant human-environment perspectives explain the distribution of coral
reef finfish that are vulnerable to exploitation by fishing, and the other paper focused on
how these perspectives explain the ecological function and diversity of finfish. The
rationale for writing two papers was that the ecological measures in each paper
represent different dimensions of the ecology of coral reef fish. The paper on fish that
are vulnerable to overfishing is more relevant to fisheries livelihoods, whilst the paper
on function and diversity is more relevant to ecosystem resilience. Both papers partly
fill research gap 1 by including fishing and coral reef habitat as a mediating variables
within the models. The studies are conducted at the local-level, in a peripheral nation,
Solomon Islands, and therefore both papers also address research gaps 2 and 3. The
results of both papers show that, within the study context, both local human population
pressure and access to markets explains the use of sophisticated fishing gear, which, in
turn, best explains lower biomass of fish that are vulnerable to overfishing, and
decreased fish species diversity, and biomass of key functional groups. Thus local
population growth and market access are likely driving ecological decline, which
supports the Malthusian overpopulation and market expansion perspectives
respectively, and refutes the modernization perspective.
Figure 1.5 Generalised model used in this thesis to test the relative merit of each of the three dominant
perspectives for explaining natural resource state. Grey dashed line is the component of the model
addressed in chapter 2. Black dashed line is the model component addressed in chapter 3. Thus, the
33
application of this novel model addresses research gap 1, and applying it at the local-level in a peripheral
nation addresses research gaps 2 and 3. Chapter 4, which addresses research gap 4 is derived from
perceptions based research so does not fit the model a priori.
Publications derived from chapter 2:
Brewer, T.D., Cinner, J.E., Green, A., Pressey, R.L. Local human population density
and proximity to external markets explain patterns of exploitation of vulnerable coral
reef fishes. Conservation Biology. DOI: 10.1111/j.1523-1739.2012.01963.x
Brewer, T.D., Cinner, J.E., Fisher, R., Green, A., Wilson, S.K. 2012. Market access,
population density, and socioeconomic development explain diversity and functional
group biomass of coral reef fish assemblages. Global Environmental Change. 22; 399406
Chapter 3: Social determinants of coral reef resource management institution
occurrence
In this chapter I empirically examine the relative merit of each of the three perspectives
in explaining the occurrence of coral reef resource management institutions using
comparative methods (black dashed line in Figure 1.5), and thus fill, in part, research
gap 1. I also fill, in part, research gaps 2 and 3 because, as with chapter 2, it is
conducted in Solomon Islands at the local-level. I conclude that human population
density has a dramatic negative effect on the likelihood of any given community having
fishery management institutions, which lends weight to the Malthusian overpopulation
perspective. Yet, relatively modernized (modernization was measured as summed
infrastructure and amenities in communities) communities and communities with fish
markets are more likely to have a fishery management institution that could help
mediate a given population’s environmental impact. These findings lend weight to the
modernization perspective, but detract from the market expansion perspective.
Therefore, based on the results of chapters two and three, I conclude that local
population pressure (Malthusian overpopulation) intensifies exploitation and has a
negative effect on management; access to markets (market expansion) also intensifies
exploitation, but has a positive effect on management; and infrastructure and amenities
34
(modernization) has minimal effect on exploitation, and a positive effect on
management.
Publication derived from chapter 3:
Brewer, T.D., Kool, J.K., Foale, S., Cinner, J.E. Social and economic drivers of natural
resource management institution occurrence. In preparation
Chapter 4: Fisher and middlemen perceptions of coral reef fish decline and
increase
This chapter, based on field surveys with fishers and fish middlemen in Solomon
Islands, assesses local perceptions of the causes of reef fish decline and increase.
Comparison of local perceptions with the findings of chapters two and three fills
research gap 4. Perceived causes of fishery decline and recovery were numerous, based
on results of surveys with 119 respondents. However, dominant themes emerged
including the role of fish markets in causing fish decline, and the role of access to
consumables, by modernization, increasing fishing effort to result in fishery decline. I
conclude that local perceptions are similar to the findings presented in chapters two and
three, and to previous published literature. Therefore, management intervention, based
on scientific evidence, might be well received.
Publication derived from chapter 4:
Brewer, T.D. 2013. Dominant discourses, among fishers and middlemen, of the factors
affecting coral reef fish distributions in Solomon Islands. Marine Policy. 37; 245-253
Chapter 5: General discussion and conclusions
This, the final chapter, summarises the findings of the thesis and discusses them in the
context of the dominant perspectives of society’s effects on natural resources.
Discussion and theoretical contributions relating to each of the three data chapters (four
papers) is contained within each respective chapter. Therefore those chapter-specific
points of discussion and theoretical contribution will not be repeated here. Instead I 1)
review the research gaps, show how they have been addressed in this thesis, and
highlight how addressing the research gaps contributes to theory, 2) present a unified
narrative of society’s effects on coral reef fishery resources in Solomon Islands as the
35
broad theoretical contribution of this thesis, 3) discuss limitations to the thesis, and
associated future research, and 4) draw general conclusions.
Note regarding chapter terminology and consistency
Because this is a thesis by publication, each of the four papers had to be tailored to the
journal audience and editorial requirements of specific journals. To provide consistency
throughout the thesis, I have amended the contents of the publications to make
terminology consistent, minimise redundancy, and maintain a consistent voice.
36
CHAPTER 2: SOCIAL DETERMINANTS OF CORAL REEF
RESOURCE DISTRIBUTIONS
37
38
CHAPTER 2A: SOCIAL DETERMINANTS OF THE
EXPLOITATION OF CORAL REEF FISHES THAT ARE
VULNERABLE TO FISHING11
ABSTRACT
Coral reef fisheries are crucial to the livelihoods of tens of millions of people, yet
widespread habitat degradation and unsustainable fishing are causing severe depletion
of reef fish stocks. Understanding how social and economic factors such as human
population density, access to external markets, and modernization interact with fishing
and habitat to affect fish stocks is vital to sustainably managing coral reef fisheries.
This chapter assessed whether these factors explain variation in biomass of coral reef
fish among 25 sites in Solomon Islands, with in situ fish data and national social and
economic data, using structural equation models. I categorized fishes into three groups
based on life history characteristics that make certain fishes more, or less, vulnerable to
extinction. The results show that the biomass of fish with low extinction vulnerability
was positively related to habitat. The biomass of fish with high extinction vulnerability
was negatively related to fishing using efficient gear that, in turn, was strongly
positively related to both population density and market proximity, suggesting additive
effects. Biomass of the fish species of medium extinction vulnerability was not
explained by fishing intensity or habitat, which suggests these species might be resilient
to both habitat degradation and fishing.
11
Brewer, T.D., Cinner, J.E., Green, A., Pressey, R.L. 2013. Local human population density and
proximity to external markets explain patterns of exploitation of vulnerable coral reef fishes.
Conservation Biology. 27; 443–452
39
2A.1 INTRODUCTION
Conservation actions frequently aim to reduce the proximate drivers of natural resource
decline, such as unsustainable fishing or land clearing. However, a sole focus on
managing proximate drivers can limit the efficacy of local conservation action by
overlooking the underlying drivers of resource exploitation (Geist & Lambin 2002;
Kramer et al. 2009). Alternatively, underlying drivers (hereafter distal drivers) such as
human population growth, economic inequality, and per capita wealth have been used to
directly explain variability in the condition of natural resources (York et al. 2003a;
Bradshaw et al. 2010). However, these distal drivers are conceptually remote from the
natural resource in question, making inference of causality tenuous (Mills & Waite
2009). For example, in the context of small-scale fisheries, modernization (which
reflects not only affluence as in economic development, but also variables such as
access to infrastructure and institutions) does not affect the biomass of targeted in situ
fish stocks per se, but could affect proximate drivers such as increased access to, and
subsequent use of, more efficient fishing gears that might, in turn, decrease fish stock
biomass (Cinner et al. 2009b).
Here, I explore how elucidating relationships among distal drivers, proximate drivers,
habitat and natural resources can inform conservation and management actions. I
investigate whether potential distal and proximate drivers explain coral reef fish
biomass across a gradient of social and economic conditions in Solomon Islands.
Theoretical and empirical work on social-ecological interactions suggest three dominant
perspectives of how societies affect the state of natural resources and so provide a
foundation for this investigation.
2A.1.1 DOMINANT PERSPECTIVES
Malthusian overpopulation
First, local human demography influences the status of natural resources; increasing
human population density is generally thought to cause resource decline (see Malthus
1798 for foundational theory). Population size of people has been shown to negatively
40
correlate with small ecological footprints (York et al. 2003a; Dietz et al. 2007), low
absolute environmental impact (Bradshaw et al. 2010), species richness of threatened
mammals and birds (McKinney et al. 2010), high mean trophic level of marine fish
(Clausen & York 2008a), and the extent of distributions of threatened marine and
freshwater fish (Clausen & York 2008b). I hypothesize three ways in which increased
local human population pressure can deplete coral reef fish stocks: increase in fishing
intensity using basic fishing gear for local consumption; increased use of efficient
fishing gear as human population size increases concordant with ‘Malthusian
overfishing’ (Pauly 1988); and reduction in habitat quality via direct damage and runoff
of land-based pollutants.
Market expansion
Second, declines in local resources can also result from net resource export through
increased production driven by access to markets (see Schnaiberg 1980 for foundational
theory). The state of coral reef fisheries has been shown to correlate negatively with
proximity to domestic markets (Cinner & McClanahan 2006; Brewer et al. 2009;
Aswani & Sabetian 2010) and international trade in coral reef fish (Warren-Rhodes et
al. 2003). I hypothesize that market proximity, as a proxy for market expansion, can
deplete fish stocks via two key proximate drivers: increasing fishing intensity using
efficient gears to supply external markets; and degradation of habitat caused by efficient
gears which damage habitat structures.
Modernization
Third, considerable research has shown that modernization and associated affluence can
influence the ways in which societies use natural resources. Modernization is related to,
for example, the tools that societies use to produce goods and services, the types of
goods and services traded, the ability of societies to extract resources from distant
locations, and the ability of societies to fund scientific and resource management
institutions (Arrow et al. 1995). Relations between modernization and resource
conditions can be complicated, with some empirical observations of a nonlinear Ushaped relation inferring improved environmental condition at high levels of
modernization (see Grossman & Krueger 1991 and; Mol et al. 2010 for foundational
41
theory). This type of relation has been observed in, for example, fish catch (Clausen &
York 2008a), in situ fish biomass (Cinner et al. 2009b), the number of threatened bird
species (Naidoo & Adamowicz 2001), CO2 emissions (Rosa et al. 2004), city air
pollution and water quality (Grossman & Krueger 1995), and deforestation (EhrhardtMartinez et al. 2002). Thus, one hypothesis is that modernization could have a
nonlinear effect on fish stocks by increased fishing pressure and habitat degradation at
low levels of modernization followed by a decline in fishing pressure, and reduced
habitat degradation at higher levels of modernization. An alternative hypothesis is that
modernization is achieved through exploitation of natural resources and its relationship
with the condition of natural resources is consistently negative.
To date, no studies have simultaneously looked at the relative importance of these three
perspectives in explaining fish biomass distributions across a gradient of vulnerability to
human activities. To address this, we collected social, economic, and ecological data
from 25 sites across Solomon Islands (Figure 2A.1) and examined relationships
between three distal drivers (population density, access to fish markets, and
modernization), two proximate drivers (fishing with basic gears requiring small capital
investment and fishing with efficient gears requiring large capital investment), habitat
(coral cover), and in situ reef fish biomass.
Figure 2A.1 a) The main islands of Solomon Islands showing study site locations, and b) a generalized
image of a study site including marine site boundary, ecological sampling location, coral reef area, and
villages.
42
2A.2 METHODS
2A.2.1 FISH BIOMASS AND VULNERABILITY
Fish biomass data were collected at 66 sites across the Solomon Islands between May to
June 2004 using underwater visual census along five 50m belt transects at each site, at a
depth of 10 m (Green et al. 2006) (see Appendix 2 for detailed sampling method).
From these survey data, we used a measure of vulnerability to extinction (hereafter
‘vulnerability’) based on the index developed by Cheung et al. (2005), and available
from FishBase (Froese & Pauly 2011). This index scores each species’ vulnerability (0
to 100) based on ecological characteristics and life history traits. I grouped an
approximately equal number of species into the three categories of vulnerability: low
(n=111), medium (n=90), and high (n=85) (Table 2A.1). It was not possible to assign
an equal number of species to each category because many species had the same
vulnerability score (Appendix 3). In cases where fish were not identified to species they
were assigned the mean vulnerability of recorded species within the respective genera
from within the sample. Species from families Kyphosidae, Diodontidae and
Synodontidae were omitted because no vulnerability values were available within the
sample at the genus level. I omitted families Carangidae and Caesionidae because their
species are highly mobile (Thresher & Gunn 1986) and can form large schools (Graham
et al. 2003), and both characteristics could have affected the accuracy of the belt
transect sampling technique. We included all other demersal reef fish. Biomass was
then summed for each vulnerability category at each site (Appendix 3).
43
Table 2A.1 Potential distal and proximate drivers, habitat, and resource state variables used in models, including raw data, data sources, and pre-model
transformations.
a
Data
Supporting
Variables within model components
Pre-model transformations
source
literatureh
Human population density
Human population density
SICd
Market proximity
Shortest distance from ecological survey
location to the nearest local fish market
(lfm), provincial capital (pc), and national
capital (nc), by road and sea
Presence of pre-school, kindergarten,
primary school, community high school,
clinic, wharf, trade store, supermarket,
postal service, fuel depot, credit facility,
bank, airport
Ln (human population/km2 coral
reef)
Sum (lfm + pc + nc)
SIVRS;
SIDLHSe
1, 2, 3, 4, 5,
6, 7, 8, 9, 10.
12, 13, 14,
15.
Ln (sum (all modernization
variables/number of villages))
SIVRSf
11.
Population consuming fish (cf)
No. fishing lines (fl)
No. wooden canoes (wc)
Population selling fish (sf)
No. eskies (e)
No. fibreglass boats (fb)
No. spear guns (sg)
No. fishing nets (fn)
PCAc (ln(cf/km2 coral reef) +
ln(fl/km2 coral reef) + ln(wc/ km2
coral reef))
PCA (ln(sf/km2 coral reef) +
ln(e/km2 coral reef) + ln(fb/km2
coral reef) + ln(sg/km2 coral reef)
+ ln(fn/km2 coral reef))
SIC;
SIVRS
% live coral cover
N/A
REAg
All demersal fish
Vulnerability scoreb = 10 to 23
Biomass/ha.
Biomass/ha.
REA
REA
Model Components
Distal Drivers
Modernization
Proximate Drivers
Small-investment, basic gear
fishing
Large-investment,
gear fishing
efficient
SIC;
SIVRS
Habitat
Live coral cover
16, 17, 18.
Fish Biomass
All demersal fish
Low vulnerability fish
44
Medium vulnerability fish
Vulnerability score = 24 to 35
Biomass/ha.
REA
High vulnerability fish
Vulnerability score = 36 to 76
Biomass/ha.
REA
a
Description of acronyms of variables within model components: lfm - a small local market where reef fish are likely to be frequently sold. pc - a capital exists in each
of the provinces, and each capital has frequently operating fish markets, likely to be larger than local fish markets, and selling fish at a higher price. nc - national
capital, having the largest fish market in the nation, where fish prices are likely to be higher than elsewhere, attracting fish sellers from further afield. cf - the number of
people consuming fish at each study site. fl - fishing lines, likely comprising mainly handlines. wc - wooden canoes are typically dugouts powered by paddle. sf - the
number of people selling fish at each site. e - insulated ice boxes frequently used for preserving perishable food including fish. fb - fibreglass boats are typically 5m to
8m in length and powered by outboard motors. sg - spearguns are likely to include both Hawaiian sling-like spears which do not have a trigger mechanism, but are
exceptionally efficient when used at night, and some more advanced models with trigger mechanisms, either locally made or imported. fn – fishing nets are likely to
include both traditional bush material nets and nylon gill nets.
b
See Cheung et al. (2005)
c
Principal Components Analysis
d
Solomon Islands 1999 National Census
e
Solomon Islands Departments of Lands, Housing, and Survey
f
Solomon Islands 2008 Village Resource Survey
g
Rapid Ecological Assessment (Green et al. 2006)
h
Supporting literature: 1. Jennings & Polunin (1996), 2. Jennings & Polunin (1997), 3. Dulvy et al. (2004a), 4. Dulvy et al. (2004b), 5. Newton et al. (2007), 6.
Williams et al. (2008), 7. Mora (2008), 8. Sandin et al. (2008), 9. Stallings (2009), 10. Mora et al. (2011), 11. Cinner et al. (2009b), 12. Cinner & McClanahan (2006),
13. Brewer et al. (2009), 14. Aswani & Sabetian (2010), 15. Schmitt & Kramer (2010), 16. Friedlander & Parrish (1998), 17. Graham et al. (2008), 18. Beger &
Possingham (2008). Citations are only to literature that provides quantitative evidence of effects on resource state, in a coral reef context.
45
2A.2.2 SOCIAL AND ECONOMIC DATA
Social and economic data were derived from national surveys including national census
data (Solomon Islands Government 1999), and a national village resource survey
(Solomon Islands Government 2008) (Table 2A.1). All social and economic data were
measured at the village scale. I defined the spatial extent of each site to determine
which villages (and the related social and economic data) were associated with the fish
data from the rapid marine assessment. The spatial extent of each site was elicited from
individuals possessing local knowledge of marine resource use by people residing in
villages adjacent to the fish survey location. The interviews were conducted in Honiara,
the national capital. One constraint of this method is that, particularly for finfish, site
boundaries are not necessarily strictly adhered to; probably due to their relatively low
economic value compared to other fisheries such as trochus and bȇche-de-mer (Ruddle
1996). Therefore fishers with adequate transport are able to fish over vast distances,
rather than being constrained to their territories. Alternative methods exist for
estimating resource use boundaries, including friction mapping using thiessen polygons
(Mulller & Zeller 2002), ethnographic studies (Aswani 1999), and participatory GIS
mapping (Aswani 2011). However, the large-scale nature of this study inhibited the use
of these more localized resource use mapping techniques. The marine boundary, as
elicited from experts, was defined as the area within the vicinity of fish survey sites
likely to be exploited by people living in villages within 1 km of the adjacent coastline
(Fig. 2A.1b). Boundaries were drawn on 1:150,000 digital maps.
Distal Drivers
Three variables were used to represent potential distal drivers associated with each of
the perspectives of how societies affect natural resources: human population density,
market proximity, and modernization (Table 2A.1; Figure 2A.2). Human population
density was measured as the total number of inhabitants within the boundary of each
site per coral reef area (km2). Fisher mobility across boundaries is likely to constrain the
accuracy of this method of measuring human population density as mentioned above.
However, this method is used based on the assumption that there is not bias fishing
effort outside marine boundaries across the study sites. Coral reef area was measured at
each site by tracing all visible coral reef within site boundaries, using Google Earth
46
Pro, defined as the total visible coral reef area within site boundaries, as derived from
the expert elicited site boundary maps (Fig. 2A.1b) (Brewer et al. 2009). Market
proximity was measured as the shortest distance from the centre of each ecological
sample location to the centre of the nearest local fish market, provincial capital, and
national capital (all of which have fish markets) using roads and sea as possible routes
within the same distance measure, using ArcGIS (Table 2A.1). A single measure of
market proximity was developed, for each site, by summing the unweighted distances
from the ecological sampling location to the nearest local fish market, provincial
capital, and the national capital (Table 2A.1). Modernization was measured as the sum
of a set of unweighted infrastructures and amenities within site boundaries (Table
2A.1), using indicators of modernization similar to previous studies (Cinner et al.
2009b; Pollnac et al. 2010). The aggregate score for each site was then divided by the
number of villages at each respective site, to control for infrastructure and amenity
accessibility (Cinner & McClanahan 2006).
Proximate Drivers
Two potential proximate drivers (Table 2A.1) likely to mediate the effect of distal
drivers on fish biomass were measured: small-investment fishing using basic gear
(hereafter “basic gear fishing”), and larger-investment fishing using efficient modern
gear (hereafter “efficient gear fishing”) (Figure 2A.2). Basic gear fishing was measured
as the total human population consuming fish, the numbers of wooden canoes (Photo
2A.1), and the number of fishing lines, all expressed per km2 of reef area at each site,
the data for which were derived from the census and village resource survey (Table
2A.1). Efficient gear fishing was measured as the total human population selling fish
and numbers of fiberglass boats (Photo 2A.2), insulated ice boxes (referred to as
“eskies”) (Photo2A.3), spearguns, and fishing nets, all expressed per km2 of coral reef at
each site, the data for which were also derived from the census and village resource
survey (Table 2A.1). Within basic and efficient gear categories, we combined the
variables using Principal Components Analysis (PCA) for each fishery separately. The
two fishing types were distinguished by the investment required to acquire and maintain
the respective gears, and the relative increase in catch-per-unit-effort that can be
expected with efficient gear (Hallwass et al. 2011). Basic gears and efficient gears also
reflect fishing for local use and fishing for markets respectively.
47
Photo 2A.1 Fishers in traditional wooden paddle canoes in Roviana lagoon, heading out to the reef edge
for fishing at dusk.
Photo 2A.2 A typical fibreglass boat used for fishing and transport throughout Solomon Islands. Most are
roughly 5 -7 metres in length, equipped with a 6-15 horsepower engine. They require significant financial
outlay and are costly to run due to local fuel and fibreglass costs, as well as outboard maintenance, but far
more efficient and stable than dug-out canoes. This particular boat belonged to Michael Giningele, the
father of Joe, who assisted with the field work for this thesis.
48
Photo 2A.3 A very kind fish seller, ‘Buss’, who introduced me to fish sellers at the Honiara market. Seen
here replenishing ice in his esky on a hot day at the Fishing Village market situated on the outskirts of
Honiara.
Habitat
Habitat occurrence and condition is an important determinant for explaining ecological
communities. Habitat was defined as percent living coral cover (Table 2A.1) which has
previously been shown to explain reef fish distributions (e.g. Friedlander & Parrish
1998; Beger & Possingham 2008; Graham et al. 2008; Pinca et al. 2012) (Figure 2A.2).
To do this substrate type was measured, including coral cover, at three points every 2m
along five 50m belt transect (totalling 375 points at each survey location), using the
same transects used in the fish survey (Hughes 2006).
2A.2.3 LINKING FISH DATA TO SOCIAL AND ECONOMIC DATA
A number of the initial 66 ecological survey sites could not be included in the final
analysis. Reasons included incomplete fish data, absence of social and economic data,
unclear association between villages and ecological data (due largely to complex
resource-use rights determined by genealogies), and the need to reduce ecological
49
variability by omitting fish survey locations classified as sheltered from prevailing
weather (Karlson et al. 2004). Consequently, prior to analysis, the data set included
three potential distal drivers, two potential proximate drivers, habitat, total fish biomass,
and fish biomass in three vulnerability categories: low, medium and high (Table 2A.1)
for 25 sites.
2A.2.4 ANALYSIS
Partial least squares regression, in the program Warp PLS, was used to build structural
equation models (SEMs) (Figure 2A.2). Partial least squares was chosen over
covariance-based approaches primarily because it suited the small sample size (Chin &
Newstead 1999; Reinartz et al. 2009). Distal drivers, proximate drivers and habitat
variables remained consistent across models with only the fish biomass response
changing between models. This resulted in unique models for each of the four fish
biomass categories - total fish biomass, biomass of fish of low vulnerability, biomass of
fish with medium vulnerability, and biomass of fish of high vulnerability - each of
which had the structure presented in figure 2A.2. The partial least squares method
partials out each analysis (e.g. the effect of population density and modernization on
coral cover) from the overall model and therefore, in this study, is equivalent to sets of
non-linear regressions, except that overall model fit statistics are also generated. The
models were bootstrapped, set at 999 iterations. All models were constrained to secondorder polynomial relationships, thereby allowing simple, non-linear relationships
between variables. Warp PLS software has an inbuilt function whereby the relationship
between two variables will default to a smaller order polynomial if it is deemed linear
(Kock 2010). The output generated included individual standardized path coefficients
(β), partial model fit scores (r2) and overall model p values calculated through
resampling estimations coupled with Bonferroni-like corrections (Kock 2010). The
total effect of each distal driver (market proximity, modernization and population
density) was calculated by multiplying the standardized coefficients (β) within each
pathway then summing these values for pathways associated with each distal driver.
50
Figure 2A.2 Schematic structural equation model of the social and economic determinants of coral reef
fish biomass distributions. Arrows show hypothesized correlations between variables within the model.
Unknown effect of modernization due to divergent perspectives. Note “Population density” is the
dominant surrogate variable for the “Malthusian overpopulation” perspective, and “Market proximity” is
the dominant surrogate variable for the “market expansion” perspective.
2A.3 RESULTS
2A.3.1 DATA REDUCTION
One principal component was adequate to describe each fishing intensity variable: basic
gear fishing (λ = 2.4; variance explained = 79.3%) and efficient gear fishing (λ= 3.3;
variance explained = 65.4%). The variables that comprised both basic gear and efficient
gear fishing had positive factor loadings of ≥ 0.65 on each principal component, and
therefore all variables contributed positively and strongly to each respective fishing
intensity variable. The mean density, per reef area, of basic gear fishing variables was
markedly higher than those representing efficient fishing (Figure 2A.3).
51
Figure 2A.3 Density of variables comprising basic gear fishing and efficient gear fishing, across sites.
The central bar within the box represents the median value. The range within the closed box represents
the middle 50% of data points (25% below and 25% above the median). The range between the ends of
the box and the ‘whisker’ lines represents the upper and lower 25% of data, excluding outliers.
2A.3.2 EFFECTS OF DISTAL DRIVERS ON PROXIMATE DRIVERS AND HABITAT
Distal drivers explained much of the variance of the proximate drivers and some of the
variance of coral cover. Together, the three distal drivers - modernization, population
density and market proximity - explained 76% of the variance of efficient gear fishing.
Modernization and population density explained 82% of the variance of basic fishing
gear. Modernization, population density and efficient gear fishing explained 33% of the
variance of coral cover. Therefore, the distal drivers proved to be good predictors of
fishing, but poor predictors of our measure of habitat condition.
52
2A.3.3 DISTAL AND PROXIMATE DRIVERS OF TOTAL FISH BIOMASS
Total fish biomass was best explained proximately by the negative effect of efficient
gear fishing (β = -0.62; p <0.01) (Figure 2A.4A). Coral cover had a non-significant (p ≥
0.05) negative effect on total fish biomass, and basic gear fishing had a negligible
effect. The two proximate drivers and coral cover explained 40% of the variance of
total fish biomass. The effect of efficient gear fishing on total fish biomass was
explained by both population density (β = 0.39; p <0.01) and market proximity (β =
0.55; p <0.05). Modernization had a weak negative effect (β = -0.1; p ≥ 0.05) on
efficient gear fishing. Therefore, population density and market proximity together,
through increased efficient gear fishing, best explained the distribution of total coral
reef fish biomass in Solomon Islands.
2A.3.4 DISTAL AND PROXIMATE DRIVERS OF FISH BIOMASS IN VULNERABILITY
CATEGORIES
The biomass of fish with low vulnerability to fishing was best explained proximately by
coral cover (β = 0.39; p <0.01) (Figure 2A.4B). Basic gear fishing also had some weak
negative effect (β = -0.21; p ≥ 0.05). These two proximate drivers combined and coral
cover explained only 26% of the variance of low vulnerability biomass. Coral cover, in
turn, was partly, but not significantly, explained by efficient gear fishing (β = -0.38; p
=0.06). Therefore, coral cover had a clear positive effect, but no distal drivers had a
discernable effect, on the biomass of fish with low vulnerability. The biomass of fish
with medium vulnerability to fishing was not significantly (p >0.05) explained by any
of the proximate drivers or coral cover (Figure 2A.4C). The biomass of fish with high
vulnerability was best explained by fishing with efficient gears, which, as with total
biomass, was explained by both population density and market proximity (Figure
2A.4D). Coral cover had a negative, but not significant, effect on the biomass of fish of
high vulnerability. This unexpected effect might be explained by one site that had low
coral cover but exceptionally high biomass of highly vulnerable fish. Combined, the
two proximate drivers and coral cover explained 36% of the variance of high
vulnerability biomass.
53
Figure 2A.4 Structural equation modeling results (SEM) of the total effect size (determined by multiplication of path coefficients (β) along each distinct path, prior to
summing of distinct paths) for the different distal and proximate drivers for each of the resource state variables based on the general model (Fig. 2A.2). Unshaded bars
show direct effects of coral cover, basic gear fishing, and efficient gear fishing on fish biomass. Black bars show the effect of distal drivers and efficient gear fishing on
each category of vulnerability through coral cover. Dark grey bars show the effect of distal drivers on fish biomass through basic gear fishing. Light grey bars show the
effect of distal drivers on fish biomass through efficient gear fishing. APC = average path coefficient (β) value within the model. ARS = average variance explained
(r2) within the model from each of four response variables. AVIF = average variance inflation factor. (*p ≤0.05, *p ≤0.01, *p ≤0.001).
54
2A.4 DISCUSSION
This study determined whether potential distal and proximate drivers explained spatial
variation in the biomass of reef fish in Solomon Islands. Total fish biomass was explained
proximately by fishing with efficient gears, which was, in turn, explained by market
proximity and population density. However, the findings differed when total fish biomass
was disaggregated into low, medium, and high vulnerability categories. Variation in
biomass of low vulnerability reef fish was explained proximately by living coral cover.
This suggests that fish that are less vulnerable to fishing are likely vulnerable to factors that
degrade habitat (Graham et al. 2011). As with total biomass, the biomass of high
vulnerability fish species was explained proximately by fishing with efficient gear, which
in turn was significantly explained best by market proximity but also by population density.
This suggests that fish in this highly vulnerable category are sensitive to multiple human
activities, requiring a multifaceted management approach to ensure their persistence.
Variation in biomass of fish species of medium vulnerability was not explained
significantly by any of the proximate drivers. In a study using creel survey (fish landings)
data from the neighbouring country of Papua New Guinea (where fishing techniques could
be considered broadly comparable), only 34% (31/90) of species in the medium
vulnerability category were recorded in catch records (Cinner et al. 2009c) , suggesting that
the majority of medium vulnerability species are not targeted by fishers. Furthermore, the
medium vulnerability fishes only comprised 13% of 223 species targeted by Papua New
Guinea fishers. Understanding the functional roles of fish (i.e. the roles of different fish
assemblages in maintaining broader ecosystem function) in this medium vulnerability
category could lend insight into the potential resilience of coral reefs to both habitat
degradation and fishing pressure.
Broadly, the findings suggest that, in Solomon Islands, market proximity and local human
population density explain the effects of fishing on fish biomass distributions. The strong
relationship observed between human population density and fish biomass supports
previous studies (e.g. Jennings & Polunin 1997; Mora 2008; Williams et al. 2008) and the
55
Malthusian overpopulation perspective. This simultaneous exploration of distal and
proximate drivers showed that the effect of population density on fish biomass was greatest
through the use of efficient fishing gear. This finding provides some support for the
‘Malthusian overfishing’ concept, whereby growing local human populations overexploit
resources, and use more efficient technologies to maintain exploitation levels, which can
ultimately lead to resource collapse (Pauly 1988). However, consistent with other detailed
studies in the region (e.g. Cinner & McClanahan 2006), this study also shows that market
proximity can have an equal or greater effect, which supports the market expansion
perspective.
Market proximity best explained the biomass of coral reef fish in Solomon Islands.
Market-driven investment in technology to improve profitability has previously been
observed in the Solomon Islands reef fishery (Sabetian & Foale 2006; Brewer et al. 2009).
Increased market access, through road construction, has been shown elsewhere to increase
fish sales to non-local buyers, and increase the diversity of marine products sold at markets
(Schmitt & Kramer 2010). More broadly, the importance of market proximity in
explaining resource state highlights a key future challenge for conservation initiatives in the
face of increased trade in diminishing natural resources, particularly with increasing
globalization that could make social-ecological systems more open to trade and migration
(Wallerstein 1976; Berkes et al. 2006; Kramer et al. 2009).
56
Photo 2A.4 The fish section in the Honiara fish market. On busy days, when many of the provincial ships are
in port there can be in excess of 30 esky’s containing roughly 150kilograms of fish. The high prices at the
central market mean fishers and traders are drawn from across much of Solomon Islands to sell their catch.
Previous research (Brewer et al. 2009) has shown the significant negative relationship between the distance to
this particular market and reef fish biomass.
Modernization was not significantly correlated with fishing using basic or efficient gear, or
coral cover. Therefore, the level of modernization was not related to the state of coral reef
fisheries in Solomon Islands through any of the pathways hypothesized in this study. One
plausible explanation is that our study was conducted over a limited modernization gradient
within a single country that is at the lower end of the development spectrum (United
Nations Development Programme 2009).
The application of structural equation modeling in this study allowed exploration of how
distal drivers explain relationships between proximate drivers and resources. Distal drivers,
and particularly population density and market proximity, explained the effect of fishing on
57
resources. However, responses varied greatly depending on the path between distal driver
and fish biomass. Broadly, these results suggest that distal drivers do affect local patterns
of resource exploitation, so need to be considered in the development of resource
management strategies, but the results also indicate that the responses of resource state can
be both complex and variable. The results suggest that successful reef fishery management
initiatives will require multiple strategies that include local-level conservation efforts such
as locally managed protected areas (Aswani & Lauer 2006), gear restrictions (McClanahan
& Cinner 2008; McClanahan 2010), and improved governance of markets across all levels
of institutions involved in the trade of reef fish.
58
CHAPTER 2B: SOCIAL DETERMINANTS OF THE
DIVERSITY AND FUNCTION OF CORAL REEF FISH
ASSEMBLAGES12
ABSTRACT
There is overwhelming evidence that many local-level human activities (e.g. fishing) have a
deleterious effect on coral reef fish assemblages. Our understanding of how broad social
phenomena (e.g. modernization) affect the diversity and function of coral reef fish
assemblages however, is still poor. Here, structural equation models are used to reveal how
human population density, modernization, and market proximity affect fishing pressure and
coral cover to, in turn, explain the diversity and biomass of key functional groups of reef
fish assemblages within Solomon Islands. Fishing pressure is predominantly driven by
both market proximity and local population density, and has a clear negative effect on the
diversity and function of coral reef fishes. The strong positive effect of market proximity
on fishing pressure makes clear the importance of understanding social-ecological linkages
in the context of increasingly connected societies. This study highlights the need to address
broad social phenomena rather than focusing on proximate threats such as fishing pressure,
to ensure the continued flow of coral reef goods and services in this time of rapid global
social and environmental change.
12
Brewer, T.D., Cinner, J.E., Green, A., Fisher, R., Wilson, S. 2012. Market access, population density, and
socioeconomic development explain diversity and functional group biomass of coral reef fish assemblages.
Global Environmental Change 22: 399-406
59
2B.1 INTRODUCTION
There is overwhelming evidence that human activities are profoundly altering marine
ecosystems on a global scale (e.g. Hughes 1994; Pandolfi et al. 2003). Of particular
concern are the poorly understood, yet potentially disastrous environmental changes that
human activity is causing to the functioning of coral reef ecosystems upon which millions
of people depend (Mora et al. 2011). Ecosystem function is conceptually and analytically
complex, requiring a diverse array of metrics to understand ecosystem response to human
activity. High biological diversity is thought to contribute to maintaining ecosystem
resilience (e.g. McCann 2000; Cardinale et al. 2006; Tilman et al. 2006) through increased
response diversity to perturbations and functional redundancy (Naeem 1998; Chapin III et
al. 2000; Hooper et al. 2005; but see Ives & Carpenter 2007; Maestre et al. 2012), assuming
that species respond to threats uniquely. The use of diversity metrics as surrogates for
ecosystem function however, does not come without criticism. There is, for example, some
evidence that particular species (Bellwood et al. 2003; Bellwood et al. 2006; Hoey &
Bellwood 2009), and functional groups (e.g. Hughes et al. 2007) perform
disproportionately important functional roles, acting as energy conduits through trophic
levels and maintaining broader ecosystem processes. Therefore, it is important to consider
measures of both diversity and functional groups to understand how ecosystems may
respond to human activities.
Coral reef fishes are vital to ecosystem function, and provide significant goods and services
to people. A range of factors has been identified as important drivers of the diversity,
biomass, and abundance of reef fish functional groups. At large biogeographic scales,
distributions of diversity and function can be explained by environmental factors, including
available habitat, latitude-longitude gradients, the mid-domain effect, gyre influence,
history of environmental stress, and larval subsidy from species-rich regions (Bellwood &
Hughes 2001; Connolly et al. 2003; Mora et al. 2003; Bellwood et al. 2005; Mora &
Robertson 2005; McClanahan et al. 2011b). At local and national social-political scales,
various environmental and social factors have been used to explain fish diversity and
60
biomass of functional groups. Environmental factors include depth, exposure to prevailing
weather, season, reef zone, coral cover, substrate rugosity, habitat complexity, and larval
dispersal (Luckhurst & Luckhurst 1978; Molles Jr. 1978; Bell & Galzin 1984; Roberts &
Ormond 1987; Friedlander & Parrish 1998; Friedlander et al. 2003; Gratwicke & Speight
2005; Jones et al. 2005; Graham et al. 2006) (Table 2B.1). In contrast to the depth of work
assessing environmental drivers of fish diversity and function, assessments of the
potentially important role that human activity might have in shaping ecological
assemblages have focused largely on human population density (Jennings et al. 1995;
Jennings & Polunin 1996, 1997; Bellwood et al. 2003; Dulvy et al. 2004a; Dulvy et al.
2004b; Mora 2008; Williams et al. 2008; Stallings 2009; Williams et al. 2011) and fishing
pressure (DeMartini et al. 2008; Wilson et al. 2008). However, recent research has
highlighted the potentially important role of factors such as market proximity and
modernization (including for example, affluence and urbanization) in explaining functional
group distributions (Brewer et al. 2009; Cinner et al. 2009b; Stallings 2009; Aswani &
Sabetian 2010). What is not clear, however, is how market proximity and modernization
affect fish species diversity, and whether market proximity and modernization have an
effect on fish diversity and function beyond what is explained by human population
density. This paper aims to contribute to this research gap by examining relationships
between social drivers and the diversity and function of reef fish communities.
61
Table 2B.1 Key environmental and human factors that explain in situ coral reef fish diversity and functional
group distributions at biogeographic scales relevant to this study.
Explains diversity
Factor
measures
a
Explains functional
group biomass
b
Controlled for in
this study?
Environmental
Depth
Exposure
Time
Reef zone
% Coral cover
Habitat complexity
Habitat rugosityg
1, 2, 3.c
4.
5.
1.
6, 7.
4, 8, 9.
1, 4, 10.
1, 3.
11, 12.
1, 13.
1, 3, 7.
9, 14.
1, 15.
Sd
S
S
S
Me
*f
*
Human
Proximate drivers
Fish consumption
14.
M
Fishing pressure
16.
16, 19, 20.
M
Distal drivers
Population density
17, 18.
15, 17, 18, 21-26.
M
Affluence
15, 18h.
M
Urban development
24, 27.
M
Market proximity
28.
M
a
references relate to any measure of diversity (e.g. richness, evenness)
b
references relate to any functional group abundance or biomass measure (e.g. herbivore biomass)
c
Supporting references:
1. Friedlander and Parrish (1998), 2. Roberts and Ormond (1987), 3. Öhman and Rajasuriya (1998), 4.
Friedlander et al. (2003), 5. Molles Jr. (1978), 6. Bell and Galzin (1984), 7. Wilson et al. (2006), 8. Gratwicke
and Speight (2005), 9. Graham et al. (2006), 10. Luckhurst and Luckhurst (1978), 11. Fulton and Bellwood
(2005), 12. Floeter et al. (2007), 13. Russ (2003), 14. Wilson et al. (2008), 15. Cinner et al. (2009b), 16.
Jennings et al. (1995), 17. Jennings and Polunin (1997), 18. Stallings (2009), 19. DeMartini et al. (2008), 20.
Jennings and Polunin (1996), 21. Bellwood et al. (2003), 22. Dulvy et al. (2004a), 23. Dulvy et al. (Dulvy et
al. 2004b), 24. Mora (2008), 25. Williams et al. (2011), 26. Williams et al. (2008), 27. Aswani and Sabetian
(2010), 28. Brewer et al. (2009).
References include only those that show, statistically, the effect of the factors listed, on measures of coral reef
fish diversity or function.
d
controlled during sampling
e
controlled in model
f
* correlated with coral cover (Graham et al. 2008)
g
also measured as number of ‘holes’ and hole volume of reef substrate (Friedlander & Parrish 1998).
h
not significantly correlated
62
Social scientists working on social-ecological interactions often differentiate between
proximate (e.g. fishing pressure) and distal (e.g. market proximity, modernization, and
human population density) drivers of environmental degradation (Forester & Machlis 1996;
Agrawal & Yadama 1997; Geist & Lambin 2002; Kramer et al. 2009; McKinney et al.
2010). In a coral reef context, there is clear evidence that, at the local-level, people directly
affect coral reef fish diversity and function through proximate drivers such as fishing
pressure and habitat degradation (Wilson et al. 2008). What is less clear, however, is the
role of distal drivers, in shaping these proximate drivers and ultimately coral reef fish
diversity and function. For example, increased socioeconomic development (akin to
modernization) does not directly affect fish diversity and function, but might intensify local
fishing pressure through greater access to more efficient fishing gear, which might, in turn,
decrease diversity and function of coral reef fish. Alternatively, increased socioeconomic
development might reduce dependence on local resources, or enable improved resource
management practices, resulting in increased fish diversity and function (Cinner et al.
2009b).
Here, I explore the linkages between three recognised distal drivers (population density,
modernization and market proximity), two proximate drivers (fishing pressure and coral
cover), and a range of metrics of fish diversity and function. Similarly to chapter 2A,
structural equation models are used to understand the sequential effects of distal drivers on
proximate drivers, and proximate drivers on diversity and function metrics across 25 sites
in Solomon Islands.
2B.2 METHODS
2B.2.1 SITE SELECTION AND DELINEATION
The 25 sites used in this chapter are the same as used in chapter 2A (Figure 2A.1). The
only variation in the social and economic data is that ‘basic gear fishing’ was not included
here because it was found to have limited effect in the models in chapter 2A.
63
2B.2.2 ECOLOGICAL RESPONSE VARIABLES
Fish species used in this study included all fishes surveyed across the same 25 sites used in
chapter 2A (Appendix 4). Four metrics of species diversity were used to test the effect of
proximate and distal drivers on fish diversity; 1) species richness, 2) Pielou’s species
evenness, 3) average taxonomic distinctness (AvTD), and 4) variation in taxonomic
distinctness (VarTD). Species evenness warrants investigation as it considers the relative
abundance of species and can have important ecosystem ramifications well before species
become locally extinct (Chapin III et al. 2000). AvTD is a measure of the average distance
between all pairs of species in a taxonomic tree, which captures phenotypic differences and
functional richness (Clarke & Warwick 1999; Rogers et al. 1999). VarTD is the variance
of the path lengths between every pair of species in a taxonomic tree, and represents the
unevenness of the taxonomic tree (Clarke & Warwick 2001). Taxonomic hierarchy levels
used to measure AvTD and VarTD were Class, Order, Family, Genus and Species. Path
lengths between taxonomic levels were equally weighted.
Total biomass estimates were derived for two key functional groups: piscivores and
herbivores. Piscivores were classified as fishes that, based on gut content analyses (Froese
& Pauly 2011) predominantly consume fishes. Piscivores can inhibit increase in abundance
of lower trophic level species through predator prey interaction (Jennings et al. 1995;
Graham et al. 2003), and are particularly sensitive to fishing pressure (e.g. Jennings &
Polunin 1997; DeMartini et al. 2008; Sandin et al. 2008). Herbivores were classified as
those species that predominately feed on large fleshy algae or the epilithic algal matrix
(censuWilson & Bellwood 1997). This includes fish that remove part of the reef by
scraping or excavating the substratum, and grazers that mainly ingest filamentous algae
(censu Choat et al. 2002). Herbivores are thought to play a critical role in the resilience of
coral reef ecosystems by preventing algal overgrowth that can smother corals (Mumby
2006; Hughes et al. 2007; Green & Bellwood 2009). Piscivore and herbivore species were
divided into target and non-target species to further explore the effect of fishing on these
functional groups. The list of target and non-target species was constructed using expert
64
opinion of Solomon Islands target species (Green et al. 2006), and creel survey data from
adjacent Papua New Guinea (Cinner et al. 2009c) (Appendix 4).
2B.2.3 PROXIMATE DRIVERS
We measured two proximate drivers previously shown to be related to fish diversity and
function: 1) coral cover, and 2) fishing pressure. Coral cover here is the same variable used
in chapter 2A. Fishing pressure here is the same variable as ‘efficient gear fishing’ used in
chapter 2A. As stated above, ‘basic gear fishing’, as a proximate driver, has been omitted
because it had limited effect on the ecological response variables (biomass in vulnerability
categories) used in chapter 2A.
2B.2.4 DISTAL DRIVERS
This chapter used the same distal driver variables that were used in chapter 2A; human
population density (Malthusian overpopulation), modernization (modernization), and
market proximity (market expansion). The distal drivers were measured by the same
method among the same 25 sites, and are therefore identical.
2B.2.5 MODEL CONSTRUCTION
As with chapter 2A, this chapter used partial least squares regression, in the program Warp
PLS, to build structural equation models (SEMs) of the general form: distal drivers →
proximate drivers → ecological response to analyse the data. Distal and proximate drivers
remained consistent across models with only the ecological response changing between
models (Figure 2B.1a). All distal drivers (market proximity, modernization and population
density) were linked to the two proximate drivers (fishing pressure and coral cover), except
market access to coral cover as there was no theoretical justification for this link. Both
proximate drivers were linked to the ecological response variable in all models. This
resulted in unique models for each ecological response; species richness, Pielou’s evenness,
65
AvTD, VarTD, total herbivore biomass, non-target herbivore biomass, total piscivore
biomass, and non-target piscivore biomass. As in chapter 2A, the output generated
included individual standardized path coefficients (β), partial model fit scores (r2), overall
model p values calculated through resampling estimations coupled with Bonferroni-like
corrections (Kock 2010), and individual explanatory and response x, y plots (Appendix 5).
The total effect of distal drivers (market proximity, modernization and population density)
were calculated by multiplying the standardized coefficients (β) within each pathway then
summing these values for pathways associated with each driver.
2B.3 RESULTS
2B.3.1 EFFECTS OF PROXIMATE DRIVERS ON FISH FUNCTION AND DIVERSITY
Fishing pressure had a clear negative effect on both fish diversity and the biomass of key
functional groups of fish. Specifically, fishing pressure correlated negatively with species
richness, and AvTD, and positively with species evenness (Figure 2B.1b-d). Fishing
pressure however, did not noticeably affect VarTD, with only a small decrease in VarTD
associated with increased fishing pressure (Figure 2B.1e). Also, fishing pressure had a
clear negative effect on both all piscivore and all herbivore biomass, yet non-target biomass
of the two functional groups was negligibly affected by fishing pressure (Figure 2B.f-i).
Coral cover generally had a smaller effect on diversity and functional group metrics than
fishing pressure (Figure 2B.1b-i); Coral cover was positively related to richness, AvTD,
VarTD and non-target piscivores. Coral cover was strongly negatively correlated with
species evenness and all herbivore biomass (Figure 2B.1c, g).
66
Fig. 2B.1 Structural equation modeling results (SEM) showing (a) general model used including distal and
proximate drivers and (b-i) the total effect size (determined by multiplication of β coefficients along each
distinct path, prior to summing of distinct paths) of the different distal and proximate drivers for each of the
ecological response variables. The effect of each distal driver, on each ecological response variable, is
categorized by proximate drivers to show the positive and negative effect of each path. In (a) values adjacent
to arrows are beta (β) coefficients for relationship between respective distal and proximate driver, and values
above proximate driver boxes are r2 values. In (b-i) r2 values are variance explained by fishing pressure and
coral cover, and p is the likelihood of the model fit occurring by chance based on resampling estimates
coupled with Bonferroni-like corrections (Kock 2010).
67
2B.3.2 EFFECTS OF DISTAL DRIVERS ON FISH FUNCTION AND DIVERSITY
Distal drivers explained much of the variance of fishing pressure (r2 = 0.73), particularly
market proximity and population density (Figure 2B.1a). Population density and
modernization were, however, comparatively poor descriptors of coral cover (r2 = 0.24).
Modernization had a weak negative effect on fishing pressure and on coral cover, thus had
both positive and negative effects on fish diversity and function, except for all herbivore
biomass which was positively affected by modernization through both decreased fishing
pressure and decreased coral cover. Population density had a negative effect on all
herbivore biomass through increased fishing pressure, and a positive, but weaker, effect on
all herbivore biomass through decreased coral cover. Market proximity and population
density, more than modernization, explained decreased diversity and function of coral reef
fish (Figure 2B.1b-i). The strong indirect effect of market proximity on diversity and
function was particularly noteworthy because the model specified that market proximity
indirectly affected function and diversity only through fishing pressure, rather than through
both fishing pressure and coral cover (Figure 2B.1a).
2B.4 DISCUSSION
In this sub-chapter I explored how habitat and social factors explain spatial variability in
the diversity and functional group biomass of coral reef fishes at 25 sites across Solomon
Islands. Results indicate that population density and market access increase fishing
pressure, which is a major driver of fish diversity and functional group biomass. These
distal social drivers have a negative effect on the biomass of piscivores and herbivores
targeted by fishers. Moreover the relative abundance of species becomes more even, whilst
species richness and AvTD decline as population density increases and markets become
more accessible.
68
2B.4.1 EXPLAINING THE EFFECTS OF PROXIMATE DRIVERS ON FISH FUNCTION AND
DIVERSITY
A decline in taxonomic distinctness is often associated with a decline in functional diversity
(Rogers et al. 1999; Chapin III et al. 2000; Nyström et al. 2000). This is supported here by
the finding that fishing pressure had a negative effect on average taxonomic distinctness
and the biomass of two important functional groups, herbivores and piscivores.
Conversely, there was negligible effect of fishing on non-target species from these
functional groups. Thus, the direct effect of fishing is likely to be confined largely to those
species and functional groups that are targeted by fishers. A decrease in diversity, and
increased evenness with increased fishing pressure, might relate to removal of relatively
rare large bodied predators, which are often targeted by fishers (Pauly et al. 1998).
Target species on coral reefs tend to be large bodied (Dulvy et al. 2004b; Graham et al.
2005), while many of the non-target species tend to be small and have close affiliation with
the reef benthos (Munday & Jones 1998). In this study, coral cover and fishing pressure
had a similar effect on non-target herbivore and piscivore biomass, compared to all
herbivore and all piscivore biomass which was largely explained by fishing pressure alone.
Interestingly, the relationship between non-target herbivore biomass and coral cover was
negative, possibly because many of these fish are damselfishes that maintain territories
covered with algae (Ceccarelli 2007) (Appendix 4). Conversely, biomass of piscivores,
particularly non-targeted species, tended to increase with coral cover. This may be because
many smaller bodied non-target predators and their prey take refuge among corals. Indeed
a loss of coral and associated structural complexity can lead to declines in small bodied
prey fish and their medium sized predators (Graham et al. 2007). Functionally, non-target
species are likely to perform a very different role to the larger bodied species targeted by
fishers. Fishing and habitat degradation might therefore have different consequences for
both herbivore and piscivore assemblages and the functional services associated with these
groups.
69
2B.4.2 EXPLAINING THE EFFECTS OF DISTAL DRIVERS ON FISH FUNCTION AND DIVERSITY
By disaggregating distal and proximate drivers and modeling fish assemblage response to
different causal paths of human activity, this study has shown that social drivers can have
both positive and negative effects on fish communities and their functional role in
ecosystems. Population density had both positive and negative effects on all herbivore
biomass through coral cover and fishing pressure, respectively. The positive effect,
through decreased coral cover, might be explained by increased nutrient levels indirectly
caused by high coastal population densities without access to sewage treatment facilities.
Resultant excess nutrients have been shown to increase algal growth (e.g. Pastorok &
Bilyard 1985), and consequently increase food availability to herbivores.
Modernization had a negative effect on coral cover, resulting in marginally reduced species
richness and taxonomic distinctness, and increased species evenness and total herbivore
biomass. Modernization however, had a weak negative effect on fishing pressure, leading
to marginally increased species richness, average taxonomic distinctness, and functional
group biomass. These results are broadly consistent with studies conducted across five
Indian Ocean countries that found a decrease in fishing with higher levels of modernization
(Cinner et al. 2009b; Cinner & Bodin 2010). In comparison to the large modernization
spectrum in these multi-nation studies, the relatively small effect size of modernization on
fishing pressure presented in this study might reflect, as suggested in chapter 2A, a small
development gradient in Solomon Islands.
The majority of studies that have explored the effect of human activity on coral reef fish
diversity and function have shown that these assemblage characteristics are explained by
either fishing pressure (Jennings et al. 1995; Jennings & Polunin 1996; DeMartini et al.
2008) or human population density (Jennings & Polunin 1997; Bellwood et al. 2003; Dulvy
et al. 2004a; Dulvy et al. 2004b; Mora 2008; Williams et al. 2008; Stallings 2009; Williams
70
et al. 2011) (Table 2B.1). While it is clear that local human population density and direct
fishing effects are important in explaining ecological gradients, this study has shown that
trade, measured as market proximity, is also important (Figure 2B.1). In Solomon Islands
trade likely affects fish diversity and function through small-scale commercial fishing to
supply urban markets, whereas population density likely affects diversity and function
through semi-subsistence based fishing to supply local needs. Trade allows societies to
acquire resources from further afield, externalizing environmental footprints beyond local
human-environment systems (Arrow et al. 1995; Berkes et al. 2006; Shandra et al. 2009).
Resource management and biodiversity conservation initiatives must recognize that trade
and local population pressure represent different drivers of ecological degradation, and
consequently apply different strategies to address their effects on ecosystems. For
example, strong governance of markets through sustainable harvesting certification, and
market-specific gear and species restrictions, will become increasingly important if coral
reef fish continue to be a readily traded commodity (Berkes et al. 2006).
2B.4.3 FUTURE MODEL EXTENSIONS
Expansion of the models developed in this paper to other social-ecological contexts would
help to provide a better understanding of how marine ecosystems will respond to key social
dynamics. However, three key advancements are necessary to improve the predictive
capacity of such models. First, analysis of the indirect effects of distal drivers on the
proportionate representation of multiple functional groups (including higher resolution
herbivore functional groups such as grazers, scrapers, and excavators) (Wilson & Bellwood
1997) and species might lend further insight into the role of distal drivers in shaping
ecosystem function (Wilson et al. 2008). Second, coral cover is only one measure of coral
reef habitat and more detailed models including other environmental and habitat variables
(e.g. Wilson et al. 2008), could shed additional light on the relative contribution of distal
drivers on diversity and function, particularly for species richness and non-target
assemblages of coral reef fish. Third, temporal assessments would be vital to understand
the feedbacks that might exist in this system.
71
2B.5 CONCLUSION
Management measures which address proximate drivers, such as fishing pressure, typically
have localized effects on diversity and ecosystem function. Yet, they are limited in their
ability to alleviate the effects of distal social drivers such as market proximity and
modernization (Birkeland 2004). Therefore, whilst managing proximate threats represents
an important (if not limited) management approach, and means of increasing local
resilience, governing reefs in a changing world will require becoming better acquainted
with the threats, and potential solutions posed by broader social drivers such as markets and
population growth.
72
CHAPTER 3: SOCIAL DETERMINANTS OF CORAL REEF
RESOURCE MANAGEMENT INSTITUTION OCCURRENCE13
ABSTRACT
Resource management institutions are vital for constraining natural resource exploitation.
There is evidence that a society’s characteristics explain whether or not the society is able
to collectively manage their resources. This study assessed the effects of key social and
economic characteristics (herein drivers) of resource management institution occurrence
and efficacy; local population size and density, modernization and market access) on a set
of common resource management strategies. The study is conducted in a Solomon Islands
across ≥ 723 coastal villages adjacent to coral reefs. In accordance with current theory, a
medium village population size of ≈ 350 presented the highest probability of management
institution occurrence. However, population density had an overwhelming negative effect
on the probability of institution occurrence. Both modernization and the presence of
markets had week positive effects on some management types. Broadly, the findings
suggest that, contrary to popular belief, not all dominant drivers of institution occurrence
erode local resource management institutions, but human population density negates the
positive effect of medium population size, market access and modernization.
13
Brewer, T.D., Cinner, J.E., Kool, J., Foale, S. Social and economic drivers of natural resource management
institution occurrence. In preparation.
73
3.1 INTRODUCTION
There is growing concern that humanity does not possess institutions able to buffer the
negative effects of social and economic change (such as human population growth and
commoditization of resources) on the earth’s finite natural resources (Walker et al. 2009).
In developing countries, where much of the world’s biodiversity lies, natural resources are
often collectively managed by local communities (Ostrom 1990; Donner & Potere 2007).
These local institutions play a significant role globally in maintaining biodiversity, but are
highly vulnerable to the negative effects of some social and economic drivers of change
(Agrawal & Yadama 1997).
An enduring debate exists, on whether institutions can adapt to social and economic drivers
of change. This debate is particularly prominent in relation to communities of the AsiaPacific region that depend on marine resources for their livelihoods. There is extensive
evidence of decreased prevalence, or efficacy, of traditional community-based management
institutions with increased social and economic change (Baines 1989; Ruddle 1993; Cinner
2005; Cinner et al. 2007). In his seminal work, Johannes (1978) argues that westernization;
the introduction of money economies, the breakdown of traditional authority, and the
imposition of colonial laws and practice are responsible for the demise of traditional
community-based marine resource management in the Pacific. However, there is also
support for the notion that local management institutions are adaptive and flexible, which
might enable them to endure social and economic change (Hviding & Baines 1994;
Hviding 1998). For example, in retraction of his earlier stance, or perhaps through personal
observation of contextual change, Johannes (2002) champions the ‘renaissance’ of
community marine resource management institutions in Oceania in response to
‘westernization’.
Broadly, the aim of this chapter was to determine the likelihood of institution occurrence
across a gradient of social and economic drivers of change. More specifically, this study
74
tested a suite of hypotheses relating to the effect of population pressure (Malthusian
overpopulation), access to resource markets (market expansion), and development and
affluence (modernization) on local-level fishery management institutions in Solomon
Islands. First, it has long been asserted that human population size (number of people with
access to a commons) is likely to affect collective action designed to manage common-pool
resources (Olson 1965). Recent theoretical and empirical evidence suggests that there is
likely to be an optimal population size to effectively manage resources through an
institution; effective institutions are unnecessary for small populations and cost inhibitive
for larger populations (Agrawal & Golyal 2001). Further, dissolution of resource
management institutions in communities with large populations might also be a function of
increased social and cultural heterogeneity caused by, for example, migration and rapid
population growth (Aswani 2002; Poteete & Ostrom 2004). Population size is considered
in this chapter and not in earlier chapters of the thesis because it has substantial theoretical
relevance to institutions. Second, population density (human population per units of
resource), affects the occurrence and efficacy of institutions. One hypothesis is that, as with
population size, there is an optimum population density for collective action (Pender &
Scherr 1999). The logic follows that at low population density the demand for collective
action is low because there is an abundance of resource. As population density increases
the resulting resource scarcity induces collective action. However, at high population
density the benefits of collective action may be outweighed by incentives for individuals to
‘free-ride’ or transgress institutional rules due to increased resource scarcity (Gebremedhin
et al. 2003). Therefore, based on current evidence, one would expect to see a non-linear
institutional response to both population size and population density. Third,
commoditization of natural resources will lead to a failure of resource management
institutions. Some empirical evidence exists of the negative effect of market access on
exclusivity of marine tenure in the Indo-Pacific (Cinner 2005), yet there is a need to better
understand how access to trade effects particular local resource management institutions
(Agrawal 2001) that are often embedded within the marine tenure system (Ruddle 1998).
Fourth, with increased modernization, resource management institutions will fail (Cinner et
al. 2007), to a point, after which they will re-emerge as societies can afford and demand
environmental quality, in accordance with environmental Kuznets curve theory (Arrow et
75
al. 1995; Cinner et al. 2009b). This theory implies that an increase in modernization (from
an undefined point) will result in decline of environmental quality, and yet further
modernization will result in improved environmental quality.
3.2 METHODS
To test these hypotheses this study measured the effect of the four key social and economic
drivers ; human population size, human population density, market access, and
modernization, on a suite of management institutions common in artisanal coral reef
fisheries, across a nation. A range of data sources were used on a minimum of 723 (range
= 723-1123) communities for any single analysis. Population size was measured as the
number of people living within each community. Population density was measured as the
number of people living in each community per resource area (coral reef). Market access
was measured as the presence, or absence, of a fish market within each community.
Modernization was measured as the summed occurrence of a set of 16 infrastructure and
amenity items in each community (Pollnac et al. 2010). Components of modernization
were also measured using Principal Component’s Analysis, on the infrastructure and
amenity items that comprised modernization. The management institutions assessed were
temporary spatial closures, species restrictions and fishing gear restrictions (Johannes 1978;
Cinner & Aswani 2007); all measured as present or absent.
3.2.1 DATA SOURCES AND REDUCTION
All communities recorded in the 2007/08 Solomon Islands Village Resource Survey (VRS)
(Solomon Islands Government 2008) were spatially referenced using the 1999 Population
and Housing Census (PHC) (Solomon Islands Government 1999) locations, which was
deemed to be more accurate of the two sources. Those villages that could not be spatially
identified using the PHC or were not spatially located within the ward (local political
constituency) they were assigned in the VRS, were considered potential errors, and were
subsequently omitted from the data set. As with chapter 2, villages greater than 1 km from
76
the coastline were also omitted from the data set. Subsequently, spatial boundaries between
communities were measured using thiessen polygons. Thiessen polygons are generated
such that each community boundary is equidistant from the location of each adjacent point
(community) location. This method has been previously applied to estimating community
resource use boundaries (Mulller & Zeller 2002). W hilst this method of associating
resource user groups with resource does not account for intra- or inter-community resource
use-rights, it was deemed appropriate because the management institution questions in this
study relate explicitly to community-level institutions. Coral reef area was then overlaid
with population data and thiessen polygons to derive a measure of coral reef area available
to each community. Communities that did not have coral reef area within their thiessen
polygon boundary were omitted from the data set.
3.2.2 SOCIAL AND ECONOMIC DRIVERS
Following the data reduction process, human population size was measured as the total
number of people living in communities within 1 km of the coast, in each thiessen polygon
that contained coral reef. Data on human population size was not available from the VRS
so population data and locations were derived from the PHC. Human population density
was measured as the derived human population size divided by coral reef area in each
thiessen polygon. Change in population size between the time of the PHC, and the time of
the VRS was corrected for all communities assuming an annual growth rate of 2.8% (World
World Bank 2012). Modernization was measured as the equally weighted summed set of
infrastructure and amenity items derived from the VRS (Table 3.1). Principal Components
Analysis (PCA), using a varimax rotation, was used to derive sub-components of
modernization from the entire set of infrastructure and amenity items. Data on market
access was derived from the VRS, and defined as the presence, or absence, of a fish market
within each community.
77
Table 3.1 Principal components analysis of modernization variables. (Kaiser-Meyer-Olkin measure of
sampling adequacy = 0.73; Bartlett’s test of sphericity = 2764***). All communities included in PCA (n =
975) had responses for all modernization variables. Variables with loading of ≥ 0.4 are shown in bold, and
represent those variables which contribute most to each respective component.
% occurrence
Health and
education
Public
infrastructure
Economic
Social
Tourism
Modernization Components
Primary school
23.4
0.79
0.06
0.07
0.23
-0.04
Pre-school
High school
30.2
0.72
0.67
0.03
0.07
0.13
0.04
0.33
-0.04
-0.07
0.10
0.57
0.15
0.33
-0.05
0.04
0.05
0.08
0.85
0.81
0.07
0.10
-0.03
-0.04
0.06
-0.02
0.09
0.68
-0.05
0.03
0.03
0.11
0.18
-0.02
0.07
0.78
0.69
0.15
0.02
0.03
-0.02
0.12
0.01
0.63
0.31
0.06
0.23
0.18
-0.02
-0.04
0.07
0.08
0.75
0.67
-0.07
0.04
-0.15
0.02
0.26
0.44
0.04
-0.12
0.29
0.08
-0.15
-0.10
0.07
0.18
-0.16
0.77
0.62
-0.05
0.25
0.33
-0.06
0.43
Eigenvalue
3.22
1.95
1.37
1.19
1.04
% variance explained
20.15
12.16
8.56
7.43
6.50
Clinic
5.9
14.1
Government offices
Postal service
1.2
Airport
1.0
2.2
Fuel depot
Market
21.2
Trade store
11.4
36.5
Church
Village hall
63.5
Water source
26.0
50.4
Tourism
Social club
1.1
Banking
0.6
1.3
3.2.3 RESOURCE MANAGEMENT INSTITUTIONS
Community leaders were surveyed, as part of the VRS, to identify the presence of
management institutions. Community leaders were defined as a recognized elder or chief,
but might have included other community members such as school teachers, or local
pastors. Community leaders are generally responsible for enforcing marine harvest
78
restrictions, particularly in the traditional context (Hviding 1998). Enumerators were
chosen to survey particular communities because of their affiliation with the communities.
Enumerator training was conducted over a three week period prior to enumeration. During
the enumeration field period, villages were defined as a large settlement, encompassing
smaller satellite villages within 15 minutes walking distance. The satellite villages were
likely to include many of the additional communities recorded in the PHC that were not
recorded in the VRS. The enumerators grouped settlements within a single polity (e.g.
under the jurisdiction of a single chief) where possible. Thiessen polygons, as used to
define human populations and coral reef area, compared to alternate methods of remotely
defining of defining spatial boundaries, such as radial distance, was deemed more
compatible with the definition used during the VRS enumeration. The three questions,
used in this study, that pertain to current management were intentionally general to capture
the diversity of institutions that exist in Solomon Islands and broader Melanesia (Cinner &
Aswani 2007). Explicitly the questions asked of the community leaders were:
Does your village have any of the following community fishing regulations?
7. Reef area closed on and off (Yes/No)
8. Particular species restrictions (Yes/No)
9. Fishing gear restrictions (Yes/No)
Data on permanent spatial closures was also elicited, but omitted because of possible
misinterpretation. Specifically, it was possible that many of the recorded permanent
closures represented sacred sites with no explicit resource management purpose.
3.2.4 ANALYSIS
Multicolinearity between the social and economic drivers was tested using Spearman’s rank
correlation. The effect of the presence of a market on each management institution was
tested using Fisher’s exact test. In addition, the relationship between the continuous
predictor variables (population size, population density, modernization) and response
(management institutions) variables was modeled using a combination of locally weighted
79
scatter plot smoothing (lowess) and logistic regression. Logistic regression evaluates the
probability of occurrence for a binary outcome (e.g. yes/no) in relation to a given
independent variable (Hilbe 2009). Lowess is used to perform locally weighted regression
by passing a sliding window (convolution) over the data and evaluating the predicted
relationship within its range (Cleveland & Devlin 1988). A neighboring-point approach
was used to define the scope of the window. Neighboring values within 100 points to
either side of the reference value were used to calculate the regression relationship. If the
dependent variable value was ‘No Data’, then it was not used in determining the predicted
value. The window size was not adjusted to make up for values having ‘No Data’. A
Gaussian scheme was used to weight the points (implemented using MATLAB’s gausswin
function), so that points near the center of the sliding window would have a proportionally
greater degree of influence than those near the edges. For reference points near the edge of
the data set (i.e. less than 100 points), the maximum number of data points available were
used, and the Gaussian weighting was truncated according to the data points that were not
used. The data was bootstrapped 4999 times, merged with the observed data (yielding a
total of 5000 curves) and then 5% and 95% confidence limits were calculated using
percentiles, as well as the average trend.
3.3 RESULTS AND DISCUSSION
Average community population size was 170, median population density was 302
people/km2 coral reef, 4% (43) of communities had recognized fish markets, and
communities had an average of 2.75 modernization items. Of the communities that
responded to the management institution questions; 35% (389) had temporary spatial
closures, 24% (258) had species restrictions, and 20% (215) had gear restrictions. There
was some colinearity between independent variables (p < 0.05) however, correlations were
all less that 0.5 (rho value) which was deemed adequately low to retain all variables;
particularly given their individual theoretical merit.
80
The occurrence of resource management institutions is, in part, dependent on human
population size in Solomon Islands. Population size had a positive effect on occurrence of
management institutions(Table 3.2), however, at high population size (≈350) the
probability of each; temporary spatial closures, species restrictions, and fishing gear
restrictions occurring, is diminished (Figure 3.1A). The observed curvilinear trend fits
current theory that medium sized populations are more likely to have resource management
institutions. Indeed, the highest probability of management institution occurrence was
observed in communities with population size comparable to previously published
optimum population size estimates for forest management in India, measured as frequency
of resource management meetings (Agrawal & Golyal 2001); a vastly different socialecological context. However, the confidence intervals increase notably at population size
beyond the optimum (Figure 3.1A), and therefore should be considered with caution.
81
Table 3.2 Effects of social and economic drivers, including components of modernization, on communitylevel management institutions. Numbers in parentheses indicate the number of communities in each analysis.
* p ≤ 0.05, ** p ≤ 0.01, ***p ≤ 0.001.
a
b
Temporary
Species
Fishing gear
closures
restrictions
restrictions
Population sizea
15.2***
(1123)
6.76**
(1069)
4.5*
(1059)
Population densitya
-21.6***
(1123)
-30.35***
(1069)
-21.23***
(1059)
Market accessb
5.25*
(802)
1.01
(785)
3.01
(778)
Modernizationa
1.08
(745)
5.07*
(729)
11.52***
(723)
Health and educationa
1.71
(745)
6.02*
(729)
4.178*
(723)
Public infrastructurea
-2.47
(745)
0.152
(729)
2.02
(723)
Economica
-1.52
(745)
3.47
(729)
2.29
(723)
Sociala
0.56
(745)
0.112
(729)
6.01*
(723)
Tourisma
-1.61
(745)
-2.82
(729)
-1.01
(723)
Absolute values were log10(x+1) transformed prior to performing binary logistic regression.
Fisher’s exact test.
82
Figure 3.1 Effect of (A) human population size, (B) human population density, (C) modernization, and (D)
market access, on the probability of management institution occurrence (± 95% C.I. for A, B, C). X axis has
been clipped where C.I. large and site (village) occurrence infrequent (i.e. a large gap in the x axis between
data points). Optimum population size range estimate (A) is based on the optimum number of households (61100) (for highest incidence of resource management meetings as a proxy for collective action) presented in
Agrawal & Golyal (2001) multiplied by the mean number of occupants per household (5.3) in Solomon
Islands in 2007 (Solomon Islands Statistics Solomon Islands Government 2007).
83
Population density had a dramatic negative effect on the occurrence of all management
institutions (Table 3.2; Figure 3.1B). Indeed, there is no evidence that institutional
response to increased population density is non-linear, as shown elsewhere (Gebremedhin
et al. 2003). Melanesian society, of which Solomon Islands is a part, is renowned for being
egalitarian (Baines 1989). Consequently, communities are generally likely to ensure
relatively equal internal distribution of resources, particularly for subsistence needs, rather
than commercial gain (Hviding and Baines 1994). It is therefore plausible that
management institutions are doomed to failure in high population density areas because of
cultural norms that demand equality of resource allocation by precluding restrictions on
harvesting; a finding that resonates with the long standing tragedy of the commons
perspective (Malthus 1798; Hardin 1968; Pauly 1988).
Management institutions, particularly temporary closures, were more likely to occur in
communities with recognized fish markets (Table 3.2; Figure 3.1D). This finding
challenges the theory that commoditization of resources adversely effects management
institutions (Cinner et al. 2007). However, markets are likely to provide benefits to a select
few (Carrier 1987; Ruddle 1993). Thus, in contrast to the institutional response observed
with increasing population density, it is possible that restricting exploitation in close
proximity to markets would ensure that those who do exploit for market sale do not gain
excessive advantage through exploitation (Hviding & Baines 1994), which would otherwise
result in inequality and social hierarchy. Alternatively, institutions might have been
established by those exploiting the fishery to maximise commercial gain (Ruttan 1998).
Identifying which proposition is true would require the identification of who is imposing
and benefiting from the restrictions.
Modernization had a significant positive effect on both species restrictions and fishing gear
restrictions, but no clear effect on temporary closures (Table 3.2). However, mean
probability of the occurrence of all institutions declined markedly at high levels of
modernization (≥ 7 infrastructure and amenity items) (Fig 3.1C). This result counters
84
theory that suggests higher incidence of management institutions at higher levels of
development. However, if one considers the potential range of community level
modernization globally, Solomon Islands communities lie at the lower end of the
continuum(but see Grossman & Krueger 1995 for an example of modernization observed
within a single nation). Thus the range of modernization tested here might represent the
left side of the environmental Kuznets curve. However, because the measure of
modernization used in this study is not directly comparable to any previous studies in more
modernized communities dependent on coral reefs (e.g. Cinner et al. 2009b) (i.e. does not
use the same variables), it is not possible to conclude that this is the case. In the absence of
a repeatable measure of modernization, (that is more holistic than, for example, gross
domestic product or the human development index) it will not be possible to discern the
level of modernization of any one community to that of any other community outside the
study sample.
The principal components analysis on the 16 modernization items resulted in 5 components
that were classed; health and education, public infrastructure, economic, social, and tourism
(Table 3.1). Each component affected the occurrence of management strategies differently.
Health and education had a statistically significant positive effect on both species
restrictions and gear restrictions, and social modernization had a statistically significant
positive effect on gear restrictions (Table 3.2). The variables associated with social
modernization; church, village hall and water source, might engender social capital, which
is likely to promote collective action (Pretty 2003). The reason for health and education
positively affecting institutions is less clear. However, natural resource awareness
programs in schools, if they exist, could conceivably instigate exploitation restrictions.
Importantly, with the exception of the effect of tourism modernization on all three
institutions, and public infrastructure modernization and economic modernization on
temporary closures, all effects were positive. Yet economic modernization which is often
considered a key factor in environmental Kuznets curve trends did not have a significant
effect on institution occurrence.
85
With the exception of human population density, the social and economic drivers tested in
this study have either a positive effect, or non-linear effect, on the probability of institution
occurrence which suggests that institutions are adapting to social and economic change
(Hviding & Baines 1994; Hviding 1998) in Solomon Islands. Yet, evidence suggests that,
by way of increasing fishing pressure, population density and markets negatively effect,
and modernization has no effect on reef fish stocks in Solomon Islands (Brewer et al. 2009;
Aswani & Sabetian 2010; Brewer et al. 2012a). Therefore it is possible that despite higher
probability of occurrence in more modernized communities with medium population size
and fish markets, management institutions exist, but are not succeeding in stemming
resource decline due to efficacy limitations such as transgression of institutional rules.
3.4 LIMITATIONS
This study has tested theory on the effects of social and economic drivers on common-pool
resource management institutions. The findings both confirm and challenge commonly
held notions of these relations. However, I suggest three areas of research that would refine
the general trends identified in this study. First, the findings are based on occurrence data,
rather than efficacy of management institutions. There is significant evidence that efficacy
of management institutions for coral reef resources varies from a set of rules that are tightly
adhered to with limited transgression, to what are commonly referred to as ‘paper parks’, in
the case of spatial closures, which exist on paper but not in practice (Alcorn 1993;
Campbell et al. 2012). Second, historical analysis would complement the spatial
comparison used in this study by, for example, determining whether long enduring
institutions are adapting to, or failing because of change, or contemporary institutions are
emerging because of change (Ruddle 1998). Third, management institutions governing the
exploitation of marine resources occur across multiple levels on the social-political scale in
Solomon Islands ranging from national legislation such as species bans to unwritten userrights based on historical genealogies. Communities, as used in this study, are only one
level at which marine resources are used and governed in Solomon Islands.
86
3.5 CONCLUSIONS
This study tested a suite of recognised social and economic drivers of collective action for
managing common-pool resources. The findings support the hypothesis that, locally,
community-level resource management institutions are surviving and adapting to social and
economic change including modernization and commoditization of resources by way of
access to markets (Hviding & Baines 1994; Hviding 1998). The findings also support the
theory of optimum population size (Agrawal & Golyal 2001), and challenges the theory
that resource commoditization, by way of market access, can inhibit collective action to
manage common-property resources. Importantly, however, the over-riding negative effect
of population density cannot be over-emphasized and must be better understood to prevent
failure of common-property institutions, particularly in places of high and rapidly
increasing population density.
87
88
CHAPTER 4: FISHER AND MIDDLEMEN PERCEPTIONS OF
CORAL REEF FISH DECLINE AND INCREASE14
ABSTRACT
Understanding resource stakeholders’ perceptions of resource condition and management is
vital to the formulation of efficacious management policy to sustain natural systems
because agreement among stakeholders is likely to result in more effective outcomes.
Understanding perceptions is particularly important in the context of coral reefs because
threats are often diverse and management options are numerous, and therefore perceptions
are likely to be diverse. This chapter identified the dominant discourses of reef fish
decline, and increase, among 119 fishers and fish traders (herein middlemen) in Solomon
Islands, and compared these discourses to current scientific knowledge (earlier work and
chapters’ 2 and 3 of this thesis). Discourses were then explored for dominant themes that
might improve understanding of resource user perceptions. The findings suggest that
certain fisher and middlemen discourses align with scientific understanding of the causal
links between human activity and fish stock declines, and that many of the elicited
management strategies are aligned with current scientific recommendations. A theme that
emerged across the fisher and middlemen discourses of fish decline was a dichotomy in
perception between fishing for economic affluence and fishing for subsistence and
economic survival. A theme that emerged across discourses of fish increase was a
dichotomy between support for command-and-control approaches and support for
community-based approaches to management. Differences between some fisher and
middlemen discourses were explained by the location in which interviews were conducted
suggesting consensual perceptions achieved through local knowledge networks. Similarity
between scientific understanding and local perceptions suggests that local resource users
are aware of, and might support fishery management strategies based on scientific
evidence. Such strategies must consider factors such as location because resource user
14
Brewer, T.D. 2013. Dominant discourses, among fishers and middlemen, of the factors affecting coral reef
fish distributions in Solomon Islands. Marine Policy. 37; 245-253.
89
perceptions differ between locations and because many threats to the fishery and preferred
management strategies are likely to be context specific.
90
4.1 INTRODUCTION
Coral reef fish stocks, as with so many natural resources, are declining globally (Hughes
1994; Pandolfi et al. 2003). The causes of reef fish decline are diverse, including, but not
limited to, fishing pressure, destructive fishing, habitat degradation due to destructive
fishing and pollution, and coral bleaching (Russ & Alcala 1989; Grigg 1994; Graham et al.
2006; Graham et al. 2007). As with the causes of decline, there are also a diverse range of
approaches prescribed for sustaining and increasing coral reef resources, ranging from
designation of areas that exclude extractive activities, species restrictions, fishing gear
restrictions to reef restoration and reduction of carbon dioxide emissions (Hoegh-Guldberg
1999; McClanahan & Mangi 2004; McClanahan et al. 2006).
Faced with diverse threats and management prescriptions it is likely that different
stakeholders (e.g., resource users, governments, scientists, and third parties including nongovernment organizations (NGOs)), with different agendas and mental models, will have
different perceptions on appropriate courses of action for increasing fish stocks. For
example, ecologists might support measures that maintain key species to ensure ecosystem
function, environmental NGOs might aim for maximizing biodiversity by, for example,
establishing no take areas, whilst resource users are more likely to focus on measures that
ensure livelihoods to meet immediate food security needs and aspirations of economic
affluence. Strategies to limit and reverse current trajectories of decline might be more
likely to succeed when stakeholders are in agreement of both the causes of decline, and the
means of slowing and ultimately reversing the decline (Grimble & Wellard 1997; Brown et
al. 2001; Pomeroy & Douvere 2008). In the absence of agreement it is likely that
management measures desired by different stakeholders will attract resistance from other
stakeholders, potentially resulting in inefficiencies, conflict, and failure to improve the state
of resources (human-induced climate change is a poster-child example of this
phenomenon).
91
It has been argued that there are significant differences in understanding, between scientists
and local people, on factors that affect coral reef fish populations in Melanesia and the
broader Pacific (Bulmer 1982; Polunin 1984; Carrier 1987; Foale 1998) . This difference is
particularly relevant to natural resource exploitation wherein traditional knowledge asserts
that, for example, the spiritual realm affects resource abundance (Bulmer 1982; Carrier
1987; Foale 2005). A more specific example observed at West Ngella in Solomon Islands
is that locals perceive that trochus (a species of turban snail with market value) reside in
deep water, and migrate to shallow water to replenish harvested stocks (Foale 1998). There
is no scientific evidence to support this perception. Such traditional dogma, according to
scientific ‘western’ understanding, could lead to a fatalistic relationship between people and
resources as exploitation pressure intensifies (Foale 2006) because there is a belief that no
matter how much exploitation occurs, the resource will always recover. This apparent
difference in understanding of both natural systems, and the effect of human agency on
natural systems, has long been acknowledged by resource management and conservation
scientists and practitioners throughout the region, as evidenced by Bob Johannes’ (1978,
p349.) observation 33 years ago in relation to Oceania societies:
“Understanding a conservation system means understanding not only the nature of what is
being conserved, but also the viewpoint of the conserver. Knowledge of this second element
is essential if we are to comprehend a system of resource management employed by a people
whose perception of their environment differs from our own.”
Traditional knowledge and scientific knowledge, however, are not necessarily
incommensurable (Foale 2006). In fact, traditional ecological knowledge is frequently used
to complement scientific knowledge in inshore fisheries management in the region (e.g.
Foale 1998; Aswani & Hamilton 2004; Aswani & Lauer 2006; Cinner & Aswani 2007;
Hamilton et al. 2012), and has been advocated as a primary means of fisheries management
(Johannes 1998; Johannes et al. 2000). Such knowledge relates to, but is not limited to,
fish spawning aggregation locations and timing, seasonal variability in fish abundance and
spatial distributions of fish and habitat. It is also generally accepted that Melanesian fishers
recognize that increased fishing pressure can deplete fish stocks (Foale et al. 2010).
Therefore, there is a wealth of local knowledge on the distribution of fished species in
92
space and time, yet there has been relatively little research into local causal explanations for
these patterns (but see Carrier 1987; Lieber 1994; Foale 1998; Foale et al. 2010). If,
therefore, the perceived causes of declining fish stocks and of management intervention
differ between scientists and local resource users then there is limited scope for efficacious
fishery management derived from scientific evidence (Sabetian & Foale 2006; Brewer et al.
2009; Aswani & Sabetian 2010; Brewer et al. 2012a).
Solomon Islands, a nation situated within Melanesia, is an appropriate location to explore
this question of differing perceptions for a number of reasons. First, there is an extensive
literature discussing traditional ecological knowledge (e.g. Hviding & Baines 1994;
Hviding 1996; Foale 1998; Lauer & Aswani 2008). Second, there exists scientific
knowledge on the historic (Richards et al. 1994) and contemporary causes of coral reef
resource decline. For example, there is evidence to suggest that fishing to supply domestic
markets is significantly reducing coral reef fish stocks, and in particular, that larger market
centres are having a pronounced effect on in situ biomass (Sabetian & Foale 2006; Brewer
et al. 2009; Aswani & Sabetian 2010). There is contemporary evidence for particular distal
drivers; markets, population density, and modernization affecting both proximate causes of
fish decline (largely market-based fishing), and management institutions. In particular,
access to fish markets and local human population density both increase market-based
fishing which, in turn, decreases in-situ fish stock function and diversity (Brewer et al.
2012a)(chapter 2B of this thesis). Fish that are vulnerable to extinction, by fishing,
measured as in situ biomass, are also particularly susceptible to market-based fishing
(Brewer et al. 2012b)(chapter 2A of this thesis). Moreover, the occurrence of management
strategies, including species restrictions, gear restrictions, and temporary spatial closures
has been explained by presence of fish markets, local human population density, and
modernization (chapter 3 of this thesis). This study represents an opportunity to test
whether the perceptions of the agents (fishers and fish traders (herein middlemen) in the
artisanal fishery), who are in-part responsible for fish decline as evidenced by previous
studies (Sabetian & Foale 2006; Brewer et al. 2009; Aswani & Sabetian 2010), are aligned
with scientific perceptions.
93
As with a number of the scientific assessments, perceptions of both the proximate and distal
factors associated with fishery decline, and the proximate and distal factors associated with
increasing fish stocks were elicited. Obtaining the distal factors, such as human population
pressure, that might be perceived to be driving activities such as over-fishing, or stronger
governance that might be perceived to enable establishment of spatial closures, facilitates a
better understanding of the discourses and a broader discussion on numerous factors, and
their interaction, that potentially affect fish stock distributions. This approach also enables
a comparison between the current scientific discourse described above, and dominant
discourses of fishers and middlemen involved in the artisanal fishery in Solomon Islands.
4.2 METHODS
4.2.1 FIELD INTERVIEWS
From September to November 2010, 119 people, including fishers and middlemen, were
interviewed at six sites across Solomon Islands (Figure 4.1; Table 4.1). Dunde is classed as
a provincial sub-station. Auki, Buala, Gizo, and Tulaghi are provincial capitals. Honiara is
the national capital. All sites are major urban centres and have significant infrastructure,
including port facilities, medical facilities, and all sites except Buala and Tulaghi had
functional airstrips during the survey period. Given that current evidence suggests that the
artisanal fishery, comprising fishers and middlemen, has a significant negative effect on
coral reef fish stocks, interviews focused on this sector of society.
94
Figure 4.1 Main island chain of Solomon Islands with provinces denoted in uppercase, and survey sites
denoted in lower case.
Due to the informal, complex, and frequently dispersed nature of reef fish marketing in
Solomon Islands, it was necessary to employ multiple sampling strategies. Systematic
sampling, whereby all willing respondents were interviewed within a given time period,
was used at Honiara and Gizo which have geographically nuclear fish markets. Snowball
sampling was used at Dunde and Buala (Photo 4.1) due to the geographically and socially
dispersed nature of the fish marketing networks (Goodman 1961). It was also necessary to
use snowball sampling at Tulaghi and Auki because few fishers or middlemen were selling
fish at the respective markets during the sampling period.
Interviews were conducted in, and adjacent to, major open-air fish markets in each of the
locations, except Dunde and Buala, which do not have open air fish markets, but instead
have a number of private middlemen who on-sell to the general public. All interviews were
conducted in Solomon Islands Pijin.
95
Specifically, respondents were asked to explain what they thought reduced the number of
fish inhabiting coral reefs, and what they thought could increase the number of fish
inhabiting coral reefs. Respondents were asked, explicitly, to divulge their own opinions.
To do so, the phrase ‘ting ting blo iu’ (what do you think) was verbalized proceeding the
initial question.
Photo 4.1 Fera island with Buala township in the background. Captain ‘Jack Sparrow’ (second from left) and
Sonny (far right) fed and housed me, and taught me a lot about local customs and fishing, including the
sedating effect of eating too much crab. Joe Giningele (second from right) travelled with me and helped with
the research.
Respondents were asked to divulge both proximate and distal factors associated with each
decline and increase of fish stocks. For example, if a respondent said that ‘overfishing’
reduced the number of fish on the reef, then the interviewer probed to identify what the
respondent thought caused overfishing. A response to this might have been ‘the need for
money to help the family buy food’, thus both proximate and distal causes of fish decline
were identified. Respondents were not constrained to single answers for either proximate
96
or distal factors. Thus, the model developed in this chapter is relatively comparable with
the model presented in chapters 2 and 3 of this thesis.
Socio-demographic attributes were obtained from the respondents using a survey, during
the interviews, to determine whether these attributes could explain discourses of perceived
fish decline or increase. Socio-demographic variables collected were: site; age; years of
formal education; gender; whether the respondent was a migrant; primarily a middleman or
fisher; head of their household; and whether income from the sale of fish was their primary
household income (Table 4.1). Some perceived causes of resource decline are likely to be
site specific which might be reflected in the discourses. Likewise, management options for
increasing fish stocks might have greater support at some sites than others, particularly if
the respondents within sites have been exposed to particular management approaches that
they have seen succeed or fail. Older people might identify with longer-term, or chronic,
factors that shape the fish resource, while young people might identify with short-term, or
pulse, variability in accordance with the shifting baseline syndrome (Pauly 1995). Years of
formal education, including primary school, high school and tertiary education, is likely to
introduce western worldviews including scientific models that emphasize the role of human
agency in resource variability. Gender is a significant social division in Melanesia (Knauft
1997). Therefore it is possible that men and women are likely to have different life
experience, and consequently hold differing views on issues such as fisheries degradation
and management. Migrants, defined as respondents who migrated to where they currently
reside at some time after their early childhood, are more likely to be socially and culturally
marginalized (Cinner 2009). Therefore they might have less site-specific knowledge, and
therefore perceive ecological variation differently to non-migrants. Middlemen and fishers
perform different functions within the fishery, and are therefore likely to hold different
perceptions. Fishers might have a more intimate relationship with the fish in situ, whilst
middlemen are likely to have a better understanding of the effect of, for example, supply
and demand on fish stocks. Heads of households, who are generally men in Solomon
Islands, are responsible for the welfare of the household, and might therefore have a greater
awareness of, for example, threats to the viability of the fishery. Those whose primary
97
source of income is from fish are likely to have different perceptions of resource decline
and, potentially, negative attitudes towards conservation (Marshall et al. 2010) due to fear
of regulations, and therefore propose factors other than fishing to primarily reduce fish
stocks.
Table 4.1 Distribution of respondent socio-demographic attributes across study sites.
All Sites
Auki
Buala
Dunde
Gizo
Honiara
Tulaghi
(119)
(20)
(17)
(35)
(16)
(18)
(13)
Age (mean)
Education (mean)
Fish primary income source (yes)
Gender (male)
Migrant (yes)
Head of household (yes)
39.39
8.39
88
112
38
102
38.45
8.45
16
20
6
20
40.65
8.82
12
17
4
14
44.69
8.34
25
29
11
28
34.44
7.50
13
16
6
13
36.83
9.72
13
17
6
15
34.62
7.08
9
13
5
12
Middleman / fisherman (middleman)
17
1
2
5
1
8
0
98
4.2.2 DATA ANALYSIS
Three sequential analyses were performed on the data. First, qualitative responses relating
to perceived causes fish decline and increase were coded to generate quantitative variables.
All perceived proximate and distal factors of fish stock decline and increase were identified
for each respondent (n=119) in the form of notes taken during interviews. Notes were
subsequently categorized to themes that emerged by coding the notes (Glaser & Strauss
1965). Categorizing the qualitative responses provided a set of variables for distal and
proximate factors of both decline and increase. Second, the dominant discourses of each
decline and increase of fish stocks were identified by coupling perceived proximate factors
with their associated perceived distal factors. Principal Components Analysis (PCA), with
varimax rotation, was used on the variable set to generate latent variables (variables that are
inferred from a set of observed variables) that represented different discourses of fish stock
decline and increase, such that all factors affect each latent variable, but some factors have
a stronger effect than others and consequently contribute more to defining the latent
variable. A PCA comprising all proximate and distal factors violated the test requirements
of a Kaiser-Meyer-Olkin (KMO) value of ≥ 0.5 (Kaiser 1974) for both decrease and
increase of fish stocks. Therefore, to generate the dominant discourses, the PCA included,
using fish decline as an example, the most frequently stated proximate cause of fish decline
and its associated distal causes, followed by the second most stated proximate cause of fish
decline and its associated distal causes, and so on in a forward step-wise manner, until
KMO measure of sampling adequacy was <0.5. The data set from the PCA immediately
preceding the PCA of KMO <0.5 was retained. By utilizing this step-wise procedure, it
was possible to ensure that the more dominant discourses were retained, that the results
conform to the analysis requirements, and to retain a high number of respondents in the
analysis. Third, each of the latent variables generated by the two PCAs (one each for
decline of fish stocks and increase of fish stocks), which here reflect a dominant discourse,
was then tested against key socio-demographic attributes to determine whether dominant
discourses could be explained by respondent attributes.
99
4.3 RESULTS
4.3.1 FISH DECLINE
A total of 17 unique perceived proximate factors associated with fish decline were derived
from the 119 respondents (Table 4.2). Fishing effects, including general overharvesting
(39/119) and harvesting with modern fishing gear, comprised the majority of responses. In
particular, dynamite fishing (28/119), net fishing (34/119), and spear fishing (23/119)
(Photo 4.2) were perceived to decrease fish stocks. Dynamite fishing, in particular, was
highly site specific. Other proximate factors associated with fish decline included
particular forms of habitat degradation. A limited number of respondents stated that fish
behaviour, such as migration, also reduced fish stocks.
Photo 4.2 A typical catch from a night spearfishing trip in Roviana lagoon, Western Province that I was
fortunate to participate in. The catch includes bumphead parrotfish (‘Topa’) that were later sold to a local
tourist resort.
100
Table 4.2 Proximate causes of fish decline as perceived by respondents across sites. Values are the
percentage of the sample population that mentioned particular proximate factors. Columns do not sum to
100% because respondents were not constrained to a single answer. Grey shaded causes are those retained as
dominant proximate causes in the PCA.
Total
Auki
Buala
Dunde
Gizo
Honiara
Tulaghi
(119)
(20)
(17)
(35)
(16)
(18)
(13)
39
34
28
23
17
9
5
4
4
2
25
15
50
20
10
0
10
5
0
5
53
18
0
6
0
18
6
6
0
0
43
43
0
43
29
20
9
9
14
0
38
56
0
31
31
0
0
0
0
0
39
50
72
11
6
6
0
0
0
6
38
15
77
0
15
0
0
0
0
0
12
12
11
1
10
30
25
0
6
41
18
0
17
0
6
0
0
0
6
0
11
6
11
0
23
0
0
8
10
7
5
0
29
0
6
3
13
31
6
6
8
8
Fishing effects
General overfishing
Net fishinga
Dynamite fishing
Spear fishingb
Poison fishingc
Custom vine fishingd
Efficient gear (general)
Line fishing
Target spawning aggregations
Lamp fishinge
Habitat degradation
Pollutionf
Mangrove harvest
Coral harvestg
Stonesh
Fish behaviour
Fish mobility
Natural variability
Not sure
1
0
6
0
0
0
0
Net fishing included more precise factors such as nets with fine mesh, and mosquito nets used to harvest
juvenile fish.
b
Spear fishing includes both trigger mechanism spear fishing and hand spear fishing, a technique which is
frequently used at night to harvest sleeping fish such as parrotfish.
c
Includes a number of locally acquired poisons such as bush leaves and vines, and bêche-de-mer poison.
d
A traditional method of cooperative fishing, frequently used to harvest fish for ceremonies and community
fundraising.
e
Lamp fishing is relatively common in Malaita province. Fishers use lamps to attract fish.
f
Pollution includes sediment and urban waste run-off from land, and discharge from WWII wrecks and
vessels currently operating.
g
Coral is primarily harvested for the aquarium trade, to produce lime for consumption with betel nut, and for
coastal construction.
h
Line fishermen commonly use stones as weights to get their baited hook to the substrate.
a
101
Forward step-wise inclusion of proximate factors, and associated distal factors resulted in a
PCA that included four proximate factors and eight distal factors (KMO = 0.501; Bartlett's
Test of Sphericity = 235; p ≤0.05) (Table 4.3). Eighty seven percent (104/119) respondents
stated at least one of the four proximate factors as causing decline in fish stocks. Here,
each of the five Principal Components (PCs) is a latent variable which represents a
different discourse, with the five discourses explaining a total of 66% of the variance of
responses from the 104 respondents. Three of five PCs include both proximate and distal
factors associated with fish decline at a factor loading score of ≥ 0.3. PC1 represents a
discourse of ‘net fishing’ and ‘spear fishing’ caused by ‘fishing for immediate economic
gain’ and ‘laziness’, and ‘general overharvest’ not caused by ‘fishing for immediate
economic gain’. The second PC, which does not include any proximate factors, represents
a dichotomy in discourses between ‘fishing for economic affluence’, and ‘fishing for
economic survival’ and ‘no alternatives to fishing’. PC3 represents a dichotomy in
discourse between ‘dynamite fishing’ caused by ‘poor knowledge of sustainable fishing
techniques’, and ‘spear fishing’ caused by a ‘lack of alternatives’. PC4 represents a
discourse of ‘dynamite fishing’ caused by ‘fishing for immediate economic gain’, ‘laziness’
and ‘lack of alternatives’, and not with ‘consumption related survival’. PC5 represents a
less clear discourse; however, a weak ‘general overharvesting’ effect (-0.27 loading) is
caused by ‘population growth’ and not by ‘poor knowledge of sustainable fishing
techniques’.
102
Table 4.3 Principal Components Analysis of key proximate factors (P) and associated distal factors (D), for
fish stock decline. Bold values are loadings of ≥ 0.3. Components 1, 3 and 4 contain both proximate and distal
factors.
PC1
PC2
PC3
PC4
PC5
-0.79
-0.08
0.10
0.72
0.01
-0.19
0.03
0.35
-0.27
Fishing for immediate economic gain (D)
Net fishing (P)
0.71
-0.15
-0.84
0.16
-0.14
-0.13
0.11
0.12
0.22
0.09
-0.69
-0.03
0.42
0.09
0.35
0.12
-0.13
-0.75
0.01
0.01
-0.84
General overfishing (P)
a
Fishing for economic affluenceb (D)
Fishing for economic survivalc (D)
Dynamite fishing (P)
No alternatives to fishingd (D)
Spear fishing (P)
Fishing for consumption survivale (D)
Lazinessf (D)
Population growthg (D)
Poor knowledge of sustainable fishing techniquesh (D)
Eigenvalue
% variance explained
0.03
-0.04
0.82
0.21
0.26
0.10
0.18
-0.11
0.51
0.32
0.67
-0.07
0.58
0.22
0.30
0.04
0.08
-0.14
0.08
0.51
-0.21
0.11
0.00
-0.08
0.02
-0.16
-0.40
-0.07
0.55
2.35
1.76
1.53
1.18
1.03
0.09
19.6
14.65 12.74 9.87
8.59
Responses relate to ‘quick’or ‘easy’ money obtained from selling fish. For example, some respondents
referred to fishing locations as their ‘bank’ or ‘atm’ (automatic teller machine). Assuming a fishing trip is
successful, and that fish are sold, fishing provides a means of rapidly obtaining income compared to, for
example, gardening which requires planning and significant work before a return is realized.
b
Responses relate to fishing and selling fish to accrue financial wealth.
c
Responses relate to using income to meet economic needs such as school fees and basic household expenses
such as kerosene and clothing.
d
Responses relate to a lack of opportunities to pursue other sources of income which is an ongoing challenge
in Solomon Islands for reasons too complex to extrapolate here.
e
Responses relate to, for example, the purchase of rice, common in areas where people do not have land for
gardening, such as around Auki.
f
Responses relate to respondents perception that work ethic is absent among artisanal fishers.
g
Responses relate to the perception that increasing human populations is causing increased fishing.
h
Responses relate to the perceived reason why people use particular fishing gears.
a
103
4.3.2 FISH INCREASE
Proximate factors perceived to increase fish stocks did not correspond with proximate
factors perceived to decrease fish stocks. For example, whilst specific fishing gears were
commonly perceived to be the proximate cause of stock decrease (Table 4.2), the banning
of particular gears was infrequently perceived as a means of increasing fish stocks (Table
4.4). Instead spatial closures were the most common solution proposed for increasing fish
stocks. In particular, strong support was observed for spatial closures from respondents in
Dunde and Buala, both of which have protected area programs which restrict human
activities.
Photo 4.3 The provincial market in Gizo, Western Province, with local fishers selling their catch, primarily
caught by night spearfishing using torches and sling spears.
104
Table 4.4 Proximate causes of fish stock increase as perceived by respondents across sites. Values are the
percentage of the sample population that mentioned particular proximate factors. Columns do not sum to
100% because respondents were not constrained to a single answer. Grey shaded causes are those retained as
dominant proximate causes in the PCA.
Total
Auki
Buala
Dunde
Gizo
Honiara
Tulaghi
(119)
(20)
(17)
(35)
(16)
(18)
(13)
63
55
76
80
50
50
46
46
20
19
8
8
2
6
6
15
13
1
30
25
25
5
15
0
0
10
10
15
0
71
12
0
0
0
0
0
0
12
24
0
54
31
17
9
0
3
11
6
14
14
3
38
13
13
13
0
6
6
0
19
6
0
39
17
28
11
17
0
0
6
28
6
0
38
8
38
15
31
0
15
15
8
8
0
6
2
1
2
20
5
5
5
6
0
0
0
0
0
0
0
6
0
0
0
6
6
0
0
0
0
0
8
4
1
0
0
6
0
3
0
19
0
0
0
0
8
Fishing restrictions
Spatial restrictions
a
General spatial restriction
Spatial restriction for spawningb
Gear restrictions
Ban net fishingc
Stop dynamited
Ban poison fishinge
Reduce / ban spear fishingf
Line fishing only
Effort restrictions
Size restrictions
Species Restrictions
Habitat management
Ban habitat harvestg
Stop land-based pollutionh
Ban sea cucumber harvesti
Build artificial structure
Fish behaviour
Good habitat and food
Oceanographic variability
Not sure
3
5
6
0
13
0
0
Includes both permanent and periodic closures. Responses were often unspecified.
b
Relates primarily to the closure of areas when and where target species aggregate to spawn
c
Includes the use of nets with small mesh size including, in some instances, the use of mosquito nets.
d
Dynamite is largely sourced from WWII ordinances. It is an illegal and destructive, but potentially highly
profitable method of fishing.
e
Includes toxins from terrestrial plants and sea cucumbers.
f
Spear fishing, particularly at night using torches to target parrotfish, and other fish that sleep at night, has
become a very popular and efficient means of obtaining a substantial catch.
g
Habitat harvest includes mangroves for firewood and construction, and coral for construction, lime
production, and the aquarium trade.
h
Includes sediment from logging and urban waste run-off from land.
i
Primarily at Auki and Buala some respondents perceived an ecological relationship between sea cucumbers
and reef fish, such that overharvesting sea cucumbers caused fish to leave the overharvested location.
a
105
Forward step-wise inclusion of proximate factors, and associated distal factors resulted in a
PCA that included four proximate factors and eight distal factors (KMO = 0.507; Bartlett's
Test of Sphericity = 156; p ≤0.05) (Table 4.5). Eighty five percent (101/119) of
respondents stated at least one of the four proximate factors as causing increase in fish
stocks. Here, as with dominant discourses of fish decline, each of the six PCs is a latent
variable which represents a different discourse, with the six PCs explaining a total of 66%
of the variance of responses from the 101 respondents. All PCs explain a relatively equal
portion of the variance, suggesting no definitive pattern or single dominant discourse. Five
of six PCs include both proximate and distal causes of fish decline at a factor loading score
of ≥ 0.3. PC1 represents a dichotomous discourse, with one reflecting ‘spatial restrictions’
enabled through community cooperation, and the other representing ‘effort restrictions’ and
‘size restrictions’ enabled through ‘market regulation’. PC2 represents a dichotomy
between ‘spatial restrictions’ and ‘gear restrictions’ enabled through ‘bylaws with
penalties’. PC3 represents a dichotomy between ‘size restrictions’ enabled through
‘community law and leadership’ and ‘government law and enforcement with penalties’, and
‘community cooperation’ and ‘alternatives to fishing’. PC4, absent of proximate factors, is
a discourse of compatibility between ‘paid security’ and ‘bylaw with penalties’ at one end
of the range, and ‘community cooperation’ at the other end. PC5 is a dichotomy between
‘size restrictions’ enabled through ‘co-management’ and ‘bylaws with penalties’, and
‘effort restrictions’. PC6 is a dichotomy between ‘size restrictions’ enabled through
‘education and awareness’, and ‘strong community law and leadership’.
106
Table 4.5 Principal Components Analysis of key proximate factors (P) and associated distal factors (D), for
increasing fish stocks. Bold values are loadings of ≥ 0.3. Components 1, 2, 3, 5, 6 contain both proximate and
distal factors.
PC 1
PC 2
PC 3
PC 4
PC 5
PC 6
Market regulation (D)
-0.72
0.17
-0.04
0.08
0.24
-0.07
Effort restrictions (P)
-0.70
-0.26
0.03
-0.41
0.06
0.14
0.62
-0.03
-0.84
0.18
0.08
0.04
-0.07
0.62
-0.07
0.09
-0.03
0.04
-0.10
-0.13
0.77
0.17
0.03
-0.04
0.29
-0.78
0.09
0.00
-0.12
-0.05
0.54
-0.01
0.77
0.01
0.50
0.14
0.38
a
Gear restrictions (P)
Spatial restrictions (P)
Government law and enforcement with penaltiesb (D)
Alternatives including aquaculturec (D)
Paid securityd (D)
Community cooperation ('one mind')e (D)
Co-managementf (D)
Bylaw with penaltiesg (D)
-0.08
0.17
-0.57
0.20
0.39
0.22
-0.10
-0.35
0.00
0.00
-0.39
0.08
-0.33
Size restrictions (P)
Education and Awareness by government and NGOsh (D)
i
Strong community law and leadership (D)
0.04
0.26
0.18
0.14
0.24
0.21
-0.06
-0.04
0.39
0.11
0.33
0.11
-0.50
-0.07
-0.10
0.44
0.11
-0.02
0.83
0.13
0.05
-0.59
Eigenvalue
1.91
1.76
1.49
1.24
1.13
1.08
% variance explained
14.72 13.51
11.46
9.57
8.70
8.28
a
Includes numerous strategies focused on controlling the sale of fish.
b
Relates to the perceived need for Ministry of Fisheries and Marine Resources to legislate, disseminate and
enforce restrictions.
c
Relates to the provision of economically viable alternatives to reduce fishing pressure.
d
Anecdotal evidence suggests that poaching, particularly from protected areas, is prolific in some places.
Previously, there was security for protected areas around Dunde however the security failed to prevent
poaching.
e
A number of respondents referred to the need for ‘one mind’ which, I believe, relates to the need for
communities, and society more broadly, to agree on management strategies, and act accordingly.
f
Relates to cooperation between different levels of management including collaboration between government
and communities.
g
Provincial bylaws provide a legally binding foundation for communities to be able to establish resource use
rules and have them enforced through the respective provincial government.
h
Natural resource education and awareness is primarily conducted by NGOs in Solomon Islands in
collaboration with various government ministries. The perceived need for further education and awareness
suggests that some respondents perceived that lack of knowledge is an indirect cause of fish decline.
i
Social and cultural change is eroding traditional power systems in Solomon Islands communities leading to a
disregard for local resource management rules.
107
4.3.3 SOCIO-DEMOGRAPHIC ATTRIBUTES
Some socio-demographic attributes exhibited co-linearity (Table 4.6). Therefore, to retain
the maximum number of explanatory socio-demographic attributes, whilst removing those
that were significantly correlated (p ≤ 0.05), education and head of household were omitted
from further analysis. Only 7 women were interviewed, so gender was also omitted from
further analysis.
Table 4.6 Spearman’s Rank correlations between candidate socio-demographic explanatory variables. Sociodemographic variables retained for further analysis denoted in bold. *p ≤0.05, **p ≤0.01, ***p ≤0.001.
Education (ln+1)
Dependence (Y=1)
Gender (Male=1)
Migrant (Y=1)
Head of household (Y=1)
Middleman / fisherman (M=1)
-0.05
-0.14
-0.18*
-0.08
-0.04
0.00
-0.03
0.02
-0.01
-0.13
0.26**
0.11
-0.06
0.221*
-0.13
-0.17
0.31***
-0.10
-0.15
0.13
Age (ln)
Education
(ln+1)
Dependence
Gender
(Male=1)
Migrant
(Y=1)
(Y=1)
-0.11
Head of
household
(Y=1)
A number of the remaining socio-demographic attributes explain, significantly, some of the
dominant discourses of each fish decline and increase (Table 4.7). Site explained,
significantly, PC2, PC3, and PC5 of fish decline which represent the dichotomies between;
(a) ‘economic affluence’ and ‘economic survival’ caused by a ‘lack of alternatives’; (b) use
of ‘dynamite’ caused by ‘poor knowledge of sustainable fishing techniques’, and ‘spear
fishing’ caused by a ‘lack of alternatives’; and (c) ‘poor knowledge of sustainable fishing
techniques’ and ‘general overharvest’ caused by ‘population growth’, respectively. No
other socio-demographic attributes explained discourses of fish decline.
108
Table 4.7 Effect of socio-demographic attributes on the dominant discourses (PC’s) of both fish stock decline
and fish stock increase.*p ≤0.05, **p ≤0.01, ***p ≤0.001.
Sitea
Ageb
Dependencec, d
Middlemanc, e
Migrantc, f
PC 1
1.69
3-3
-0.66
0.08
0.14
PC 2
5.04***
-0.13
0.24
-0.57
1.26
PC 3
PC 4
8.23***
1.83
0.09
-0.09
-1.18
0.77
-1.54
-1.24
0.64
-0.24
PC 5
2.38*
0.05
0.59
-1.31g
0.83
PC 1
0.44
0.05
-0.35
-2.16*g
0.29
PC 2
PC 3
3.78**
2.2
0.06
-0.1
-0.78
0.65
-0.27
0.65
-2.09*
1.4
PC 4
4.42**
-0.01
-0.3
0.78g
-2.0*
PC 5
3.9**
0.09
-0.26
-0.74
0.29
PC 6
1.05
0.15
Analysis of variance (F statistic)
b
Pearson’s correlation coefficient
c
Independent sample t-test (t statistic)
d
Fishing as primary occupation = 1
e
Fisher = 0; Middleman = 1
f
Non-migrant = 0; Migrant = 1
g
Equal variance not assumed
-0.59
0.33
0.59
Fish stock decrease
Fish stock increase
a
Site also explained PC2, PC4, and PC5 of fish increase which represented the dichotomies
between; (a) ‘spatial restrictions’ and ‘gear restrictions’ enabled through ‘bylaws’; (b)
‘community cooperation’ and ‘paid security’ in conjunction with ‘bylaws with penalties’;
and (c) ‘effort restrictions’ and ‘size restrictions’ enabled through ‘co-management’ in
conjunction with ‘bylaws with penalties’, respectively. Middlemen were significantly more
likely to be supportive of effort and size restrictions enabled through market regulation, and
less likely to support spatial restrictions through increased community cooperation, than
were fishers. Migrants were more likely to be supportive of gear restrictions enabled
through bylaws, and less supportive of spatial closures, than non-migrants. Migrants were
also more likely to be supportive of bylaws in conjunction with paid security, and less
supportive of community cooperation, as a means of increasing fish stocks, than non-
109
migrants. Respondent age and dependence on fishing as a primary source of income did
not explain, significantly (p ≤0.05), any of the discourses of fish stock decline or increase.
4.4 DISCUSSION
4.4.1 SCIENTIFIC AND LOCAL EXPLANATIONS OF CORAL REEF FISH DISTRIBUTIONS
The perceived causes of fish decline identified in this study, among artisanal fishers and
middlemen in Solomon Islands, are concordant with scientific evidence. I n particular,
respondents most frequently identified fishing, and its derivatives including specific gear
types, as the proximate cause of fish decline. The perceived distal factors of overfishing
also have some compatibility with earlier studies that identified population growth, access
to markets, modernization and associated urbanization as driving increased market-based
fishing pressure (Sabetian & Foale 2006; Brewer et al. 2009; Aswani & Sabetian 2010).
For example, the perceived distal factors associated with efficient gears used for marketbased fishing included fishing for cash income and associated economic survival, gain and
affluence. This perception aligns with links, identified in this thesis, between market-based
fishing and access to markets (Brewer et al. 2012a).
The perceived means of increasing fish stocks are aligned with current scientific and
government views on fishery management. Spatial closures, which are readily advocated
in the literature as a primary fishery management tool, were perceived by the majority of
respondents to be an efficacious approach to managing the reef fishery. Importantly,
permanent spatial closures are very rare in Solomon Islands so respondents were likely to
instead be advocating temporary spatial closures. Secondary to spatial closures,
respondents perceived that gear, effort, and size restrictions would increase fish stocks,
which is also aligned with current scientific recommendations for Melanesia (Cinner &
Aswani 2007; McClanahan & Cinner 2008; Cinner et al. 2009c). Particular gears,
however, were readily perceived to cause fish decline, yet far fewer respondents perceived
that banning specific gears would be an appropriate management action. Fishers are likely
110
to own and possess greater skill with particular fishing gear, and would therefore consider
the banning of gear that they own or are skilled at using to be an unfair regulation
compared to spatial restrictions which would, depending on their location, restrict all gear
types and be a fairer solution.
Local knowledge can provide important insights, not apparent in broader scientific
assessments, of our effects on resources (Johannes 1981; Johannes et al. 2000), and
therefore contribute to broader resource management knowledge (e.g. Aswani & Hamilton
2004). A number of the distal causes of fish decline in this study relate to fisher
motivations to fish, which are not directly reflected in the previous studies that identified
human population pressure, market access and socio-economic development as distal
drivers of fish decline (Brewer et al. 2012a). These factors include laziness, fishing for
immediate economic gain and poor knowledge of sustainable fishing techniques. Improved
understanding of motivations to exploit, at the scale of the individual person, might provide
opportunities for targeting management in a manner that individuals can empathize with
and potentially respond to.
4.4.2 DOMINANT DISCOURSES
There is no single dominant discourse within the population sampled. Proximate factors
are numerous, PCA was not possible for the complete sample, and the derived discourses
including both proximate and distal factors are multiple and complex. This result reflects
the diversity of challenges to the management of inshore fisheries in Solomon Islands.
The most pronounced theme across the discourses of fish decline is that of the divide
between what I will term ‘self-interest and affluence’ on one side, and what I will term
‘poverty and lack of alternatives’ on the other, which reflects a gradient of perceived
inequality. For example, the first discourse (PC1) is polarized into respondents who
perceive fish decline due to the use of modern gears motivated by economic gain and
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laziness, and those who perceive general overharvest to be a major cause of fish decline.
The second discourse (PC2) is polarized into fishing for affluence and fishing for survival
motivated by a lack of alternatives. The fourth discourse (PC4) is polarized into those who
perceive that laziness induced destructive fishing practices (dynamite) causes fish decline,
and those who perceive fish decline is due to basic consumption survival. This polarity of
perception across multiple discourses might reflect the social-political transformation
underway in Solomon Islands whereby the increasing availability of consumer
commodities, facilitated through trade under a common domestic currency, is driving
fishers to over-exploit resources for income to attain increased social status (Ruddle 1993)
and force inequality. However, the perception of affluence as a driver of overfishing is
likely to be only perceived rather than real because there was, based on field observations,
little evidence of fishers or middlemen attaining significant economic affluence from the
fishery. Rather, affluence likely reflects resentment toward fishers and middlemen who, for
example, have access to more efficient fishing gear or have exclusive rights to particular
markets, and therefore aspire to, rather than realize, significant affluence.
A dominant theme across discourses for fish increase is that of a gradient from top-down
command-and-control government management to decentralized community management
based on an environmental ethic of resource users. Distal factors associated with
command-and-control are market regulation, government law and enforcement with
penalties, and bylaws with penalties. Distal factors associated with decentralized
management are community cooperation, education and awareness, and strong community
law and leadership (Table 4.5). There has been significant adverse reaction, in recent years,
to command-and-control fisheries management and concurrent advocacy for the devolution
of inshore fisheries management to the level of resource user groups, and for comanagement whereby government and resource users work in dynamic partnership (e.g.
Cinner et al. 2012b). Supporting arguments for the shift away from command-and-control
management include the potential for empowerment of resource users, and increased socialecological resilience achieved through a shift from panacea management toward context
dependent management (Holling & Meffe 1996; Knight & Meffe 1997) that relies more
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heavily on local knowledge. Indeed, while the people of Solomon Islands have always had
control over the exploitation and management of their resources, there is growing support
of resource management by people with user rights from national and provincial
government. For example, the national and provincial governments are taking action to
ensure there is legislative support for community regulations in co-management-like
arrangements, including fisheries management plans that explicitly include communitybased management (Govan et al. 2011), provincial bylaws and forthcoming amendments to
the National Fisheries Act.
It is possible that the support for command-and-control by some fishers and middlemen is
because respondents perceive that small social-political groups such as clans, which
theoretically control resource use, are impotent in enforcing regulations. This potential
impotence might stem from the weakening of traditional management authorities such as
village chiefs (Ruddle 1993; Dinnen 2002) and more recently the church. Therefore, while
command-and-control fisheries management clearly has limitations, fisheries managers
should not ‘throw the baby out with the bathwater’. That is, some dimensions of
command-and-control management, such as banning the importation of destructive fishing
gears, might be well received by the fishers and middlemen. Further research, is needed,
that identifies which social-political levels, from nation to resource user groups, are best
suited to formulating and enforcing different management approaches (but see Govan et al.
2011).
4.4.3 SOCIO-DEMOGRAPHIC ATTRIBUTES
Respondents within sites have similar perceptions relative to respondents between sites
across a number of discourses. It is possible that fishers and middlemen, through frequent
within-site dialogue relating to fish stocks, have developed some consensual perceptions
(Evans et al. 2011). Cultural consensus has been shown to relate to marine ecological
knowledge and customary sea tenure in Solomon Islands (Grant & Miller 2004; Aswani
2005). Therefore it is possible that artisanal fishers and middlemen have developed a site113
specific market culture relating to the fishery, including a shared understanding of causality
of fish stock variability.
Middlemen were more likely than fishers to be supportive of size and effort restrictions
enabled through market regulation, whilst fishers were more supportive of spatial
restrictions enabled through community cooperation. This finding suggests an element of
altruism because such measures would (at least temporarily) restrict middlemen, requiring
them to adapt their business practices, and fishers because it would reduce the area from
which they are able to fish. One possible explanation for this result is that both middlemen
and fishers believe that fish stocks are adequately depleted to justify a reduction in potential
income to ensure the long-term viability of the fishery (Cinner et al. 2009a). However,
there are a diverse set of both forms of altruism, and motivations for altruistic behaviour
(Fehr & Flschbacher 2003), which would have to be further explored to more confidently
explain this finding. Alternatively, the responses might reflect a dichotomy in knowledge
between fishers and middlemen, whereby fishers are better acquainted with community
fishing regulations and middlemen are better acquainted with markets.
4.4.4 LIMITATIONS
The interviews were conducted in major urban centres where markets exist because there is
strong evidence that market-based fishing is having a negative effect on reef fish
distributions across Solomon Islands (Brewer et al. 2009; Aswani & Sabetian 2010; Brewer
et al. 2012a). Therefore the population sampled in this study does not explicitly consider
remote populations where market-based fishing is less pervasive. Remote populations
might have different perceptions and a different discourse. However, at the time of the
interviews, a number of the respondents were living in remote rural areas and travelling to
urban centres to sell their catch.
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It is not possible to infer whether the results of this study represent true fisher and
middlemen perceptions or rhetoric obtained through information networks divulged to
please the interviewers. Conservatively assuming that responses largely represent rhetoric,
it is possible to conclude that fisher’s and middlemen are informed of the scientific
explanation for fishery decline and management strategies. The most likely answer,
however, is that the responses represent a combination of both true perception and rhetoric.
4.5 CONCLUSIONS
This chapter has generated two insights that are directly relevant to the establishment of
marine policy. First, fishers and middlemen involved in market-based fishing in Solomon
Islands generally are aware that fishing pressure affects fish stocks and that broad social
and economic factors affect fishing pressure. Therefore the perceptions of fishers and
middlemen are compatible with the current perceptions of scientists, and support the
findings of this thesis. Second, there is a dichotomy in perceptions for the causes of fish
stock decline and increase. Respondents tended to perceive that fish decline was caused by
either fishing for survival-related reasons or fishing for reasons of affluence and aspiration
which highlights perceived inequality. Respondents also tended to perceive that either
command-and-control or community-based management would increase fish stocks.
Further research interrogating these dichotomies of both decline and increase might
contribute to improved management approaches for identified causes of resource decline.
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CHAPTER 5: GENERAL DISCUSSION AND CONCLUSIONS
In this thesis I have compared the relative merit of the three dominant environmental
sociology perspectives; Malthusian overpopulation, market expansion, and modernization,
using a novel comparative model that accounts for resource exploitation and management,
in a novel social-political context at the local-level (chapters 2 and 3). I have also
identified the dominant discourses of local resource users regarding the social factors that
affect natural resource conditions (chapter 4), thus triangulating the comparative modeling
(chapters 2 and 3). In doing so, this thesis has contributed to theory of human-environment
interactions and has consequently broadened our understanding of the social processes that
explain variability in the state of natural resources.
Discussion and theoretical contributions relating to each of the three data chapters (four
papers) is contained within each respective chapter. Therefore those chapter-specific points
of discussion and theoretical contribution will not be repeated here. Instead I: 1) review the
research gaps, show how they have been addressed in this thesis, and highlight how
addressing the research gaps contributes to theory, 2) present a unified narrative of
society’s effects on coral reef fishery resources in Solomon Islands as the broad theoretical
contribution of this thesis, 3) discuss limitations to the thesis, and avenues of potential
future research, and 4) draw general conclusions.
5.1 REVIEW OF THE RESEARCH GAPS ADDRESSED IN THIS THESIS INCLUDING
THEORETICAL CONTRIBUTIONS
The broad aim of this thesis was to determine which environmental sociology perspective
about society’s effects on natural resources best explains natural resource distributions in
the Solomon Islands. Many scholars have addressed this aim using particular models (i.e.
testable frameworks such as Figure 1.5 in this thesis), at particular scales (e.g. York et al.
2003a; Hoffmann 2004), and in particular ecological contexts. However, there is clear
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evidence that the merit of each of the dominant perspectives varies across models, scales,
and contexts (Fisher & Freudenburg 2001). In this thesis, I used a novel model that
incorporates elements of human behaviour (exploitation and management institutions), to
test the merit of the perspectives in a novel context at the local-level. In doing so, this
thesis 1) incorporated elements of behaviour into the model, advancing our understanding
of the social processes that explain the state of natural resources; 2) contributed to the
growing quantitative literature for and against each of the dominant perspectives by
quantitatively analyzing results in a novel context and an important, but understudied
social-political scale; 3) triangulated the findings derived from the quantitative model with
local perceptions of the drivers of natural resource state. In doing so, the model was
internally verified. That is, the people within the context of this study confirmed the
conclusions drawn from the general model. I proceed by reiterating the identified research
gaps and how they were addressed in this thesis, and outline the theoretical contributions
derived from doing so.
The first identified research gap was one of ‘limited understanding of causal links between
social and ecological systems’. The majority of studies that compare the relative merit of
each perspective (Malthusian overpopulation, market expansion, modernization) examine
the effect of distal drivers on resource state (Figure 1.2) by direct correlation (e.g. York et
al. 2003a; Hoffmann 2004). This thesis advanced this general model by including both
exploitation and management institution variables within the model as proximate drivers
that mediate the relations between the distal drivers and resource state variables (Figure
1.5). Inclusion of these proximate drivers added to our understanding of each of the
perspectives by presents the perspectives as a sequential process, rather than a direct
correlation. For example, in the context of coral reefs there is evidence that increased
fishing pressure (proximate driver), unsurprisingly, is negatively correlated with in situ fish
assemblages (e.g. biomass) (e.g. Jennings et al. 1995; Jennings & Polunin 1996). There is
also evidence that the distal drivers including market access and population pressure,
explain in situ fish assemblages (Brewer et al. 2009; Cinner et al. 2009b; Cinner et al.
2012b). Yet there is little evidence of the sequential effects of distal drivers on proximate
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drivers, and proximate drivers on fish assemblages (a paucity of evidence that extends to all
ecological systems). One exception is an aforementioned study by Cinner (2009b) that
found that, across a number of countries in the Western Indian Ocean, 77% of the variance
of fish biomass was explained by local-level socioeconomic development concordant with
the environmental Kuznets curve, and population density was a poorer descriptor of fish
biomass. Further, the study explained the effect of socioeconomic development on fish
biomass by a number of mechanisms (equivalent to proximate drivers) including more
benign fishing gears such as handlines and higher salaried employment at higher levels of
socioeconomic development. The study by Cinner and colleagues showed that some of the
proposed modernization mechanisms did explain why environmental conditions are better
at high levels of modernization. This thesis has arguably advanced on the study by Cinner
et al. by analysing the three identified dominant perspectives within a single system model
(Figure 1.5), showing how distal drivers (as manifestations of the three dominant
perspectives) relate key proximate drivers, and how exploitation, as a proximate driver,
explains the state of the natural resource. In doing so, this thesis has built a more complete
social-ecological system model, than earlier studies, based on a firm foundation of
environmental sociology theory.
Inclusion of these proximate drivers, and testing their relation with distal drivers and
natural resources, has contributed to theory of how human societies affect natural resources.
Specifically, chapter 2 of this thesis shows that, in Solomon Islands, both distance to
market (as a manifestation of the market expansion perspective) and local population
density (as a manifestation of the Malthusian overpopulation perspective) explained 76% of
the variance of fishing pressure (using efficient fishing gear) which, in turn, explains, to
varying degrees, a number of in situ fish assemblage parameters including biomass,
biomass of fish that are vulnerable to fishing, species diversity, and functional group
biomass. Importantly, their effects represent different variance explained (i.e. population
density and distance to markets have additive effects) and so both the Malthusian
overpopulation and market expansion perspectives have merit, and therefore attachment to
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any single perspective is likely inappropriate when formulating policy to address issues of
resource scarcity.
Chapter 3 of this thesis showed the effects of distal drivers on the occurrence of resource
management institutions [institutions could not be linked to resource state for reasons
outlined in the limitations (section 5.3)]. There is a significant literature on social and
economic factors that affect the success of resource management institutions, particularly
relating to common-property resources (Ostrom 1990; Agrawal 2001; Cinner 2005;
Agrawal & Chhatre 2006; Cinner et al. 2007; Ostrom 2007; Cinner et al. 2012b). However,
no studies, that I am aware of, have explicitly considered how the dominant perspectives
(measured as manifest variables such as human population density as done in this thesis)
explain institutional efficacy or occurrence. Chapter 3 shows that, within the scope of the
thesis, population size (as a manifestation of Malthusian overpopulation) has an overall
positive effect on the probability of institution occurrence, suggesting management
response to declining resources driven by high populations, which supports optimum
population size theory (Agrawal & Golyal 2001). However, human population density had
a strong negative effect on institution occurrence, suggesting possible failure of institutions
with increased population per available resources, which is also supported in fisheries
literature (Pauly 1988). That population size had a positive effect on probability of
institution occurrence and population density had a negative effect on institution occurrence
will require further investigation. While the merit of the Malthusian overpopulation
perspective, for explaining institutional occurrence, is not clear, it is probable that
management is more likely to occur in instances of relatively large populations (for the
Solomon Islands) with a large resource base. The positive effect of market presence on
institution occurrence counters market expansion claims, that economic growth and
expansion over-ride environmental concerns (Schnaiberg et al. 2002). However, it is
possible that the positive effect of market presence, on institution occurrence might be a
result of resource owners using management institutions to exclude non-owners, thus
maximising economic gain (Ruttan 1998). This proposition is likely because the effect of
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markets on management institution occurrence was only significant for temporary closures
– which might represent a more discrete approach for excluding non-owners.
The second identified research gap was one of ‘social-political scale’. There is a distinct
paucity of studies that compare the three perspectives at the local-level on the socialpolitical scale, yet social-ecological patterns vary across the social-political hierarchy
(individual person to global) (Warren 2005), and it has been acknowledged that there is a
need to understand how the different perspectives explain resources at different socialpolitical levels (Clausen & York 2008a). All quantitative analyses of the three perspectives
have been conducted at the national-level (York et al. 2003a; Hoffmann 2004; Clausen &
York 2008b, a; McKinney et al. 2009). National-level data is useful because it shows
general global trends across a broad spectrum of modernization, Malthusian overpopulation
and market expansion. However, it does not allow the use of detailed ecological data that
is more relevant to, for example, ecosystem function. Neither does it allow the inclusion of
detailed exploitation and management institutions, for specific resource types, as used in
this thesis. Further, in a peripheral nation context, resources are often only managed at the
local-level. Analysis at the local-level in this thesis has overcome these limitations
showing variation in ecological responses to different social factors (chapter 2). As a result
this thesis has shown strongest support, at the local-level, for both the Malthusian
overpopulation and market expansion perspectives; a result that is broadly aligned with the
national-level analyses. However, given the different model used in this thesis (research
gap 1) and the geo-political context (research gap 2) it is not possible to draw direct
comparison between this thesis and the nation-level studies.
The third identified research gap was one of ‘geo-political context’. Studies that compare
and contrast all three perspectives tend to focus on modernized and affluent nations and
societies (e.g. Schnaiberg 1980; Grossman & Krueger 1995; Mol 1995; Weinberg et al.
2000; Luck 2007), and no comparative studies have focused on the global economic
periphery. Yet, there is strong evidence that the position of a nation in the world system
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(Wallerstein 1974), be it peripheral, semi-peripheral, or core, has a bearing on the state of
its natural resources (Hoffmann 2004; Bunker 2005; Shandra et al. 2009; McKinney et al.
2010). World system position has particular relevance to the modernization perspective,
because the theory implies that more affluent, or modernized, societies are able to
externalise their ecological footprints. Thus, quantitative evidence of the modernization
perspective within core nations (Grossman & Krueger 1995; M'henni et al. 2011) might be
due to import of resources and export of pollutants (Figure 1.1). Therefore, there was a
distinct need to understand, better, the effects of societies on natural resources within a
peripheral nation context, where a large portion of global biodiversity exists (Myers et al.
2000; Kramer et al. 2009). I addressed this research gap by focusing analyses on Solomon
Islands, a peripheral nation (Babones 2005). In doing so, I found only limited substantive
evidence for the modernization perspective in Solomon Islands. In fact, modernization had
no discernable effect on fishing pressure, suggesting that in the within-peripheral nation
context, modernization has little bearing on natural resources and that markets and local
population pressure are the dominant forces. However, there was some evidence of higher
incidence of species and gear restrictions in more modernized communities, suggesting
that, overall, and modernization might have a net positive effect on coral reef fisheries in
Solomon Islands. Yet, the communities in this study would certainly lie at the lower end of
the global modernization spectrum; therefore the positive effect of modernization of species
and gear restrictions is not explained as the environmental Kuznets curve.
The fourth research gap was one of ‘triangulation of findings’. None of the quantitative
comparative studies of the three perspectives have used local perceptions data to triangulate
comparative findings. Yet, two significant benefits to theory development are likely to be
derived from analysis of local perceptions. First, local perceptions will either support or
refute the comparative model, adding to weight of evidence, or force a review of the
comparative model and its assumptions, respectively. Generally, the analysis of local
perceptions in this thesis (chapter 4) (Brewer 2012) supported the findings of the
comparative analyses. In particular, fishers and middlemen perceived that efficient and
destructive fishing gears (e.g. fishing nets and spears) were the dominant proximate drivers
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– a finding that supports the results of chapter 2. Further, distal drivers of resource decline
perceived by fishers and middlemen were concordant with both Malthusian overpopulation
and market expansion, including population growth, fishing for consumption survival and
fishing for economic gain. Modernization was not a perceived driver of fish decline [partly
because the terminology is not common in the local vernacular, however, ‘development’ as
a comparable concept which is common in the vernacular (Foale 2001), was not mentioned
explicitly], but does relate to fishing for affluence and immediate economic gain for
aspirations associated with modernization. Fisher and middleman perceptions of means of
increasing fish stocks were also broadly concordant with the findings of chapter 3.
Frequently elicited proximate drivers of fish stock increase included spatial restrictions and
fishing gear restrictions that were both analysed in chapter 3. Distal drivers associated with
spatial restrictions included market regulations and bylaws with penalties which supports,
in part, the market expansion perspective. The only distal drivers perceived to assist gear
restrictions was bylaws with penalties. The perceived importance of bylaws shows the
perceived need for assistance with local regulation from the provincial and national-levels
of governance (which is raised further as an issue of social-political scale in the limitations
section). Also interesting was that, despite the Malthusian overpopulation perspective
dominating the comparative analysis in chapter 3, managing population effects was not
perceived by any respondents as a means of increasing fish stocks. The reason for this
difference is not clear, especially given that population growth was frequently perceived as
a cause of fishery decline. All evidence considered, local perceptions were broadly
supportive of the results of the comparative analyses in chapters 2 and 3, except for the
effects of population size and density on the occurrence of fishing restrictions that I believe
contributes robustness to the conclusions of the comparative analysis. Second, local
perceptions are likely to include factors that operate at the level of the individual rather than
the local- or national-level (following research gap three above). Indeed, there were a
number of perceived factors identified by resource users, which likely drive individuals to
over-exploit coral reef fisheries in Solomon Islands that were not considered in the locallevel analysis in this thesis. These factors included, for example, ‘laziness’ and ‘poor
knowledge of sustainable fishing techniques’. As mentioned in chapter 4, consideration of
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these factors might provide opportunities for targeting management in a manner that
individuals can empathize with and potentially respond to.
5.2 THE BROAD THEORETICAL CONTRIBUTION OF THIS THESIS: A UNIFIED
NARRATIVE OF SOCIETY’S EFFECTS ON CORAL REEF FISHERY RESOURCES IN
SOLOMON ISLANDS.
It is clear from the results presented in each of the data chapters, that no single perspective
explains society’s effects on coral reef resources at the local-level in Solomon Islands. In
fact, there is evidence that elements of all three perspectives operate within the fishery.
There is support for both the Malthusian overpopulation and market expansion perspectives
with regards to fishery exploitation and the state of the fishery (chapters 2 and 4).
Relatively efficient fishing gears explain the state of the fishery, with greater density of
more efficient fishing gear correlated with reduced biomass of vulnerable species, species
diversity, and biomass of functional groups (Figure 5.1 (a)). Efficient fishing gear is
synonymous with both Malthusian overpopulation and market expansion perspectives.
Within the Malthusian overpopulation narrative, local human population growth leads to
declining resources, forcing resource exploiters to increase gear efficiency to maintain
catch-per-unit effort (Pauly 1988). Within the market expansion narrative, labour is
exchanged for technology (efficient gears) to maximise profit (Schnaiberg 1980). That both
human population density and access to markets explain efficient fishing gear (Figure 5.1
(b, c)) lends further support to the Malthusian overpopulation and market expansion
perspectives, respectively. These findings are broadly consistent to previous studies,
conducted at the nation-level that showed Malthusian overpopulation and the market
expansion perspectives best explained resource distributions (York et al. 2003a; Hoffmann
2004; Clausen & York 2008b, a; McKinney et al. 2009) (Table 1.1). Further, fisher and
middlemen perceptions of the cause of fishery decline supported both the Malthusian
overpopulation and market expansion perspectives. In particular, respondents perceived
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that fishing for affluence and fishing to meet immediate family needs were primary drivers
of fishery decline, which support the market expansion and Malthusian overpopulation
perspectives, respectively.
Figure 5.1 Local-level process-based model (which could also be considered a narrative) of society’s effects
on coral reef resources in Solomon Islands derived from chapters 2 and 3 of this thesis.+/- = direction (slope)
of effects; a-f = see text above and below.
The support for both Malthusian overpopulation and market expansion perspectives
highlights a spectrum of drivers of resource decline. Malthusian overpopulation, at one
extreme likely relates to exploitation to meet local needs. In times past, when there was not
cash-based trade of resources, but only barter or the use of local currency, population was
likely the dominant driver of the state of natural resources. Indeed, Malthus’ calculations
considered local and national population growth, without any explicit mention of the
potential for trade to buffer future environmental catastrophe (Malthus 1798). Then, the
insurgence of other ways of thinking and doing, by increased globalisation, opened
communities to trade, through a common currency, and novel material goods that presented
incentive to exploit resources beyond immediate needs (Ruddle 1993; Sabetian & Foale
2006). This change represents a transition from population to markets and trade as drivers
of over-exploitation, from fishing motivated by needs to fishing motivated by material
wants, and, socio-politically, from relatively egalitarian communities (Marx 1887; Baines
1989) to communities containing entrepreneurial capitalist enterprise aimed at maximising
personal gain (Smith 1843; Brewer 2011). The result of this transition, from one end of the
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spectrum to the other (which is likely continuing), is increased inequality in the allocation
in benefits from the fishery.
To contextualise this spectrum I turn to field observations of the two extremes. In one
community visited, there was a women’s fishing group that used basic fishing gear
including wooden canoes and handlines. They would frequently fish through the night, and
return with a small catch. Some of the members of the group reported that most of the fish
were for personal consumption or for local sale to meet basic household needs including
family support. This group epitomises the egalitarian fishery, elsewhere viewed as the
welfare fishery (Béné et al. 2010), where fishery resources are seen as insurance against
poverty and unemployment. In the same community there were young men who fished
using comparatively sophisticated gear including fibreglass boats with outboard motors,
spears, and torches for night-spearing. Catches could be significant, particularly if fish
spawning aggregations were targeted, or particular parrotfish were found in abundance. The
catch of this group was invariably sold. Indeed, in this community and others, particular
reefs were given names, relating to immediacy of the economic utility of the resource, such
as “A.T.M.” (automatic teller machine) – rapid access to cash. While I cannot confirm how
income from the catch was spent, it is likely a portion was spent on luxury items including
imported non-essentials, purchased at local stores. This group represented the capitalist
production, or rent-maximisation fishery (Béné et al. 2010) – the more recent of the two.
These two groups, though targeting the same resource, represent markedly different sectors
of the small-scale fishery, and of the community. The support of either of these fishery
types must be carefully considered in policy relating to maximising societal benefits (rent
or welfare) from small-scale fisheries.
However, the narrative of society’s effects on coral reef resources is not fully explained by
this spectrum. With the exception of human population density, the distal drivers have a
positive effect on the probability of institution occurrence. These positive effects suggest
that institutions might be adapting to social and economic change (Hviding & Baines 1994;
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Hviding 1998) in Solomon Islands (Chapter 3). In particular, institutions are more likely to
occur in communities with fish markets (Figure 5.1 (d)), in more modernized communities
(Figure 5.1 (e)), and in communities with medium- to large-sized populations (Figure 5.1
(f)). This finding lends some weight to the modernization perspective. Yet, evidence
suggests that, by way of increasing fishing pressure using sophisticated gears, population
density and markets negatively effect, and modernization has no effect on, reef fish stocks
in Solomon Islands (Chapters 2 and 4) (Brewer et al. 2009; Aswani & Sabetian 2010;
Brewer et al. 2012a). It is possible, therefore, that despite higher probability of occurrence
in more modernized communities with medium to large population size and fish markets,
management institutions exist, but are not succeeding in stemming resource decline. This
begs the question of why institutions are not sustaining or improving resource condition
with high population pressure and access to fish markets.
According to the modernization perspective, the primary reason why institutions are not
stemming resource decline is because a high enough level of modernization has not been
attained for consideration of the environment, to the point of increased resource abundance.
Instead, focus remains on meeting basic needs including food security and housing
(Maslow 1943), which is certainly evident in Solomon Islands. Secondarily, and associated
with increased modernization, the mechanisms for improved resource conditions are not
present, including adequate investment in scientific and management institutions that
prevent overexploitation (see Cinner & Aswani 2007 for a review of institutions relevant to
the context), alternative livelihoods outside of resource exploitation, and importation of
resources instead of local exploitation. Logically, therefore, if the modernization
perspective is relevant to Solomon Islands communities, there is a need for increased
modernization to enable decreased exploitation pressure on local resources.
However, it is likely that factors operating at larger social-political levels (national and
global) are driving local-level over-exploitation and constraining local-level modernization.
It is possible that because of poor governance (Kaufmann et al. 2009) including corruption
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in extractive industries (Larmour 1997), social and political instability, and poor terms of
trade internationally, Solomon Islands [as is likely in other peripheral nations (Wallerstein
1976)] might not reach a level of modernization that enables discernable consideration of
environmental welfare, as predicted by the environmental Kuznets curve (Figure 5.2). For
example, timber has historically been the major source of federal revenue – largely shipped
offshore, to more affluent nations, as unprocessed logs to the economic benefit of
multinational companies (Foale 2001). Anecdotally, little income from logging is received
at the local-level, and when it is, it is not equitably distributed, and often squandered. Few
significant timber resources remain in Solomon Islands due to overexploitation. Further,
Solomon Islands does not possess significant secondary (e.g. manufacturing) or tertiary
(e.g. information technology and services) industries, and is consequently heavily reliant on
imports. The primary means of accessing these imports is through resource rents from
fisheries, forestry and mining. Therefore, I think that the poor return on investment from
extractive activities subject communities in Solomon Islands to chronic poverty that might
not change with continued resource exploitation. Instead poverty traps - a self-reinforcing
mechanism which causes poverty to persist (Azariadis & Stachurski 2005; Barrett &
Swallow 2006; Cinner 2011) - might become more prevalent if local-level resources
continue to diminish without significant improvements in terms of trade and improved
national-level governance. The relevance of social-political scale in explaining local-level
resource conditions is further discussed in the limitations (section 5.3).
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Figure 5.2 A heuristic model of the effect of world systems trade on modernization trajectories for core and
peripheral nations. Here, I hypothesise that core nations achieve environmental Kuznets curve trajectories by
way of importation of resources from, and export of pollutants to, peripheral nations. Based on this
hypothesis, there is a need for national- and global- level shifts in terms of trade if local-level communities in
peripheral nations are to modernize in the form of the environmental Kuznets curve.
In summary, local population growth and commoditization of resources, and a transitioning
economy, from one of egalitarian distribution of resources to one of personal gain, is
driving increased exploitation using efficient fishing gear. However, there is a local-level
response, in increased likelihood of occurrence of management institutions in more
modernized communities with fish markets, and in communities with medium to large
populations. Yet, ensuring future sustainable use of resources locally will likely require
addressing issues such as trade inequalities in national and global social-political systems.
5.3 LIMITATIONS TO THE THESIS AND CONSEQUENT FUTURE RESEARCH
The narrative presented in section 5.2 is the process-based model that has resulted from this
thesis, including the comparative analyses in chapters 2 and 3, and the information elicited
from surveys associated with chapter 4. In this section I describe limitations to the thesis
129
narrative outlined above. In doing so, I build on the narrative to incorporate the broader
system properties that represent limitations to the thesis. This results in an extended model
including tested (this thesis) and hypothesised factors that are likely to explain resource
distributions in peripheral nations at the local-level. Thus, this section culminates in a
broader model for future testing.
5.3.1 THE WRONG METHOD OR MISSING VARIABLES IN THE GENERAL MODEL?
This thesis has used mixed methods (Tashakkori & Teddlie 2002) to reach its conclusions;
quantitative analysis was used for chapters 2 and 3, and a combination of quantitative and
qualitative analyses were used for chapter 4. The conclusions of the thesis are derived from
the quantitative analyses in chapters 2 and 3, and qualitative responses from fishers and
middlemen to triangulate the quantitative findings.
Detailed fishers’ and middlemen’s perceptions, combined with the complex narratives of
each of the perspectives (summaries of which are presented in the Introduction) highlights
the incompleteness of the overarching thesis model (Figure 1.5). That is, there is
contextual complexity that cannot be captured only by such statistically testable,
quantitative, reductionist models (Johnson & Onwuegbuzie 2004). For example, there are a
number of environmental non-government organisations now based in Solomon Islands,
including The Nature Conservancy, WorldFish, World Wildlife Fund, and the Coral
Triangle Initiative that focus on natural resource management and rural livelihoods. The
actions of these organizations, in theory, are supportive of the modernization perspective
because they represent a dampening response to environmental degradation, and the
evolution of traditional management systems towards hybrid systems more adept at
managing modern resource management challenges (Cinner and Aswani 2007). In
addition, review of national fisheries policy might show a shift from a focus on resource
exploitation to one of conservation that would also lend weight to the modernization
perspective. Consequently, the thesis might have benefited from the inclusion of a
qualitative description of evidence for each of the perspectives. The main benefits of doing
130
so would be further triangulation of the quantitative findings and further embedding of each
of the perspectives within the context. However, it is possible that focus on a particular
strand of qualitative evidence (such as the effect of an environmental non-government
organization on a few villages) would produce bias towards a certain perspective where the
quantitative analysis was less likely to have done so.
One alternative to a qualitative description would be to incorporate contextual factors such
as the presence of environmental non-government organizations, or alternate sources of
income such as coral reef tourism that may have accounted for additional variance in the
quantitative model (Figure 1.5). The diagnostic framework for analyzing social-ecological
systems developed by Elinor Ostrom (2007) provides a comprehensive example of the
numerous indicators that may contribute to different types of social-ecological outcomes.
However, as noted by Ostrom, simultaneously examining all potential variables would
require an enormous sample size. Compared to other social-ecological studies with
comparably detailed ecological data (Cinner et al. 2009b), this thesis used a moderately
large sample size (for Chapter 2), but adding more explanatory variables would have
overfitted the models. Further, the model I developed (Figure 1.5) did explain much of the
variance in fishing pressure, institution occurrence, and ecological distributions (i.e. it had
reasonable power of prediction), and represents the study system distilled to an arguably
minimum adequate model. Therefore, despite omitting some potentially important
contextually relevant variables, the model was successful in addressing my research aims.
5.3.2 A MISSING LINK IN THE MODEL
The general model used in this thesis (Figure 1.5) to test the effects of proxy variables for
each of the perspectives, on exploitation and management institutions, to explain natural
resource distributions, was missing one key link. The missing link was the effect of
resource management institutions on the relationship between resource exploitation and in
situ resources (red arrow in Figure 5.3). Inclusion of this link would have shown, directly,
whether institutions were actually constraining exploitation. The reason why I was unable
131
to include this link in my study of Solomon Islands is because I integrated two datasets that
were collected for different objectives, which meant there was little geographic overlap
between the surveys. Specifically, data on management institutions (from the village
resource survey) were sparse across the sites where ecological data were collected, and
consequently there were not enough sites to test the complete model. Consequently, the
model was split into two components, focusing on exploitation and management
institutions separately (see Figure 1.5). While I would expect that institutions would have
some dampening effect on the effect of fishing pressure on the fishery (Agrawal & Yadama
1997; McClanahan et al. 2011a), thus a positive effect on fish stocks (natural resource in
Figure 5.3), it is not possible to definitively draw such a conclusion with the data used in
this thesis. To address this limitation it would be necessary to identify the occurrence, and
efficacy, of the relevant coral reef resource management institutions across the 25 sites used
in chapter 2. This was not possible due to a range of reasons including difficulties in
obtaining field permits for all sites, and the extremely remote locations of some sites.
Figure 5.3 Generalised model used in this thesis. Black arrows denoting links that were tested and showed
significant correlation, and the red arrow denoting a link that was not tested. +/- = direction of significant
effect. ? = unknown strength and direction of effect.
132
5.3.3 A MODELED SYSTEM OF FLOWS AND FEEDBACKS
Analyses within this thesis have assumed that social manifestations cause change to
ecological manifestations. This assumption is concordant with the human exceptionalism
paradigm (HEP); that social change is independent of the environment the society exists in.
That is, cause and effect is unidirectional from society to ecology. However, the New
Ecological Paradigm (Catton Jr & Dunlap 1978), which is now widely accepted in
environmental sociology, challenged the HEP by arguing that the interactions between
society and ecology are bi-directional. Indeed, there is a growing body of social-ecological
systems literature that explicitly acknowledges, and models, bi-directional effects (flows
and feedbacks) (e.g. Cinner 2011; Nyström et al. 2012). For example declining fish catch,
due to overfishing, might cause increased fishing pressure, or force fishers to exit the
fishery (Cinner et al. 2011).
Feedbacks can be explored using time series data (Granger 1969). Crucial feedbacks in the
system would include effects of changing resource state on distal and proximate drivers
(Figure 5.4). Time series data would also be beneficial in identifying lag effects, which aid
in inference of causality (Granger 1969). For example, as shown in figure 5.5, there is a lag
effect between the hypothesised sequential effects of increased population density on
fishing pressure, increased fishing pressure on declining resource state, and declining
resource state on institutional efficacy. Time series data would be particularly useful for
management because it would enable the identification of system dynamics including
effects of interventions such as government policy, changing economic structure, or the
influence of external agency such as the Coral Triangle Initiative.
133
Figure 5.4 Proposed generalised model of the dominant sociological perspectives of society’s effects on
natural resources at the local-level embedded within a social-ecological framework. Links tested in this thesis
denoted as black arrows. Link identified as missing from the unidirectional model (Figure 5.1) denoted as red
solid arrows. Links to be tested for social-ecological feedbacks denoted as red dashed arrows.
Figure 5.5 Heuristic model showing hypothetical lag effects between model variables, driven by increasing
population density.
To develop a time series for the general model including feedbacks (Figure 5.4) would
require a long-term data collection program. The program would require frequent
measurement of variables to ensure that cause and effects were observed, dependent on the
rate of social-ecological change occurring within the system and how tightly coupled
various variables are. For example, increase in population density might have a very
immediate effect on increase in fishing pressure, improvements in institutional efficacy
134
might occur when resources are still abundant, or when severely depleted, and ecological
systems can be prone to rapid shift to alternate states (Hughes 1994; Lester & Fairweather
2011).
5.3.4 LINKAGES AMONG AND BETWEEN LEVELS IN THE SOCIAL-POLITICAL SCALE
This thesis focused on the local-level (chapters 2 and 3) (supported by the individual-level
analysis) to draw its conclusions, for sound reasons. First, coral reef social-ecological
systems are relatively tightly coupled at the local-level (Almany et al. 2013). For example,
in Solomon Islands natural resources are largely exploited and managed by local
communities of people (Hviding & Baines 1994; Hviding 1998; Foale & MacIntyre 2000;
Govan 2009) (exceptions being examples such as large logging companies that are socially
exogenous to the local social-ecological system). Further, more detailed data, particularly
ecological, is available at the local-level compared to, for example the nation-level (e.g.
York et al. 2003a; Hoffmann 2004; Bradshaw et al. 2010), allowing the observation of
social effects on key aspects of ecology such as species diversity and functional group
biomass.
However, as ‘no man is an island’ neither is any local-level community or individual fisher
or middleman, isolated from other social-political levels (Wallerstein 1976), particularly in
our increasingly interconnected world (Cash et al. 2006; Young et al. 2006). According to
theory of human geography, there are levels of organisation on the social-political scale that
takes the form of a vertical hierarchy (Warren 2005), with lower levels nested in those
above (see Agnew 1995; Marston 2000 for early work on socio-political levels, and critique
of scale in human geography; Marston et al. 2005). Levels include, but are not necessarily
limited to, the; individual, family/household, community/village/town, province, nation,
and global. Each of the levels within the hierarchical scale is affected by all other levels,
indirectly or directly (red bi-directional arrows with associated numbers in Figure 5.6).
135
In the context of small-scale reef fisheries in Solomon Islands, the resource ownership
group, which operates at the local-level and was the focus of chapters 2 and 3 of this thesis,
is the primary social-political level of coral reef resource exploitation and management.
However, the within the local-level there exists families/households, and within
families/households there are individuals (chapter 4 of this study). Individuals within
communities are likely to affect exploitation and management by, for example, showing
strong leadership qualities (Ostrom 2007). Differences among households might also affect
local-level exploitation and management of resources. For example, cultural heterogeneity
among households is not conducive to collective action at the local-level (Aswani 2002;
Thompson et al. 2003). Local-level communities also interact with one another, primarily
through trade and migration, including resource dispersal (Figure 5.6, number 1). Further,
local-level communities are nested within provinces in Solomon Islands15. Factors
operating at the provincial-level will affect local exploitation and management patterns
(Figure 5.6, number 2). For example bylaws, which were a commonly elicited
management response in chapter 4, operate at the provincial level, and offer support for
local-level resource management. The national social-political level also affects local-level
resource exploitation and management, either directly (Figure 5.6, number 3), or indirectly
through provincial governance (Figure 5.6, number 7). Direct effects include bans on the
exploitation of particular species (e.g. bȇche-de-mer) and the use of particular fishing gears
(e.g. dynamite). Indirect effects include the national-level support of provincial fisheries
officers who are responsible for fisheries law enforcement, and in aiding marketing of
fisheries products. The global-level also affects, directly and indirectly, the exploitation
and management of local-level coral reef resources. For example, from time to time
particular species are exploited locally to supply markets in Asia through the live reef food
fish trade (Warren-Rhodes et al. 2003), which represents a direct link between global and
local social-political levels (Figure 5.6, number 4).
15
The social-political scale used here is the scale implemented during British colonisation. It is used for
simplicity and so that it is comparable with other contexts. I am not using it because I think it should be the
dominant scale, or necessarily the scale most suited to natural resource management. The other socialpolitical scale - the traditional system of social-political power, still maintains influence in enforcement of
traditional laws, is essential to local custom and cultural survival, and plays a significant role in the
management of coral reef resources in Solomon Islands. In fact, both social-political systems play integral
roles in both the exploitation and management of natural resources.
136
Accounting for these multi-level effects on local-level exploitation and management of
coral reef resources will improve the predictive capacity of social-ecological systems
models. Further, it might enhance coral reef resource management approaches by
improving our understanding of the interactions among levels and the possible positive and
negative effects of factors operating at multiple levels, on local-level resources.
The set of limitations described above represents a suite of extensions on the model
developed in this thesis. I have shown, where addressing the limitation would contribute to
broader system linkages and feedbacks. The above model (Figure 5.6) represents the next
step, in my opinion, in modeling linked social-ecological systems, at the local-level in
economically peripheral contexts16.
16
Over a significant career Elinor Ostrom developed a well-recognised framework for testing the
sustainability of local-level social-ecological systems (discussed in section 5.2.1). The purpose of the model
presented in this thesis (Figure 5.4) is not to suggest the framework of Ostrom (Ostrom 2007) is in any way
inadequate or obsolete. Rather, the model in this thesis does not have global application to social-ecological
systems because of the specific peripheral nation context. Further, the model in this thesis is based on
environmental sociology theory, whilst the framework of Ostrom is based on a rich career in studying
common-property.
137
Figure 5.6 Nested social-political levels that interact to effect the local-level exploitation and management
(institutions) of coral reef resources in Solomon Islands. In interpreting this figure consider that there are
multiple local social-ecological systems within the provincial-level social-political system, multiple
provincial-level social-political systems within the national-level social-political system, and multiple
national-level social-political systems (countries) within the global-level social-political system. Black arrows
show tested and significant effects. Red arrows show untested effects. Note that the individual and
family/household level is not depicted in this figure because their effects on local-level social-ecological
systems used in this thesis, is not clear.
138
5.4 GENERAL CONCLUSIONS
The broad aim of this thesis was to explain the state of coral reef resources using dominant
environmental sociology perspectives of human-environment interaction; Malthusian
overpopulation, market expansion, and modernization. To do so I used a novel
comparative model at the-local level in a geo-politically peripheral nation (chapters 2 and
3). I have also identified the dominant discourses of locals within the context of the thesis,
of the social factors that affect natural resource conditions (chapter 4), thus triangulating the
comparative modeling (chapters 2 and 3). In doing so, this thesis has contributed to theory
of human-environment interactions and has consequently broadened our understanding of
the social processes that explain variability in the state of natural resources. Key
conclusions are that no one perspective best fits the scale and context used for this thesis,
which is a finding that resonates with nation-level analyses. Further, whilst the Malthusian
overpopulation and market expansion perspectives best explained exploitation effects on
the fishery, there is also evidence of a possible management response to population growth
and markets. Therefore, there is some evidence of modernization-like characteristics;
however, these characteristics have not translated into real improvements in resource
conditions in more modernized communities.
These findings are directly relevant to policy for natural resource management. Broadly,
focus should be on shifting from a Malthusian overpopulation and market expansion
fishery to a modernization fishery. To instigate this shift will require two areas of focused
effort. First, fishing overcapacity should be addressed. To do so, the model suggests a need
to dampen the current drivers of overexploitation, including population pressure and market
access. Obvious, but not necessary feasible (due to limited capacity) solutions include
limiting entry into the fishery and managing fishing gears (McClanahan et al. 2008) to
constrain Malthusian overpopulation effects, and market restrictions including species and
size restrictions (Brewer 2011) to constrain market expansion effects. Importantly, the
national government should avoid subsidising the fishery through provision of boats and
fishing gears, forcing the industry to find a point of economic viability and avoid subsidy139
driven over-exploitation. The second area of focus should be supporting the conditions that
are likely to result in a modernized fishery. That is, the focus should be on factors that are
theorized to cause the change in trajectory in the environmental Kuznets curve. These
factors include improved management, a decrease in direct exploitation pressure, and
limiting the use of destructive gears (Cinner et al. 2009b) through stronger, integrated
institutions.
A critical challenge pervasive across many countries is balancing economic development
and environmental concerns. Constraining resource exploitation (including market-based
artisanal fishing) will also constrain development because exploiting and selling natural
resources, including fisheries, contribute to economic growth. For example, Jaunky (2011)
found that fisheries export contributes significantly to sustained economic growth in Small
Island Developing States. Yet, rather than maximising economic rent as rapidly as
possible, it is essential to take a longer, and more strategic, view on development, with the
aim to achieve a higher level of affluence and wellbeing whilst avoiding significant, if not
irreparable, damage to the environment.
Part of the longer view strategy lies in developing management institutions that enable
strategic, evidence based decisions to be made relating to the intensity and extent of
resource exploitation, and some control over how the derived capital should be invested to
enable more efficient development. That is, Solomon Islands needs systems that provide
the greatest development return for the given level of environmental degradation. A part
of this return-on-investment approach includes implementing numerous strategies such as
banning destructive exploitation approaches and developing networks of protected areas
that would, collectively, increase returns-on-investment. However to achieve resilient
improvements in resource stewardship at the local-level, there must also be changes at the
national-level. Such changes include increased social stability, absence of corruption, fair
and sustainable international trade in natural resources, and some collective vision of
desired development; all of which are limited in Solomon Islands. Solomon Islands is a
140
young nation with an under-resourced national government forced with the daunting task of
caring for a very diverse set of ancient customs and contemporary vested interests.
Navigating sustainable development in a way that suits Solomon Islands traditions and
current context, and the evolving collective vision of desired development will require
significant trial-and error and tenacity. However, other nations in the region, with a loosely
similar context have been experimenting with different management strategies for some
time, and therefore present Solmon Islands with a wealth of knowledge that might limit
failures and strengthen successes. For example, Philippines which is relatively more
modernized and has more depleted coral reef resources, but where institutions are evolving
to counter continued degradation (i.e. Philippines is likely at the inflection point of the
environmental Kuznets curve). Coastal communities in Philippines have, for over three
decades, been experimenting with different approaches to coastal artisanal fisheries
management in response to awareness of resource degradation (White et al. 2006). Indeed,
since the late 1970s there has been a rapid proliferation of community-based marine
protected areas across the Philippines (Weeks et al. 2010). Contributing to the success of
the growth and evolution of the institutions are a set of key factors. First, awareness of
resource decline, through fishing pressure, was apparent in the 1970s (Green et al. 2003).
Second is evidence of increased resource stocks following implementation of management
restrictions (Lowrie et al. 2009). Third, community involvement and ownership of
management responsibility has been heavily prioritized (White et al. 2006; Alcala & Russ
2006). Fourth, government support for community-based management has been in place
since 1998 (White et al. 2006). Finally, across-scale integration of management planning
and implementation has been made possible through positive collaboration between
government, non-government organizations and local communities (Courtney & White
2000; Christie et al. 2002; White et al. 2006; Lowrie et al. 2009).
141
Solomon Islands is actively learning lessons from Philippines, and other similar nations,
through programs such as the Coral Triangle Initiative, and it is hoped that management
measures can be fast-tracked through lessons learnt. Certainly, Solomon Islands Fisheries
Department, a number of non-government organizations and numerous other organisations
and individuals are already taking action in these areas, including, for example, the
application of social network analysis to identify strengths and weaknesses in collaboration
networks among stakeholders (Cohen et al. 2012). Yet, coral reef resources in Solomon
Islands are still in much better condition than Philippines, so it might take significant
further education and awareness before there is a proliferation of protected areas, and other
management measures, across Solomon Islands. Still, building networks of protected areas,
and other such measures does not address population and market pressures discussed in this
thesis, and so, does not represent a long term solution as long as there is continued resource
dependency, growing populations and access to markets. To address issues such as
population growth and market expansion will require truly integrated efforts including
government departments and non-government organizations involved in issues such as
family planning, economics, and alternative livelihoods.
Both social systems and ecological systems are complex. Predicting the timing, intensity,
direction, and type of change in either system is fraught with challenges. Understanding
interaction between the two systems adds further complexity. Certainly, the effect of basic
human behaviours on simple ecological systems (e.g. fishing on a single species fishery)
can be predicted with some certainty. However, when we acknowledge, and try to account
for the effect of broader social drivers such as modernization on behaviours such as
exploitation on diverse ecological systems, the challenge of predicting timing, intensity,
direction, and type of change becomes significantly harder. However, complex social
process and ecological responses are our reality, and therefore represent true challenges to
sustainability. In this thesis I have been able to show, with some certainty, society’s effects
on a complex ecological system. This has only been possible because of previous research
on the three perspectives that have been refined over time through debate in environmental
sociology and allied fields. Thus, it is this body of work that provided a strong theoretical
142
foundation for this thesis. Further advancements in our understanding of social-ecological
systems will probably come more readily if analysis is based on this rich theoretical
foundation. Research that fails to use this foundation (e.g. research that collects, and
analyses, a large suit of social and ecological data without a clear suite of a priori questions
or understanding of social-ecological processes, theoretically and in application) will likely
be peripheral to the debate on society’s effects on natural systems, and therefore have less
impact than desired.
Current trends of anthropogenically-driven natural resource decline are concerning for
anyone abreast of the literature. What the future holds remains unclear except that, in the
near to medium future, there will be further depletion of the natural resource base globally.
Shifting the narrative of our relationship with nature, from Malthusian overpopulation and
market expansion to modernization will require social-ecological systems to internalise
their environmental footprints, thus existing within the limits of their production potential
(Dasgupta & Ehrlich 2013). To achieve this will require significant enhancement in our
understanding of ecological systems, and of society’s effects on ecological systems, to
improve the accuracy of environmental accounting. Sophisticated institutions will be
required to administer and enforce the environmental accounting mechanisms. This is
likely at some point in the future simply because there is no alternative if humanity is to
prosper.
143
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Anthropogenic Sources of Global Climate Change with the STIRPAT Model.
International Journal of Sociology and Social Policy 23:21.
171
York, R., E. A. Rosa, and T. Dietz. 2003c. STIRPAT, IPAT and ImPACT: analytic tools
for unpacking the driving forces of environmental impacts. Ecological Economics
46:351-365.
Young, O. R., F. Berkhout, G. C. Gallopin, M. A. Janssen, E. Ostrom, and S. van der
Leeuw. 2006. The globalization of socio-ecological systems: An agenda for
scientific research. Global Environmental Change 16:304-316.
172
CHAPTER 6: APPENDICES
173
APPENDIX 1: RESEARCH CONDUCTED, AND SYMPOSIA/CONFERENCES ATTENDED
DURING DISSERTATION PERIOD NOT INCLUDED WITHIN THE THESIS
Peer-reviewed Publications:
Brewer, T.D., Cinner, J., Green, A., Pandolfi, J. 2009. Thresholds and multiple scale
interaction of environment, resource use, and market access on reef fishery resources in the
Solomon Islands. Biological Conservation 142: 1797-1807.
Skinner, M. P., Brewer, T.D., Johnstone, R., Fleming, L. E., Lewis, R.J. 2011. Ciguatera
fish poisoning in the Pacific Islands (1998 to 2008). PLoS Neglected Tropical Diseases 5:
e1416.
Bohensky, E., Smajgl, A., Brewer, T.D. 2012. Patterns in household engagement with
climate change in Indonesia. Nature Climate Change. DOI:10.1038/nclimate1762.
Albert, S., Love, M., Brewer, T.D. 2013. Historically driven spatial variability of the
shifting baseline syndrome on Melanesian coral reefs. Pacific Science. In Press
Pandolfi, J. M., Kaplan, D., Brewer, T.D., Schultz, J.K., Kittinger, J.N., Prescott, R.,
Lewis, N, Friedlander, A.M., Berzunza-Sanchez, M, Bird, C.E., Cinner, J.E., Toonen, R.J.,
Fa‘anunu, A.I., Pikitch, E.K., Wilcox, B.A.. The de-coupling of human and ecological
heath in Pacific Island nations. PNAS. In preparation
Wamukota, A., Brewer, T.D. Market access and income inequality among small-scale
Kenyan coral reef fishery: Implications for management. In preparation
Other Publications (reports, book chapters, other):
Brewer, T.D. 2011. Coral reef fish value chains in Solomon Islands: Market opportunities
and market effects on fish stocks. ARC Centre of Excellence for Coral Reef Studies report
to Solomon Islands Ministry of Fisheries and Marine Resources and Secretariat of the
Pacific Community. 46 pages.
174
Pratchett, M.S., Munday, P.L., Graham, N.A.J., Kronen, M., Pinica, S., Friedman, K.,
Brewer, T.D., Bell, J.D., Wilson, S.K., Cinner, J.E., Kinch, J.P., Lawton, R.J., Williams,
A.J., Chapman, L., Magron, F., Webb, A. (20011) Vulnerability of coastal fisheries in the
tropical Pacific to climate change Chapter 9 In: Bell, J.D., Johnson, J.E. and Hobday, A.J.
(eds) (2011) Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate
Change. Secretariat of the Pacific Community, Noumea, New Caledonia.
Brewer, T.D. 2010. Putting Census Data to work. Science. 329: 901-902.
Kool, J., Brewer, T.D., Mills, M., Pressey, R.L. 2010. Ridges to Reefs Conservation Plan
for the Solomon Islands. ARC Centre of Excellence for Coral Reef Studies. 50 pages.
Biggs, D., Brewer, T.D. 2010. Make your conservation PhD relevant – bridging the
research-implementation gap. Published online: conservationbytes.com.
Symposia / Conference Presentations / Workshops / Guest lectures
Brewer, T.D. et al. 2012. Globalization explains diversity and function of coral reef fish.
International Coral Reef Society, Cairns.
Brewer, T.D. et al. 2011. Social and economic drivers explain diversity and function of
coral reef fish. International Conference of Environmental Futures. Newcastle, United
Kingdom.
Brewer, T.D. et al. 2011. Social and economic drivers explain diversity and function of
coral reef fish. 22nd Pacific Science Congress. Kuala Lumpur.
Brewer, T.D. 2010. Guest lecture on causes of resource decline given at the school of
Natural Resources, Solomon Islands College of Higher Education.
Invited participant at the “Vulnerability and adaptation of coastal fisheries to climate
change” workshop. Noumea, New Caledonia. April, 2010.
175
Brewer, T.D., Cinner, J., Green, A., Pandolfi, J. 2009. Thresholds and multiple scale
interaction of environment, resource use, and distribution on reef fishery resources in the
Solomon Islands. Pacific Science Inter-Congress. Papeete., French Polynesia.
Advisory role at the “Coral Triangle Initiative workshop”, Townsville, Australia,
November, 2008.
Pandolfi, J. Schultz, J. Friedlander, A., Brewer, T.D. 2008. Decoupling the linkages
between human and coral reef ecosystem health in the Pacific. Ecohealth in Coupled
Human-Natural Systems. Anthropogenic Change, Biodiversity Loss and Disease
Emergence. (NSF IGERT ECPB). University of Hawaii.
176
APPENDIX 2: FISH SURVEY METHODS AND BIOMASS ESTIMATION
Fish survey methods and biomass estimation used for chapter 2 (adapted from Green et al.
2006).
Fish survey methods
Coral reef fish communities were surveyed using underwater visual census methods
including a) transects and b) timed swims. A restricted list of 37 families was used
comprising only those families that are amenable to visual census techniques, because they
are relatively large, diurnally active and conspicuous in coloration and behaviour. This
method excludes species that are not amenable to the technique because they are very
small, nocturnal or cryptic in behaviour (e.g. gobies, blennies, cardinalfish).
Transects
Fish were surveyed along five replicate transects on the reef slope at a depth of 10 metres at
each site. Fishes were surveyed by three passes along the transect counting different species
in each pass, using different transect dimensions for each group (based on their behaviour,
size and abundance):
1. Large, highly mobile species that are most likely to be disturbed by the passage
of a diver (such as parrotfishes, snappers and emperors) were surveyed on the
first pass using transect dimensions of 50m x 5m.
2. Medium sized mobile species (including most surgeonfishes, butterflyfishes and
wrasses) that are less disturbed by the presence of a diver, were counted on the
second pass using transect dimensions of 50m x 3m.
177
3. Small, site attached species (mostly damselfishes) that are least disturbed by the
presence of a diver, were counted on the third pass using transect dimensions of
30m x 1m.
During each pass of the transect, the number of individuals of each species was counted
and recorded. The size of each individual (length in cm) was also estimated and recorded.
Fish identifications were based on Allen (2003). Transect lengths were measured using
50m tapes, and transect widths were estimated using known body proportions. Transect
tapes were laid during the first pass by an assistant following the observer (to minimize
disturbance to the fish communities being counted). The tapes then remained in situ until
all the surveys were completed at that site. Fish counts (i.e. each pass of the transect) were
separated by a waiting period of ~5 minutes between counts.
Timed swims
Key fisheries species of food fish that are large and particularly vulnerable to overfishing
were counted (and their size estimated) using long swim methods specifically developed
for this purpose (Choat and Spears 2003). Species included in this study that were sampled
using timed swims included:
4. Maori wrasse (Cheilinus undulatus);
5. Humphead parrotfish (Bolbometopon muricatum) and steephead parrotfish
(Chlorurus microrhinos);
6. Large groupers (Cromileptes altivelis and Variola louti);
7. Large and uncommon emperors (Lethrinus olivaceus, Lethrinus erythropterus,
Lethrinus rubrioperculatus and Lethrinus xanthochilus).
This method was developed to improve estimates of the abundance of these species, since
they tend to be uncommon and clumped in distribution, so smaller transects dimensions
(e.g. 50m x 5m) are not suitable for obtaining reasonable estimates of their abundance. In
this method, the observer surveys a wide area during a single pass of the reef slope over a
set time period (15 mins) scanning the reef slope for these species. This method was
repeated at each site.
178
Biomass Calculation
Fish biomass was calculated by converting estimated fish lengths to weights using the
allometric length-weight conversion formulae [weight (kg) = (total length in cm x constant
a)b] where a and b are constants for each species. Constants were not available for most
species in the Solomon Islands, so they were obtained from New Caledonia (Kulbicki,
unpublished data), which was the closest geographic area where this information was
available. Where constants were not available for a species, the constants for a similar
species (usually a congeneric species) were used.
References
Allen, G.R., R. Steene, P. Humann, and N. Deloach. 2003. Reef Fish Identification.
Tropical Pacific. New World Publications, 470 pp.
Green, A., P. Lokani, W. Atu, P. Ramohia, P. Thomas, and J. Almany. 2006. Solomon
Islands Marine Assessment: Technical report of survey conducted May 13 to June
17, 2004. Page 530, TNC Pacific Island Countries Report No. 1/06.
Choat, H., and R. Pears. 2003. A rapid, quantitative survey method for large, vulnerable
reef fishes. In: Wilkinson, C., Green, A., Almany, J., and Dionne, S. Monitoring
Coral Reef Marine Protected Areas. A Practical Guide on How Monitoring Can
support Effective Management MPAs. Australian Institute of Marine Science and
the IUCN Marine Program Publication. 68pp.
179
APPENDIX 3: LIST OF FISH INCLUDING VULNERABILITY CATEGORY AND SCORE
USED FOR CHAPTER 2A
Fish species of low vulnerability
Family
Species
Vulnerability
Biomass (kg/ha./site)
Acanthuridae
Acanthuridae
Acanthurus lineatus
Ctenochaetus cyanocheilus
23
22
5.0040
0.3979
Acanthuridae
Ctenochaetus striatus
17
61.0205
Acanthuridae
Chaetodontidae
Ctenochaetus tominiensis
Chaetodon auriga
22
12
0.0976
0.2934
Chaetodontidae
Chaetodon baronessa
14
3.1991
Chaetodontidae
Chaetodontidae
Chaetodon bennetti
Chaetodon citrinellus
15
10
0.2257
0.0308
Chaetodontidae
Chaetodon ephippium
23
2.0336
Chaetodontidae
Chaetodontidae
Chaetodon kleinii
Chaetodon lunula
12
15
0.2837
0.1197
Chaetodontidae
Chaetodon meyeri
15
0.2932
Chaetodontidae
Chaetodontidae
Chaetodon ocellicaudus
Chaetodon ornatissimus
12
15
0.0295
2.5697
Chaetodontidae
Chaetodon oxycephalus
20
0.5551
Chaetodontidae
Chaetodontidae
Chaetodon pelewensis
Chaetodon rafflesi
10
14
0.0918
1.2611
Chaetodontidae
Chaetodon reticulatus
14
0.0971
Chaetodontidae
Chaetodontidae
Chaetodon semeion
Chaetodon speculum
20
14
0.6706
0.1777
Chaetodontidae
Chaetodon trifasciatus
10
2.0621
Chaetodontidae
Chaetodontidae
Chaetodon ulietensis
Chaetodon unimaculatus
12
15
0.5169
0.1769
Chaetodontidae
Chaetodon vagabundus
17
2.8173
Chaetodontidae
Chaetodontidae
Coradion chrysozonus
Forcipiger flavissimus
12
17
0.0666
0.5530
Chaetodontidae
Heniochus chrysostomus
14
2.9402
Chaetodontidae
Chaetodontidae
Heniochus monoceros
Heniochus singularius
18
23
1.0319
2.7884
Chaetodontidae
Heniochus varius
14
7.0017
Cirrhitidae
Cirrhitichthys falco
10
0.0097
180
Cirrhitidae
Paracirrhites arcatus
10
0.0817
Cirrhitidae
Paracirrhites forsteri
11
0.0843
Labridae
Labridae
Diproctacanthus xanthurus
Halichoeres biocellatus
20
23
0.0027
0.1501
Labridae
Halichoeres chrysus
23
0.0206
Labridae
Labridae
Halichoeres hortulanus
Halichoeres marginatus
21
20
2.6858
0.0345
Labridae
Halichoeres melanurus
23
0.0834
Labridae
Labridae
Halichoeres scapularis
Labroides pectoralis
23
21
0.0206
0.0431
Labridae
Labropsis alleni
20
0.0060
Labridae
Labridae
Labropsis australis
Macropharyngodon negrosensis
20
23
0.0170
0.0084
Labridae
Pseudocheilinus evanidus
15
0.0218
Labridae
Labridae
Pseudocheilinus hexataenia
Stethojulis trilineata
20
13
0.0251
0.0877
Labridae
Thalassoma hardwicke
14
0.2007
Lutjanidae
Lutjanidae
Lutjanus fulvus
Lutjanus semicinctus
23
19
0.2616
0.5875
Monocanthidae
Oxymonacanthus longirostris
23
0.0222
Mullidae
Nemipteridae
Mulloides vanicolensis
Scolopsis affinis
23
23
0.9772
0.0461
Nemipteridae
Scolopsis bilineatus
22
1.3443
Ostraciidae
Ostraciidae
Ostracion cubicus
Ostracion meleagris
23
13
0.1362
0.1590
Pinguipedidae
Parapercis millipunctata
21
0.1292
Pomacanthidae
Pomacanthidae
Centropyge bicolor
Centropyge bispinosus
23
15
1.1761
0.0105
Pomacanthidae
Centropyge vroliki
19
0.2576
Pomacentridae
Pomacentridae
Abudefduf vaigiensis
Amblyglyphidodon curacao
16
23
0.1715
1.0077
Pomacentridae
Amphiprion chrysopterus
16
0.7299
Pomacentridae
Pomacentridae
Amphiprion leucokranos
Chromis acares
19
11
0.0387
0.0203
Pomacentridae
Chromis alpha
22
0.0286
Pomacentridae
Pomacentridae
Chromis amboinensis
Chromis atripes
19
19
3.1789
2.5232
Pomacentridae
Chromis delta
14
0.1107
Pomacentridae
Pomacentridae
Chromis lepidolepis
Chromis lineata
19
14
0.3917
0.0901
Pomacentridae
Chromis margaritifer
19
2.3466
Pomacentridae
Pomacentridae
Chromis retrofasciata
Chromis spp.
11
18.85*
0.0770
0.1848
181
Pomacentridae
Chromis ternatensis
21
8.5608
Pomacentridae
Chrysiptera flavipinnis
16
0.0039
Pomacentridae
Pomacentridae
Chrysiptera parasema
Chrysiptera rex
14
14
0.0358
0.0108
Pomacentridae
Chrysiptera rollandi
15
0.0695
Pomacentridae
Pomacentridae
Chrysiptera talboti
Plectroglyphidodon dickii
12
23
0.6596
0.5536
Pomacentridae
Plectroglyphidodon lacrymatus
21
11.4002
Pomacentridae
Pomacentridae
Pomacentrus adelus
Pomacentrus amboinensis
17
19
0.6167
3.4391
Pomacentridae
Pomacentrus bankanensis
19
5.9765
Pomacentridae
Pomacentridae
Pomacentrus brachialis
Pomacentrus coelestis
21
19
5.9182
0.9157
Pomacentridae
Pomacentrus grammorhynchus
23
0.2176
Pomacentridae
Pomacentridae
Pomacentrus lepidogenys
Pomacentrus nagasakiensis
23
21
3.0712
0.0001
Pomacentridae
Pomacentrus nigromanus
19
0.7355
Pomacentridae
Pomacentridae
Pomacentrus philippinus
Pomacentrus reidi
23
19
7.4159
3.3443
Pomacentridae
Pomacentrus vaiuli
23
1.0856
Scaridae
Scaridae
Chlorurus sordidus
Scarus chameleon
20
22
9.5128
0.3435
Scaridae
Scarus niger
23
14.3341
Scaridae
Serranidae
Scarus psittacus
Cephalopholis urodeta
22
14
0.8923
1.8228
Serranidae
Epinephelus merra
23
0.0444
Serranidae
Serranidae
Luzonichthys waitei
Pseudanthias dispar
11
14
0.0067
0.4483
Serranidae
Pseudanthias huchti
16
0.7194
Serranidae
Serranidae
Pseudanthias spp.
Pseudanthias tuka
15.33*
16
0.1495
2.6516
Siganidae
Siganus argenteus
22
0.1288
Siganidae
Siganidae
Siganus doliatus
Siganus fuscescens
23
21
0.6248
0.0876
Siganidae
Siganus vulpinus
23
1.2620
Tetradontidae
Zanclidae
Canthigaster papua
Zanclus cornutus
15
12
Total
0.2037
1.7779
207.0384
* Average vulnerabililty score within Genus used because fish not identified to species
182
Fish species of medium vulnerability
Family
Species
Vulnerability
Biomass (kg/ha./site)
Acanthuridae
Acanthuridae
Acanthurus nigricans
Acanthurus nigricauda
34
25
2.0568
1.7686
Acanthuridae
Acanthurus nigrofuscus
27
2.6951
Acanthuridae
Acanthuridae
Acanthurus nubilus
Acanthurus olivaceus
26
31
0.1128
1.3853
Acanthuridae
Acanthurus pyroferus
29
20.2638
Acanthuridae
Acanthuridae
Acanthurus spp.
Acanthurus thompsoni
31.83*
26
89.5172
0.1372
Acanthuridae
Ctenochaetus binotatus
24
8.0510
Acanthuridae
Acanthuridae
Naso brevirostris
Naso lituratus
33
34
8.8320
11.8811
Aulostomidae
Aulostomus chinensis
34
0.5457
Balistidae
Balistidae
Balistapus undulatus
Melichthys vidua
30
34
5.5174
1.3268
Balistidae
Pseudobalistes flavimarginatus
29
3.6983
Balistidae
Balistidae
Sufflamen bursa
Sufflamen chrysopterus
27
30
0.1135
0.2887
Balistidae
Xanthichthys auromarginatus
30
0.0299
Chaetodontidae
Labridae
Chaetodon trifascialis
Anampses meleagrides
24
31
0.3119
0.0411
Labridae
Anampses twistii
28
0.0718
Labridae
Labridae
Bodianus mesothorax
Cheilinus oxycephalus
33
27
0.9806
0.0673
Labridae
Cirrhilabrus punctatus
24
1.9820
Labridae
Labridae
Coris batuensis
Halichoeres spp.
27
23.75*
0.0602
0.0212
Labridae
Halichoeres prosopeion
28
0.4557
Labridae
Labridae
Halichoeres richmondi
Halichoeres spp.
29
23.75*
0.0254
0.0196
Labridae
Labrichthys unilineatus
27
0.2772
Labridae
Labridae
Labroides bicolor
Labroides dimidiatus
25
24
0.0963
0.1807
Labridae
Labropsis xanthonota
24
0.0107
Labridae
Labridae
Macropharyngodon meleagris
Novaculichthys taeniourus
30
35
0.3474
0.1478
Labridae
Oxycheilinus celebicus
32
0.0044
Labridae
Labridae
Pseudocoris yamashiroi
Pseudodax moluccanus
26
35
0.0493
0.3822
Labridae
Stethojulis bandanensis
25
0.0594
183
Labridae
Stethojulis strigiventer
25
0.0061
Labridae
Thalassoma amblycephalum
32
0.1217
Labridae
Labridae
Thalassoma lunare
Thalassoma quinquevittatum
35
27
0.4007
0.0239
Lethrinidae
Gnathodentex aurolineatus
29
15.5337
Lutjanidae
Lutjanidae
Lutjanus biguttatus
Lutjanus gibbus
24
32
0.3031
258.0318
Monacanthidae
Amanses scopas
30
0.0713
Monacanthidae
Mullidae
Cantherhines pardalis
Parupeneus bifasciatus
33
30
0.0149
5.0068
Mullidae
Parupeneus spp.
33*
8.0798
Mullidae
Mullidae
Parupeneus multifasciatus
Parupeneus pleurostigma
30
29
2.9440
0.0224
Nemipteridae
Scolopsis margaritifer
25
0.2562
Pomacanthidae
Pomacanthidae
Apolemichthys trimaculatus
Pomacanthus navarchus
31
32
0.1297
0.4162
Pomacentridae
Acanthochromis polyacanthus
25
9.4741
Pomacentridae
Pomacentridae
Amblyglyphidodon aureus
Amblyglyphidodon leucogaster
24
24
0.2860
10.8926
Pomacentridae
Amphiprion clarkii
32
1.1349
Pomacentridae
Pomacentridae
Chromis weberi
Chromis xanthochira
25
25
0.7488
0.2859
Pomacentridae
Chromis xanthura
26
6.3538
Pomacentridae
Pomacentridae
Dascyllus reticulatus
Dascyllus trimaculatus
25
26
0.9045
0.3593
Pomacentridae
Neoglyphidodon melas
29
0.4599
Pomacentridae
Pomacentridae
Neoglyphidodon nigroris
Pomacentrus moluccensis
24
25
16.2043
2.8391
Pomacentridae
Stegastes gascoynei
26
0.4542
Pomacentridae
Scaridae
Stegastes spp.
Calotomus carolinus
26*
35
0.0399
0.1971
Scaridae
Chlorurus bleekeri
33
7.3324
Scaridae
Scaridae
Chlorurus pyrrhurus
Hipposcarus longiceps
25
29
9.2043
132.3466
Scaridae
Scarus dimidiatus
29
2.4359
Scaridae
Scaridae
Scarus flavipectoralis
Scarus forsteni
29
35
0.3729
11.4253
Scaridae
Scarus frenatus
24
6.4976
Scaridae
Scaridae
Scarus oviceps
Scarus quoyi
27
29
1.4516
1.0246
Scaridae
Scarus spinus
25
0.7426
Serranidae
Serranidae
Cephalopholis leopardus
Diploprion bifasciatum
28
29
0.0447
0.1157
184
Serranidae
Epinephelus melanostigma
34
0.0387
Serranidae
Epinephelus spilotoceps
34
0.1451
Serranidae
Siganidae
Variola albimarginata
Siganus corallinus
29
30
0.2209
0.0613
Siganidae
Siganus lineatus
25
47.3128
Siganidae
Siganidae
Siganus puellus
Siganus punctatissimus
26
30
2.7992
0.3153
Tetraodontidae
Arothron nigropunctatus
31
Total
0.2507
729.95
* Average vulnerabililty score within Genus used because fish not identified to species
185
Fish species of high vulnerability
Family
Species
Vulnerability
Biomass (kg/ha./site)
Acanthuridae
Acanthuridae
Acanthurus blochii
Acanthurus fowleri
38
47
0.1633
0.5765
Acanthuridae
Acanthurus mata
39
15.3112
Acanthuridae
Acanthuridae
Acanthurus xanthopterus
Naso hexacanthus
37
41
2.6495
42.4215
Acanthuridae
Naso spp.
41.25*
11.8413
Acanthuridae
Acanthuridae
Naso unicornis
Zebrasoma scopas
57
66
14.5074
5.4352
Acanthuridae
Zebrasoma veliferum
37
0.8837
Balistidae
Balistidae
Balistoides conspicillum
Balistoides viridescens
38
53
0.7218
36.0977
Balistidae
Odonus niger
38
13.5517
Chaetodontidae
Chanidae
Chaetodon melannotus
Chanos chanos
47
76
0.0554
10.0704
Haemulidae
Plectorhinchus albovittatus
67
7.3199
Haemulidae
Haemulidae
Plectorhinchus chaetodonoides
Plectorhinchus chrysotaenia
54
49
2.5569
0.3832
Haemulidae
Plectorhinchus lineatus
37
24.1888
Haemulidae
Haemulidae
Plectorhinchus spp.
Plectorhinchus vittatus
53.6*
61
0.2245
17.0489
Holocentridae
Sargocentron spiniferum
41
0.5042
Labridae
Labridae
Anampses caeruleopunctatus
Anampses neoguinaicus
43
36
0.0563
0.0308
Labridae
Bodianus diana
40
0.1349
Labridae
Labridae
Cheilinus chlorourus
Cheilinus fasciatus
46
54
0.1233
4.8089
Labridae
Cheilinus undulatus
74
22.7236
Labridae
Labridae
Cheilio inermis
Coris gaimard
60
41
0.0043
0.5248
Labridae
Epibulus insidiator
61
1.0505
Labridae
Labridae
Gomphosus varius
Hemigymnus fasciatus
45
62
0.4504
0.3629
Labridae
Hemigymnus melapterus
64
0.7457
Labridae
Labridae
Hologymnosus annulatus
Hologymnosus spp.
41
41*
0.0087
0.0205
Labridae
Oxycheilinus diagrammus
54
0.8135
Lethirinidae
Lethrinidae
Monotaxis grandoculis
Lethrinus erythropterus
42
37
192.6851
0.7211
Lethrinidae
Lethrinus olivaceus
40
0.7672
186
Lethrinidae
Lethrinus rubrioperculatus
40
1.5256
Lethrinidae
Lethrinidae
Lutjanidae
Lethrinus spp.
43.5*
13.6711
Lethrinus xanthochilus
Aphareus furca
57
36
0.6482
0.6353
Lutjanidae
Aprion virescens
61
6.8274
Lutjanidae
Lutjanidae
Lutjanus argentimaculatus
Lutjanus bohar
60
69
0.2661
204.2151
Lutjanidae
Lutjanus monostigma
40
0.2762
Lutjanidae
Lutjanidae
Macolor macularis
Macolor niger
39
46
120.9320
78.8201
Lutjanidae
Macolor spp.
42.5*
24.3949
Lutjanidae
Monocanthidae
Symphorichthys spilurus
Aluterus scriptus
39
70
0.2488
1.2908
Monocanthidae
Cantherhines dumerilii
39
0.0657
Mullidae
Mullidae
Mulloides flavolineatus
Parupeneus barberinus
39
40
0.3218
2.4638
Mullidae
Parupeneus cyclostomus
36
1.1200
Pomacanthidae
Pomacanthidae
Pomacanthus imperator
Pomacanthus semicirculatus
50
50
2.1887
0.5212
Pomacanthidae
Pomacanthus sexstriatus
41
3.4934
Pomacanthidae
Pomacanthidae
Pomacanthus xanthometopon
Pygoplites diacanthus
36
38
0.5212
3.0100
Scaridae
Bolbometopon muricatum
67
233.3674
Scaridae
Scaridae
Cetoscarus bicolor
Chlorurus microrhinos
58
41
3.0512
21.1597
Scaridae
Scarus ghobban
37
0.8547
Scaridae
Scaridae
Scarus prasiognathos
Scarus rivulatus
39
39
4.6046
1.0140
Scaridae
Scarus rubroviolaceus
52
5.4201
Scaridae
Serranidae
Scarus schlegeli
Aethaloperca rogaa
38
49
1.1600
0.3538
Serranidae
Anyperodon leucogrammicus
52
0.2756
Serranidae
Serranidae
Cephalopholis argus
Cephalopholis cyanostigma
49
36
0.6027
0.3995
Serranidae
Cephalopholis miniata
61
0.0676
Serranidae
Serranidae
Cephalopholis spp.
Cromileptes altivelis
43.5*
54
0.0138
0.0309
Serranidae
Epinephelus corallicola
41
0.1190
Serranidae
Serranidae
Epinephelus fasciatus
Epinephelus spp.
46
35.6*
0.0716
0.1943
Serranidae
Plectropomus areolatus
56
3.7583
Serranidae
Serranidae
Plectropomus laevis
Plectropomus leopardus
72
51
1.2491
1.2954
187
Serranidae
Plectropomus oligacanthus
56
0.3693
Serranidae
Serranidae
Plectropomus spp.
58.75*
0.5982
Variola louti
49
Total
9.2550
1189.29
* Average vulnerabililty score within Genus used because fish not identified to species
188
APPENDIX 4: LIST OF FISH INCLUDING FUNCTIONAL GROUPING, AND WHETHER
THEY ARE FISHERIES SPECIES, USED IN CHAPTER 2B
Family
Species
Piscivore
Herbivore
Fisheries Species
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Acanthuridae
Balistidae
Balistidae
Balistidae
Balistidae
Balistidae
Balistidae
Balistidae
Balistidae
Balistidae
Chaetodontidae
Chaetodontidae
Acanthurus blochii
Acanthurus fowleri
Acanthurus lineatus
Acanthurus mata
Acanthurus nigricans
Acanthurus nigricauda
Acanthurus nigrofuscus
Acanthurus nubilis
Acanthurus olivaceus
Acanthurus pyroferus
Acanthurus spp.
Acanthurus thompsoni
Acanthurus xanthopterus
Ctenochaetus binotatus
Ctenochaetus cyanocheilus
Ctenochaetus striatus
Ctenochaetus tominiensis
Naso brevirostris
Naso hexacanthus
Naso lituratus
Naso spp.
Naso unicornis
Zebrasoma scopas
Zebrasoma veliferum
Aulostomus chinensis
Balistapus undulatus
Balistoides conspicillum
Balistoides viridescens
Melichthys vidua
Odonus niger
Pseudobalistes flavimarginatus
Sufflamen bursa
Sufflamen chrysopterus
Xanthichthys auromarginatus
Chaetodon auriga
Chaetodon baronessa
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
1
1
1
0
1
1
1
0
1
0
0
0
0
0
0
1
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
1
0
0
0
0
1
0
1
1
1
1
1
1
1
1
1
1
0
0
0
1
0
1
0
0
1
0
0
0
0
0
2
189
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Chaetodontidae
Cirrhitidae
Cirrhitidae
Cirrhitidae
Haemulidae
Haemulidae
Haemulidae
Haemulidae
Haemulidae
Haemulidae
Holocentridae
Kyphosidae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Chaetodon bennetti
Chaetodon citrinellus
Chaetodon ephippium
Chaetodon kleinii
Chaetodon lunula
Chaetodon melannotus
Chaetodon meyeri
Chaetodon ocellicaudus
Chaetodon ornatissimus
Chaetodon oxycephalus
Chaetodon pelewensis
Chaetodon rafflesi
Chaetodon reticulatus
Chaetodon semeion
Chaetodon speculum
Chaetodon trifascialis
Chaetodon trifasciatus
Chaetodon ulietensis
Chaetodon unimaculatus
Chaetodon vagabundus
Coradion chrysozonus
Forcipiger flavissimus
Heniochus chrysostomus
Heniochus monoceros
Heniochus singularius
Heniochus varius
Cirrhitichthys falco
Paracirrhites arcatus
Paracirrhites forsteri
Plectorhinchus albovittatus
Plectorhinchus chaetodonoides
Plectorhinchus chrysotaenia
Plectorhinchus lineatus
Plectorhinchus spp.
Plectorhinchus vittatus
Sargocentron spiniferum
Kyphosus spp.
Anampses caeruleopunctatus
Anampses meleagrides
Anampses neoguinaicus
Anampses twistii
Bodianus diana
Bodianus mesothorax
Cheilinus chlorourus
Cheilinus fasciatus
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
1
0
1
1
1
0
0
0
0
0
0
0
1
190
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Labridae
Cheilinus oxycephalus
Cheilinus undulatus
Cheilio inermis
Cirrhilabrus punctatus
Coris batuensis
Coris gaimard
Diproctacanthus xanthurus
Epibulus insidiator
Gomphosus varius
Halichoeres biocellatus
Halichoeres chrysus
Halichoeres hortulanus
Halichoeres marginatus
Halichoeres melanurus
Halichoeres
nebulosus/margaritaceus/miniatus
Halichoeres prosopeion
Halichoeres richmondi
Halichoeres scapularis
Halichoeres spp.
Hemigymnus fasciatus
Hemigymnus melapterus
Hologymnosus annulatus
Hologymnosus sp
Labrichthys unilineatus
Labroides bicolor
Labroides dimidiatus
Labroides pectoralis
Labropsis alleni
Labropsis australis
Labropsis xanthonota
Macropharyngodon meleagris
Macropharyngodon negrosensis
Novaculichthys taeniourus
Oxycheilinus celebicus
Oxycheilinus diagrammus
Pseudocheilinus evanidus
Pseudocheilinus hexataenia
Pseudocoris yamashiroi
Pseudodax moluccanus
Stethojulis bandanensis
Stethojulis strigiventer
Stethojulis trilineata
Thalassoma amblycephalum
Thalassoma hardwicke
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
191
Labridae
Labridae
Lethrinidae
Lethrinidae
Lethrinidae
Lethrinidae
Lethrinidae
Lethrinidae
Lethrinidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Lutjanidae
Malacanthidae
Malacanthidae
Malacanthidae
Malacanthidae
Malacanthidae
Mullidae
Mullidae
Mullidae
Mullidae
Mullidae
Mullidae
Mullidae
Mullidae
Nemipteridae
Nemipteridae
Nemipteridae
Ostracidae
Ostracidae
Pinguipedidae
Pomacanthidae
Pomacanthidae
Pomacanthidae
Pomacanthidae
Thalassoma lunare
Thalassoma quinquevittatum
Gnathodentex aurolineatus
Lethrinus erythropterus
Lethrinus olivaceous
Lethrinus rubriopeculatus
Lethrinus spp.
Lethrinus xanthochilus
Monotaxis grandoculis
Aphareus furca
Aprion virescens
Lutjanus argentmaculatus
Lutjanus biguttatus
Lutjanus bohar
Lutjanus fulvus
Lutjanus gibbus
Lutjanus monostigma
Lutjanus semicinctus
Macolor macularis
Macolor niger
Macolor spp.
Symphorichthys spilurus
Aluterus scriptus
Amanses scopas
Cantherhines dumerilii
Cantherhines pardalis
Oxymonacanthus longirostris
Mulloides flavolineatus
Mulloides vanicolensis
Parupeneus barberinus
Parupeneus bifasciatus
Parupeneus bifasciatus/trifasciatus
Parupeneus cyclostomus
Parupeneus multifasciatus
Parupeneus pleurostigma
Scolopsis affinis
Scolopsis bilineatus
Scolopsis margaritifer
Ostracion cubicus
Ostracion meleagris
Parapercis miillipunctata
Apolemichthys trimaculatus
Centropyge bicolor
Centropyge bispinosus
Centropyge vroliki
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
1
1
1
1
1
1
0
1
1
0
1
0
1
1
0
1
1
1
1
0
0
0
0
0
0
1
1
1
1
1
0
0
0
0
0
1
0
0
0
0
0
0
192
Pomacanthidae
Pomacanthidae
Pomacanthidae
Pomacanthidae
Pomacanthidae
Pomacanthidae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacanthus imperator
Pomacanthus navarchus
Pomacanthus semicirculatus
Pomacanthus sexstriatus
Pomacanthus xanthometopon
Pygoplites diacanthus
Abudefduf vaigiensis
Acanthochromis polyacanthus
Amblyglyphidodon aureus
Amblyglyphidodon curacao
Amblyglyphidodon leucogaster
Amphiprion chrysopterus
Amphiprion clarkii
Amphiprion leucokranos
Chromis acares
Chromis alpha
Chromis amboinensis
Chromis atripes
Chromis delta
Chromis lepidolepis
Chromis lineata
Chromis margaritifer
Chromis retrofasciata
Chromis spp.
Chromis ternatensis
Chromis weberi
Chromis xanthochira
Chromis xanthura
Chrysiptera flavipinnis
Chrysiptera parasema
Chrysiptera rex
Chrysiptera rollandi
Chrysiptera talboti
Dascyllus reticulatus
Dascyllus trimaculatus
Neoglyphidodon melas
Neoglyphidodon nigroris
Plectroglyphidodon dickii
Plectroglyphidodon lacrymatus
Pomacentrus adelus
Pomacentrus amboinensis
Pomacentrus bankanensis
Pomacentrus brachialis
Pomacentrus coelestis
Pomacentrus grammorhynchus
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
193
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Pomacentridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Scaridae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Pomacentrus lepidogenys
Pomacentrus moluccensis
Pomacentrus nagasakiensis
Pomacentrus nigromanus
Pomacentrus philippinus
Pomacentrus reidi
Pomacentrus vaiuli
Stegastes gascoynei
Stegastes spp.
Bolbometopon muricatum
Calotomus carolinus
Cetoscarus bicolor
Chlorurus bleekeri
Chlorurus microrhinos
Chlorurus pyrrhurus
Chlorurus sordidus
Hipposcarus longiceps
Scarus chameleon
Scarus dimidiatus
Scarus flavipectoralis
Scarus forsteni
Scarus frenatus
Scarus ghobban
Scarus niger
Scarus oviceps
Scarus prasiognathos
Scarus psittacus
Scarus quoyi
Scarus rivulatus
Scarus rubroviolaceus
Scarus schlegeli
Scarus spinus
Scarus spp.
Anyperodon leucogrammicus
Cephalopholis argus
Cephalopholis cyanostigma
Cephalopholis leopardus
Cephalopholis miniata
Cephalopholis spp.
Cephalopholis urodeta
Cromileptes altivelis
Diploprion bifasciatum
Epinephelus corallicola
Epinephelus fasciatus
Epinephelus melanostigma
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
1
0
0
1
0
0
0
0
194
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Serranidae
Siganidae
Siganidae
Siganidae
Siganidae
Siganidae
Siganidae
Siganidae
Siganidae
Synodontidae
Tetraodontidae
Tetraodontidae
Tetraodontidae
Epinephelus merra
Epinephelus spilotoceps
Epinephelus spp.
Luzonichthys waitei
Plectropomus areolatus
Plectropomus laevis
Plectropomus leopardus
Plectropomus oligacanthus
Plectropomus spp.
Pseudanthias dispar
Pseudanthias huchti
Pseudanthias spp.
Pseudanthias tuka
Variola albimarginata
Variola louti
Siganus argenteus
Siganus corallinus
Siganus doliatus
Siganus fuscescens
Siganus lineatus
Siganus puellus
Siganus punctatissimus
Siganus vulpinus
Synodus spp.
Arothron nigropunctatus
Canthigaster papua
Diodon sp
1
1
1
0
1
1
1
1
1
0
0
0
0
1
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
0
0
0
0
1
0
0
0
1
1
1
1
1
0
0
0
0
1
1
0
0
0
1
1
1
0
0
0
0
0
0
Zanclidae
Zanclus cornutus
0
0
0
APPENDIX 5: X, Y PLOTS OF STANDARDISED A) PROXIMATE DRIVERS AND
DIVERSITY AND FUNCTION, AND B) DISTAL AND PROXIMATE DRIVERS
A)
195
196
197
198
B)
199
APPENDIX 6: SURVEY USED TO ELICIT FISHER AND MIDDLEMEN PERCEPTIONS
Field Survey questionnaire
Tom Brewer
PhD field period in Solomon Islands
Survey ID:
Time of day:
Surveyor name:
Date:
Halo, nem blo mi Tom, and dis wan hem Joe, hem bai helpem mi for save lelebt lo langus
blo yu. Mi wanfala Scientist lo James Cook University lo Australia and mi doim study for
fisheries department lo Solomon Islands.
Mi laik aaskem yu lo samfala tingting blo yu aboutem solwata fisheries lo Solo (SI).
Tufala main part lo survey blo mi aboutem fish markets and oketa samting wea save
mekem gud or spoilem risoses blo yufala.
Bai mi no talem nem blo yu lo report blo mi bata bai mi usim oketa totok blo yu wetem
oketa nara answers in sait lo riport. Hem nomoa and mi laik tok tangiu tumas for tekem
taim blo yu for sidaun lelebet and stori wetem mi.Hem orait for totok dis time?
A: Demographics (ALL RESPONDENTS)
8. Gender ( M / F )
9. What is your age? _____
10. Where do you live?
11. Province :
Ward:
Village:
200
12. Were you born in the village that you now live in? (Y/N)
13. If no then where were you born?
14. Nation _______
15. Province :_______
16. Ward : _________
17. Village: _________
18. What age were you when you moved to this village? ________
19. Why did you move to this village?
________________________________________________________________
_______
20. How many years of education have you received? _____
21. How many adults in your household?:___
22. How many children live in your household?:____
23. Are you married? (Y/N)
24. Are you the head of your household?(Y / N)
25. Do the children in your household go to school? (Y / N)
201
B: Fishing Gear (Artisanal and subsistence fishers)
I would like to know what sort of fishing gear you use to fish and how important it is to your fishing
26. Which of the following do you use for fishing or fishing related activities such as
transporting fish to markets? (
How
Use?
Gear
How
Use?
many
many
do you
do you
own?
own?
Transport and storage
Fishing Gear
Car/Truck (taraka) /Tractor
Mask
Taxi
Dive torch (Dive tos)
Public Transport (boat/bus)
Poison rope (Poisin)
Outboard engine
Fishing line
Fibreglass boat
Deep sea line
Wooden Canoe
Fishing net
Esky (size)
Hand spear / sling
Other
Spear gun
Fins / flippers
Dynamite
Other:
c) Is your outboard currently working? (Y/N)
What size is your outboard motor (hp)?
1.
2.
202
C: Market chain analysis & target species (Artisanal fishers and middlemen)
Where do you catch or buy reef fish?
How many
PR.
Ward
How many
kilograms of
years have
reef fish do you
you been
What
If you do not
How often do
transport do
catch the
catch or buy on
you catch /
you normally
Who catches
fish, what
catching /
a good/
buy reef fish
use to catch
the reef fish
price do you
Place /
buying reef
average /bad
here (days
or buy reef
that you
pay for the
Why do you catch /
Village
fish here?
trip?
per fortnight)
fish here?
sell?
reef fish / kg
buy fish here?
203
Reef fish Sale
27.
W
here do you sell reef fish?
PR.
Ward
Place
How
How many
What
many
kilograms of reef
transport do
What
What
years
fish do you sell
How often do
you normally
price do
price do
have you
on
you sell reef
use to get
you get
you get
How much
been
good/average/b
fish here on a
your reef fish
per kg for
per kg for
profit do you
selling
ad trip?
good/average
to this
fresh reef
fresh reef
make on an
Why do you sell
/ bad month)
market?
fish?
fish?
average trip?
fish here?
fish here?
204
Do you
How much
How
use ice
do you use
much do
to keep Where do for 1 esky for you pay
fish
you get
a trip to
for ice for
What do you think fisheries should do to make
fresh?
your ice?
market?
1 esky?
the market better?
Market
28. Do you try to catch/buy particular fish to sell? (Y / N)
29. If yes which fish? (Use fish id book)
Type
Local
Common
name
name
Latin name
Why do you target
Where do you
this fish?
sell this fish?
30. Are you satisfied with the money you make from selling reef fish? (Y / N)
31. Would you like to make more money from selling fish? (Y / N)
32. If yes, then what could you do to increase the amount of money you make
from selling fish?
_____________________________________________________________________
_____________________________________________________________________
205
33. If yes (to 24) then what is another way to make more money from selling fish
without spending your own money?
_____________________________________________________________________
_____________________________________________________________________
34. Why don’t you do this now?
_____________________________________________________________________
_____________________________________________________________________
206
D: Livelihoods (ALL RESPONDENTS)
35. What activity do you spend most of your time doing?
____________________________________________________________________
____________________________________________________________________
36. What activities do people in your household do for food and income?
Check if
Activity
yes
Rank of importance for
# of people
income
Fishing (Fishing)
Gleaning
Gardening
Selling reef fish
Selling other marine resources
Selling garden products
Informal economic activity (e.g. selling
cigarettes)
Government Employee
Other salaried employment (regular pay
Tourism
Other
E : Perceived causes of resource condition change, and impacts and response. (ALL
RESPONDENTS)
37. What can affect the number of fish on the reef?
38. What can affect the number of beche-de-mer on the reef?
207
F: Recommendations (ALL RESPONDENTS)
39. What do you think people fishing should do to increase the number of fish on the
reef?
____________________________________________________________________________
____________________________________________________________________________
40. What do you think village leaders should do to increase the number of fish on
the reef?
____________________________________________________________________________
____________________________________________________________________________
41. What do you think the church should do to increase the number of fish on the
reef?
____________________________________________________________________________
____________________________________________________________________________
42. What do you think fisheries centres should do to increase the number of fish on the
reef?
___________________________________________________________________________
___________________________________________________________________________
43. What do you think provincial governments should do to increase the number of
fish on the reef?
___________________________________________________________________________
___________________________________________________________________________
44. What do you think the ministry of fisheries should do to increase the number of fish
on the reef?
___________________________________________________________________________
___________________________________________________________________________
45. What do you think NGO’s and other international organizations should do to
increase the number of fish on the reef?
___________________________________________________________________________
___________________________________________________________________________
208