Global Environmental Change 21 (2011) 1128–1140
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Vulnerability and resilience of remote rural communities to shocks and global changes: Empirical analysis from Solomon Islands Anne-Maree Schwarz a,*, Christophe Be´ne´ b,1, Gregory Bennett c, Delvene Boso a, Zelda Hilly c, Chris Paul a, Ronnie Posala c, Stephen Sibiti c, Neil Andrew b a b c
The WorldFish Center, P.O. Box 438, Honiara, Solomon Islands The WorldFish Center, P.O. Box 500 GPO, 10670 Penang, Malaysia The WorldFish Center, P.O. Box 77, Gizo, Solomon Islands
A R T I C L E I N F O
A B S T R A C T
Article history: Received 29 October 2010 Received in revised form 28 April 2011 Accepted 28 April 2011 Available online 8 June 2011
Successful management of socio-ecological systems not only requires the development and field-testing of robust and measurable indices of vulnerability and resilience but also improved understanding of the contextual factors that influence societal capacity to adapt to change. We present the results of an analysis conducted in three coastal communities in Solomon Islands. An integrated assessment map was used to systematically scan the communities’ multiple dimensions of vulnerability and to identify factors affecting households’ perception about their capacity to cope with shocks (resilience). A multivariate probit approach was used to explore relationships amongst factors. Social processes such as community cohesion, good leadership, and individual support to collective action were critical factors influencing the perception that people had about their community’s ability to build resilience and cope with change. The analysis also suggests a growing concern for a combination of local (internal) and more global (external) contingencies and shocks, such as the erosion of social values and fear of climate change. ß 2011 Elsevier Ltd. All rights reserved.
Keywords: Adaptation Climate change Perception Social cohesion Governance Fishing community
1. Introduction It is now widely recognized that shocks, uncertainty, and local and global changes are inherent in the dynamics of socialecological systems. In that context, a new consensus has emerged in the literature which highlights the importance of concepts such as resilience, vulnerability, and adaptation for the understanding of these socio-ecological systems (e.g. Walker et al., 2002; Janssen and Ostrom, 2006; Miller et al., 2010). It is suggested, in particular, that ‘managing for resilience’ might become a central objective for planning and management, since it is expected to enhance the likelihood of sustaining desirable pathways for development in an environment where the future is recognized to be unpredictable and surprises are expected to occur (Walker et al., 2004, 2010; Adger et al., 2005). In that context, ‘‘the integration of activities geared towards the improvement of community resilience is [becoming] of utmost priority’’ (FAO, 2009, p. 1). This research agenda is not, however, without challenge (see Adger (2006) and Folke (2006) for reviews of the theoretical
* Corresponding author. Tel.: +677 25090; fax: +677 23296. E-mail address:
[email protected] (A.-M. Schwarz). 1 Present address: The Institute of Development Studies (IDS) University of Sussex, Brighton BN1 9RE, United Kingdom. 0959-3780/$ – see front matter ß 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.gloenvcha.2011.04.011
literature on vulnerability and resilience). Many definitions and frameworks have been proposed (Janssen and Ostrom, 2006) and even within specific fields or disciplines, competing definitions and approaches have often made the situation relatively complex. Cutter (1996), for example, identified more than 18 definitions of ‘vulnerability’ in the hazards literature alone. This situation has slowed the development of common methods and as a result there are too few empirical studies to provide a solid foundation for further theoretical work. Beyond these conceptual challenges of language and generic definitions, vulnerability, resilience and adaptation are notoriously difficult to measure quantitatively. Resilience for instance is recognized to be complex, context specific, and highly dynamic – qualities that make it hard to measure through simple proxies (Berkes and Folke, 1998; Walker et al., 2002; Kallstrom and Ljung, 2005). As a result, despite the apparent appeal of resilience and vulnerability as useful concepts to better understand humanenvironment relations (Holling, 1973; Gunderson and Holling, 2002; Smit and Wandel, 2006), natural resource managers have found it difficult to define and use these concepts on the ground (Adger, 2000; Folke, 2003; Colding et al., 2003; Olsson et al., 2005; Mills et al., 2011). The danger is that these concepts remain largely academic and theoretical, and not of a great help in improving the way natural resources are managed. In order to avoid this shortfall, more and different research is needed to develop and field-test
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approaches that enhance our capacity to use these concepts in planning and management (Thomas et al., 2007; Turner et al., 2007; Osbahr et al., 2008). Successful management of socio-ecological systems requires not only the development and field-testing of robust and measurable indices of resilience or vulnerability but also a better understanding of the social and economic mechanisms that make people vulnerable, and of contextual factors that drive changes in resource-use patterns and influence societal capacity to adapt to change (Turner et al., 2007; Ayers and Forsyth, 2009). This in turn requires a better understanding of the knowledge, perceptions and motivations of resource users in order to identify factors that influence their behaviors and decisions (Coulthard et al., 2011). The idea is therefore to ‘expand’ vulnerability and resilience analysis beyond the initial assessment of the degree of exposure to risks and/or frequency and severity of unexpected contingencies, to include the individual and collective processes and mechanisms that mediate people’s agency to respond and adapt. Although shocks, unforeseen events, and changes affecting people’s lives and livelihood are part of an objective reality, individual and collective responses and adaptation are also influenced by the subjective perceptions people have about reality (Camfield and McGregor, 2005; McLaughlin and Dietz, 2007; Devine et al., 2008; Weber, 2010). In these circumstances, it becomes as important to try and understand people’s perceptions about a particular event (e.g. a cyclone) as it is to assess the actual impacts of that particular event. Understanding such perceptions is complicated by the fact that communities are not homogenous, either in terms of exposure to threats or in peoples’ individual resilience and ability to adapt. For example, in the face of covariate events such as climate impacts or economic crises, or idiosyncratic shocks such as illness or loss of employment, people respond in different ways. Whether small or large, communities are highly differentiated in terms of access to resources and factors such as age, gender, class and ethnicity. These differences are highly significant to the vulnerability and adaptive capacity (resilience) of particular individuals. In this study we worked with communities living in rural coastal areas in Solomon Islands. These remote and economically less developed communities face the ‘classic’ challenge of sustaining rapidly growing populations in the context of limited agricultural land and natural resources (see e.g. Reenberg et al., 2008), as well as more recently emerging ‘modern’ problems related to their increasing exposure to the global economy (Nunn, 2003, 2004). Macintyre and Foale (2004) highlight for instance how gold, timber and tuna extracted from these islands since the 1970s have been increasingly incorporated into the world’s market economy, and describe the impacts that these changes have had on local economies in increasing demand for cash and inflation in prices for basic necessities. In addition, the islands of the Pacific region are vulnerable to climate change and sea level rise (Brookfield, 1989; Nurse et al., 1998). Although scenarios for future climate change in the region are still relatively uncertain (Bengtsson et al., 1996; Knutson and Tuleya, 2004), there is now a consensus that Pacific Islands will be particularly exposed to increased risks of extreme events (Hay and Mimura, 2006). This paper describes research that aims to expand vulnerability and resilience analysis beyond the metrics of exposure to risk and unexpected contingencies. The main objective is to develop and field-test methods that enable the identification of the different sources of vulnerability affecting a specific community, and to better understand the contextual factors and processes that can mediate (positively or negatively) households’ perception about resilience through the effects that these factors have on individual and collective capacities and incentives to adapt to change. To
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provide context, we first summarize some recent events that have affected Solomon Islands. 2. Recent shocks and crises in Solomon Islands More than 80% of Solomon Islanders live in rural areas where they rely primarily on root crops (e.g. tapioca, sweet potato) or imported foods (e.g. rice) for their subsistence. Marine resources provide almost all the protein in peoples’ diets (Aswani, 2002; Bell et al., 2009). In recent years economic development and the need for cash have in some places eroded local subsistence activities, although the rural economy remains based upon the production and marketing of a small number of commodities—food crops and fresh fruit, coconut, cocoa, timber, fish and marine products, oil palm and livestock (ARDS, 2007). Wage income through direct employment accounts for about 26% of the household income nationally, rising to 48% in urban areas (GoSI, 2006). In Solomon Islands, as elsewhere in the Pacific region, customary marine tenure and a body of traditional ecological knowledge are associated with a high dependence on marine resources (Ruddle et al., 1992; Veitayaki, 1997; Aswani and Hamilton, 2004), reflecting the historical importance of fish as a reliable source of protein. Solomon Islands’ coral reefs support high levels of marine biodiversity (Green et al., 2006) and the marine eco-region contains areas of global significance (Veron et al., 2009). There is however evidence of localized depletion in finfish in many parts of the archipelago (Green et al., 2006; Brewer et al., 2009) and in December 2005, the commercial beˆche-de-mer fishery, a major fishery exploited by rural fishers for cash (Sulu et al., 2000), was closed by the government following evidence of overfishing and the expected collapse of the stock (Nash and Ramofafia, 2006). In recent times, two shocks in particular have traumatized Solomon Islands society. The serious political unrest which broke out across the Solomon Islands in the late 1990s had major impacts on the economy of the country and displaced many people. Of particular note was an exodus of people from the capital Honiara back to their provinces of origin. This crisis, while often presented as an ethnic conflict, has been described as being initially triggered by a combination of factors (Dinnen, 2002) including some that were linked to rapid population growth, such as unemployment, limited economic opportunities and divisions over distribution of resources. Secondly, in April 2007 an earthquake of magnitude 8.1 on the Richter scale, followed by a tsunami, struck the western provinces of the country (USGS, 2007). The earthquake and tsunami killed 52 people and caused substantial destruction to villages and coastal habitats, severely disrupting livelihoods (Schwarz et al., 2007; Prange et al., 2009). Many fishers’ homes close to sea were destroyed and their fishing gear, including canoes, totally lost. Coral reefs sustained severe earthquake damage in some locations. 3. Methods Three clusters of rural communities with varying, but high, degrees of reliance on fisheries (Molea and Vuki, 2008; Prange et al., 2009) were used as case studies for the empirical work. These are located in the Dovele Region of Vella Lavella Island and Toumoa on the island of Fauro; both in the Western Province, and within Lau Lagoon in Malaita Province (Fig. 1). All communities are part of a wider WorldFish programme which began in 2008, aiming to test a conceptual scheme for the diagnosis and management of smallscale fisheries (Andrew et al., 2007), and are involved in implementing community based adaptive management for their marine resources. The approach we used drew on a livelihood vulnerability assessment method developed and recently field-tested in fishing
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Fig. 1. Solomon Islands and the location of the three community clusters where the research was undertaken.
communities in developing countries (Be´ne´ et al., 2008; Garcia et al., 2008; Mills et al., 2011). The objective was to identify key threats and resilience indicators specific to a social-ecological system. A 3608 integrated assessment map was used to guide researchers to systematically scan multiple dimensions of the social-ecological system being considered while developing a household questionnaire (Fig. 2). Four generic domains were included in the integrated assessment: (i) the natural system, (ii) people and livelihoods, (iii) institutions and governance, and (iv) external drivers, that is, those factors and trends originating outside the control of the local community and originate usually from distant events and/or processes. Paying explicit attention to external drivers acknowledges that many issues impacting on fisheries systems and fisheries-dependent people are beyond their control and originate from sources outside the focal scale. Questionnaires sought information on the general demographic characteristics of households (number of persons, ethnic group, age, etc.), their assets and livelihood strategies (on-farm and offfarm activities), and their perceptions of governance and social
cohesion characterizing their communities. A section of the questionnaire focused events that respondents had experienced in the past and perceived as potentially affecting household livelihoods; the capacity of the community to cope with past and future threats; the barriers to successful natural resource management; and ways to reduce threats and improve livelihoods through individual and collective action. Finally, because these communities are strongly dependent on fishing activities, identification of issues related to marine resource management and business development opportunities were also incorporated in the questionnaire. The terms vulnerability and resilience were not explicitly mentioned. Each of the three clusters had a different local language. Many of the respondents also understood English but the common language amongst all three clusters was Solomon Islands Pidgin. Some of the older respondents were comfortable conversing only in their local language. The questionnaire was written in English then tested and modified by local researchers fluent in English and Pidgin to clarify any ambiguities. Interviews were conducted in
Fig. 2. A generic 3608 integrated assessment map used to structure the vulnerability assessment.
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Pidgin or, if researchers were from the study area, in local language. If necessary, translation to local language was assisted by a village volunteer. Trained project staff completed the fieldwork between January and May 2009 in Toumoa (one community), Dovele (three communities) and Lau Lagoon (two main community groupings based on tribal affiliations). Household questionnaires were administered to sub-samples of 14, 32 and 21 households respectively that were randomly selected within each cluster of communities (representing 25% of those communities’ respective populations), making a combined total of 67 households. In each household, the male household head or his wife was interviewed or, if both were absent, the eldest member of the household present. Interviews were conducted during the day or night to fit around the community’s livelihood activities and typically took from 30 to 50 min to complete. A multivariate probit approach (Maddala, 1992) was used to explore relationships amongst answers. The analysis estimated relationships between binary or ordinal/categorical dependent variables and independent (explanatory) variables. The analyses were done using Stata Statistical Software (Release 10.0, Stata Corp., College Station, TX). Because of our focus on vulnerability
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and resilience, we investigated whether specific institutional and governance conditions could have mediated the capacity of communities to cope with shocks. For this we used three indicators that were evaluated through the interviews: ‘participation’, ‘support’ and ‘leadership’. ‘Participation’ refers to the level of involvement of the villages’ households in communal activities; ‘support’ refers to the level of respect accorded to local leaders and community support for implementing leaders’ decisions; and ‘leadership’ refers to the (perceived) strength of leadership. Additional variables were included to control for factors such as geographical location; age, and gender of respondent, wealth, and occupation; and types and nature of the shocks or threats (Table 1). As a proxy for wealth we used an index combining the number and type of housing (semi-permanent, permanent) owned by the respondent (variable ‘housing’ in Table 1). We used this index, rather than income because the latter is often problematic for households heavily engaged in subsistence-based activities. The variable ‘occupation’ corresponded to the main activity of the household head: farming, fishing, small trading business, and so forth. The variable ‘type’ (type of contingency) corresponded to generic categories used to distinguish categories of threat or shock identified by the respondents (see Table 1 for detail); The binary
Table 1 The list of variables used in the resilience analysis. Variable
N
Description
Tsunamia Age Gender Naturea Past_copeda Better_equippeda Community_Ca Housing_0a Housing_1a Housing_2a Housing_3a Housing_4a Occupation_1a Occupation_2a Occupation_3a Occupation_4a Occupation_5a Occupation_6a Occupation_7a Occupation_8a Occupation_9a Support_1a Support_2a Support_3a Support_4a Support_5a Leadership_1a Leadership_2a Leadership_3a Leadership_4a Leadership_5a Participation_1a Participation_2a Participation_3a Participation_4a Participation_5a Help_0a Help_1a Help_2a Type_1a Type_2a Type_3a Type_4a Type_5a Type_6a Type_7a
67 67 67 67 67 67 67 67 67 67 67 67 66 66 66 66 66 66 66 66 66 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67
Community affected by the tsunami = 1; not affected = 0 Age of the respondent (in years) Gender of the respondent (female = 1; male = 0) Idiosyncratic shock = 1; covariate shock = 0 Coped with past contingencies: strongly agree or agree = 1; otherwise = 0 Learned from past and better equipped for future contingencies: strongly agree or agree = 1; otherwise = 0 Community No. C = 1; other communities = 0, C = 1,2,. . .,6 No habitable house = 1; otherwise = 0 One semi-permanent house = 1; otherwise = 0 One permanent house = 1; otherwise = 0 Two houses, one of which at least is permanent = 1; otherwise = 0 Three houses, one of which at least is permanent = 1; otherwise = 0 Milling as primary occupation = 1; otherwise = 0 Builder/carpenter/carving as primary occupation = 1; otherwise = 0 Small business as primary occupation = 1; otherwise = 0 Copra as primary occupation = 1; otherwise = 0 Waged employment as primary occupation = 1; otherwise = 0 Fishing as primary occupation = 1; otherwise = 0 Agriculture/gardening/farming as primary occupation = 1; otherwise = 0 Pastor as primary occupation = 1; otherwise = 0 Student as primary occupation = 1; otherwise = 0 The community supports the leader’s initiatives: strongly disagree = 1; otherwise = 0 The community supports the leader’s initiatives: disagree = 1; otherwise = 0 The community supports the leader’s initiatives: no opinion = 1; otherwise = 0 The community supports the leader’s initiatives: agree = 1; otherwise = 0 The community supports the leader’s initiatives: strongly agree = 1; otherwise = 0 Level of leadership of the community is very weak = 1; otherwise = 0 Level of leadership of the community is weak = 1; otherwise = 0 No opinion of the respondent about the level of leadership = 1; otherwise = 0 Level of leadership of the community is strong = 1; otherwise = 0 Level of leadership of the community is very strong = 1; otherwise = 0 Level of participation of the community is very week = 1; otherwise = 0 Level of participation of the community is week = 1; otherwise = 0 No opinion of the respondent about level of participation = 1; otherwise = 0 Level of participation of the community is strong = 1; otherwise = 0 Level of participation of the community is very strong = 1; otherwise = 0 Type of major help received: no help = 1; otherwise = 0 Type of major help received: external help = 1; otherwise = 0 Type of major help received: self- help = 1; otherwise = 0 Type of contingency: ‘Extreme climatic events’ = 1; otherwise = 0 Type of contingency: ‘Community conflict and ethnic tensions’ = 1; otherwise = 0 Type of contingency: ‘Fisheries-related issues’ = 1; otherwise = 0 Type of contingency: ‘Local Economy crisis’ = 1; otherwise = 0 Type of contingency: ‘Household-level issues’ = 1; otherwise = 0 Type of contingency: ‘None’ = 1; otherwise = 0 No opinion about the type of contingency = 1; otherwise = 0
a
Indicates dummy variables constructed from the range of respondents’ answers.
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Past threats (N=134) 2007 earthquake/tsunami Local economic crisis Climate-related changes + natural disasters Household-level issue Community conflict and ethnic tensions Fisheries-related issues Dovele No threat
Lau Lagoon Toumoa
No answer 0.00
0.05
0.10
0.15
0.20
0.25
0.30
Proporon of total responses Fig. 3. Threats that respondents had experienced, identified during the vulnerability analysis.
variable ‘nature’ distinguished between idiosyncratic (=1) threats that affected individual households and covariate threats (=0) that affected the entire community. The dummy variable ‘tsunami’ allowed communities affected by the 2007 earthquake and tsunami to be differentiated from those that were not (Lau Lagoon, for example, is on the north eastern side of Malaita and was not affected). Note that, because respondents were allowed to identify more than one threat (or positive event) and all answers were recorded, the total number of answers was greater than the total number of respondents (67). Respondents provided 134 answers for the question on past threats, 145 for future threats, and 122 for positive past events. To make the results of the analysis more illustrative, we computed not only the standard z statistics and p > jzj, but also the ‘marginal effect’ (dF/dx) of each explanatory variable on the probability of success of the dependent variable. This ‘marginal effect’ illustrates how the probability that the respondents answer positively to any of the dependent variables changes if there is a one-unit change in the explanatory variable. For illustration, if the ‘marginal’ effect’ dF/dx of an explanatory variable X on the dependent variable Y is, say, 68%, it means that the probability that Y = 1 (positive answer) is increased by 68%. Pearson x2 goodnessof-fit tests were used to verify the statistical validity of the models. We hypothesized that the ability of a household to cope with contingencies was influenced by its wealth: better-off households were expected to be more able to respond and adapt after a shock than poorer households. We also hypothesized that the level of social cohesion and governance within communities influenced the ability of the community to cope with contingencies. Strong leadership by the local customary authority, high participation in collective action by the community, or a strong sense of support to the leaders were hypothesized to positively affect resilience and adaptive capacity. Finally, we investigated whether the nature of the threat itself (i.e. idiosyncratic shock as opposed to an event affecting the entire community – covariate shock) would influence the respondents’ answers.
unique to communities or even households, some were common across several communities, such as the ‘economic crisis’ that followed the global fuel and food crises during 2008–2009 and was perceived as the major past threat across the three clusters (Fig. 3, Table 2). The April 2007 earthquake that severely affected Dovele and Toumoa was identified as a major past threat by the households of those two clusters. Next, but with a much lower score, were categories of threat grouped as ‘climate-related change and natural disaster’ (e.g. king tides, a term referring to any high tide well above average height, cyclones, droughts and floods). Lesser threats were perceived to come from smaller-scale events, comprising a suite of chronic threats and acute events that affected some households but not others, such as illness, family conflict or, for example, rats eating garden crops. Following this category is the ‘community conflict and ethnic tensions’ category, which included not only the political unrest that broke out in the late 1990s and continued over the 2000s, but Table 2 Previous threats identified by the respondents.
The first part of the analysis focused on past events that households had experienced and were perceived to have been major threats to their livelihoods. Although many threats were
Detail of the types of answers included in the generic categories
Earthquake/tsunami Local economic crisis
April 2007 earthquake and associated tsunami Fuel price rise/rice price rise/store goods price rise/food price expensive/high community store prices Cyclone/drought/flood/high tide/king tide
Climate-related changes and natural disasters Household-level issues
Community conflict and ethnic tensions Fisheries-related issues
No threat
4. Results 4.1. Sources of vulnerability
Generic category
No answer a
Garden food eaten by rats/pigs destroyed garden/illness/family conflict/garden food stolen Church destroyed during tension/Bougainville crisisa/ethnic tension/land dispute/youth disturbance/drunken people Failure of government fisheries projects/ stealing reef resources/closing of the beˆchede-mer fishery Respondents considered that no threat affected their community No answer given by respondents
Between 1988 and 1990 internal conflict on the island of Bougainville caused around 20,000 lives to be lost and the destruction of infrastructure and law and order. With only a short distance separating Bougainville from the Shortland Islands in Western Province, many western Solomon Islanders were affected by the protracted emergence from that conflict.
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Future threats (N=145) Climate-related changes + natural disasters Malthusian scenario Social cohesion erosion Land dispute and inter-community conflict over resources Local economic crisis Household-level issues Dovele
No answer/don't know
Lau Lagoon Fisheries-related issues
Toumoa 0.00
0.05
0.10
0.15
0.20
0.25
0.30
Proporon of total responses Fig. 4. Future threats, identified by the respondents during the vulnerability analysis.
also some intra-community conflicts regarding access to land or events perceived as social disruptions (e.g. youth misbehavior, public drunkenness, etc.). Issues related to fisheries were ranked relatively low by all the households across the three clusters, despite the fact that fishing is a central element in the livelihood of these populations and that the local beˆche-de-mer fishery had been closed via a national export ban, thereby removing one of the few regular sources of cash. The second part of the analysis consisted of identifying the future sources of threat as perceived by the local population. The aggregated results of this analysis are displayed in Fig. 4 for the three clusters, while the disaggregated information is shown in Table 3. At a household scale, perceptions about future risks of ‘fisheries-related’ and ‘household-level’ issues were relatively similar to recollections of past threats. Also consistent with the past vulnerability analysis was the fact that risks associated with ‘climate and natural disasters’ (including earthquakes, storms, king tides, and cyclones) were identified as a major source of future vulnerability. The fact that ‘local economic crises’ still appeared in the analysis but with a lower score than for the past vulnerability analysis may reflect people’s expectation that the aftermath of the world fuel and food crises will fade in the future. In contrast, respondents believed that community conflicts and tensions (in particular regarding land disputes) were not going to disappear. Instead they projected that these types of conflicts would increase - as confirmed by the emergence of two new sources of vulnerability: ‘social cohesion erosion’ (including issues such as ‘‘community collapsing’’, ‘‘selfishness’’, ‘‘disobedience and disre-
spect’’), and a ‘Malthusian narrative’ threat (referring to issues worded by people as ‘‘population increase’’ etc.). These new sources of perceived vulnerability were characterized by high scores, the Malthusian narrative being identified as the second major source of future vulnerability by the communities, just after ‘climate-related and natural disasters’. If ‘land dispute and intercommunity conflict over resources’ was considered a subset of this ‘Malthusian scenario’, then the aggregated category would become the main perceived source of threat. 4.2. Sources of resilience Our analysis of resilience was done in two stages: First, past positive events that respondents had experienced were identified – using the same method as for the negative events. Second, for each of the past threats identified, respondents were asked to agree/disagree whether or not ‘‘the community coped well with this particular event at the time’’; and whether or not ‘‘the community has learnt from these experiences and can now cope better in the future’’. In using these variables as proxies of resilience, we assume that part of the ability of households and communities to adapt to change, and respond so as to retain their essential structure, is conditioned by subjective elements in the same way that risk aversion has been recognized to be a critical element affecting household’ decisions on investment and livelihood strategies (e.g. Dercon, 2004; Adger et al., 2009). As a counterpoint to the important negative perception of the 2007 earthquake/tsunami, respondents in Western Province commonly identified the post-disaster aid received in its aftermath
Table 3 Future threats identified by the respondents. Generic category
Detail of the types of answers included in the generic categories
Climate-related changes and natural disasters Malthusian scenario Social cohesion erosion
Natural disasters/sea level rise/high tide Population increase/young mother with 2–4 children/population control Community collapse/alcohol and drug consumption/disobedience/independency of young/ selfishness/disrespect/culture degrading/ Outsiders – Bougainville disturbance/land dispute/land shortage/unresolved conflict/gold mining negative effects Price increase/lack of money/poverty/high food prices Wild pig/illness/pigs destroying food gardens/crop not growing well No answer given by respondents Less fish/reef resources/marine resource shortage
Land dispute and inter-community conflict over resources Local economic crisis Household-level issues No answer Fisheries-related issues
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Posive events (N=122) External post-disaster help Intra and inter-community acvies Fisheries opportunies None No answer Economic opportunies Church acvies
Dovele Lau Lagoon
Miscellaneous
Toumoa
Government social intervenons 0.00
0.10
0.20
0.30
0.40
0.50
Proporon of total responses Fig. 5. Positive events that respondents had experienced, identified during the resilience analysis.
as a positive event (Fig. 5). This assistance took the form of provision of significant infrastructure including dugout canoes, clinics, schools and water supplies. In some instances such infrastructure had not existed prior to the earthquake/tsunami, or had been in very poor condition beforehand. The second major thread of positive events was intra and/or inter-community initiatives, mainly in the form of social events (e.g. sport carnivals, memorial feasts) or collective actions (‘‘participation in voluntary work’’, ‘‘co-operation between community members’’). Beyond these two positive events–which represented in aggregate more than 60% of the answers, the next answer was ‘‘fisheries opportunities’’ referring to positive (individual or collective) actions or situations related to the fisheries (e.g. ‘‘community organized to manage marine resources’’, ‘‘fishing income’’). ‘‘None’’, meaning that respondents could not recall any particular positive event came next with slightly less than 10% of the answers (Fig. 5). Slightly more than half of respondents (56%) disagreed or strongly disagreed that their community had coped well with past shocks (Fig. 6). This in itself may not necessarily be surprising especially when we keep in mind that most shocks came from external sources and so households and communities had very limited control over these events. Interestingly, more than half (57%) of respondents agreed or strongly agreed that their communities had learned from past shocks and would be in a better position to cope with shocks in the future (Fig. 7). In contrast, only 38% of household thought the communities had dealt well with them at the time (Fig. 6).
about the communities’ capacity to cope with past contingencies. This contrasts with the absence of significant correlation between the respondents’ answers and the ‘extreme climatic events’ variable (Table 4). Indeed, none of the dummy variables corresponding to the different types of threat appeared significant. Likewise, geographical location had little effect on respondents’ perceptions: households from community No. 5 (part of the Lau Lagoon cluster) were the only ones that indicated a statistically significant coefficient – in that case, negative. More critical is the observation that the group characterized by the higher wealth indicator (housing_4) appeared to have a relatively high marginal effect (61%) – although not significant at 5% – on the dependent variable (Table 4). If this interpretation is correct it suggests that wealth may positively influence the perception people have about their capacity to cope with uncertainty. In particular, the better-off households felt their communities had been able to cope relatively well with the contingencies they faced in the past. The main economic activities in which households were engaged affected their perceptions about the ability of their community to cope with past threats. This variable was significant for two groups: the households who produced copra (occupation_4) had a significant negative perception about the ability of
Strongly agree 8%
No opinion/no answer 6%
Strongly disagree 3%
4.3. Probit analysis The first probit model investigated the factors and contextual variables that may have influenced the capacity of communities to cope with past contingencies. For this, the binary variable ‘past_coped’ was used as the dependent variable while other variables were used as explanatory variables. The goodness-of-fit test confirms the statistical validity of the model. Some interesting points emerge from this analysis (Table 4). First, in line with the earlier identification of the 2007 earthquake/tsunami as a common past threat for many communities (cf. Fig. 3), the probit model indicated a significant negative effect of the tsunami variable on the respondents’ answer. In fact the dF/dx figure suggests that a change from 0 to 1 for this variable increases by 81% the chance that the respondent answered ‘‘did not cope’’ (=1) to the question
Agree 30%
Disagree 53%
Fig. 6. Respondents’ answers to the question: ‘‘Do you think that your community has coped well with contingencies in the past?’’.
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Strongly disagree 4%
No opinion/no answer 16%
Disagree 23%
Strongly agree 7%
Agree 50% Fig. 7. Respondents’ answer to the question: ‘‘Do you think that your community has learnt from past contingencies is are now better equipped to deal with future contingencies?’’.
the community to deal with past contingencies; and fishing households (occupation_6) had a strong positive view (p < 0.01). The marginal effect for this latter group was large (79%). Using cyclones as an example, a plausible explanation for this result could be that crop-based occupations such as copra will be
severely disrupted for months or even years as coconut trees regrow. In contrast, in the absence of damage to reefs, fishers are able to resume their activities soon after the cyclone has passed. Finally, a high level of leadership (leadership_4) had a significant positive effect on respondents’ answers. Households
Table 4 Probit model for the capacity of communities to cope with past contingencies (dependent variable: ‘past_coped’ – see Table 3 for variable definition). Explanatory variables Age Tsunamia Community_1a Community_2a Community_4a Community_5a Housing_0a Housing_2a Housing_3a Housing_4a Occupation_1a Occupation_2a Occupation_4a Occupation_5a Occupation_6a Support_2a Support_4a Support_5a Leadership_2a Leadership_3a Leadership_4a Type_ 1a Type_2a Type_4a Naturea Gendera Statistical summary Number of obs Pseudo R2 Log likelihood Goodness-of-fit test Number of covariate patterns Pearson x2(65) Prob > x2 a
dF/dx 0.005 0.814 0.537 0.078 0.571 0.558 0.352 0.165 0.221 0.612 0.200 0.161 0.469 0.252 0.798 0.297 0.347 0.476 0.185 0.106 0.863 0.165 0.315 0.391 0.383 0.114
Std. err.
z
p>z
[95%
C.I.]
0.006 0.193 0.301 0.308 0.315 0.116 0.543 0.240 0.191 0.307 0.277 0.260 0.090 0.359 0.134 0.134 0.339 0.303 0.385 0.278 0.131 0.305 0.109 0.201 0.099 .0302
0.830 2.360 1.530 0.240 1.50 2.690 0.640 0.620 0.830 1.390 0.50 0.510 2.540 0.730 3.420 1.110 0.940 1.370 0.500 0.390 2.480 0.540 1.340 1.410 1.940 0.40
0.405 0.018* 0.125 0.813 0.132 0.007** 0.520 0.533 0.409 0.163 0.620 0.612 0.011* 0.467 0.001*** 0.266 0.350 0.169 0.618 0.695 0.013* 0.588 0.181 0.159 0.052 0.692
0.017 1.186 0.073 0.672 0.084 0.781 0.431 0.626 0.596 0.032 0.783 0.659 0.646 0.428 0.525 0.567 1.008 1.079 0.592 0.443 0.585 0.430 0.530 0.784 0.578 0.478
0.007 0.403 1.121 0.511 1.147 0.325 1.326 0.317 0.169 1.207 0.432 0.318 0.292 0.964 1.059 0.013 0.318 0.128 0.912 0.648 1.126 0.762 0.098 0.010 0.185 .707
112 0.50 37.70 91 54.53 0.79
dF/dx is for discrete change of dummy variable from 0 to 1; z and p > jzj correspond to the test of the underlying coefficient being 0; *p < 5%; **p < 1%; ***p < 1%; rows highlighted in grey are the explanatory variables with a marginal effect greater than 60%.
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in communities characterized by strong, effective leaders tended to think that their communities coped well with past shocks. The marginal effect of this variable was, in fact, the largest of the model: 86%. The next step was to conduct a similar analysis of the perceptions of households regarding the degree to which communities learned from shocks and felt that they were better equipped to cope in the future. The major difference from the previous analysis was that the binary variable ‘past_coped’ was used as an explanatory variable (it was the dependent variable in the first probit analysis) and the variable ‘better_equipped’ (which was not used in the first probit model) became the dependent variable. The objective was to test whether the capacity of the communities to cope with past events may influence the degree to which people perceive their communities were able to learn and to cope better in the future. The goodness-of-fit test confirmed the statistical validity of the model (Table 5). The results show that, as one could expect, the variable ‘past_coped’ had a significant positive effect on respondents’ answers, meaning that the capacity to cope with past events had a positive effect on the degree to which people perceive their ability to deal with future threats. The marginal effect of ‘past_coped’ was high (71%). As for the other variables, geographical location seems to have a mixed effect whereby only one community (No. 6 from Lau Lagoon) shows a significant negative effect (as was the case with community No. 5 for the past threat analysis) while the others have non-significant (positive or negative) effects. The other two variables with significant effect were ‘leadership’ and ‘support’. The negative effect of location on people’s perception of having not coped well in the past (community No. 5) or not being able to cope well in the future (community No. 6) may in part be explained by the fact that these two communities live on artificial islands. Often referred to as ‘‘saltwater people’’ because of their close
association with the marine environment, these people have limited access to land for generating livelihoods (Molea and Vuki, 2008). The negative events most commonly listed by households in communities 5 and 6 were fuel and food price rises, cyclones and gardens being destroyed by rats. Sea level rise and future population increase were identified as the main future threats; consistent with a high degree of exposure to extreme weather events and limited options for population expansion and livelihood diversification. The statistical significance of the dummy variable ‘Leadership_2’ (corresponding to the group of households that considered leadership in their community was ‘‘weak’’) is hard to explain – its marginal effect is relatively small (46%) compared to the marginal effect of ‘leadership_5’ (answer = ‘‘very strong’’; p < 0.01 and marginal effect = 93%). Similarly, the dummy variable ‘support_4’ (indicating the answer ‘‘strong’’ to the question regarding the level of support offered by the community to their local leader) was positively significant (p < 0.05) and had a very large marginal effect (92%). Finally we note that the dummy variable ‘participation_2’ (corresponding to the group of households who considered that the degree of participation in collective actions was ‘‘weak’’) was not significant but was associated with a relatively strong negative marginal effect (68%) suggesting that poor participation reduced the probability of success. Taken together these results indicate that the degree of community collaboration and cohesion around their leader were important factors in the perception people had about their capacity to learn from the past and to cope with future threats. 5. Discussion The findings of this research highlight the trauma that unexpected extreme events can have on people. Two years after
Table 5 Probit model for the capacity for communities to cope with future contingencies (dependent variable: ‘better_equipped’ – see Table 3 for definition). Explanatory variables Past_coped* Age Tsunamia Community_1a Community_2a Community_4a Community_6a Occupation_2a Occupation_5a Occupation_6a Occupation_8a Leadership_2a Leadership_4a Leadership_5a Participation_2a Participation_4a Support_2a Support_4a Support_5a Help_1a Help_2a Naturea Statistical summary Number of obs Pseudo R2 Log likelihood Goodness-of-fit test Number of covariate patterns Pearson x2(37) Prob > x2 a
dF/dx 0.719 0.022 0.004 0.118 0.366 0.096 0.924 0.061 0.210 0.421 0.189 0.468 0.121 0.929 0.680 0.241 0.257 0.918 0.134 0.039 0.302 0.018
Std. err.
z
p>z
[95%
C.I.]
0.148 0.007 0.270 0.192 0.484 0.254 0.083 0.311 0.402 0.440 0.105 0.114 0.359 0.086 0.351 0.170 0.109 0.134 0.385 0.203 0.454 0.299
2.37 2.44 0.01 0.5 0.84 0.33 2.19 0.17 0.59 0.99 1.41 2.42 0.37 2.78 1.49 1.18 1.58 2.15 0.36 0.19 0.77 0.06
0.018* 0.015* 0.99 0.618 0.4 0.743 0.029* 0.862 0.555 0.32 0.159 0.015* 0.708 0.005** 0.137 0.237 0.114 0.032* 0.718 0.847 0.44 0.951
0.429 0.035 0.532 0.260 1.315 0.403 1.086 0.549 0.999 1.283 0.016 0.245 0.825 0.761 1.267 0.092 0.045 0.656 0.889 0.437 1.192 0.605
1.010 0.009 0.525 0.495 0.584 0.594 0.762 0.670 0.579 0.440 0.394 0.691 0.582 1.097 0.108 0.575 0.470 1.180 0.620 0.359 0.588 0.569
90 0.55 26.76 60 36.92 0.47
dF/dx is for discrete change of dummy variable from 0 to 1; z and p > jzj correspond to the test of the underlying coefficient being 0; *p < 5%; **p < 1%; ***p < 1%; rows highlighted in grey are the explanatory variables with a marginal effect greater than 60%.
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the disaster, the April 2007 earthquake and tsunami that devastated the western part of the archipelago was still very much in people’s minds. In comparison, recurrent meteorological events such as cyclones or tropical storms were acknowledged but not as important as a source of vulnerability. This result is interesting as Solomon Islands is just north of the latitudinal belt of greatest seasonal cyclone activity in the southern hemisphere (10– 208S) meaning these communities do occasionally experience extreme cyclone-related weather events, and seasonal storms from cyclones located further to the south are common (Bureau of Meteorology Australia, 2010). The lower ranking of seasonal, but relatively predictable events may reflect that people consider disruption associated with these recurrent events as an inherent and ‘natural’ component of their lives and do not therefore perceive them as so detrimental to their livelihood. This potential decoupling between the actual impact of threats, be they large or minor, and the perception that people construct about these events due to their recurrent nature needs further exploration as an attribute of vulnerability and resilience. If a decoupling is confirmed, it would suggest a potential limitation in the interpretation of participatory vulnerability assessment if the frequency and severity of repeated events are not included in the analysis. A slightly different explanation was proposed by Barnett (2001) who reported that considerable resilience to shortterm, seasonal hazards has been documented for the Pacific region. Citing Campbell (1990, 1998), in particular, Barnett (2001) argued that Pacific Island societies have historically had a range of practices that made them resilient to climate extremes. Under this narrative, the low level of (perceived) vulnerability to seasonal weather-related events would reflect a relatively high capacity to adapt and react to these events. Irrespective of whether an ability to cope with seasonal weather events is perceived or actual, our results reinforce the conclusion that individual and collectives perceptions matter when it comes to assessing adaptation (Adger et al., 2009; O’Brien and Wolf, 2010). This result adds to a growing body of empirical evidence indicating that values and perspectives play a critical role in individual and collective decision-making on adaptation options (Grothmann and Patt, 2005; Adger et al., 2009; Heyd and Brooks, 2009; O’Brien, 2009; Weber, 2010). In order to meaningfully evaluate adaptation options, it thus becomes crucial to understand beliefs, perceptions and values, and how in turn these influence individual and community responses and decision-making patterns. In particular, recent analyses suggest that adaptations considered successful by the affected people often appear to depend on what people perceived to be worth achieving and protecting. For instance, Schipper and Dekens (2009) showed that numerous efforts to reduce risks have been unsuccessful because not enough attention was paid to cultural or social factors. This is consistent with a more specific analysis of fisheries by Coulthard et al. (2011) who argued that the inclusion of values, motivation and social relationships into the development of fisheries policy can improve fisheries governance and human wellbeing. In addition to the impact of the 2007 earthquake, our analysis revealed some less dramatic but equally important events for the livelihood of the study communities. For example, remote communities in this isolated archipelago in the Pacific Ocean were not spared the effects of the fuel and food crisis that spread across the world in 2008–2009. The vulnerability of these communities was increased largely through a marked rise in the price of imported fuel (Asian Development Bank, 2008), a commodity on which remote communities are increasingly dependent for sea travel to urban centres and markets, and in the price of store-bought goods, in particular imported rice, which is now considered a food staple in many parts of Solomon Islands (GoSI, 2006).
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While the analysis of past contingencies suggests that climate change was not recognized as a major source of vulnerability, the analysis of the future threats shows that the perception communities have about climatic risks is changing. ‘‘Climaterelated changes and natural disasters’’ was ranked first in the list of future source of vulnerability, indicating that even in these remote rural areas the awareness about the issue of climate change is increasing (see also Tschakert, 2007). The analysis of local populations’ perception about future sources of vulnerability revealed another marked difference from the past vulnerability analysis. This relates to the emergence of a ‘Malthusian’ threat. This threat is associated with a relatively high population growth rate of 2.5% (World Bank, 2008) and reasonably conservative population projections suggesting that by 2015 the working-age population of Solomon Islands could increase by 30% from 2004 levels (World Bank, 2006). On current trends, formal employment would only absorb around 10% of these people, leaving the remainder to earn income from informal activities or subsistence rural activities (Warner, 2007). Although subsistence livelihood strategies adopted by smallholders in Solomon Islands have been effective in the past, population pressures suggest that these strategies will not provide a basis for maintaining or increasing living standards in the long term. Nevertheless the Malthusian threat has been described as being kept at bay so far in Solomon Islands communities through various coping strategies including diversification of livelihoods, a fuller integration into the wider economic activity of the country, out-migration and a reliance on remittances and goods from relatives living away from the rural islands (Reenberg et al., 2008; Bayliss-Smith et al., 2010). In the context of the perceived threat of population increase, it is not surprising to observe that the third major source of future vulnerability identified by communities relates to erosion of social cohesion. The rural society of Solomon Islands is going through important social and economic transformations. The principles of intra-community solidarity, reciprocity and collective support that have been norms in the social fabric of these communities (e.g. Ruddle et al., 1992) are now challenged directly through the ‘monetization’ of inter-household interactions and indirectly by the newly-introduced principles of ‘modernity’ and ‘democracy’ which put emphasis on individualism and freedom and gradually erode the collective nature of the traditional social system. In addition, emerging societal issues such as drug use (especially alcohol) exacerbate the sentiment amongst community members that traditional systems, which have been seen as the foundation for social and institutional ‘stability’, are now struggling. This is probably part of the reason why the second, third and fourth most important sources of future vulnerability identified by the respondents are related to intra and inter-community ‘negative’ dynamics and revolved around issues such as social cohesion erosion, conflicts, competition and tension. More surprising perhaps was the finding that although these communities depend to a large extent on fish as critical source of protein and cash, and that they identify these as being under increasing pressure (Boso and Schwarz, 2009; Prange et al., 2009), fisheries-related issues were not identified as being amongst the major sources of future vulnerability. One could hypothesize that this result reflects the fact that this analysis was conducted during the initial stages of a larger community based fisheries management initiative in the study communities or that not all households interviewed depended on fisheries (and therefore that the fishers’ answers were ‘diluted’ amongst the larger population). However, a ‘fisher-specific’ analysis shows that the group of fishers was never associated with any significant negative correlation. Indeed, it appeared to have a strong significant positive effect on the answers regarding past events, suggesting that fisher households were relatively positive about how their community had coped with
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past threats. This may be explained in part by the fact that although fishers were amongst those most affected by the tsunami, many received targeted support during the post-disaster programmes (Schwarz, 2009). From a wider perspective, our results challenge some entrenched narratives regarding natural resource management and the type of vulnerability that affects rural communities. While the literature often presents fluctuating or unpredictable level of natural resources as important source(s) of vulnerability in communities that depend upon these resources for their livelihoods (e.g., Shahbaz, 2008; Allison et al., 2009; Armah et al., 2010), our results suggest that these communities consider other sources of threats deserve more urgent attention. Similar findings have been observed in recent assessments of fishing communities in other parts of the world (e.g. Mills et al., 2011; Salas et al., 2010). These studies advocate for a broader vulnerability assessment process resulting in the identification of very different entry points for fishery management that may still include some intra-sectoral interventions such as gear controls, but also elements outside the domain of the fishery (e.g. water management allocation and planning), or even cross-sectoral issues such as alternative livelihoods, improving literacy, and better access to health services. Much has been written about the various strategies adopted by households to deal with shocks and uncertainty, including ex-ante strategies and ex-post coping responses (Roumasset et al., 1979; Dercon, 1996; Carter, 1997; Kinsey et al., 1998). These different works highlight the importance of livelihood diversification and migration (McDowell and de Haan, 1997; Ellis, 1998; Be´ne´ et al., 2003, but see also Be´ne´, 2009). Much less has been written about the social/institutional factors that strengthen the capacity of households or communities to cope with contingencies and increase the resilience of the socio-ecological systems of which they are part. The resilience analysis presented here provides information with which to start addressing these questions. It stresses in particular the critical role that leadership, participation, and community self-support seem to play in the creation of the appropriate social environment for resilience building and adaptation. These findings are in agreement with recent work suggesting that individuals and communities may be more ready to engage/invest in the individual or collective actions and behavioral changes that are required to ensure adaptation and change if they evolve in a supportive social environment (Spaargaren and van Vliet, 2000; Nye and Burgess, 2008; Adger et al., 2009). Our research, which was conducted in the specific context of fisheries-dependent rural communities exposed to multi-origin shocks and uncertainties, confirms these results and provides empirical evidence illustrating the importance of leadership, participation and community self-support as some of the key social factors fostering adaption and resilience building. 6. Conclusion This research was motivated by the increasing attention given in the scientific literature to concepts such as vulnerability, adaptability, and resilience. While the theoretical literature is rich and rapidly expanding, the empirical application of these analyses and concepts in developing countries is still very limited. There is an urgent need for more empirical research on how to operationalise these theories to make them meaningful and applicable to local communities in developing countries. This need for more empirical research includes, not only fieldtesting robust and measurable indices of resilience or vulnerability, but also a need to better understand the social and institutional factors that influence the capacities of individuals and societies to react and adapt to uncertainty and changes. Research to date
suggests that perceptions of risk, preference, belief, knowledge, and experience are key-factors that determine, at the individual and societal level, whether and how adaptation takes place. Our research suggests that elements of good community-level governance such as social cohesion, leadership, or individual support for collective action improve the perception that people have of the capacity of their community to cope with change. We contend that these components are necessary to create (or support) the enabling environment to build resilience and facilitate adaptation to external drivers. Acknowledgements We are very grateful to the Solomon Islands communities who gave their time and knowledge to work with the research team and to host the team in their communities. This work was supported by WorldFish-Solomon Islands staff, particularly Cletus Oengpepa at the Nusa Tupe field station and officers from the Solomon Islands Ministry of Fisheries and Marine Resources especially Lionel Luda and Max Kori. Tim Alexander provided useful comments on the text which was greatly improved by the comments of anonymous reviewers. This research was funded by the Australian Centre for International Agricultural Research (ACIAR). ACIAR had no role in the study design, collection, analysis and interpretation of data, writing of the report or in the decision to submit the paper for publication. References Adger, W.N., 2000. Social and ecological resilience: are they related? Progress in Human Geography 24, 347–364. Adger, W.N., 2006. Vulnerability. Global Environmental Change 16, 268–281. Adger, N.W., Hughes, T.P., Folke, C., et al., 2005. Social-ecological resilience to coastal disasters. Science 309, 1036–1039. Adger, W.N., Dessai, S., Goulden, M., et al., 2009. Are there social limits to adaptation to climate change? Climatic Change 93, 335–354. Allison, E.H., Perry, A., Badjeck, M.-C., et al., 2009. Vulnerability of national economies to potential impacts of climate change on fisheries. Fish and Fisheries 10, 173–196. Andrew, N., Be´ne´, C., Hall, S.J., et al., 2007. Diagnosis and management of small-scale fisheries in developing countries. Fish and Fisheries 8, 227–240. ARDS, 2007. Solomon Islands Agricultural Rural Development Strategy. Solomon Islands Government, Ministry of Development Planning and Aid Coordination, p. 73. Armah, F.A., Yawson, D.O., Yengoh, G.T., et al., 2010. Impact of floods on livelihoods and vulnerability of natural resource dependent communities in northern Ghana. Water 2, 120–139. Asian Development Bank, 2008. ADB and Solomon Islands (online). www.adb.org/ solomonislands. Aswani, S., 2002. Assessing the effects of changing demographic and consumption patterns on sea tenure regimes in the Roviana Lagoon, Solomon Islands. Ambio 31, 272–284. Aswani, S., Hamilton, R., 2004. Integrating indigenous ecological knowledge and customary sea tenure with marine and social science for conservation of bumphead parrotfish (Bolbometopon muricatum) in the Roviana Lagoon, Solomon Islands. Environmental Conservation 31, 69–83. Ayers, J., Forsyth, T., 2009. Community-based adaptation to climate change: strengthening resilience through development. Environment 51, 23–31. Barnett, J., 2001. Adapting to climate change in Pacific Island Countries: the problem of uncertainty. World Development 29, 977–993. Bayliss-Smith, T., Gough, C.V., Christensen, A.E., et al., 2010. Managing Ontong Java: Social institutions for production and governance of atoll resources in Solomon Islands. Singapore Journal of Tropical Geography 31, 55–69. Bell, J., Kronen, M., Vunisea, A., et al., 2009. Planning the use of fish for food security in the Pacific. Marine Policy 33, 64–76. Be´ne´, C., 2009. Are fishers poor or vulnerable? Assessing economic vulnerability in small-scale fishing communities. Journal of Development Studies 45, 911–933. Be´ne´, C., Mindjimba, K., Belal, E., et al., 2003. Inland fisheries, tenure systems and livelihood diversification in Africa: the case of the Yae´re´ floodplains in Cameroon. African Studies 62, 187–212. Be´ne´, C., Andrew, N., Russell, A., et al., 2008. Managing Resilience in West African small-scale fisheries. Unpublished paper presented at the Second International Forum on Water and Food (Addis Ababa 10–14 Nov 2008). Bengtsson, L., Botzet, M., Esch, M., 1996. Will greenhouse gas induced warming over the next 50 years lead to higher frequency and greater intensity of hurricanes? Tellus Series A: Dynamic Meteorology and Oceanography 48, 57–73.
A.-M. Schwarz et al. / Global Environmental Change 21 (2011) 1128–1140 Berkes, F., Folke, C., 1998. Linking social and ecological systems for resilience and sustainability. In: Berkes, F., Folke, C. (Eds.), Linking Social and Ecological Systems: Management Practices and Social Mechanisms for Building Resilience. Cambridge University Press, pp. 1–25. Boso, D., Schwarz, A., 2009. Livelihoods and Resilience Analysis in Two Community Clusters: The Funa’afou and Foueda Artificial Island Communities, Lau lagoon, Malaita Province, Solomon Islands. WorldFish Center Report to ACIAR, Project FIS/2007/116. Brewer, T.D., Cinner, J.E., Green, A., et al., 2009. Thresholds and multiple scale interaction of environment, resource use, and market proximity on reef fishery resources in Solomon Islands. Biological Conservation 142, 1797–1807. Brookfield, H., 1989. Global change and the Pacific problems for the coming halfcentury. The Contemporary Pacific 1, 1–17. Bureau of Meteorology Australia, 2010. Australian government, average annual information for tropical cyclones (online). http://reg.bom.gov.au/jsp/ncc/climate_averages/tropical-cyclones/index.jsp. Camfield, L., McGregor, J.A., 2005. Resilience and wellbeing in developing countries. In: Ungar, M. (Ed.), Handbook for Working with Children and Youth: Pathways to Resilience across Cultures and Contexts. Sage Publications, Thousand Oaks, CA. Campbell, J., 1990. Disasters and development in historical context: tropical cyclone response in the Banks Islands, northern Vanuatu. International Journal of Mass Emergencies and Disaster 8, 401–424. Campbell, J., 1998. Consolidating mutual assistance in disaster management within the Pacific: principles and application. In: South Pacific Applied Geoscience Commission (Ed.), Seventh South Pacific Regional IDNDR Disaster Management Meeting, pp. 61–71. Suva, South Pacific Applied Geoscience Commission. Carter, M., 1997. Environment, technology, and the social articulation of risk in West African agriculture. Economic Development and Cultural Change 45, 557–591. Colding, J., Elmqvist, T., Olsson, P., 2003. Living with disturbance: building resilience in social-ecological systems. In: Folke, C., Berkes, F., Colding, J. (Eds.), Navigating Social-Ecological Systems: Building Resilience for Complexity and Change. Cambridge University Press, UK. Coulthard S., Johnson D., McGregor J. A., 2011. Poverty, sustainability and human wellbeing: a social wellbeing approach to the global fisheries crisis. Global Environmental Change (online). doi:10.1016/j.gloenvcha.2011.01.003. Cutter, S., 1996. Vulnerability to environmental hazards. Progress in Human Geography 20, 529–539. Dercon, S., 1996. Risk, crop choice and savings: evidence from Tanzania. Economic Development and Cultural Change 44, 485–513. Dercon, S. (Ed.), 2004. Insurance against poverty. Oxford University Press, Oxford. Devine, J., Camfield, L., Gough, I., 2008. Autonomy or dependence – or both? Perspectives from Bangladesh. Journal of Happiness Studies 9, 105–138. Dinnen, S., 2002. Winners and losers: Politics and disorder in the Solomon Islands 2000–2002. The Journal of Pacific History 37, 285–298. Ellis, F., 1998. Household strategies and rural livelihood diversification. Journal of Development Studies 35, 1–38. FAO, 2009. Resilience of rural communities to climatic accidents – a need to scale up socio-environmental safety nets (Madagascar, Haiti): Policy Brief EASYPol: Food and Agriculture Organization (online). www.fao.org/easypol. Folke, C., 2003. Conservation, driving forces, and institutions. Ecological Applications 6, 370–372. Folke, C., 2006. Resilience: The emergence of a perspective for social-ecological systems analyses. Global Environmental Change 16, 253–267. Garcia, S.M., Allison, E.H., Andrew, N.L., et al., 2008. Towards integrated assessment and advice in small-scale fisheries: principles and processes. FAO Fisheries and Aquaculture Technical Paper. No. 515, p. 84. Rome, FAO. GoSI (Government of Solomon Islands), 2006. Household Income and expenditure survey 2005/6 National Report (Part One). Solomon Islands Statistics Office, Department of Finance and Treasury, Honiara. Green, A., Lokani, P., Atu, W., et al. (Eds.), 2006. Solomon Islands Marine Assessment: Technical report of survey conducted May 13 to June 17, 2004. TNC Pacific Island Countries Report No. 1/06. Grothmann, T., Patt, A., 2005. Adaptive capacity and human cognition: the process of individual adaptation to climate change. Global Environmental Change 15, 199–213. Gunderson, L., Holling, C.S., 2002. Panarchy: Understanding Transformations in Human and Natural Systems. Island Press, Washington, D.C., USA. Hay, J., Mimura, N., 2006. Supporting climate change vulnerability and adaptation assessment in the Asia-Pacific region: an example of sustainability science. Sustainability Science 1, 23–35. Heyd, T., Brooks, N., 2009. Exploring cultural dimensions of adaptation to climate change. In: Adger, N., Lorenzoni, I., O’Brien, K. (Eds.), Adapting to climate change, Thresholds, Values, Governance. Cambridge University Press, Cambridge. Holling, C.S., 1973. Resilience and stability of ecological systems. Annual Review of Ecology and Systematics 4, 2–23. Janssen, M., Ostrom, E., 2006. Resilience, vulnerability, and adaptation: a crosscutting theme of the International Human Dimensions Programme on Global Environmental Change. Global Environmental Change 16, 237–239. Kallstrom, H.N., Ljung, M., 2005. Social sustainability and collaborative learning. Ambio 34, 376–382. Kinsey, B., Burger, K., Gunning, J., 1998. Coping with drought in Zimbabwe: survey evidence on responses of rural households to risk. World Development 26, 89–110.
1139
Knutson, T.R., Tuleya, R.E., 2004. Impact of CO2-induced warming on simulated hurricane intensity and precipitation: sensitivity to the choice of climate model and convective parameterization. Journal of Climate 17, 3477–3495. Macintyre, M., Foale, S., 2004. Global imperatives and local desires: competing economic and environmental interests in Melanesian communities. In: Lockwood, V. (Ed.), Globalisation and Culture Change in the Pacific Islands. Pearson Prentice Hall, Upper Saddle River, New Jersey, pp. 149–164. McDowell, C., de Haan, A., 1997. Migration and sustainable livelihoods: a critical review of the literature. IDS Working Papers 65, Brighton: University of Sussex Institute of Development Studies. McLaughlin, P., Dietz, T., 2007. Structure, agency and environment: toward an integrated perspective on vulnerability. Global Environmental Change 39, 99–111. Maddala, G.S., 1992. Introduction to Econometrics, 2nd edn. Macmillan. Miller, F., Osbahr, H., Boyd, E., et al., 2010. Resilience and vulnerability: complementary or conflicting Concepts? Ecology and Society 15 (3) 11 (online). http:// www.ecologyandsociety.org/vol15/iss3/art11/. Mills, D., Be´ne´, C., Ovie, S., et al., 2011. Vulnerability in African small-scale fishing communities. Journal of International Development 23, 308-313 (online). doi:10.1002/jid.1638. Molea, T., Vuki, V., 2008. Subsistence fishing and fish consumption patterns of the saltwater people of the Lau Lagoon, Malaita, Solomon Islands: a case study of Funa’afou and Niuleni islanders. SPC Women in Fisheries Bulletin 18, 30–35. Nash, W., Ramofafia, C., 2006. Recent developments with the sea cucumber fishery in Solomon Islands. SPC Beˆche-de-mer Information Bulletin 23, 3–4. Nunn, P.D., 2003. Nature-society interactions in the Pacific islands. Geografiska Annaler 85B, 219–229. Nunn, P.D., 2004. Through a mist on the ocean: Human understanding of island environments. Tijdschrift voor Economische en Sociale Geografie 95, 311–325. Nurse, L., McLean, R., Suarez, A., et al., 1998. Small islands states. In: Watson, T., Zinyowera, M., Moss, R. (Eds.), The Regional Impact of Climate Change: An Assessment of Vulnerability. Cambridge University Press, Cambridge, pp. 333–354. Nye, M., Burgess, J., 2008. Promoting durable change in household waste and energy use behaviour. A research report completed for the Department for Environment. In: Food and Rural Affairs, School of Environmental Sciences, University of East Anglia, Norwich, UK. O’Brien, K., 2009. Do values subjectively define the limits to climate change adaptation? In: Adger, W.N., Lorenzoni, I., O’Brien, K. (Eds.), Adapting to Climate Change: Thresholds, Values, Governance. Cambridge University Press, Cambridge, pp. 164–180. O’Brien, K., Wolf, J., 2010. A value-based approach to vulnerability and adaptation to climate change. Climate Change 1(2) (online). doi:10.1002/wcc.30. Olsson, P., Carpenter, S., Gunderson, L., et al., 2005. Shooting the rapids: navigating transitions to adaptive ecosystem governance. Ecology and Society 11 (1), 18 (online). http://www.ecologyandsociety.org/vol11/iss1/art18. Osbahr, H., Twyman, C., Adger, W.N., et al., 2008. Effective livelihood adaptation to climate change disturbance: scale dimensions of practice in Mozambique. Geoforum 39, 1951–1964. Prange, J.A., Schwarz, A., Tewfik, A., 2009. Assessing needs and management options for improved resilience of fisheries-dependent communities in the earthquake/ tsunami impacted Western Solomon Islands, p. 36. WorldFish Center Report. Reenberg, A., Birch-Thomsen, T., Mertz, O., et al., 2008. Adaptation of Human Coping Society in Small Island Society in the SW Pacific—50 years of change in the coupled human–environment on Bellona, Solomon Islands. Human Ecology 36, 807–819. Roumasset, J., Boussard, J., Singh, I., 1979. Risk, Uncertainty and Agricultural Development. Agricultural Development Council, New York. Ruddle, K., Hviding, E., Johannes, R.E., 1992. Marine resources management in the context of customary marine tenure. Marine Resource Economics 7, 249–273. Salas, S., Bjørkan, M., Bobadilla, F., et al., 2010. How fishers cope with vulnerability: a Mexican case study. In: Paper presented at the 9th Conference of the International Institute for Fisheries Economics and Trade, July Montpellier France. Shahbaz, B., 2008. Risk, vulnerability and sustainable livelihoods: insights from Northwest Pakistan. Project report series No.13, Sustainable Development Policy Institute, Islamabad Pakistan, p. 20. Schipper, E.L., Dekens, J., 2009. Understanding the role of culture in determining risk from natural hazards. Earth and Environmental Science 6 (57) (online). doi:10.1 088/1755-1307/6/57/572010. Schwarz, A., 2009. Solomon Islands – Fisheries Livelihoods Recovery Project. The WorldFish Center Solomon Islands. Project Completion Report to NZAID. Schwarz A., Ramofafia C., Bennett G., et al., 2007. After the earthquake: An assessment of the impact of the earthquake and tsunami on fisheries-related livelihoods in coastal communities of Western Province, Solomon Islands, Report to the Solomon Islands Ministry of Fisheries and Marine Resources, the WorldFish Center and WWF-Solomon Islands Programme, p. 82. Smit, B., Wandel, J., 2006. Adaptation, adaptive capacity and vulnerability. Global Environmental Change 16, 282–292. Spaargaren, G., van Vliet, B., 2000. Lifestyle, consumption and the environment: the ecological modernization of domestic consumption. Society and Natural Resources 9, 50–76. Sulu, R., Hay, C., Ramohia, P., et al., 2000. The status of Solomon Islands’ coral reefs. A report prepared for the Global Coral Reef Monitoring Network, p. 59. Thomas, D.S.G., Twyman, C., Osbahr, H., et al., 2007. Adapting to climate change and variability in southern Africa: farmer responses to intra-seasonal precipitation trends. Climatic Change 83, 301–322.
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A.-M. Schwarz et al. / Global Environmental Change 21 (2011) 1128–1140
Tschakert, P., 2007. Views from the vulnerable: perceptions on climatic and other stressors in the Sahel. Global Environmental Change 17, 381–396. Turner, R.A., Cakacaka, A., Graham, N.A.J., et al., 2007. Declining reliance on marine resources in remote South Pacific societies: ecological versus socio-economic drivers. Coral Reefs 26, 997–1008. USGS, 2007. Earthquake Hazard Program (online). http://earthquake.usgs.gov/ earthquakes/eqinthenews/2007/us2007aqbk/ (accessed 15.10.10). Veitayaki, J., 1997. Traditional marine resource management practices used in the Pacific Islands: an agenda for change. Ocean and Coastal Management 37, 123–136. Veron, J.E.N., Devantier, L.M., Turak, E., et al., 2009. Delineating the Coral Triangle. Galaxea, Journal of Coral Reef Studies 11, 91–100. Walker, B., Carpenter, J., Anderies, N., et al., 2002. Resilience management in socialecological systems: a working hypothesis for a participatory approach. Conservation Ecology 6 (1), 14 (online). http://www.consecol.org/vol6/iss1/art14.
Walker, B., Holling, C.S., Carpenter, S.R., et al., 2004. Resilience, adaptability and transformability in social-ecological systems. Ecology and Society 9(2), 5 (online). http://www.ecologyandsociety.org/vol9/iss2/art5. Walker, B., Sayer, J., Andrew, N.L., et al., 2010. Should enhanced resilience be an objective of natural resources management research for developing countries? Crop Science 50, 10–19. Warner, B., 2007. Smallholders and rural growth in Solomon Islands. Pacific Economic Bulletin 22 (3), 63–80. Weber, E.U., 2010. What shapes perceptions of climate changes? Climate Change 1 (3), 332–342 doi:10.1002/wcc.41. World Bank, 2006. At Home and Away: Expanding job opportunities for Pacific islanders through job mobility, World Bank, Washington, DC. World Bank, 2008. World Development Indictors (online). http://www.google.com/ publicdata?ds=wb-wdi&met=sp_pop_grow&idim=country:SLB&dl= en&hl=en&q=solomon+islands+population+growth+rate.
