Supporting Information: J Cinner et al. Comanagement of coral reef social-ecological systems
Data collection methods
We studied 42 independent comanagement arrangements spanning five Indo-Pacific countries: Kenya, Tanzania, Papua New Guinea, Indonesia, and Madagascar. Some comanagement arrangements included multiple villages, leading to a total of 65 surveyed villages. Sites were purposively selected to represent a variety of governance systems and user characteristics, as well as social, economic, and political settings. We used purposive sampling to ensure variation in independent variables and to allow for causal inferences with relatively low levels of bias (1). Whereas purposive sampling is an appropriate strategy for exploratory studies such as this (1), caution should be used when interpreting our results because the villages were not selected randomly. A priori assumed success was not part of our site selection criteria but we did select one to two sites in each country where the authors had long-enduring (i.e. 10-25 years) relationships as research scientists and were intimately familiar with the local ecology, culture, and institutions (these sites were not necessarily considered successful). The exception to our purposive sampling strategy was Kenya, where sites were randomly selected from a list of 33 pilot comanagement institutions. Random selection was feasible in Kenya because a comprehensive list of comanagement sites was available and the relatively small coastline meant it was feasible to study any site on the list. These conditions were not present in the other countries we studied and we consequently used purposive sampling. In these types of linked social-ecological systems studies, it is not necessarily feasible to have strict control sites (i.e. there may not be a similar unmanaged site with social and ecological characteristics that are both comparable). Likewise, given the long history of some of the management systems we have studied (e.g. formal recognition since the 17th century 2), before and after management experiments were clearly not possible. Nevertheless, we have done everything possible to reduce bias from our sampling strategy. This type of field-based comparative study has important advantages over meta-analyses of published literature (3) because it is more likely to fit the statistical assumptions of haphazard or random selection of treatments and not subject to publication bias (i.e. only publishing studies of comanagement where there is a significant positive result).
To gather information and triangulate results in each study site, we employed a combination of household surveys, semi-structured interviews with key informants (community leaders, resource users, and other stakeholders), and analyses of secondary sources such as population censuses (Table S1). All interviews were conducted in the local language by highly trained scientists from the respective countries. In total, we conducted 1374 household surveys (of which 960 were resource users), 53 key informant interviews, 54 community leader interviews, and 51 organizational leader interviews. These interviews provided information on 22 covariate attributes relating to the local governance system; the social, economic, and political setting; and the socioeconomic characteristics of resource users in each community (Fig. S1, Table S1).
Fig. S1. Social-ecological system attributes, grouped according to classifications described by Ostrom (4, 5). The social-ecological system is organized into several key sub-components, including: the governance system (GS), consisting of the institutional design and the operational rules in use; key socioeconomic characteristics of the resource users (U), which incorporates issues such as poverty and dependence on resources; the social, economic and political setting (S) in which they both operate; and the social and ecological outcomes (O) resulting from the interactions of the other sub-components. Bold font indicates components according to Ostroms classification, followed by a summary of how they have been measured in this study (further details in Table S1). Dotted lines indicate potential inter-relationships between system components (4, 5), although co-linearity measures were minimal (SI).
* Denotes the variable was not included in the final analysis
Key informant interviews were conducted using a semi-structured interview form in their native languages. Key informants were selected using non-probability sampling techniques, such as convenience sampling (for example, a respondent may be approached during resource use activities) (6). Between one and five key informants were interviewed per comanagement site. Community walk-throughs were also used to identify new issues and verify responses from surveys (7). Secondary sources, such as previous studies, local by-laws, population censuses, etc. were examined to gather information on operational rules in use, and population size (Table S1).
Two sampling strategies were used to target resource users. In Kenya and some Indonesian villages, where it was not feasible to survey enough resource users using household surveys within the community (due, for example, to low numbers of fishing households), respondents were randomly selected from lists of resource users provided by comanagement leaders. Lists were cross-referenced with other fishermen for accuracy. In all other sites, households were systematically surveyed, whereby a sampling fraction of every ith house (e.g. 2nd, 3rd, 4th) was determined by dividing the total village population by the desired sample size (6). Variance from the systematic sample was assumed to be equal to the estimated variance based on a simple random sample (8). For the purposes of this study, we only examined resource users, so households that did not engage in marine resource use were dropped from further analysis. After dropping non-resource user households, the average number of resource users surveyed per community was 23, but ranged between 7 and 75.
Operationalization of indicators
We collected data on 22 institutional and socioeconomic covariates (16 of which remained in the final results) and three comanagement outcomes. These indicators were developed to operationalize Ostroms diagnostic framework for social-ecological systems (4, 5) (Fig. S1, Table S1). This framework organizes a social-ecological system into several key sub-components, including: the governance system (GS); key socioeconomic characteristics of the resource users (U); the social, economic and political setting (S) in which the system operates; aspects of the resource and resource system, and the social and ecological outcomes (O) resulting from the interactions of the other sub-components (Fig. S1, Table S1). Our study focuses on a single resource system, shallow-water coral reef fisheries, to standardise for a number of resource characteristics (e.g. the productivity, mobility, and predictability of the resource being managed) thought to influence the success of common property institutions (5) (Table S1).
Governance System (GS)
Governance system covariates were primarily those associated with Ostroms institutional design principles (9).
Operational rules. All comanagement arrangements provided members with de jure or de facto rights to develop and enforce at least one of the following operational rules: fishery closures, gear restrictions, temporal closures, and restricted access of non-members. Each operational rule was a covariate in the analysis, except for gear management, which was related to at least one other variable.
Existence of clearly defined resource boundaries was recorded as yes or no, depending on whether all key informants agreed that there has never been confusion about the boundaries. In cases where there has been confusion, the interviewee was probed for further details and where possible, court cases or other documents were examined. Likewise, clearly defined membership was also recorded as yes or no depending on whether key informants agreed that there has not been confusion over who are members of the organization involved in comanagement.
Collective choice rules. Respondents participation in resource management decision-making was examined by asking them how they participated in decisions about resource management and classifying responses as: 0= no attendance; 1= passive attendance (e.g. attend meetings but do not talk or participate) and; 2= active participations (e.g. elected role, actively voice opinions in meetings etc.).
Monitoring and sanctioning processes. A comanagement site was considered to have graduated sanctions when key informants and community leaders affirmed that sanctions increased with the severity or number of offences committed. The effectiveness of conflict resolution mechanisms was examined by asking key informants and organizational leaders whether mechanisms were in place to resolve conflicts between organizational members. If so, they were asked whether they had successfully resolved none, few, half, most, or all of the conflicts. These responses were treated as a five point ordinal scale of the effectiveness of resolving conflicts. Having no conflict resolution mechanisms in place was considered a lower ordinal level than one that was in place, but was unable to effectively resolve any conflicts.
User characteristics (U)
Number of users. Population size was taken from local census information or gathered from our surveys by multiplying the average household size by the total number of households in the community. We also looked at human population density from the Socioeconomic Data and Applications Center (SEDAC) gridded population of the world database (available Online http://sedac.ciesin.org/gpw/global.jsp). Geograph
