A sea change on the African coast? Preliminary social and ecological outcomes of a governance transformation in Kenyan fisheries

A sea change on the African coast? Preliminary social and ecological outcomes of a governance transformation in Kenyan fisheries

Global Environmental Change 30 (2015) 133–139 Contents lists available at ScienceDirect Global Environmental Change journal homepage: www.elsevier.c...

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Global Environmental Change 30 (2015) 133–139

Contents lists available at ScienceDirect

Global Environmental Change journal homepage: www.elsevier.com/locate/gloenvcha

A sea change on the African coast? Preliminary social and ecological outcomes of a governance transformation in Kenyan fisheries Joshua E. Cinner a,*, Tim R. McClanahan b a b

Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville QLD 4811, Australia Wildlife Conservation Society, Marine Program, Bronx, NY 10460-1099, USA

A R T I C L E I N F O

A B S T R A C T

Article history: Received 23 June 2014 Received in revised form 5 October 2014 Accepted 13 October 2014 Available online 30 October 2014

We examined social and ecological outcomes over a period of transformational change in the governance of Kenyan fisheries. Devolving decision-making power to local communities initially promoted a perception of winners and losers among resource users, but after just 6 years, there were virtually no resource users who felt that the new governance arrangement was detrimental to their livelihood. The current lack of negative perceptions toward co-management provides a critical window of opportunity to strengthen local governance institutions by investing in leadership capacity, transparency, and enforcement. This newly acquired authority to capture the benefits from local management resulted in an unexpected proliferation of community-based marine reserves – a substantial change to the antireserve discourse that halted the government’s most recent attempt to establish a national marine reserve. Several community-based reserves showed increases in fish biomass and coral cover, while others did not and likely suffered from poor compliance and weak management. Despite some seemingly positive early social and ecological outcomes, co-management should not be viewed as a panacea to Kenya’s fisheries challenges, but rather as one of many tools for improving the chances of achieving social–ecological sustainability. ß 2014 Elsevier Ltd. All rights reserved.

Keywords: Social–ecological systems Fisheries Co-management Decentralization

1. Introduction Globally, small-scale fisheries directly employ more than 200 million people (Teh and Sumaila, 2013). These fisheries are challenging to manage through top-down approaches because they are often multi-species, multi-gear, and operate from dispersed landing sites, which together make it particularly difficult to collect data and enforce regulations (McClanahan et al., 2009). Consequently, many top-down managed small-scale fisheries may be unable to simultaneously sustain marine ecosystems and the livelihoods of fishers (Costello et al., 2012). To potentially address these social and ecological challenges, a number of countries have attempted to transform top-down national governance of small-scale fisheries toward more inclusive and participatory approaches – often called co-management (Alcala and Russ, 2006; Gelcich et al., 2010; Olsson et al., 2008). For example, many sub-Saharan African countries have recently developed co-management arrangements that devolve governance

* Corresponding author. Tel.: +61 7 4781 6751. E-mail address: [email protected] (J.E. Cinner). http://dx.doi.org/10.1016/j.gloenvcha.2014.10.003 0959-3780/ß 2014 Elsevier Ltd. All rights reserved.

of both inland and marine fisheries to a more local level (ranging from local governments to resource user organizations) (Be´ne´ et al., 2009; Cinner et al., 2012a). Although social contexts and governance frameworks under which co-management arrangements operate can vary considerably, co-management generally provides resource users with a greater say in developing and enforcing fisheries rules (Pomeroy and Berkes, 1997; Cinner et al., 2012a; Jentoft, 1989). In principle, this is meant to make management more reflective of local opinions and conditions, take advantage of existing knowledge and capacities, and provide local-scale incentives for people to comply with management initiatives of their own accord (Gutierrez et al., 2011; Pomeroy and Berkes, 1997; Jentoft et al., 1998; Pretty, 2003; Grafton, 2005). Yet, critical questions remain about how governance shifts to co-management actually impact societies and ecosystems (Be´ne´ et al., 2009; Blaikie, 2006; Ribot et al., 2006). Most studies of governance shifts toward participatory marine fisheries management to date have been largely descriptive in nature (e.g., Gelcich et al., 2010; Olsson et al., 2008; Ayers and Kittinger, 2014), rely on one time sampled spatial comparisons (Cinner et al., 2012b), or are meta-analyses gleaned from the literature (Evans et al., 2011; Gutierrez et al., 2011). Few primary

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data studies have quantitatively examined how key social and ecological outcomes associated with governance transformations to co-management change over time (Evans et al., 2011). Here, we quantify how both ecological conditions and resource users’ perceptions about their livelihoods changed after a governance transformation in Kenya that transferred key aspects of decisionmaking power of near-shore fishery resources to resource users (Cinner et al., 2012a). In 2006, the Kenyan government introduced co-management legislation that allowed 33 pilot coastal communities to develop and enforce local bylaws regarding the use of and access to fisheries. These bylaws can include banning certain gears, restricting access of non-members to fishing grounds, and prohibiting fishing in delineated areas, such as no-take marine reserves (see Cinner et al., 2009, 2012a for a more detailed account of the historical and institutional aspects of Kenyan co-management). The bylaws had to be consistent with existing fisheries laws (i.e. one could not pass a bylaw allowing the use of illegal gears) and all bylaws had to be approved by the Fisheries Department (Cinner et al., 2012a). These co-management arrangements represent a major governance shift from a previously de facto open-access governance regime. These governance changes in Kenya, which were associated with a constitutional reform, provided a rare opportunity to address key questions about how transformations in fisheries governance can impact both people and ecosystems. Here, we ask the following research questions: (1) ‘‘What forms of management emerge from the ability to create local-level rules?’’ (2) ‘‘How do ecological systems respond to varying rules of devolved management over time?’’ and (3) ‘‘How do resource users perceive impacts of co-management on their livelihoods?’’ 2. Methods We randomly selected 10 of the 33 pilot co-management sites (30%) in 2008 and resurveyed 8 of these again in 2012 (pirate and terrorist activity near the Somali border made it impossible to revisit the other two sites in 2012, so these sites were dropped from all analyses). To gather information in each study site [referred to as Beach Management Units (BMUs)], we employed a combination of household surveys and semi-structured interviews with BMU leaders. In total, we conducted 368 resource user surveys from the 8 resurveyed sites (125 surveys in 2008 and 243 surveys in 2012, which were randomly selected from lists of resource users operating out of the landing site) and 16 BMU leader interviews. Our response rate was very high (approximately 95% of

respondents agreed to be interviewed), but we did not systematically record refusals because they were so rare. We examined the types of rules that were developed under comanagement by interviewing BMU leaders and key informants about the types of operational rules in place in each BMU. We quantitatively examined three key social dimensions of comanagement across the two time periods: (1) Perceived livelihood benefits – responses about the perceived impact of co-management on resource users’ livelihoods were ascertained on a five point Likert scale: strongly beneficial, slightly beneficial, neutral, slightly detrimental, strongly detrimental. An alternative response option was ‘don’t know’ but these responses (10% of respondents) were not included in the analysis below. To compare resource users’ perceptions of benefits over time, we used a cumulative links mixed model (CLMM) with community as a random effect to account for the non-independence of samples within communities. CLMM is an ordinal regression model that allows for random effects. We employed an information theoretic approach (Burnham and Anderson, 2002), whereby we compared a model with a covariate for time (i.e. 2008 and 2012) against a null model that did not include time. (2) Perceived compliance – resource users were also asked to gauge their perceptions of the level of compliance within their site on a four point Likert scale (full compliance, some people break rules, most break rules, all break rules) for each operational rule limiting resource use (operational rules included protected areas, gear restrictions, and access restrictions). In cases where compliance for separate operational rules was ranked differently (e.g., better compliance for a protected area than a gear restriction), the scores were averaged across rules. To compare compliance scores across time, we used a T-test. (3) Training and leadership capacity – we asked BMU leaders whether they had received training on conflict resolution, financial management/ accounting, proposal writing, environmental education, roles and responsibilities, health/sanitation, reef/fisheries monitoring, and/ or laws/regulations. We used a generalized linear mixed model to compare the average number of trainings per leader in 2008 and 2012, which allowed us to account for the non-independence of samples within a community by including a random effect for community. To quantify whether the number of training events leaders had attended had changed over time, we compared a model with a covariate for time (i.e. 2008 and 2012) against a null model that did not include time. In addition, we used underwater visual census to examine fish biomass and coral cover conditions over time in eight co-managed and three ‘‘control’’ sites (Table 1). The control sites consisted of

Table 1 Description of the study sites and types of data collected at each site. Site name

Type of management

Ecological data

Socioeconomic data

Mombasa/Bamburi Kuruwitu Kibuyuni Mradi Mtangata Tiwi Mayungu Takaungu Rasiwatine Funzi Gazi Shimoni Vanga Kanami Diani

National marine reserve/BMU Tengefu/BMU Tengefu/BMU Tengefu/BMU Tengefu/BMU Tengefu/BMU BMU BMU BMU BMU BMU BMU BMU None None

Y (Pre = 2, 1–3 = 3, 3+ = 16) Y (Pre = 14, 1–3 = 3, 3+ = 3) Y (Pre = 1, 1–3 = 2) Y (Pre = 1, 1–3 = 2) Y (Pre = 1, 1–3 = 1) Y (Pre = 1, 1–3 = 2) Y (1–3 = 1, 3+ = 1) Y (1–3 = 1, 3+ = 1) Y (Pre = 10, 1–3 = 2, 3+ = 2) N N N N Y (Pre = 14, 1–3 = 2, 3+ = 3) Y (Pre = 14, 1–3 = 2, 3+ = 1)

Y Y N N N N Y Y N Y Y Y Y N N

BMU = Beach Management Unit; CBMR = small, community-based marine reserve; Y means data is present; N means data is absent. For ecological data, ‘‘Pre’’ refers to the number of years pre-implementation data were collected at each site (i.e. Pre = 2 means there were 2 years of pre-implementation data for that site); ‘‘1–3’’ refers to the number of years that data from the first 3 years after implementation were available, and ‘‘3+’’ refers to the number of years that the site had been surveyed after the management had been in place for more than 3 years.

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two ‘baseline’ sites that lacked local level management (where we did not collect socioeconomic data) and one long-enduring and well-enforced no-take marine reserve, which represents the maximum likely ecological recovery (the landing site adjacent to this reserve is also a BMU where we collected socioeconomic data). Five of the BMUs where we collected ecological data had developed community-based marine reserves (where fishing was prohibited), and three sites did not. Thus, the term BMU refers to all co-managed sites, but only a subset of these has developed community-based marine reserves. There was not perfect overlap between the social and ecological data collection (Table 1): Some of the ecological data were part of a long-term monitoring program, and others were collected in partnership with communities that requested assistance developing community-based marine reserves (locally called tengefu, the Swahili word for ‘‘set aside’’). Although these did not all overlap with the randomly collected socioeconomic data, we used all available evidence collected as rigorously as possible. We used the line-intercept method for estimating coral and benthic cover and underwater visual belt transects (5 100 m) to estimate fish numbers, sizes and biomass (e.g., McClanahan and Shafir, 1990). Coral cover estimates are based on 9–18 haphazardly placed 10 m loosely draped lines per sites per sampling period. Fish biomass is based on 2–4500 m2 belt transects undertaken during neap tides in shallow (2–4 m) water near-shore sites where benthic cover estimates were made. Fish were identified to the family, counted, and lengths estimated to the nearest 10 cm. Length–weight relationships from Fishbase (Froese and Pauly, 2008) and from creel surveys from Kenya (McClanahan and Hicks, 2011) were used to calculate assemblage biomass. We pooled all available fish biomass and coral cover data over three time periods: (1) before the governance shift; (2) 1–3 years after; and (3) 3+ years after (Table 1). We used an ANOVA with a Tukey’s post hoc test to compare whether there were significant differences in overall ecological conditions between pre-implementation, short-term (1–3 years), and longer-term (3+ years) time periods. 3. Results 3.1. Development of rules All of the co-managed sites we surveyed had banned the use of destructive gears such as beach seine nets, three of the sites had restricted access to their fishing grounds for non-members, and one had developed a community-based no-take marine reserves (where fishing is prohibited). The most unexpected result of Kenya’s governance transformation toward co-management is that the freedom for communities to create rules and capture the benefits from managing their fishery (e.g., through collecting fees for tourist access to snorkel and dive on reefs) provided a platform for the proliferation of 18 community-based marine reserves throughout Kenya, totaling 4.2 km2. 3.2. Ecological outcomes We examined changes in fish biomass and coral cover over time across four types of management systems; (1) a national marine park; (2) five community-based closures; (3) three co-managed sites where community-based protected areas were not developed; and (4) two areas that lacked effective management (Fig. 1, Fig. S2). The nationally managed marine reserve of around 6 km2 (the Mombasa Marine National Park) may indicate the maximum potential for contemporary change in this region. This national marine reserve showed an order of magnitude increase in fish biomass, but considerable variation associated with the 1998 El ˜ o Southern Oscillation (ENSO) that resulted in widespread coral Nin

Fig. 1. Response of fish biomass to different types of management. (A) Despite considerable variability, fish biomass increases after both national and communitybased marine reserves were established, but not for areas without management or for Beach Management Unites (BMUs). Year 0 is the date when each specific management regime was implemented, which varies by management type and site. The national marine reserve (green) is the maximum likely recovery potential. Note the y-axis is distorted to provide higher resolution for our focal period 6 years before and after management. (B) Fish biomass by management type clustered into three time periods: before management, 1–3 years after management, and 3+ years after management. Arrows indicate significant increases in biomass between the different time periods.

mortality and resultant changes to the community structure of corals and fish (Fig. 1a, Fig. S1a; Graham et al., 2008). Supplementary Figs. S1 and S2 related to this article can be found, in the online version, at doi:10.1016/j.gloenvcha.2014.10.003. Overall, fish biomass increased inside the community-based closures (Fig. 1: F = 20.9, p < 0.0001), although there was considerable heterogeneity among sites, likely due to poor compliance in some areas. For example, the oldest and bestmonitored community-based closure, Kuruwitu, showed rapid recovery after nearly 20 years of consistently low fish biomass (Fig. 1a). Likewise, a second site, Mradi, also showed a rapid increase in fish biomass, but several of the other community-based marine reserves showed smaller or no increases in fish biomass, possibly due to weak compliance, high exploitation in surrounding areas, and inappropriate habitat locations. Overall, these early stage ecological responses suggest that there were significant

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improvements in fish biomass inside the community-based marine reserves, but that these gains were smaller than those experienced in a well-enforced and larger national marine reserve (Fig. 1b). The sites with no effective management, where only poorly complied with national fisheries laws pertained, did not change measurably over time, nor did the BMU sites where community-based marine reserves were not developed (Fig. 1a and b). There were also statistically significant increases in coral cover over the first three years in community-based marine reserves (Fig. S1). However, these increases were not consistent over longer time frames or in the national marine reserve, the latter of which is likely due, in part, to environmental disturbances (Fig. S1; Graham et al., 2008) and coral cover being a less reliable variable for measuring management effects (McClanahan et al., 2011). 3.3. Social outcomes

Fig. 2. Comparison of resource users’ perceptions of the impacts of co-management on their livelihoods 2 and 6 years after the policy was introduced.

The BMU policy initially created divergent perspectives of both winners (the 30% of respondents who felt it was beneficial for their livelihood in 2008) and losers (the 22% who felt it was detrimental) (Fig. 2). However, resource users’ perceptions about how comanagement impacted their livelihoods changed significantly over time (Fig. 2, Table 2). Specifically, there was a dramatic decrease in perceptions that co-management was detrimental to users’ livelihoods (to 3%) and a slight increase in perceptions that it was beneficial (to 33%). Although the majority of respondents stated that co-management had no impact on their livelihood, after 6 years, there were virtually no resource users that felt that comanagement had been detrimental to their livelihood. Importantly, at the community-scale, perceptions of co-management in Kenya have become more homogeneous over time (Fig. S1). Despite the decrease in negative perceptions, reported compliance with the BMU regulations did not significantly change over time (t = 0.91, df = 216.8, p = 0.36). However, key aspects of leadership capacity have decreased significantly over time (Table 3). Specifically, turnover in BMU leadership has resulted in 2012 leaders having received significantly fewer types of training on issues such as conflict resolution financial accounting, proposal writing, and laws/regulations than those in 2008. 4. Discussion The development of 18 community-based marine reserves represents a substantial (8%) unforeseen complement to Kenya’s national marine reserve system (totaling 54.3 km2). This effort by

communities to close fishing grounds on their own accord represents a substantial shift in the discourse about marine reserves in many Kenyan coastal communities (Evans, 2009). Kenya’s history of government controlled marine reserves has been riddled with conflict. Indeed, the last attempt by the government to develop a national marine reserve on the south coast was abandoned due to protests that turned violent (McClanahan et al., 2005). Kenya’s history of colonial rule and high levels of corruption are critical to understanding the complex nature of these conflicts. Specifically, people do not necessarily view the state as a benign agent acting in the best interest of individuals or communities (Meredith, 2011). Since the implementation of the co-management legislation, local communities now have the potential to capture more of the benefits from reserved use, for example by charging tourists access fees to go snorkeling. Additionally, resource users may also have other incentives to develop marine reserves, such as formal recognition of rights over resources, social status, and increased access to donor funding. Although it is not possible to ascribe causation, we believe that this expansion of community-based reserves was also facilitated by various learning platforms, such as site visits to communitybased protected areas in neighboring countries (e.g., Wells et al., 2007) and an annual community leader, government and NGO ‘‘Fishers’ Forum’’ that presented fishers with the results of ecological and socioeconomic studies conducted along the coast.

Table 2 Cumulative Links Mixed Model (CLMM) results of changes to resource users’ perceptions of co-management over time. df Perception on livelihood (LR.stat(1) = 25.738, p < 0.0001***) Model 1: year + (1jcommunity) 7 Null model: 1 + (1jcommunity) 6

logLik

AIC

dAIC

wAIC

475.26 488.13

964.53 988.27

0 23.74

0.999993 7.00E-06

df = Degrees of freedom; logLik = the log likelihood ratio statistic; AIC is the Akaike information Criteria; dAIC is the difference in AIC between the two models. The delta AIC (dAIC) value is substantially greater than two, suggesting that the model 1 (which includes year) outperforms the null model; wAIC is the model weight, which highly favors model 1. Table 3 Generalized linear mixed model (GLMM) results examining whether the average number of training events a leader has attended has changed between 2008 and 2012. Model

k

logLik

AIC

dAIC

wAIC

BIC

dBIC

wBIC

pcdev

Model 1: Year + (1jcommunity) Null Model: 1 + (1jcommunity)

4 3

25.88 27.99

59.77 61.98

0 2.21

0.75 0.25

62.6 64.1

0 1.50

0.679 0.321

7.52 0

k = Number of parameters in the model; logLik = the log likelihood ratio statistic; AIC is the Akaike information Criteria; dAIC is the difference in AIC between the two models. The delta AIC (dAIC) value is greater than two, suggesting that the model 1 (which includes year) outperforms the null model; wAIC is the model weight, which favors model 1 over the null model.

J.E. Cinner, T.R. McClanahan / Global Environmental Change 30 (2015) 133–139

These types of learning platforms have been identified as critical aspects of successful governance transformations and adaptive comanagement (Berkes, 2009; Gelcich et al., 2010; Osterblom et al., 2010). For example, by hearing about the status of a number of landing sites in the Fishers’ Forum, fishers learned about their relative position in terms of the status of resource conditions, profits from fisheries, socioeconomic status, and perceptions about the causes of fisheries decline and options for management. Critically, this Fishers’ Forum also provided an open and transparent arena whereby results from case studies of early experimentation with community-based protected areas, gear restrictions, and other forms of management could be communicated, evaluated, and questioned. A key and surprising finding from this study is that initial perceptions among resource users that the co-management process created winners (those that benefited from co-management) and losers (those who felt it was detrimental to their livelihood) changed dramatically over time: after 6 years, there were virtually no resource users who felt that co-management was detrimental to their livelihood. The mechanisms behind this shift are unclear. It is plausible that the co-management losers were marginalized and forced out, but qualitative discussions with resource users and BMU leaders did not reveal support for this explanation. It is more likely that, after the co-management process played out for several years, resource users were better able to navigate the policy change such that it did not detract from their livelihood. However, it is important to note that this research focused on the preliminary outcomes, and these perceptions may change again with time. Should the BMU policy be viewed as ‘successful’ for resource users? To provide insight into this, we examined how resource users perceived livelihood outcomes from co-management. Definitions and constructs of livelihoods can vary considerably, from narrower perspectives about occupations to broader concepts of identity and wellbeing. Importantly, in this study, the term livelihood was conceptualized as being broadly synonymous with wellbeing (e.g., Allison and Ellis, 2001). On one hand, the policy could be considered relatively unsuccessful at improving people’s livelihoods because after 6 years, a substantial majority (two-thirds) of resource users felt that the policy had not resulted in benefits for their livelihoods. Alternatively, the economic concept of Pareto efficiency suggests that a policy will be beneficial if you can make someone better off without making someone worse off. An adaptation of this, the Kaldor–Hicks criterion, is used in welfare economics when some people are made worse off by a policy, but could, in theory be compensated by those who were made better off. Importantly, in our study, only 3% of resource users perceived co-management as being detrimental to their livelihoods (after 6 years). Thus, according to the resource users themselves, Kenya’s co-management policy made 10 people better off (i.e. it was perceived to be beneficial to their livelihood) for every person it made worse off (i.e. perceived to be detrimental to their livelihood). Even considering that people tend to weigh losses more than gains, this policy still appears to create substantial benefits from a Kaldor–Hicks efficiency perspective. Our results also seem positive when compared with a study of the perceptions of recreational fishers three years after a major policy change that involved the re-zoning the Great Barrier Reef Marine Park in Australia (Sutton and Tobin, 2009). In Australia, which is widely considered to have the best-managed coral reef in the world, the majority of respondents also felt that the major policy change had no impact on their fishing activities. However very few fishers perceived that the rezoning improved their fishing, whereas nearly 30% of respondents in our study perceived a livelihood benefit, even in the early stages.

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Our findings echo important debates about the trade-offs created when benefits get unevenly distributed among individuals (i.e. winners and losers) and among scales (i.e. generating private versus public benefits) (Cinner et al., 2014; Grafton et al., 2009). We found that benefits were not evenly distributed, with some resource users perceiving co-management as detrimental and others perceiving it as beneficial. This perceived inequity could have implications on cooperation and compliance (Grafton et al., 2009). Previous studies have also demonstrated how resource users with different socioeconomic characteristics bear the costs or reap the benefits of co-management initiatives (Cinner et al., 2012b, 2014; MacNeil and Cinner, 2013), potentially reinforcing existing power dynamics between wealthier and poorer actors. Additionally, we found considerable heterogeneity in the generation of key public goods (e.g., benefits from conservation that could be shared by the public, Grafton et al., 2009), which only occurred in sites that developed community-based marine reserves. Our empirical investigation of the transformation toward participatory resource governance in Kenya was an important first step in providing quantitative evidence of how both societies and ecosystem can benefit from co-management over relatively short timeframes (6 years) – though these outcomes are clearly not uniform. Nevertheless, several caveats emerge from the dynamic nature of the governance transformations and social–ecological systems we studied. For example, the unforeseen and somewhat spontaneous development of many community-based marine reserves meant that Before–After–Control–Impact type analyses were simply not possible. Additionally, our goal was to highlight the short-term outcomes from the governance transformation, but continued research will be required to better understand how people’s perceptions may further change over time and whether these small community-based marine reserves can reach an ecological equilibrium close to that of larger reserves (Claudet et al., 2008). As more countries in Africa and further afield develop and implement fisheries co-management strategies, we suggest it will be important for scientists, managers, and the donors promoting co-management to coordinate so that the impacts that these policies have on both people and ecosystems can be rigorously evaluated using BACI type designs and over long (10–20 years) timeframes. This type of rigorous evaluation of co-management outcomes would require funding commitments extending well beyond typical funding cycles. 4.1. Challenges ahead Despite some positive initial outcomes for both resource users and marine ecosystems, the governance transformation toward comanagement in Kenya faces at least three serious challenges. First, although some community-based reserves are demonstrating resource recovery, BMUs alone are not necessarily leading to rapid improvements in their ecological conditions (Fig. 2a and b). Other small-scale fisheries co-management systems have demonstrated increased fish biomass, species richness, and density outside of notake marine reserves (Gelcich et al., 2012), but we have yet to see demonstrably positive ecological outcomes in Kenyan BMUs that did not establish marine reserves. Indeed, BMU leaders suggest that some sites are using the co-management process to actively encourage more fishing, rather than sustainably managing their fishery (Cinner et al., 2012a). For example, some communities have used the co-management system to encourage additional fishing by migrants because the migrants pay a fee to the BMU based on the amount of landed fish. Second, although government institutions, including the courts, have approved and upheld co-management by-laws, interviews with BMU leaders suggest that enforcement support from fisheries officials is sporadic and funds to cover enforcement costs are not

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available. Thus, devolution may have transferred enforcement costs from government to communities that cannot afford it (Davis and Ruddle, 2012; Gelcich et al., 2010; Ribot et al., 2006). Poaching was reported to be a particular problem where this lack of enforcement capacity is coupled with situations where neighboring communities do not recognize or respect the boundaries developed by the BMU system (Cinner et al., 2012a; Ostrom, 1990). Third, despite initial training programs run by both governments and civil society, the capacity of leaders (in terms of the types of leadership trainings they had received) had actually decreased over time. Government and donor-funded capacity building programs must provide continuing support to account for the dynamic turnover associated with the democratic leadership process. Together, these challenges highlight how socioeconomic and institutional capacities and conditions of communities are not always conducive to developing effective community-based marine reserves or successful co-management (Cinner et al., 2012b; Ostrom, 1990; Pollnac et al., 2010). The fragile gains made by Kenya’s transformation to co-management will not necessarily continue without substantial government and donor support. Indeed, the virtual lack of negative perceptions by resource users may provide a critical window of opportunity to strengthen comanagement (Be´ne´ et al., 2009). This strengthening will require substantial investments by governments, donors, and civil society in key areas such as institutional capacity building at the local level that provides training about navigating legal requirements, enforcement capacity, and transparency (especially in financial accounting). A key part of this capacity building will also be ensuring that co-management organizations are effectively nested within existing agencies to facilitate enforcement support, conflict resolution, and to organize co-management for sustainability rather than exploitation (Berkes, 2007; Cinner et al., 2012b; Ostrom, 1990). Donors and the government should also aim to foster adaptive co-management through the continued development of flexible by-laws informed by experimentation. Adaptive learning about the social–ecological system can be a critical feature of successful natural resource governance (Armitage et al., 2008b; Berkes, 2009; Folke et al., 2005). In Kenya, the annual Fishers’ Forum has served as an informal learning platform by regularly highlighting case studies detailing social and ecological outcomes associated with different types of fisheries restrictions and novel technologies, such as traps with escape slots (Gomes et al., 2013). Yet, attendance is often limited to leaders and investments could help to better disseminate information to frequently marginalized resource users (e.g., females and migrants), which may help ensure that local elites do not capture and hold vital information (Armitage et al., 2008a; Be´ne´ et al., 2009; Crona and Bodin, 2006). 5. Conclusion Early results from Kenya’s transformation toward more participatory resource governance suggest that, over time, comanagement can result in significant positive outcomes for both people and ecosystems. These outcomes are not, however, uniform. Only well complied with reserves demonstrated improvements in fish biomass or coral cover. Likewise, not all resource users perceived benefits from co-management, but after 6 years, virtually no resource users felt that it was detrimental to their livelihood. Despite some seemingly positive early outcomes, co-management should not be viewed as a panacea to Kenya’s fisheries challenges, but rather as one of many tools for improving the chances of achieving social–ecological sustainability (Be´ne´ et al., 2009; Blaikie, 2006). Critical questions remain about whether the extent of ecological recovery in Kenya will remain limited to

community-based marine reserves or whether, with proper capacity building and enforcement support, it could occur throughout BMUs. Acknowledgements The Australian Research Council, Western Indian Ocean Marine Science Association’s Marine Science for Management program, Tiffany Foundation, and the United Nations Food and Agricultural Organization (FAO) provided funding. A. Wamukota, N. Muthiga, C. Huchery, E. Darling, and A. Humphries provided data analyses and field assistance. Analyses were conducted by C. Huchery. NAJ Graham and C. Hicks provided helpful comments on earlier versions of this manuscript. Kenya’s Office of Science and Technology provided research clearance and Kenya Wildlife Service provided clearance to work in the Mombasa Marine National Park. References Alcala, A.C., Russ, G.R., 2006. No-take marine reserves and reef fisheries management in the Philippines: a new people power revolution. Ambio 35, 245–254. Allison, E.H., Ellis, F., 2001. 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