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Resource perception, livelihood choices and fishery exit in a Coastal Resource Management area
Ocean & Coastal Management 71 (2013) 326e333
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Ocean & Coastal Management journal homepage: www.elsevier.com/locate/ocecoaman
Resource perception, livelihood choices and fishery exit in a Coastal Resource Management area Matthew J. Slater a, *, Faith A. Napigkit b, Selina M. Stead a a b
School of Marine Science & Technology, Newcastle University, Ridley Building, Claremont Road, Newcastle Upon Tyne, Tyne and Wear NE1 7RU, United Kingdom Fishery Section, City Agriculture Office, Bayawan City, Negros Oriental, Philippines
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 23 November 2012
Effective measures to reduce fishing pressure require understanding of livelihood strategies and fishers’ decisions to exit or stay in a fishery. Face-to-face semi-structured interviews were conducted with 85 municipal and small-scale commercial fishers within the Bayawan Coastal Resource Management (CRM) area in the Philippines. Fishers rated management measures, perceived changes in overall catch and finfish abundance, and were asked their expectations regarding future changes in finfish abundance. They also estimated their likelihood of exiting the fishery under theoretical catch reduction scenarios. Less than half of fishers would exit the fishery if catch halved. Binary logistic regression showed that negative perceptions of future finfish abundance significantly explained increased likelihood of exiting the fishery (z ¼ 2.606, df 1, p < 0.05) and that increased livelihood diversity weakly supported staying in the fishery (z ¼ 1.818, df 1, p ¼ 0.069). Although stock management measures enjoy strong support in the studied area, fishers are most likely to exit fisheries when they consider stocks to be in continuing decline rather than sustainably managed. Increasing livelihood diversity reduced fishery exit likelihood as alternative livelihoods supplement and complement otherwise non-viable fishing. Results indicate incorrectly targeted livelihood diversification measures aimed at reducing fishing effort may achieve the opposite of their intended effect. If alternative livelihood options are to be viable and effective in reducing fishing pressure these must be attractive to fishers identified as willing to exit the fishery, and by their nature or conditions pre-require foregoing of fishing activities. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Coastal zone management plans and coastal resource management, including measures aimed at controlling fishing effort, are seen by governments worldwide, as key to sustaining fishery resources (Allison and Ellis, 2001; Tobey and Torell, 2006; Muallil et al., 2011; Pomeroy, 1991, 2010). Alongside the need to gain support amongst stakeholders, the ability of such plans to improve resource health status through reduced fishing pressure is considered a primary measure of their success (Smith et al., 2006; Andalecio, 2010). Yet, despite decades of targeted management efforts, most fisheries remain fully or over exploited, with considerable implications not only for specific fisheries, but also entire marine ecosystems and the human communities dependent on them (FAO, 2010; Pauly et al., 2000; Christensen et al., 2003; Eagle and Thompson, 2003; Perry et al., 2011). Management measures to reduce fishing pressure have developed over time from physical * Corresponding author. Tel.:þ441912225091. E-mail address: [email protected] (M.J. Slater). 0964-5691/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ocecoaman.2012.11.003
intervention (marine protected areas, regulation of effort and gear types), through yield efforts aimed at improving fishing efficiency (optimisation or provision of gear), to more recent approaches which address the influence of complex social and economic interactions in fisher’s resource use and associated dependence (Pomeroy, 1991; Smith et al., 2006; Eagle and Thompson, 2003; Allison et al., 1998; Lowry et al., 2005; Linkov et al., 2006; Cinner and Pollnac, 2004). In developing and developed nations, fishery exit, that is, fishers no longer fishing, is increasingly encouraged as a way of reducing fishing pressure (Allison and Ellis, 2001; Tobey and Torell, 2006; Muallil et al., 2011). Existing management measures in coastal communities include providing alternative livelihoods to fishers or offering direct compensation to encourage exit from fisheries (Allison and Ellis, 2001; Tobey and Torell, 2006; Muallil et al., 2011). However, fishers respond in a variety of ways to such measures, and to changes in the environmental and socio-economic conditions surrounding their fishing activities. In declining fisheries, decisions to exit the fishery can ameliorate negative impacts on the resource. Conversely, decisions to remain in a declining fishery or increase
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fishing effort can intensify impacts and result in negative feedbacks (Perry et al., 2011; Cinner et al., 2010). Fishers caught in povertytraps are generally subject to reduced mobility of resources, may lack education or skills to adapt, are increasingly unlikely to be able to alter livelihoods, and often increase efforts to obtain income through fishing (Jentoft and Midré, 2011; Cinner et al., 2008; Cabral and Alino, 2011). Understanding drivers to promote fishers in coastal communities to exit declining fisheries is central to improving future efficacy of coastal management. Most fishers are reluctant to abandon fishing even under difficult social and economic situations. A recent study of 141 Kenyan fishers reported that they were unlikely to exit the fishery, even at hypothetical catch reductions of 50% (Cinner et al., 2008; Ikiara and Odink, 2000). Similarly, Filipino fishers were unlikely to exit the fishery in drastically reduced theoretical yield scenarios and were evenly split over abandoning fishing, even when offered compensation payments equal to current fishing income (Muallil et al., 2011). Positive associations with fishing may reduce exit willingness as fishing can provide sense of economic independence and the chance of large periodic or seasonal windfalls (Smith and Hanna, 1993; Meynen, 1989). High levels of investment in fishing assets which cannot be quickly or easily sold can also bind fishers to the industry (Ikiara and Odink, 2000). Equally fishing can provide a sense of community, family status, tradition and belonging along with enjoyment and ‘easy job’ in many fisher’s opinions (Pollnac et al., 2001). The complexity of factors affecting fishery exit is influenced by governance structures impacting fisher’s decision-making at different scales, e.g., community, national and international levels (Daw et al., 2012). At a community level studies have revealed potential indicators and drivers predicting fishers’ willingness to exit fisheries. Socioeconomic modelling has previously indicated that increasing wealth and increasing number of livelihoods at the household level positively influence exit choices among fishers (Cinner et al., 2008). In contrast in fisheries in developed nations, constructed social models identify factors such as ‘perceived excessive fishing fleet size’ or ‘competition on behalf of fishers’ as driving willingness to leave a fishery; direct economic models base calculations of likelihood to exit primarily on the income obtained and costs incurred in fishing activities, including factors such as long-term capital investment in vessels or gear (Ward and Sutinen, 1994; Pradhan and Leung, 2003). Livelihood diversification is commonly viewed as a management option for reducing fishing effort and offering poverty alleviation (Allison and Ellis, 2001; Tietze et al., 2000; Andersson and Ngazi, 1998). There is some evidence to show some fishers from households with diverse livelihoods and are more likely to reduce fishing effort and consider exiting a fishery (Tobey and Torell, 2006; Muallil et al., 2011; Cinner et al., 2008; Wells et al., 2010). Conversely, income from alternative livelihoods may be reinvested in activities which increase fishing effort and pressure (Sievanen et al., 2005), thus it is possible that a higher level of livelihood diversity effectively allows for fishing efforts to be continued by subsidising fishers who would otherwise not function on fishing alone. Highly diversified fishers households maybe empowered to exert continued fishing pressure by livelihood diversification driving uneconomic fisheries into deleterious decline (Allison and Ellis, 2001; Andersson and Ngazi, 1998; Sievanen et al., 2005). These complications and interactions have led to suggestions that co-payments or measures to encourage fishery exit are required, especially for targeting fishers already inclined to exit (Muallil et al., 2011). However, these may also be equally erroneous or ineffective if not applied in a manner which takes into account the complex socialeecological and socioeconomic interactions (Muallil et al., 2011; Berkes et al., 2001).
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The Philippines is a marine biodiverse archipelago nation and a hotspot for marine conservation with more than 1.3 million impoverished local or “municipal” fishers. Declines of marine fisheries and destruction of marine habitats have forced management changes and driven current and increasing interest in encouraging fishery exit (Muallil et al., 2011; BoFa-. Philippines, 2009; Courtney and White, 2000; Christie and White, 2007). A long history of community-based coastal management and innovations in terms of managing its fishery resources has seen development from a community-based approach in the 1980s to comanagement in the 1990s to integrated management and governance in the form of coastal resource management (CRM) (Pomeroy, 1991, 2010, 2007). Measures in CRM include alternative livelihood provision along with empowering fishers and local government to take an active role in the management of coastal resources (Lowry et al., 2005). Efficacy of coastal fisheries management has been linked to fishers’ empowerment, their awareness of resource management measures, resource users’ perception of the sensibility of measures taken and resource users’ participation in the management process (Andalecio, 2010; Courtney and White, 2000). However, recent research has shown that CRM initiatives in Asia, Latin America and the Caribbean have seldom provided tangible benefits to fishers in terms of improvements in catch or quality of life (Maliao et al., 2009; Olsen, 2002). It remains unclear whether fishers believe that CRM plan measures have the capacity to effectively guarantee coastal livelihoods or stem fishery decline. Evidence of perceptions on success of management measures can be a useful indicator for determining support by those impacted which can influence level of compliance with regulations or achievement of management goals. This paper investigates drivers underpinning individuals’ willingness to exit a fishery by gauging fishers’ opinions in seven villages within an area with a 15-year CRM history and impacted by declining fisheries. The study investigates effects of demographic, social, economic and environmental variables influencing fishers’ lives and their decision making. The main aim is to show how fishers’ perceptions and livelihood choices influence willingness to exit a fishery and to inform effective measures to encourage fishery exit. 2. Methods 2.1. Study site Bayawan is a coastal city in Negros Island, Philippines covering 69,000 ha with a population of 110,000. The city has 15 km of coastline in Tolong Bay and seven coastal villages constituting 4% of its land area. There are 225 km2 of municipal waters with an average depth of around 91 m (City LGUo, 2001e2005). Bayawan manages one of the highest yield fishing grounds of the province and has been identified as part of the migration path of yellowfin tuna (Thunnus albacares). The main fishing season is from November to May, which coincides with the northeast monsoon. Commercial fishermen from other provinces historically fished heavily in Bayawan’s municipal waters, contributing to the decline of the city’s fishery resources. Bayawan became a pilot project of the Coastal Resource Management Project (CRMP), an initiative of the Philippine Government which started in 1996 (Pomeroy et al., 1997). In the year 2000, CRMP together with the Martin “Ting” Matiao Foundation assisted the city’s technical working group in formulating the 2001e2005 CRM Plan. The focus area of the plan is the seven coastal villages of Bayawan: Villareal, Tinago, Boyco, Suba, Banga, Malabugas and Pagatban (Fig. 1) which form the study sites for the work presented herein.
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Fig. 1. The Coastal Resource Management zones of Bayawan City, Philippines showing coastal villages. Source: Bayawan City Coastal Resource Management Plan 2001e2005.
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2.2. Data collection e fishers’ survey A semi-structured questionnaire was developed and piloted with four fishers (one from each user group defined below) to ensure questions were clear and understandable, questions were adjusted as required. Resource-users were interviewed between April and June 2010. Interviewees were defined as follows: municipal fishers (small boat fishers e equally split between members of cooperatives and non-members) who use motorized fishing boats of 3 gross tons and less, municipal fishers engaged in the collection of wild milkfish (Chanos chanos) fry (fry collectors), and commercial fishermen using fishing vessels of less than 20 gross tons (Table 1). A total of 85 fishers were interviewed using opportunistic sampling representing between 30 and 50% of the total number of each fisher type within the CRM zone. The questionnaire consisted of 54 questions divided into 10 sections. Twenty-seven variables were gathered and grouped into four categories: socioeconomic, ecological, attitudinal, and awareness and participation. Municipal fishers and fry collectors rated the level of successful implementation of the 10 CRM program objectives using a 5-point Likert scale (1- Poor, 2- fair, 3- Satisfactory, 4Good and 5- Excellent). Commercial fishers did not rate CRM measures because they do not (legally) fish within the municipal waters of Bayawan and did not exhibit high levels of awareness of the CRM program. All fishers were asked what action they would take in response to sustained reductions in catch of 20% or 50%. 2.3. Statistical analysis KolmogoroveSmirnov and Levene’s tests were applied to each tested category to ensure normality of distributions and homogeneity of variances respectively. Mean scores on the Likert scale for implementation of individual CRM objectives were calculated for each objective. A one sample t-test was used to compare the mean of individual objectives with a minimum expected value (for the objective to be considered successfully implemented) of 3.5. Where applicable, chi-squared tests were applied to data in order to isolate differences in response type frequency by respondent type. The binary (dichotomous) variable ‘decision to remain in or exit the fishery at 50% catch reduction’ (response options exit fishery/ remain in fishery) was recorded as fishers’ choice as to whether they would either continue fishing or would exit the fishery in the case of a theoretical 50% reduction in catch. Binary logistic regression was used to model ‘decision to remain in or exit the fishery at 50% catch reduction’ as the dependent (left-hand side) variable. Hypothesised explanatory (right-hand side) variables were selected based on literature review and exploratory chi-squared tests. The following explanatory (right-hand side) variables were
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chosen as potential predictors or response to ‘decision to remain in or exit the fishery at 50% catch reduction’: Respondent age; perceived fish abundance in 5 years; perceived current fish abundance (compared to 5 years ago); number of years fishing; catch change over last 5 years; awareness of CRM plan; type of fisher (Fry, Municipal, Commercial); livelihood diversity (defined as number of different livelihoods in a household); catch value (Philippine Peso); household size (total number of inhabitants); Rank of importance of fishing as proportion of household income (‘1’ as most important e Table 2). In the modelling process, exploratory backwards conditional binary logistic regression, an initial model containing all proposed explanatory variables is created and individual variables with the least significant influence on the distribution of dependent variable are removed stepwise from the current model. Stepwise removal and recalculation of the model produces the most parsimonious final model retaining only variables having a significant effect on response distribution. 3. Results 3.1. Fishing community demographics Interviews were conducted with 68 male and 17 female fishers ranging from 20 to over 70 years of age. Eight percent of fishers interviewed were 20e30 years old. All others were aged 31 years or older, with the largest group of respondents being within the 41e50 range. Fishing experience ranged from 10 to more than 40 years. Mean household size (adults and children) was 5.11 (1.99 SD) and most fishers’ households had three to five different occupations. Fishing was ranked as the most important household economic activity by 91% of fishers. Of the 85 fishers interviewed, 30 had had jobs in the last five years which they considered more important household economic activities than fishing. Of these, 73% said that they prefer fishing over the other occupation (Table 1). 3.2. Support for and awareness of management measures Commercial fishers (40% aware) were significantly less likely (chi2 ¼ 6.7, p < 0.01) to be aware of the Coastal Resource Management (CRM) plan than municipal fishers (organisation members e 80% aware), municipal fisher (organisation nonmembers e 65% aware) or fry fishers (77% aware) (Table 1). More than half of municipal fishers (organisation members 70%) and half of the fry fishers (50% participation) participated in the formulation of the CRM plan, while only 30% of municipal fisher (organisation non-members) and 27% of commercial fishers were involved (Table 1). Municipal fishers who were members of fishers’ organisations were more aware of the CRM plan (80%) and participant in
Table 1 Sample representative coverage, plan awareness and community participation in planning, awareness and support of regulations across fisher type and fishers’ organisation membership.
Number fishers interviewed/total number fishers per user group Awareness of the CRM Plan Awareness of City Fisheries and Aquatic Resources Management Council Participation in public consultations on fishery matters Participation in the annual fisherfolk day Participation in formulation of the CRM plan Awareness of regulations Do not support regulations Marine reserves acceptable a
Municipal fishers (organization members)
Municipal fishers (non-members)
Fish fry collectors
Commercial fishers
20/54 (37%) 16/20 (80%) 19/20 (95%)
20/40 (50%) 13/20 (65%) 9/20 (45%)
30/93 (32%) 23/30 (77%) 25/30 (83%)
15/30 (50%)a 6/15 (40%) 4/15 (27%)
14/20 16/20 14/20 18/20 0/20 19/20
11/20 14/20 6/20 20/20 0/20 16/20
23/30 22/30 15/30 27/30 1/30 24/30
8/15 3/15 4/15 15/15 0/15 15/15
(70%) (80%) (70%) (90%) (0%) (95%)
Group response distribution differs significantly from all other groups (chi2 ¼ 6.7, p < 0.01).
(55%) (70%) (30%) (100%) (0%) (80%)
(77%) (73%) (50%) (90%) (3%) (80%)
(54%) (20%) (27%) (100%) (0%) (100%)
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Table 2 Categorical variable counts and means of non-categorical variables of hypothesised explanatory (right-hand side) variables for binary logistic model to explain ‘decision to remain in or exit the fishery at 50% catch reduction’. The model and categorical variables exclude interviews with incomplete sets of variables. Categorical variables
Category
Frequency all fishers
Frequency municipal/ fry fish.
Age
Non-categorical variables
Below 35 35e50 50 and above Less Same or more 0e25 25e40 Less Same or more Less Same or more Local fisher Milkfish fry trawler Commercial fishers Yes No Mean SD
18 49 13 45 35 51 29 54 26 58 22 36 29 15 54 26 Min
15 40 10 27 28 40 25 47 18 49 16 36 29 0 48 17 Max
Livelihood diversity Rank importance fishing Catch value (Philippine Peso) Household size
3.22 (1.07) 1.16 (0.55) 30,0154 (67,319) 5.11 (1.99)
1 1 40 1
5 4 264,000 12
(Predicted) fish abundance in 5 years Years fishing Catch change over last 5 years Fish abundance compared to 5 years ago Fisher type/occupation
Awareness of CRM Program
public consultations (70%) than non-members (65% and 55% respectively e Table 1). Awareness of key fisheries regulations was similar among interviewees with only 6% of all fishers stating they were not fully aware of the regulations. Amongst all respondents only one fry fisher stated that they did not support fishery regulations. The establishment of marine reserves was acceptable to more than 80% of fishers interviewed across all groups (Table 1). Local fishers’ and fry collectors’ ratings of the level of successful implementation of CRM program objectives ranged from means of 3.5 (0.15 SEM) to 4.3 (0.11 SEM, Table 3). The mean values of individual objectives 1, 2, 3, 5, 8 and 10 (Table 3) differed significantly (one-sample t-test, p < 0.05) from (above) the minimum value of 3.5 (satisfactory). Objectives 4, 6, 7 & 9 did not differ significantly (one-sample t-test, p > 0.05) from the minimum value Table 3 Fishing community demographics all respondents. Variable
Response category
Number of responses (N)
Percentage of responses (%)
Gender
Male Female 20e30 31e40 41e50 51þ 10e20 21e30 31e40 40þ Fishing Farming Salaried employ. Inform. econ. act. Yes No Yes No 1 2 3 4 5
68 17 7 25 38 15 39 24 12 10 77 3 4 1 30 55 8 22 6 12 35 21 11
80.0 20.0 8.2 29.4 44.7 17.6 36.9 28.2 14.1 11.8 90.6 3.5 4.7 1.2 35.3 64.7 26.7 73.3 7.1 14.1 41.2 24.7 12.9
Age (years)
Fishing experience (years)
Primary economic activity
Other main economic activity in past 5 years? Prefer past economic activity to fishing? Number of household occupations
of 3.5 (satisfactory). The lowest ranking among all fishers was objective 9, the provision of alternative livelihoods (3.5 0.15 SEM). 3.3. Resource state perceptions and fishery exit Seventy-two percent of all fishers responded that they perceived lower current abundance of fish in the sea compared to 5 years ago and 53% said they expected fish abundance to be lower in five years (Table 4). Fry collectors were significantly more likely than all other groups to respond that their catch was lower now than five years ago and that they perceived lower current fish abundance (Chi2 ¼ 18.6, p < 0.001; Chi2 ¼ 7.6, p < 0.05 respectively e Table 4). Local members of fishing organisations were significantly more likely than non-members to respond that they perceived lower current fish abundance, that their catch was lower now than five years ago, and that they believed there would be lower future fish abundance in five years (Chi2 ¼ 5.5, p < 0.05; Chi2 ¼ 13.5, p < 0.001; Chi2 ¼ 4.4, p < 0.05 respectively e Table 4). When proposed theoretical catch reduction scenarios, 75% of municipal fishers, 60% of fry collectors and 53% of commercial fishers stated they would continue to fish even if the catch were to drop by 50% (Fig. 2A). Half of all fishers with only one household occupation would exit the fishery whereas less than 25% of fishers with 4 or more household occupations would exit the fishery (Fig. 2B). Only 12% of all fishers would exit the fishery in the case of a theoretical 20% drop in catch (Fig. 2B). Binary logistic regression analysis, conducted to predict ‘likelihood of exiting the fishery at 50% catch reduction’, for all fishers resulted in a model which differed significantly from the constant only model (Chi2 ¼ 9.9, p < 0.01, df ¼ 2) indicating that the retained predictors (RHS variables) reliably distinguished between those who would exit the fishery and those who would remain. Analysis of retained predictors in the final model revealed perceived fish abundance in five years as the single significant predictor of “likelihood of exiting the fishery at 50% catch reduction” for all fishers (z ¼ 2.606, df ¼ 1, p < 0.05). Number of different occupations was retained in the exploratory model for all fishers (z ¼ 1.818, df ¼ 1, p ¼ 0.069) with increased livelihood diversity at the household level weakly supporting staying in the fishery (Table 5). Binary logistic regression analysis, conducted to predict ‘likelihood of exiting the fishery at 50% catch reduction’, for all municipal fishers and fry collectors resulted in a model which also differed significantly from the constant only model (Chi2 ¼ 7.7, p < 0.05, df ¼ 2) indicating that the retained predictors (RHS variables) reliably distinguished between those who would exit the fishery and those who would remain. Among all municipal fishers and fry collectors, perceived fish abundance in five years was the single significant predictor of “likelihood of exiting the fishery at 50% catch reduction” (z ¼ 2.238, df ¼ 1, p < 0.05, Table 5) with retention of number of different occupations in the final model weakly supporting staying in the fishery (z ¼ 1.627, df ¼ 1, p ¼ 0.104, Table 5). 4. Discussion The current study shows fishers who are pessimistic about present and future fish abundance are significantly less reluctant to abandon fishing. Equally results reveal that fishers from households with increasing numbers of different livelihoods exhibited decreasing likelihood of exiting the fishery e in direct contrast with similar studies (Muallil et al., 2011; Cinner et al., 2008). Furthermore, fishers interviewed support and participate in CRM measures but do not perceive current or future benefits from management measures. While adding to the widely acknowledged view that fishers are reluctant to exit fisheries and that the factors influencing decisions fishers make are complex and varied, this study
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Table 4 Distribution of responses regarding perception of current and future fish abundance and change in catch over the past five years e responses separated by fisher respondent type. Municipal fishers (org. members) Abundance of fish in the sea compared to 5 years ago Predicted abundance of fish in the sea in five years Change in catch over the past five years
Less More/same Less More/same Less More/same
14 6 10 7 13 7
(70%)b (30%) (59%)b (41%) (65%)b (35%)
Municipal fishers (non-members)
Fish fry collectors
11 9 7 12 8 12
27 3 20 9 29 1
(55%) (45%) (37%) (64%) (40%) (60%)
(90%)a (10%) (69%) (31%) (97%)a (3%)
Commercial fishers
All fishers (total)
9 6 8 7 7 8
61 24 45 35 57 28
(60%) (40%) (54%) (46%) (46%) (54%)
(72%) (28%) (56%) (44%) (67%) (33%)
a
Group response distribution differs significantly from all other groups (chi2 ¼ 7.6, p < 0.05- Abundance; chi2 ¼ 18.6, p <0.001 - catch change). Group response distribution differs significantly from non-organisation members (Chi2 ¼ 5.5, p < 0.05- Abundance; Chi2 ¼ 4.4, p < 0.05 - future abundance; Chi2 ¼ 13.5, p < 0.001 - catch change). b
highlights specific recommendations for management intervention that can be considered by managers and policy makers (Daw et al., 2012). These are discussed in terms of their implications for CRM plans and specifically within the context the role for alternative livelihood measures in promoting fishery exit. The CRM plan in Bayawan City can be considered a success and a failure, contingent on the chosen measure examined (Andalecio, 2010; Maliao et al., 2009; Olsen, 2002). The CRM plan is successful in the sense that the majority of fishers expressed support for management measures in place and there is high awareness among targeted municipal fishers regarding fishery plan formulation. Efforts to involve stakeholders in the development and implementation of the plan have also been broadly successful. However, the CRM plan has not yet led to tangible benefits, in terms of stemming fishery decline, to fishers who support it or otherwise.
A 100% Proportion fishers
90% 80% 70% 60% 50%
Remain
40%
Exit fishery
30% 20% 10% 0% 1
B
2
3
4
5
Number of different household occupations
Table 5 Binary logistic regression results for factors explaining ‘decision to remain in or exit the fishery at 50% catch reduction’. Results for all fishers and all municipal fishers and fry collectors. Includes goodness of fit and model summary.
100% 90% 80%
Proportion fishers
The majority of fishers reported continuing reductions in catch and considered current health of remaining fisheries resources poor (Maliao et al., 2009; Olsen, 2002). The members of fishing organisations and fish fry collectors most involved in management decisions appear to be more aware of and/or pessimistic about stock and catches. The majority of CRM participants stated the measures are not effectively protecting future fisheries as evidenced by their expectations of future stocks. There may be an increasing risk to participation in measures and the near universal support of fishers when no tangible benefits are seen to arise from the plan. Based on estimates of past changes in catch and current and future stocks, the majority of fishers are convinced that fisheries exist solely in decline. If fishers perceived as likely or even inevitable the hypothetical 50% in reduction in catch (as evidence by their estimates of future stocks), they are significantly more likely to exit the fishery. This may imply many fishers who stated they will not leave the fishery were unable to relate themselves to the hypothetical scenario rendering their responses to the question invalid (Speight et al., 2009). Alternatively, conviction that future fish abundance will decline is a primary driver to fishery exit among commercial and municipal fishers. Those individuals who retain “hope” of stable or strong stock in future, despite majority attestation to past reductions in catch and abundance, are less likely to exit the fishery in the future. Members of fishers’ organisations who frequently exchange information and receive stock and catch data from the municipal authority are significantly more likely to expect future abundances to be low. If fishery exit is desirable, providing existing and projected catch data to fishers may result in more realistic expectations of future catches, in turn further increasing the large majority of fishers convinced that
Variables in the equation
70% 60% 50% 40%
Remain
30%
Exit fishery
20% 10%
Fishers
Factor
All fishers
Fish abundance in 5 years Livelihood diversity Fish abundance in 5 years Livelihood diversity
Municipal/fry fishers
Coefficient
S.E.
z-value
df
p-value
1.418
0.544
2.606
1
0.009
0.449 1.388
0.247 0.620
1.818 2.238
1 1
0.069 0.025
0.420
0.258
1.627
1
0.104
Hosmer and Lemeshow test (GoF)
0% Municipal fishers
Fry fishers
Commercial fishers
All fishers 20% reduction
Fisher type / Reduction type Fig. 2. A: Distribution of responses of all fishers to theoretical catch reductions scenarios of 50% displayed as a function of number of household occupations. B: Distribution of responses of fishers to theoretical catch reductions scenarios of 50% displayed as a function of fisher type and distribution of responses of all fishers to theoretical catch reductions scenarios of 20%.
All fishers Municipal/fry fishers
Step
Chi2
df
Sig.
10 10
6.090 4.496
6 6
0.413 0.610
Model summary Step 2 Log likelihood Cox & Snell R2 Nagelkerke R2 All fishers 10 93.690 0.116 0.160 Municipal/fry fishers 10 74.081 0.112 0.156
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future abundance will decrease. In addition, targeting alternative livelihood provision to those willing to exit, on the basis of their conviction that; a) stocks will continue to decline and; b) low current livelihood diversity, among other selection criteria, would allow efficient application of resources (Muallil et al., 2011). Despite participatory CRM measures supported by the community and enforced by governing bodies, fishers who perceive the continuing decline of a resource may react by fishing what they can before its demise. In this case the resource will be exploited to biological or economic collapse, with ensuing poverty, if fishers cannot exit the fishery (Hardin, 1968; Bene, 2003). Associated with this scenario is the assumption that fishers do not wish to exit the fishery or that they are increasingly unable to due to a lack of resources or opportunity e further enforcing feedbacks by which negative socioecological interactions lead to further reductions in resource health and fishers’ ability to alter resource exploitation e or a socioecological trap (Steneck, 2009; Folke, 2007; Cinner, 2011; Reardon and Vosti, 1995). Based on the current results regarding perception of fishery and willingness to exit, fishers will become overwhelmingly convinced of the likelihood of further decline and will increasingly decide to exit the fishery e if at all possible. In such a case negative feedbacks can be avoided if resource, opportunity and condign value limitations are overcome in provision of alternative livelihoods. A desirable reduction in fishing pressure, ultimately aiding fishery management efforts, should be strived for through provision of targeted alternative livelihoods preferably providing the income, status and satisfaction of fishing to support the exit of targeted fishers and attract further fishers to exit (Muallil et al., 2011). While in apparent agreement with frequent policy opinion that alternative livelihood provision is contingent with reduction in fishing pressure, the current study shows fishers from households with increasing numbers of different livelihoods exhibited decreasing likelihood of exiting the fishery e in direct contrast with similar studies (Muallil et al., 2011; Cinner et al., 2008). Muallil et al. (2011) specify livelihoods tourism, agriculture and industry amongst fishers in the Philippines. Cinner et al. (2008) provide examples of livelihoods as agriculture and informal economy amongst fishers in Kenya. In the current study non-fishing livelihoods were tourism, agriculture, marketing marine products, selfemployment and salaried employment. While there is little evidence to indicate livelihood options differ greatly from those available to fishers included in the study by Muallil et al. (2011) there may be differences to the value and or type of livelihood available to fishers in the study by Cinner et al. (2008). Nonetheless, the main livelihood classifications are the same across all three studies. Despite potential differences in available alternative livelihoods, this result appears to undermine the argument that alternatives can facilitate fishery exit and reduce fishing pressure. This can be reconciled in noting that those alternative livelihoods considered in the current study are neither preferred over fishing nor are they considered primary income sources e as evidenced in both cases by fishers’ own assertions e whereby 70% of fishers with other jobs in the past five years said they preferred fishing and more than 90% of all fishers considered fishing the most important economic activity of the household. We suggest that existing alternative livelihoods are also not exclusive of continuation of fishing activities and are, by nature or historical development (i.e. to complement fishers’ incomes), specifically chosen not to exclude the option of fishing at individual, household or community level. Existing livelihoods are redundant in their potential role in facilitating fishery exit. In addition to the need for alternative livelihoods to target fishers more likely to exit and providing appropriate income, status and satisfaction, our results indicate that alternative livelihoods must by nature or specification preclude fishing if they are to be effective in reducing fishing effort.
Retention of number of occupations in the final regression model and observed decrease in likelihood to exit the fishery as livelihood diversity increased may rest on the combined effects of two livelihood scenarios. In the case of the more commercial or specialised fishers with a low level of livelihood diversity, fishing is more rapidly abandoned as catch lowers, due to direct economic necessity, thus fitting established bio-economic models that show likelihood to exit as primarily dependent on income obtained and costs incurred in fishing (Ward and Sutinen, 1994; Pradhan and Leung, 2003). Bio-economic models may not apply as rapidly as in developed countries where specialisation and capital loading are comparatively high, they may still apply in developing nations after many years of resource degradation. In fishers households which are less singularly specialised towards fishing and less exclusively economically dependent on fishing, the case for most local fishers in the current study area, fishing is not abandoned as catch lowers because the economic necessity is not as apparent. This is partly explained by remaining livelihoods within the house reducing the economic impact of fishing loss and supporting continued, even deleterious, fishing effort (Sievanen et al., 2005). In developing and emerging nations such as the Philippines, fisheries may be in transition towards increasing commercial specialisation which would ultimately support the former scenario and latter mechanism leading to a bimodality of livelihood diversity responses, whereby specialised small-scale commercial fishers with low livelihood diversity exit declining fisheries and artisanal fishers with higher livelihood diversity do not. 5. Conclusions Consultation and participation are not long-term replacements for viable stocks, acceptable catches or viable alternative sources of income for fishers. Livelihood alternatives are necessary, but these require better specification in the future to support small-scale fishery management by successfully reducing fishing pressure, as indicated herein. Future alternative livelihoods must be targeted at fishers who are identified as most willing to exit the fishery, and offered livelihoods must appeal to economic and intangible values associated with fishing to make them preferable. Livelihood initiatives must directly address the problem that livelihood diversity per se frequently has the opposite effect to that desired/ predicted with regard to fishing pressure reduction in the long term (Allison and Ellis, 2001; Sievanen et al., 2005). To do so alternative livelihoods must be provided with specifications that they form a direct alternative to fishing or should if possible require a specification that fishers cease fishing. The resulting livelihood options are likely to be more strictly scrutinized by fishers before they are accepted, as they are bound to significant foregoing, and will thus be effectively exposed to test-driven development prior to implementation, making them significantly more viable in the long-term due both to depth of acceptance and tested viability. Acknowledgments The authors wish to thank Dr Aileen Mill and Prof Stephen Rushton for modelling advice. We wish to thank the reviewers of this manuscript for constructive and useful suggestions and input. Dr Slater is supported by a Leverhulme Trust Research Project Grant. References Allison, E.H., Ellis, F., 2001. The livelihoods approach and management of smallscale fisheries. Marine Policy 25 (5), 377e388. Allison, G.W., et al., 1998. Marine reserves are necessary but not sufficient for marine conservation. Ecological Applications 8 (1), S79eS92.
M.J. Slater et al. / Ocean & Coastal Management 71 (2013) 326e333 Andalecio, M., 2010. Multi-criteria decision models for management of tropical coastal fisheries. A review. Agronomy for Sustainable Development 30 (3), 557e580. Andersson, J., Ngazi, Z., 1998. Coastal communities’ production choices, risk diversification, and subsistence behavior: responses in periods of transition e a case study from Tanzania. Ambio 27 (8), 686e693. Bene, C., 2003. When fishery rhymes with poverty: a first step beyond the old paradigm on poverty in small-scale fisheries. World Development 31 (6), 949e975. Berkes, F., et al., 2001. The Canadian Arctic and the Oceans Act: the development of participatory environmental research and management. Ocean & Coastal Management 44 (7e8), 451e469. BFAR BoFaAR-. Philippines, 2009. Agriculture Do. Department of Agriculture, Quezon City, p. 66. Cabral, R.B., Alino, P.M., 2011. Transition from common to private coasts: consequences of privatization of the coastal commons. Ocean & Coastal Management 54 (1), 66e74. Christensen, V., et al., 2003. Hundred-year decline of North Atlantic predatory fishes. Fish and Fisheries 4 (1), 1. Christie, P., White, A.T., 2007. Best practices for improved governance of coral reef marine protected areas. Coral Reefs 26, 1047e1056. Cinner, J.E., Pollnac, R.B., 2004. Poverty, perceptions and planning: why socioeconomics matter in the management of Mexican reefs. Ocean & Coastal Management 47, 479e493. Cinner, J.E., et al., 2008. Socioeconomic factors that affect artisanal fishers’ readiness to exit a declining fishery. Conservation Biology 23 (1), 124e130. Cinner, J.E., et al., 2010. Differences in livelihoods, socioeconomic characteristics, and knowledge about the sea between fishers and non-fishers living near and far from marine parks on the Kenyan coast. Marine Policy 34 (1), 22e28. Cinner, J.E., 2011. Social-ecological traps in reef fisheries. Global Environmental Change 21 (3), 835e839. City LGUoB, 2001. Local Government Unit of Bayawan City Coastal Resource Management Plan (2001e2005). Courtney, A.C., White, A.T., 2000. Integrated coastal management in the Philippines: testing new paradigms. Coastal Management 28, 39e53. Daw, T.M., et al., 2012. To fish or not to fish: factors at multiple scales affecting artisanal fishers’ readiness to exit a declining fishery. PLoS One 7 (2). Eagle, J., Thompson, B.H., 2003. Answering Lord Perry’s question: dissecting regulatory overfishing. Ocean & Coastal Management 46 (6e7), 649e679. FAO, 2010. The State of World Fisheries and Aquaculture e 2010 SOFIA. FAO, Department FaA, Rome, p. 218. Folke, C., 2007. Social-ecological systems and adaptive governance of the commons. Ecological Research 22 (1), 14e15. Hardin, G., 1968. The tragedy of the commons. The population problem has no technical solution; it requires a fundamental extension in morality. Science (New York, N.Y.) 162 (3859), 1243e1248. Ikiara, M.M., Odink, J.G., 2000. Fishermen resistance to exit fisheries. Marine Resource Economics 14, 199e213. Jentoft, S., Midré, G., 2011. The meaning of poverty: conceptual issues in small-scale fisheries research. In: Jentoft, S., Eide, A. (Eds.), Poverty Mosaics: Realities and Prospects in Small-scale Fisheries. Springer, Dordrecht, p. 460. Linkov, I., et al., 2006. From comparative risk assessment to multi-criteria decision analysis and adaptive management: recent developments and applications. Environment International 32 (8), 1072e1093.
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Lowry, K., et al., 2005. National and local agency roles in integrated coastal management. Ocean & Coastal Management 48, 314e335. Maliao, R.J., et al., 2009. Performance of Community-based coastal resource management programs in the Philippines: a meta-analysis. Marine Policy 33, 818e825. Meynen, W., 1989. Fisheries development, resources depletion and political mobilization in Kerala: the problem of alternatives. Development and Change 20 (4), 735e770. Muallil, R.N., et al., 2011. Willingness to exit the artisanal fishery as a response to scenarios of declining catch or increasing monetary incentives. Fisheries Research 111, 74e81. Olsen, S.B., 2002. Assessing progress toward the goals of coastal management. Coastal Management 30, 325e345. Pauly, D., Christensen, V., Froese, R., Palomares, M.L., 2000. Fishing down aquatic food webs. American Scientist 88 (1), 46e52. Perry, R.I., et al., 2011. Marine social-ecological responses to environmental change and the impacts of globalization. Fish and Fisheries 12 (4), 427e450. Pollnac, R.B., et al., 2001. Fishery policy and job satisfaction in three southeast Asian fisheries. Ocean & Coastal Management 44, 531e544. Pomeroy, R.S., et al., 1997. Evaluating factors contributing to the success of community-based coastal resource management: the Central Visayas Regional Project-1, Philippines. Ocean & Coastal Management 36, 97e120. Pomeroy, R.S., 1991. Small-scale fisheries management and development e towards a community-based approach. Marine Policy 15 (1), 39e48. Pomeroy, R.S., 2007. Fish wars: conflict and collaboration in fisheries management in Southeast Asia. Marine Policy 31, 645e656. Pomeroy, R.S., 2010. Ecosystem-based fisheries management in small scale tropical marine fisheries: emerging models of governance arrangements in the Philippines. Marine Policy 34 (2), 98e308. Pradhan, N.C., Leung, P., 2003. Modeling entry, stay and exit decisions of the longline fishers in Hawaii. Marine Policy 28, 311e324. Reardon, T., Vosti, S.A., 1995. Links between rural poverty and the environment in developing countries: asset categories and investment poverty. World Development 23 (9), 1495e1506. Sievanen, L., et al., 2005. Weeding through assumptions of livelihood approaches in ICM: seaweed farming in the Philippines and Indonesia. Ocean & Coastal Management 48 (3e6), 297e313. Smith, C.L., Hanna, S.S., 1993. Occupation and community as determinants of fishing behaviours. Human Organization 52 (3), 299e303. Smith, T.F., et al., 2006. Improving the quality of life in coastal areas and future directions for the Asia-Pacific region. Coastal Management 34 (3), 235e250. Speight, J., et al., 2009. Not all roads lead to Rome d a review of quality of life measurement in adults with diabetes. Diabetic Medicine 26 (4), 315e327. Steneck, R.S., 2009. Marine conservation: moving beyond Malthus. Current Biology 19 (3), R117eR119. Tietze, U., et al., 2000. Demographic change in coastal fishing communities and its implications for the coastal environment. FAO Fisheries Technical Paper 403. i. Tobey, J., Torell, E., 2006. Coastal poverty and MPA management in mainland Tanzania and Zanzibar. Ocean & Coastal Management 49 (11), 834e854. Ward, J.M., Sutinen, J.G., 1994. Vessel entry-exit behaviour in the Gulf of Mexico shrimp fishery. American Journal of Agricultural Economics 76 (4), 916e923. Wells, S., et al., 2010. Lessons learnt from a collaborative management programme in coastal Tanzania. Ocean & Coastal Management 53, 161e168.
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Resource perception, livelihood choices and fishery exit in a Coastal Resource Management area Matthew J. Slater a, *, Faith A. Napigkit b, Selina M. Stead a a b
School of Marine Science & Technology, Newcastle University, Ridley Building, Claremont Road, Newcastle Upon Tyne, Tyne and Wear NE1 7RU, United Kingdom Fishery Section, City Agriculture Office, Bayawan City, Negros Oriental, Philippines
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 23 November 2012
Effective measures to reduce fishing pressure require understanding of livelihood strategies and fishers’ decisions to exit or stay in a fishery. Face-to-face semi-structured interviews were conducted with 85 municipal and small-scale commercial fishers within the Bayawan Coastal Resource Management (CRM) area in the Philippines. Fishers rated management measures, perceived changes in overall catch and finfish abundance, and were asked their expectations regarding future changes in finfish abundance. They also estimated their likelihood of exiting the fishery under theoretical catch reduction scenarios. Less than half of fishers would exit the fishery if catch halved. Binary logistic regression showed that negative perceptions of future finfish abundance significantly explained increased likelihood of exiting the fishery (z ¼ 2.606, df 1, p < 0.05) and that increased livelihood diversity weakly supported staying in the fishery (z ¼ 1.818, df 1, p ¼ 0.069). Although stock management measures enjoy strong support in the studied area, fishers are most likely to exit fisheries when they consider stocks to be in continuing decline rather than sustainably managed. Increasing livelihood diversity reduced fishery exit likelihood as alternative livelihoods supplement and complement otherwise non-viable fishing. Results indicate incorrectly targeted livelihood diversification measures aimed at reducing fishing effort may achieve the opposite of their intended effect. If alternative livelihood options are to be viable and effective in reducing fishing pressure these must be attractive to fishers identified as willing to exit the fishery, and by their nature or conditions pre-require foregoing of fishing activities. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Coastal zone management plans and coastal resource management, including measures aimed at controlling fishing effort, are seen by governments worldwide, as key to sustaining fishery resources (Allison and Ellis, 2001; Tobey and Torell, 2006; Muallil et al., 2011; Pomeroy, 1991, 2010). Alongside the need to gain support amongst stakeholders, the ability of such plans to improve resource health status through reduced fishing pressure is considered a primary measure of their success (Smith et al., 2006; Andalecio, 2010). Yet, despite decades of targeted management efforts, most fisheries remain fully or over exploited, with considerable implications not only for specific fisheries, but also entire marine ecosystems and the human communities dependent on them (FAO, 2010; Pauly et al., 2000; Christensen et al., 2003; Eagle and Thompson, 2003; Perry et al., 2011). Management measures to reduce fishing pressure have developed over time from physical * Corresponding author. Tel.:þ441912225091. E-mail address: [email protected] (M.J. Slater). 0964-5691/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ocecoaman.2012.11.003
intervention (marine protected areas, regulation of effort and gear types), through yield efforts aimed at improving fishing efficiency (optimisation or provision of gear), to more recent approaches which address the influence of complex social and economic interactions in fisher’s resource use and associated dependence (Pomeroy, 1991; Smith et al., 2006; Eagle and Thompson, 2003; Allison et al., 1998; Lowry et al., 2005; Linkov et al., 2006; Cinner and Pollnac, 2004). In developing and developed nations, fishery exit, that is, fishers no longer fishing, is increasingly encouraged as a way of reducing fishing pressure (Allison and Ellis, 2001; Tobey and Torell, 2006; Muallil et al., 2011). Existing management measures in coastal communities include providing alternative livelihoods to fishers or offering direct compensation to encourage exit from fisheries (Allison and Ellis, 2001; Tobey and Torell, 2006; Muallil et al., 2011). However, fishers respond in a variety of ways to such measures, and to changes in the environmental and socio-economic conditions surrounding their fishing activities. In declining fisheries, decisions to exit the fishery can ameliorate negative impacts on the resource. Conversely, decisions to remain in a declining fishery or increase
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fishing effort can intensify impacts and result in negative feedbacks (Perry et al., 2011; Cinner et al., 2010). Fishers caught in povertytraps are generally subject to reduced mobility of resources, may lack education or skills to adapt, are increasingly unlikely to be able to alter livelihoods, and often increase efforts to obtain income through fishing (Jentoft and Midré, 2011; Cinner et al., 2008; Cabral and Alino, 2011). Understanding drivers to promote fishers in coastal communities to exit declining fisheries is central to improving future efficacy of coastal management. Most fishers are reluctant to abandon fishing even under difficult social and economic situations. A recent study of 141 Kenyan fishers reported that they were unlikely to exit the fishery, even at hypothetical catch reductions of 50% (Cinner et al., 2008; Ikiara and Odink, 2000). Similarly, Filipino fishers were unlikely to exit the fishery in drastically reduced theoretical yield scenarios and were evenly split over abandoning fishing, even when offered compensation payments equal to current fishing income (Muallil et al., 2011). Positive associations with fishing may reduce exit willingness as fishing can provide sense of economic independence and the chance of large periodic or seasonal windfalls (Smith and Hanna, 1993; Meynen, 1989). High levels of investment in fishing assets which cannot be quickly or easily sold can also bind fishers to the industry (Ikiara and Odink, 2000). Equally fishing can provide a sense of community, family status, tradition and belonging along with enjoyment and ‘easy job’ in many fisher’s opinions (Pollnac et al., 2001). The complexity of factors affecting fishery exit is influenced by governance structures impacting fisher’s decision-making at different scales, e.g., community, national and international levels (Daw et al., 2012). At a community level studies have revealed potential indicators and drivers predicting fishers’ willingness to exit fisheries. Socioeconomic modelling has previously indicated that increasing wealth and increasing number of livelihoods at the household level positively influence exit choices among fishers (Cinner et al., 2008). In contrast in fisheries in developed nations, constructed social models identify factors such as ‘perceived excessive fishing fleet size’ or ‘competition on behalf of fishers’ as driving willingness to leave a fishery; direct economic models base calculations of likelihood to exit primarily on the income obtained and costs incurred in fishing activities, including factors such as long-term capital investment in vessels or gear (Ward and Sutinen, 1994; Pradhan and Leung, 2003). Livelihood diversification is commonly viewed as a management option for reducing fishing effort and offering poverty alleviation (Allison and Ellis, 2001; Tietze et al., 2000; Andersson and Ngazi, 1998). There is some evidence to show some fishers from households with diverse livelihoods and are more likely to reduce fishing effort and consider exiting a fishery (Tobey and Torell, 2006; Muallil et al., 2011; Cinner et al., 2008; Wells et al., 2010). Conversely, income from alternative livelihoods may be reinvested in activities which increase fishing effort and pressure (Sievanen et al., 2005), thus it is possible that a higher level of livelihood diversity effectively allows for fishing efforts to be continued by subsidising fishers who would otherwise not function on fishing alone. Highly diversified fishers households maybe empowered to exert continued fishing pressure by livelihood diversification driving uneconomic fisheries into deleterious decline (Allison and Ellis, 2001; Andersson and Ngazi, 1998; Sievanen et al., 2005). These complications and interactions have led to suggestions that co-payments or measures to encourage fishery exit are required, especially for targeting fishers already inclined to exit (Muallil et al., 2011). However, these may also be equally erroneous or ineffective if not applied in a manner which takes into account the complex socialeecological and socioeconomic interactions (Muallil et al., 2011; Berkes et al., 2001).
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The Philippines is a marine biodiverse archipelago nation and a hotspot for marine conservation with more than 1.3 million impoverished local or “municipal” fishers. Declines of marine fisheries and destruction of marine habitats have forced management changes and driven current and increasing interest in encouraging fishery exit (Muallil et al., 2011; BoFa-. Philippines, 2009; Courtney and White, 2000; Christie and White, 2007). A long history of community-based coastal management and innovations in terms of managing its fishery resources has seen development from a community-based approach in the 1980s to comanagement in the 1990s to integrated management and governance in the form of coastal resource management (CRM) (Pomeroy, 1991, 2010, 2007). Measures in CRM include alternative livelihood provision along with empowering fishers and local government to take an active role in the management of coastal resources (Lowry et al., 2005). Efficacy of coastal fisheries management has been linked to fishers’ empowerment, their awareness of resource management measures, resource users’ perception of the sensibility of measures taken and resource users’ participation in the management process (Andalecio, 2010; Courtney and White, 2000). However, recent research has shown that CRM initiatives in Asia, Latin America and the Caribbean have seldom provided tangible benefits to fishers in terms of improvements in catch or quality of life (Maliao et al., 2009; Olsen, 2002). It remains unclear whether fishers believe that CRM plan measures have the capacity to effectively guarantee coastal livelihoods or stem fishery decline. Evidence of perceptions on success of management measures can be a useful indicator for determining support by those impacted which can influence level of compliance with regulations or achievement of management goals. This paper investigates drivers underpinning individuals’ willingness to exit a fishery by gauging fishers’ opinions in seven villages within an area with a 15-year CRM history and impacted by declining fisheries. The study investigates effects of demographic, social, economic and environmental variables influencing fishers’ lives and their decision making. The main aim is to show how fishers’ perceptions and livelihood choices influence willingness to exit a fishery and to inform effective measures to encourage fishery exit. 2. Methods 2.1. Study site Bayawan is a coastal city in Negros Island, Philippines covering 69,000 ha with a population of 110,000. The city has 15 km of coastline in Tolong Bay and seven coastal villages constituting 4% of its land area. There are 225 km2 of municipal waters with an average depth of around 91 m (City LGUo, 2001e2005). Bayawan manages one of the highest yield fishing grounds of the province and has been identified as part of the migration path of yellowfin tuna (Thunnus albacares). The main fishing season is from November to May, which coincides with the northeast monsoon. Commercial fishermen from other provinces historically fished heavily in Bayawan’s municipal waters, contributing to the decline of the city’s fishery resources. Bayawan became a pilot project of the Coastal Resource Management Project (CRMP), an initiative of the Philippine Government which started in 1996 (Pomeroy et al., 1997). In the year 2000, CRMP together with the Martin “Ting” Matiao Foundation assisted the city’s technical working group in formulating the 2001e2005 CRM Plan. The focus area of the plan is the seven coastal villages of Bayawan: Villareal, Tinago, Boyco, Suba, Banga, Malabugas and Pagatban (Fig. 1) which form the study sites for the work presented herein.
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Fig. 1. The Coastal Resource Management zones of Bayawan City, Philippines showing coastal villages. Source: Bayawan City Coastal Resource Management Plan 2001e2005.
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2.2. Data collection e fishers’ survey A semi-structured questionnaire was developed and piloted with four fishers (one from each user group defined below) to ensure questions were clear and understandable, questions were adjusted as required. Resource-users were interviewed between April and June 2010. Interviewees were defined as follows: municipal fishers (small boat fishers e equally split between members of cooperatives and non-members) who use motorized fishing boats of 3 gross tons and less, municipal fishers engaged in the collection of wild milkfish (Chanos chanos) fry (fry collectors), and commercial fishermen using fishing vessels of less than 20 gross tons (Table 1). A total of 85 fishers were interviewed using opportunistic sampling representing between 30 and 50% of the total number of each fisher type within the CRM zone. The questionnaire consisted of 54 questions divided into 10 sections. Twenty-seven variables were gathered and grouped into four categories: socioeconomic, ecological, attitudinal, and awareness and participation. Municipal fishers and fry collectors rated the level of successful implementation of the 10 CRM program objectives using a 5-point Likert scale (1- Poor, 2- fair, 3- Satisfactory, 4Good and 5- Excellent). Commercial fishers did not rate CRM measures because they do not (legally) fish within the municipal waters of Bayawan and did not exhibit high levels of awareness of the CRM program. All fishers were asked what action they would take in response to sustained reductions in catch of 20% or 50%. 2.3. Statistical analysis KolmogoroveSmirnov and Levene’s tests were applied to each tested category to ensure normality of distributions and homogeneity of variances respectively. Mean scores on the Likert scale for implementation of individual CRM objectives were calculated for each objective. A one sample t-test was used to compare the mean of individual objectives with a minimum expected value (for the objective to be considered successfully implemented) of 3.5. Where applicable, chi-squared tests were applied to data in order to isolate differences in response type frequency by respondent type. The binary (dichotomous) variable ‘decision to remain in or exit the fishery at 50% catch reduction’ (response options exit fishery/ remain in fishery) was recorded as fishers’ choice as to whether they would either continue fishing or would exit the fishery in the case of a theoretical 50% reduction in catch. Binary logistic regression was used to model ‘decision to remain in or exit the fishery at 50% catch reduction’ as the dependent (left-hand side) variable. Hypothesised explanatory (right-hand side) variables were selected based on literature review and exploratory chi-squared tests. The following explanatory (right-hand side) variables were
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chosen as potential predictors or response to ‘decision to remain in or exit the fishery at 50% catch reduction’: Respondent age; perceived fish abundance in 5 years; perceived current fish abundance (compared to 5 years ago); number of years fishing; catch change over last 5 years; awareness of CRM plan; type of fisher (Fry, Municipal, Commercial); livelihood diversity (defined as number of different livelihoods in a household); catch value (Philippine Peso); household size (total number of inhabitants); Rank of importance of fishing as proportion of household income (‘1’ as most important e Table 2). In the modelling process, exploratory backwards conditional binary logistic regression, an initial model containing all proposed explanatory variables is created and individual variables with the least significant influence on the distribution of dependent variable are removed stepwise from the current model. Stepwise removal and recalculation of the model produces the most parsimonious final model retaining only variables having a significant effect on response distribution. 3. Results 3.1. Fishing community demographics Interviews were conducted with 68 male and 17 female fishers ranging from 20 to over 70 years of age. Eight percent of fishers interviewed were 20e30 years old. All others were aged 31 years or older, with the largest group of respondents being within the 41e50 range. Fishing experience ranged from 10 to more than 40 years. Mean household size (adults and children) was 5.11 (1.99 SD) and most fishers’ households had three to five different occupations. Fishing was ranked as the most important household economic activity by 91% of fishers. Of the 85 fishers interviewed, 30 had had jobs in the last five years which they considered more important household economic activities than fishing. Of these, 73% said that they prefer fishing over the other occupation (Table 1). 3.2. Support for and awareness of management measures Commercial fishers (40% aware) were significantly less likely (chi2 ¼ 6.7, p < 0.01) to be aware of the Coastal Resource Management (CRM) plan than municipal fishers (organisation members e 80% aware), municipal fisher (organisation nonmembers e 65% aware) or fry fishers (77% aware) (Table 1). More than half of municipal fishers (organisation members 70%) and half of the fry fishers (50% participation) participated in the formulation of the CRM plan, while only 30% of municipal fisher (organisation non-members) and 27% of commercial fishers were involved (Table 1). Municipal fishers who were members of fishers’ organisations were more aware of the CRM plan (80%) and participant in
Table 1 Sample representative coverage, plan awareness and community participation in planning, awareness and support of regulations across fisher type and fishers’ organisation membership.
Number fishers interviewed/total number fishers per user group Awareness of the CRM Plan Awareness of City Fisheries and Aquatic Resources Management Council Participation in public consultations on fishery matters Participation in the annual fisherfolk day Participation in formulation of the CRM plan Awareness of regulations Do not support regulations Marine reserves acceptable a
Municipal fishers (organization members)
Municipal fishers (non-members)
Fish fry collectors
Commercial fishers
20/54 (37%) 16/20 (80%) 19/20 (95%)
20/40 (50%) 13/20 (65%) 9/20 (45%)
30/93 (32%) 23/30 (77%) 25/30 (83%)
15/30 (50%)a 6/15 (40%) 4/15 (27%)
14/20 16/20 14/20 18/20 0/20 19/20
11/20 14/20 6/20 20/20 0/20 16/20
23/30 22/30 15/30 27/30 1/30 24/30
8/15 3/15 4/15 15/15 0/15 15/15
(70%) (80%) (70%) (90%) (0%) (95%)
Group response distribution differs significantly from all other groups (chi2 ¼ 6.7, p < 0.01).
(55%) (70%) (30%) (100%) (0%) (80%)
(77%) (73%) (50%) (90%) (3%) (80%)
(54%) (20%) (27%) (100%) (0%) (100%)
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Table 2 Categorical variable counts and means of non-categorical variables of hypothesised explanatory (right-hand side) variables for binary logistic model to explain ‘decision to remain in or exit the fishery at 50% catch reduction’. The model and categorical variables exclude interviews with incomplete sets of variables. Categorical variables
Category
Frequency all fishers
Frequency municipal/ fry fish.
Age
Non-categorical variables
Below 35 35e50 50 and above Less Same or more 0e25 25e40 Less Same or more Less Same or more Local fisher Milkfish fry trawler Commercial fishers Yes No Mean SD
18 49 13 45 35 51 29 54 26 58 22 36 29 15 54 26 Min
15 40 10 27 28 40 25 47 18 49 16 36 29 0 48 17 Max
Livelihood diversity Rank importance fishing Catch value (Philippine Peso) Household size
3.22 (1.07) 1.16 (0.55) 30,0154 (67,319) 5.11 (1.99)
1 1 40 1
5 4 264,000 12
(Predicted) fish abundance in 5 years Years fishing Catch change over last 5 years Fish abundance compared to 5 years ago Fisher type/occupation
Awareness of CRM Program
public consultations (70%) than non-members (65% and 55% respectively e Table 1). Awareness of key fisheries regulations was similar among interviewees with only 6% of all fishers stating they were not fully aware of the regulations. Amongst all respondents only one fry fisher stated that they did not support fishery regulations. The establishment of marine reserves was acceptable to more than 80% of fishers interviewed across all groups (Table 1). Local fishers’ and fry collectors’ ratings of the level of successful implementation of CRM program objectives ranged from means of 3.5 (0.15 SEM) to 4.3 (0.11 SEM, Table 3). The mean values of individual objectives 1, 2, 3, 5, 8 and 10 (Table 3) differed significantly (one-sample t-test, p < 0.05) from (above) the minimum value of 3.5 (satisfactory). Objectives 4, 6, 7 & 9 did not differ significantly (one-sample t-test, p > 0.05) from the minimum value Table 3 Fishing community demographics all respondents. Variable
Response category
Number of responses (N)
Percentage of responses (%)
Gender
Male Female 20e30 31e40 41e50 51þ 10e20 21e30 31e40 40þ Fishing Farming Salaried employ. Inform. econ. act. Yes No Yes No 1 2 3 4 5
68 17 7 25 38 15 39 24 12 10 77 3 4 1 30 55 8 22 6 12 35 21 11
80.0 20.0 8.2 29.4 44.7 17.6 36.9 28.2 14.1 11.8 90.6 3.5 4.7 1.2 35.3 64.7 26.7 73.3 7.1 14.1 41.2 24.7 12.9
Age (years)
Fishing experience (years)
Primary economic activity
Other main economic activity in past 5 years? Prefer past economic activity to fishing? Number of household occupations
of 3.5 (satisfactory). The lowest ranking among all fishers was objective 9, the provision of alternative livelihoods (3.5 0.15 SEM). 3.3. Resource state perceptions and fishery exit Seventy-two percent of all fishers responded that they perceived lower current abundance of fish in the sea compared to 5 years ago and 53% said they expected fish abundance to be lower in five years (Table 4). Fry collectors were significantly more likely than all other groups to respond that their catch was lower now than five years ago and that they perceived lower current fish abundance (Chi2 ¼ 18.6, p < 0.001; Chi2 ¼ 7.6, p < 0.05 respectively e Table 4). Local members of fishing organisations were significantly more likely than non-members to respond that they perceived lower current fish abundance, that their catch was lower now than five years ago, and that they believed there would be lower future fish abundance in five years (Chi2 ¼ 5.5, p < 0.05; Chi2 ¼ 13.5, p < 0.001; Chi2 ¼ 4.4, p < 0.05 respectively e Table 4). When proposed theoretical catch reduction scenarios, 75% of municipal fishers, 60% of fry collectors and 53% of commercial fishers stated they would continue to fish even if the catch were to drop by 50% (Fig. 2A). Half of all fishers with only one household occupation would exit the fishery whereas less than 25% of fishers with 4 or more household occupations would exit the fishery (Fig. 2B). Only 12% of all fishers would exit the fishery in the case of a theoretical 20% drop in catch (Fig. 2B). Binary logistic regression analysis, conducted to predict ‘likelihood of exiting the fishery at 50% catch reduction’, for all fishers resulted in a model which differed significantly from the constant only model (Chi2 ¼ 9.9, p < 0.01, df ¼ 2) indicating that the retained predictors (RHS variables) reliably distinguished between those who would exit the fishery and those who would remain. Analysis of retained predictors in the final model revealed perceived fish abundance in five years as the single significant predictor of “likelihood of exiting the fishery at 50% catch reduction” for all fishers (z ¼ 2.606, df ¼ 1, p < 0.05). Number of different occupations was retained in the exploratory model for all fishers (z ¼ 1.818, df ¼ 1, p ¼ 0.069) with increased livelihood diversity at the household level weakly supporting staying in the fishery (Table 5). Binary logistic regression analysis, conducted to predict ‘likelihood of exiting the fishery at 50% catch reduction’, for all municipal fishers and fry collectors resulted in a model which also differed significantly from the constant only model (Chi2 ¼ 7.7, p < 0.05, df ¼ 2) indicating that the retained predictors (RHS variables) reliably distinguished between those who would exit the fishery and those who would remain. Among all municipal fishers and fry collectors, perceived fish abundance in five years was the single significant predictor of “likelihood of exiting the fishery at 50% catch reduction” (z ¼ 2.238, df ¼ 1, p < 0.05, Table 5) with retention of number of different occupations in the final model weakly supporting staying in the fishery (z ¼ 1.627, df ¼ 1, p ¼ 0.104, Table 5). 4. Discussion The current study shows fishers who are pessimistic about present and future fish abundance are significantly less reluctant to abandon fishing. Equally results reveal that fishers from households with increasing numbers of different livelihoods exhibited decreasing likelihood of exiting the fishery e in direct contrast with similar studies (Muallil et al., 2011; Cinner et al., 2008). Furthermore, fishers interviewed support and participate in CRM measures but do not perceive current or future benefits from management measures. While adding to the widely acknowledged view that fishers are reluctant to exit fisheries and that the factors influencing decisions fishers make are complex and varied, this study
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331
Table 4 Distribution of responses regarding perception of current and future fish abundance and change in catch over the past five years e responses separated by fisher respondent type. Municipal fishers (org. members) Abundance of fish in the sea compared to 5 years ago Predicted abundance of fish in the sea in five years Change in catch over the past five years
Less More/same Less More/same Less More/same
14 6 10 7 13 7
(70%)b (30%) (59%)b (41%) (65%)b (35%)
Municipal fishers (non-members)
Fish fry collectors
11 9 7 12 8 12
27 3 20 9 29 1
(55%) (45%) (37%) (64%) (40%) (60%)
(90%)a (10%) (69%) (31%) (97%)a (3%)
Commercial fishers
All fishers (total)
9 6 8 7 7 8
61 24 45 35 57 28
(60%) (40%) (54%) (46%) (46%) (54%)
(72%) (28%) (56%) (44%) (67%) (33%)
a
Group response distribution differs significantly from all other groups (chi2 ¼ 7.6, p < 0.05- Abundance; chi2 ¼ 18.6, p <0.001 - catch change). Group response distribution differs significantly from non-organisation members (Chi2 ¼ 5.5, p < 0.05- Abundance; Chi2 ¼ 4.4, p < 0.05 - future abundance; Chi2 ¼ 13.5, p < 0.001 - catch change). b
highlights specific recommendations for management intervention that can be considered by managers and policy makers (Daw et al., 2012). These are discussed in terms of their implications for CRM plans and specifically within the context the role for alternative livelihood measures in promoting fishery exit. The CRM plan in Bayawan City can be considered a success and a failure, contingent on the chosen measure examined (Andalecio, 2010; Maliao et al., 2009; Olsen, 2002). The CRM plan is successful in the sense that the majority of fishers expressed support for management measures in place and there is high awareness among targeted municipal fishers regarding fishery plan formulation. Efforts to involve stakeholders in the development and implementation of the plan have also been broadly successful. However, the CRM plan has not yet led to tangible benefits, in terms of stemming fishery decline, to fishers who support it or otherwise.
A 100% Proportion fishers
90% 80% 70% 60% 50%
Remain
40%
Exit fishery
30% 20% 10% 0% 1
B
2
3
4
5
Number of different household occupations
Table 5 Binary logistic regression results for factors explaining ‘decision to remain in or exit the fishery at 50% catch reduction’. Results for all fishers and all municipal fishers and fry collectors. Includes goodness of fit and model summary.
100% 90% 80%
Proportion fishers
The majority of fishers reported continuing reductions in catch and considered current health of remaining fisheries resources poor (Maliao et al., 2009; Olsen, 2002). The members of fishing organisations and fish fry collectors most involved in management decisions appear to be more aware of and/or pessimistic about stock and catches. The majority of CRM participants stated the measures are not effectively protecting future fisheries as evidenced by their expectations of future stocks. There may be an increasing risk to participation in measures and the near universal support of fishers when no tangible benefits are seen to arise from the plan. Based on estimates of past changes in catch and current and future stocks, the majority of fishers are convinced that fisheries exist solely in decline. If fishers perceived as likely or even inevitable the hypothetical 50% in reduction in catch (as evidence by their estimates of future stocks), they are significantly more likely to exit the fishery. This may imply many fishers who stated they will not leave the fishery were unable to relate themselves to the hypothetical scenario rendering their responses to the question invalid (Speight et al., 2009). Alternatively, conviction that future fish abundance will decline is a primary driver to fishery exit among commercial and municipal fishers. Those individuals who retain “hope” of stable or strong stock in future, despite majority attestation to past reductions in catch and abundance, are less likely to exit the fishery in the future. Members of fishers’ organisations who frequently exchange information and receive stock and catch data from the municipal authority are significantly more likely to expect future abundances to be low. If fishery exit is desirable, providing existing and projected catch data to fishers may result in more realistic expectations of future catches, in turn further increasing the large majority of fishers convinced that
Variables in the equation
70% 60% 50% 40%
Remain
30%
Exit fishery
20% 10%
Fishers
Factor
All fishers
Fish abundance in 5 years Livelihood diversity Fish abundance in 5 years Livelihood diversity
Municipal/fry fishers
Coefficient
S.E.
z-value
df
p-value
1.418
0.544
2.606
1
0.009
0.449 1.388
0.247 0.620
1.818 2.238
1 1
0.069 0.025
0.420
0.258
1.627
1
0.104
Hosmer and Lemeshow test (GoF)
0% Municipal fishers
Fry fishers
Commercial fishers
All fishers 20% reduction
Fisher type / Reduction type Fig. 2. A: Distribution of responses of all fishers to theoretical catch reductions scenarios of 50% displayed as a function of number of household occupations. B: Distribution of responses of fishers to theoretical catch reductions scenarios of 50% displayed as a function of fisher type and distribution of responses of all fishers to theoretical catch reductions scenarios of 20%.
All fishers Municipal/fry fishers
Step
Chi2
df
Sig.
10 10
6.090 4.496
6 6
0.413 0.610
Model summary Step 2 Log likelihood Cox & Snell R2 Nagelkerke R2 All fishers 10 93.690 0.116 0.160 Municipal/fry fishers 10 74.081 0.112 0.156
332
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future abundance will decrease. In addition, targeting alternative livelihood provision to those willing to exit, on the basis of their conviction that; a) stocks will continue to decline and; b) low current livelihood diversity, among other selection criteria, would allow efficient application of resources (Muallil et al., 2011). Despite participatory CRM measures supported by the community and enforced by governing bodies, fishers who perceive the continuing decline of a resource may react by fishing what they can before its demise. In this case the resource will be exploited to biological or economic collapse, with ensuing poverty, if fishers cannot exit the fishery (Hardin, 1968; Bene, 2003). Associated with this scenario is the assumption that fishers do not wish to exit the fishery or that they are increasingly unable to due to a lack of resources or opportunity e further enforcing feedbacks by which negative socioecological interactions lead to further reductions in resource health and fishers’ ability to alter resource exploitation e or a socioecological trap (Steneck, 2009; Folke, 2007; Cinner, 2011; Reardon and Vosti, 1995). Based on the current results regarding perception of fishery and willingness to exit, fishers will become overwhelmingly convinced of the likelihood of further decline and will increasingly decide to exit the fishery e if at all possible. In such a case negative feedbacks can be avoided if resource, opportunity and condign value limitations are overcome in provision of alternative livelihoods. A desirable reduction in fishing pressure, ultimately aiding fishery management efforts, should be strived for through provision of targeted alternative livelihoods preferably providing the income, status and satisfaction of fishing to support the exit of targeted fishers and attract further fishers to exit (Muallil et al., 2011). While in apparent agreement with frequent policy opinion that alternative livelihood provision is contingent with reduction in fishing pressure, the current study shows fishers from households with increasing numbers of different livelihoods exhibited decreasing likelihood of exiting the fishery e in direct contrast with similar studies (Muallil et al., 2011; Cinner et al., 2008). Muallil et al. (2011) specify livelihoods tourism, agriculture and industry amongst fishers in the Philippines. Cinner et al. (2008) provide examples of livelihoods as agriculture and informal economy amongst fishers in Kenya. In the current study non-fishing livelihoods were tourism, agriculture, marketing marine products, selfemployment and salaried employment. While there is little evidence to indicate livelihood options differ greatly from those available to fishers included in the study by Muallil et al. (2011) there may be differences to the value and or type of livelihood available to fishers in the study by Cinner et al. (2008). Nonetheless, the main livelihood classifications are the same across all three studies. Despite potential differences in available alternative livelihoods, this result appears to undermine the argument that alternatives can facilitate fishery exit and reduce fishing pressure. This can be reconciled in noting that those alternative livelihoods considered in the current study are neither preferred over fishing nor are they considered primary income sources e as evidenced in both cases by fishers’ own assertions e whereby 70% of fishers with other jobs in the past five years said they preferred fishing and more than 90% of all fishers considered fishing the most important economic activity of the household. We suggest that existing alternative livelihoods are also not exclusive of continuation of fishing activities and are, by nature or historical development (i.e. to complement fishers’ incomes), specifically chosen not to exclude the option of fishing at individual, household or community level. Existing livelihoods are redundant in their potential role in facilitating fishery exit. In addition to the need for alternative livelihoods to target fishers more likely to exit and providing appropriate income, status and satisfaction, our results indicate that alternative livelihoods must by nature or specification preclude fishing if they are to be effective in reducing fishing effort.
Retention of number of occupations in the final regression model and observed decrease in likelihood to exit the fishery as livelihood diversity increased may rest on the combined effects of two livelihood scenarios. In the case of the more commercial or specialised fishers with a low level of livelihood diversity, fishing is more rapidly abandoned as catch lowers, due to direct economic necessity, thus fitting established bio-economic models that show likelihood to exit as primarily dependent on income obtained and costs incurred in fishing (Ward and Sutinen, 1994; Pradhan and Leung, 2003). Bio-economic models may not apply as rapidly as in developed countries where specialisation and capital loading are comparatively high, they may still apply in developing nations after many years of resource degradation. In fishers households which are less singularly specialised towards fishing and less exclusively economically dependent on fishing, the case for most local fishers in the current study area, fishing is not abandoned as catch lowers because the economic necessity is not as apparent. This is partly explained by remaining livelihoods within the house reducing the economic impact of fishing loss and supporting continued, even deleterious, fishing effort (Sievanen et al., 2005). In developing and emerging nations such as the Philippines, fisheries may be in transition towards increasing commercial specialisation which would ultimately support the former scenario and latter mechanism leading to a bimodality of livelihood diversity responses, whereby specialised small-scale commercial fishers with low livelihood diversity exit declining fisheries and artisanal fishers with higher livelihood diversity do not. 5. Conclusions Consultation and participation are not long-term replacements for viable stocks, acceptable catches or viable alternative sources of income for fishers. Livelihood alternatives are necessary, but these require better specification in the future to support small-scale fishery management by successfully reducing fishing pressure, as indicated herein. Future alternative livelihoods must be targeted at fishers who are identified as most willing to exit the fishery, and offered livelihoods must appeal to economic and intangible values associated with fishing to make them preferable. Livelihood initiatives must directly address the problem that livelihood diversity per se frequently has the opposite effect to that desired/ predicted with regard to fishing pressure reduction in the long term (Allison and Ellis, 2001; Sievanen et al., 2005). To do so alternative livelihoods must be provided with specifications that they form a direct alternative to fishing or should if possible require a specification that fishers cease fishing. The resulting livelihood options are likely to be more strictly scrutinized by fishers before they are accepted, as they are bound to significant foregoing, and will thus be effectively exposed to test-driven development prior to implementation, making them significantly more viable in the long-term due both to depth of acceptance and tested viability. Acknowledgments The authors wish to thank Dr Aileen Mill and Prof Stephen Rushton for modelling advice. We wish to thank the reviewers of this manuscript for constructive and useful suggestions and input. Dr Slater is supported by a Leverhulme Trust Research Project Grant. References Allison, E.H., Ellis, F., 2001. The livelihoods approach and management of smallscale fisheries. Marine Policy 25 (5), 377e388. Allison, G.W., et al., 1998. Marine reserves are necessary but not sufficient for marine conservation. Ecological Applications 8 (1), S79eS92.
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