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Co-management constitutes a certain type of institutional arrangement that has gained increased attention among both policy makers and researchers involved in the field of natural resource management. Yet the concept of co-management is broad, and our knowledge about how different kinds of management structures affect the ability to deal with chall...
Contexts in source publication
Context 1
... the structural holes argument emphasizes the importance of bridges between otherwise unconnected actors, or sets of actors, for the sake of mobilizing diversified resources and increasing performance (Burt 2000). Similar ideas have been proposed by, for example, Granovetter (1973) and Reagans and McEvily (2003). Carlsson and Sandström (2008) used the concept of network heterogeneity (Reagans and Zuckerman 2001), which refers to networks that consist of a rich diversity of different types of actors involved in extensive cross-border collaboration to capture this structural feature empirically. We also use heterogeneity as a proxy for bridges over structural holes, because the methodological approach fails to capture these links. The reason for this stems from the theoretical notion of co-management networks as institutional entities. Institutions are the rules of the game (North 1990), or the prescriptions that organize repetitive and structured interactions among stakeholders (Ostrom 2005). Accordingly, institutional structures are assumed to be composed of more stable connections, as stability and regularity are prerequisites for institutional processes to evolve. At the same time, bridging ties are essentially weaker (Granovetter 1973, Friedkin 1980). Thus, the empirical unit of analysis, as it is understood here, i.e., the co-management network forming the rules of the game, does not include these bridging ties. To deal with this problem, it is assumed that co-management networks that involve a rich diversity of actors, representing various sectors of society, will accordingly also include many bridging ties, although these are not measured explicitly using the research design applied here (see Sandström 2008). We approach network heterogeneity as enhancing the acquisition of relevant resources in co- management, for example, ecological knowledge. Thus, both closure and heterogeneity are tentatively positively correlated with the important organizing functions of problem definition, prioritization, and resource mobilization in the management process (Sandström and Carlsson 2008). The conceptual reasoning regarding closure and heterogeneity is comparable with the discussion on bonding and bridging ties in social capital theory (Woolcook and Narayan 2000, Crona and Bodin 2008). If adaptive management is defined as an active process in which rules are revised and changed based on a continuous inflow of ecological knowledge, the achievement of such a process can easily be related to the two network features discussed above. The general hypothesis is that although network heterogeneity facilitates access to different types of ecological knowledge, network closure promotes the ability to set, maintain, and monitor common management rules. Sandström and Rova (2010) studied this hypothesis in a single case study of a fishery co-management network. The empirical findings concurred with the theory, in the sense that the hypothesis could not be falsified. Yet, the limitations of a single case-study design called for more research. With the point of departure in the theoretical framework described above, this study sets out to continue our search for more knowledge about the relationship between closure, heterogeneity, and adaptability in natural resource management. Thus, the research question we posed earlier can be reformulated and further specified: do network closure and heterogeneity relate to adaptability and, if so, in what respect? Two measures, namely, density and centralization, are used as empirical indicators of network closure. These measures reflect how well connected a network is. Density is calculated by dividing the number of present connections with the maximum number of possible connections (Scott 2000). Structures like Network A (Fig. 2), in which all actors are completely connected, have a density of 1. Networks might also be well connected and characterized by closure through a coordinating actor, and this structural aspect is measured by network centralization. Different notions of centralization exist (Bonacich 1987, Freeman 1978–1979,Freeman et al. 1979–1980, Friedkin 1991, Wasserman and Faust 1994). For our purposes, we use the concept of “degree centralization.” Centralization can be explained as a calculation in several steps that starts at the individual level. First, the centrality of each individual actor is examined by counting the number of direct links connecting an actor, ascribing the most connected actor the highest centrality value. Second, the variation in centrality values is determined by summarizing the differences among the most central actor and every other actor in the network. This sum is then divided by a theoretical value reflecting the maximum possible sum of differences (Wasserman and Faust 1994, Scott 2000). Thus, network centralization reflects to what extent one actor is central for the management activities, or how “star-like” the structure is. Network B (Fig. 2) illustrates a network with the highest centralization level possible, i.e., 100%. High density and centralization levels are considered as empirical measures of network closure. Network heterogeneity is captured here by two measures: actors’ diversity and cross-boundary exchange (Sandström and Carlsson 2008). A similar approach was used by Reagans and Zuckerman (2001). Actors’ diversity is calculated by counting the number of organizations represented in the network. The cross-boundary character of the network is examined by calculating the percentage of network ties connecting actors from different organizations. The number of ties connecting actors with different affiliations is divided by the total number of connections in the network. Together, these two measures reflect the diversity of resources available and how these are exchanged. Thus, a network with many links among different types of actors, or actors representing different types of organizations, is perceived as heterogeneous. See, for example, Network C in Fig 2., where different shades of grey reflect different organizations. Closure is a compound measure, determined through density and decentralization. Likewise, heterogeneity is a compound measure, determined by one structural measure, that is, cross-boundary exchange, and one non-structural measure, that is, actors’ diversity. The adaptability of management is determined here by analyzing how the respondents describe the rule- making processes (Appendix 1). The following topics and questions guide the interpretation: (1) Framework of rules: are there rules that regulate access to and appropriation of the resource? If so, are these rules known, used, accepted, and followed by the users? These questions are determined by analyzing the actors’ responses to questions 8–9, 15–19, and 25–28 in Appendix 1. (2) Ecological knowledge: do actors involved in the rule-making process consider the resource system to be complex, non-linear, and characterized by uncertainty? Are observations, experiments, and learning important parts of the rule-making process? These questions are determined by analyzing the actors’ responses to questions 10–14 in Appendix 1. (3) Knowledge and the formulation of rules: are rules continuously changed in reaction to existing ecological knowledge? Do the conditions of the ecosystem constitute criteria for when and how rules are altered? These questions are determined by analyzing the actors’ responses to questions 23–24 in Appendix 1. Affirmative answers to the thematic questions above indicate that the management process is adaptive. Fishing rights in the inland and coastal waters of Sweden are connected to properties and belong to various types of actors: private persons, companies, municipalities, the church, or the state. Often, several property owners have fishing rights in the same waters. To handle these sometimes very complicated ownership patterns, and to enhance the possibility to commonly manage the waters, FCAs can be established (Fishery Conservation Areas Act 1981:533, Dyhre and Edlund 1982). An FCA is a state-regulated management regime that incorporates the fishing rights of all owners within a certain geographical area. The access and appropriation rules are jointly set, formally, during annual summits where fishery-rights owners are entitled to participate. Between those meetings, an elected board is responsible for the operational work (Fishery Conservation Areas Act 1981:533). Thus, in administrative terms, a FCA is a property-based co-management system (Piriz 2005). We conducted a comparative analysis of co- management networks within two FCA situated in the middle and inland parts of Sweden. A co- management network is defined as the social network of actors involved in the rule-making process. In accordance with the methodological bottom-up perspective, the real rule-making structure might in fact involve other actors and constitute other power relations than what is depicted by the formal legal framework briefly presented above (Hull and Hjern 1987, Hjern and Porter 1997, Carlsson 2000). For example, a previous study has shown that the management process of an FCA might be characterized by deliberate elements, i.e., discussions, bargaining, and resource exchange, among both fishery-rights owners, i.e., those who are mandated to rule by law, and other interested stakeholders (Sandström and Rova 2010). To clarify, a person can be a fishery- rights owner without being an actor; likewise, a person can be an actor while lacking the formal mandate to govern. This is why the social network of actors involved in the management process, and not the elected board or the set of formal property owners, constitute the unit of analysis used here. We empirically define an involved actor as a person involved in regular discussions and communications concerning the rules of the FCA. Thus, by mapping the communication patterns among actors, the rule- ...
Context 2
... are assumed to be composed of more stable connections, as stability and regularity are prerequisites for institutional processes to evolve. At the same time, bridging ties are essentially weaker (Granovetter 1973, Friedkin 1980). Thus, the empirical unit of analysis, as it is understood here, i.e., the co-management network forming the rules of the game, does not include these bridging ties. To deal with this problem, it is assumed that co-management networks that involve a rich diversity of actors, representing various sectors of society, will accordingly also include many bridging ties, although these are not measured explicitly using the research design applied here (see Sandström 2008). We approach network heterogeneity as enhancing the acquisition of relevant resources in co- management, for example, ecological knowledge. Thus, both closure and heterogeneity are tentatively positively correlated with the important organizing functions of problem definition, prioritization, and resource mobilization in the management process (Sandström and Carlsson 2008). The conceptual reasoning regarding closure and heterogeneity is comparable with the discussion on bonding and bridging ties in social capital theory (Woolcook and Narayan 2000, Crona and Bodin 2008). If adaptive management is defined as an active process in which rules are revised and changed based on a continuous inflow of ecological knowledge, the achievement of such a process can easily be related to the two network features discussed above. The general hypothesis is that although network heterogeneity facilitates access to different types of ecological knowledge, network closure promotes the ability to set, maintain, and monitor common management rules. Sandström and Rova (2010) studied this hypothesis in a single case study of a fishery co-management network. The empirical findings concurred with the theory, in the sense that the hypothesis could not be falsified. Yet, the limitations of a single case-study design called for more research. With the point of departure in the theoretical framework described above, this study sets out to continue our search for more knowledge about the relationship between closure, heterogeneity, and adaptability in natural resource management. Thus, the research question we posed earlier can be reformulated and further specified: do network closure and heterogeneity relate to adaptability and, if so, in what respect? Two measures, namely, density and centralization, are used as empirical indicators of network closure. These measures reflect how well connected a network is. Density is calculated by dividing the number of present connections with the maximum number of possible connections (Scott 2000). Structures like Network A (Fig. 2), in which all actors are completely connected, have a density of 1. Networks might also be well connected and characterized by closure through a coordinating actor, and this structural aspect is measured by network centralization. Different notions of centralization exist (Bonacich 1987, Freeman 1978–1979,Freeman et al. 1979–1980, Friedkin 1991, Wasserman and Faust 1994). For our purposes, we use the concept of “degree centralization.” Centralization can be explained as a calculation in several steps that starts at the individual level. First, the centrality of each individual actor is examined by counting the number of direct links connecting an actor, ascribing the most connected actor the highest centrality value. Second, the variation in centrality values is determined by summarizing the differences among the most central actor and every other actor in the network. This sum is then divided by a theoretical value reflecting the maximum possible sum of differences (Wasserman and Faust 1994, Scott 2000). Thus, network centralization reflects to what extent one actor is central for the management activities, or how “star-like” the structure is. Network B (Fig. 2) illustrates a network with the highest centralization level possible, i.e., 100%. High density and centralization levels are considered as empirical measures of network closure. Network heterogeneity is captured here by two measures: actors’ diversity and cross-boundary exchange (Sandström and Carlsson 2008). A similar approach was used by Reagans and Zuckerman (2001). Actors’ diversity is calculated by counting the number of organizations represented in the network. The cross-boundary character of the network is examined by calculating the percentage of network ties connecting actors from different organizations. The number of ties connecting actors with different affiliations is divided by the total number of connections in the network. Together, these two measures reflect the diversity of resources available and how these are exchanged. Thus, a network with many links among different types of actors, or actors representing different types of organizations, is perceived as heterogeneous. See, for example, Network C in Fig 2., where different shades of grey reflect different organizations. Closure is a compound measure, determined through density and decentralization. Likewise, heterogeneity is a compound measure, determined by one structural measure, that is, cross-boundary exchange, and one non-structural measure, that is, actors’ diversity. The adaptability of management is determined here by analyzing how the respondents describe the rule- making processes (Appendix 1). The following topics and questions guide the interpretation: (1) Framework of rules: are there rules that regulate access to and appropriation of the resource? If so, are these rules known, used, accepted, and followed by the users? These questions are determined by analyzing the actors’ responses to questions 8–9, 15–19, and 25–28 in Appendix 1. (2) Ecological knowledge: do actors involved in the rule-making process consider the resource system to be complex, non-linear, and characterized by uncertainty? Are observations, experiments, and learning important parts of the rule-making process? These questions are determined by analyzing the actors’ responses to questions 10–14 in Appendix 1. (3) Knowledge and the formulation of rules: are rules continuously changed in reaction to existing ecological knowledge? Do the conditions of the ecosystem constitute criteria for when and how rules are altered? These questions are determined by analyzing the actors’ responses to questions 23–24 in Appendix 1. Affirmative answers to the thematic questions above indicate that the management process is adaptive. Fishing rights in the inland and coastal waters of Sweden are connected to properties and belong to various types of actors: private persons, companies, municipalities, the church, or the state. Often, several property owners have fishing rights in the same waters. To handle these sometimes very complicated ownership patterns, and to enhance the possibility to commonly manage the waters, FCAs can be established (Fishery Conservation Areas Act 1981:533, Dyhre and Edlund 1982). An FCA is a state-regulated management regime that incorporates the fishing rights of all owners within a certain geographical area. The access and appropriation rules are jointly set, formally, during annual summits where fishery-rights owners are entitled to participate. Between those meetings, an elected board is responsible for the operational work (Fishery Conservation Areas Act 1981:533). Thus, in administrative terms, a FCA is a property-based co-management system (Piriz 2005). We conducted a comparative analysis of co- management networks within two FCA situated in the middle and inland parts of Sweden. A co- management network is defined as the social network of actors involved in the rule-making process. In accordance with the methodological bottom-up perspective, the real rule-making structure might in fact involve other actors and constitute other power relations than what is depicted by the formal legal framework briefly presented above (Hull and Hjern 1987, Hjern and Porter 1997, Carlsson 2000). For example, a previous study has shown that the management process of an FCA might be characterized by deliberate elements, i.e., discussions, bargaining, and resource exchange, among both fishery-rights owners, i.e., those who are mandated to rule by law, and other interested stakeholders (Sandström and Rova 2010). To clarify, a person can be a fishery- rights owner without being an actor; likewise, a person can be an actor while lacking the formal mandate to govern. This is why the social network of actors involved in the management process, and not the elected board or the set of formal property owners, constitute the unit of analysis used here. We empirically define an involved actor as a person involved in regular discussions and communications concerning the rules of the FCA. Thus, by mapping the communication patterns among actors, the rule- making co-management network is captured. The current study was conducted in the autumn and winter of 2007 and 2008. Data describing the two co-management networks with regard to network structure and adaptability were collected through numerous steps (see Fig. 1). To start with, a qualitative interview study was conducted to learn about the management processes and to start the identification of involved actors (Appendix 1). The respondents were selected using a “snowballing interview technique” (Miles and Huberman 1994), starting with the chairs of the boards and subsequently letting respondents nominate additional respondents. The respondents were asked to name other actors involved in management. The identified persons that were considered as important for the management process were then interviewed, and this process continued until no new actors were ascribed to any central role in management. Seven semistructured interviews were carried out in Network A, and eight interviews were conducted with people from Network B. The ...
Context 3
... For the sake of determining adaptability, we analyze the management processes in relation to existing management rules, prevailing ecological knowledge, and the link between knowledge and rule-making. The adoption of these concepts and measures is described below. The reasoning specifying the tentative relationship between structure and adaptability is primarily adopted from Burt (2000), who suggests that two structural features affect co-management performance, namely, “network closure” and “structural holes.” The concept of network closure refers to structures that are well-integrated, either directly through many connections, or indirectly through coordinating actors (Burt 2000). A closed structure promotes collaboration and facilitates the creation of a common priority process. This idea is closely associated with Coleman’s (1990) notion of effective norm-generation and trust-building within closed structures, or Lin’s (2001) proposition regarding the strengths of strong ties for expressive action. For our purposes, closure is assumed to increase the capacity of a co-management network to establish, uphold, and maintain the rules of the game. On the other hand, the structural holes argument emphasizes the importance of bridges between otherwise unconnected actors, or sets of actors, for the sake of mobilizing diversified resources and increasing performance (Burt 2000). Similar ideas have been proposed by, for example, Granovetter (1973) and Reagans and McEvily (2003). Carlsson and Sandström (2008) used the concept of network heterogeneity (Reagans and Zuckerman 2001), which refers to networks that consist of a rich diversity of different types of actors involved in extensive cross-border collaboration to capture this structural feature empirically. We also use heterogeneity as a proxy for bridges over structural holes, because the methodological approach fails to capture these links. The reason for this stems from the theoretical notion of co-management networks as institutional entities. Institutions are the rules of the game (North 1990), or the prescriptions that organize repetitive and structured interactions among stakeholders (Ostrom 2005). Accordingly, institutional structures are assumed to be composed of more stable connections, as stability and regularity are prerequisites for institutional processes to evolve. At the same time, bridging ties are essentially weaker (Granovetter 1973, Friedkin 1980). Thus, the empirical unit of analysis, as it is understood here, i.e., the co-management network forming the rules of the game, does not include these bridging ties. To deal with this problem, it is assumed that co-management networks that involve a rich diversity of actors, representing various sectors of society, will accordingly also include many bridging ties, although these are not measured explicitly using the research design applied here (see Sandström 2008). We approach network heterogeneity as enhancing the acquisition of relevant resources in co- management, for example, ecological knowledge. Thus, both closure and heterogeneity are tentatively positively correlated with the important organizing functions of problem definition, prioritization, and resource mobilization in the management process (Sandström and Carlsson 2008). The conceptual reasoning regarding closure and heterogeneity is comparable with the discussion on bonding and bridging ties in social capital theory (Woolcook and Narayan 2000, Crona and Bodin 2008). If adaptive management is defined as an active process in which rules are revised and changed based on a continuous inflow of ecological knowledge, the achievement of such a process can easily be related to the two network features discussed above. The general hypothesis is that although network heterogeneity facilitates access to different types of ecological knowledge, network closure promotes the ability to set, maintain, and monitor common management rules. Sandström and Rova (2010) studied this hypothesis in a single case study of a fishery co-management network. The empirical findings concurred with the theory, in the sense that the hypothesis could not be falsified. Yet, the limitations of a single case-study design called for more research. With the point of departure in the theoretical framework described above, this study sets out to continue our search for more knowledge about the relationship between closure, heterogeneity, and adaptability in natural resource management. Thus, the research question we posed earlier can be reformulated and further specified: do network closure and heterogeneity relate to adaptability and, if so, in what respect? Two measures, namely, density and centralization, are used as empirical indicators of network closure. These measures reflect how well connected a network is. Density is calculated by dividing the number of present connections with the maximum number of possible connections (Scott 2000). Structures like Network A (Fig. 2), in which all actors are completely connected, have a density of 1. Networks might also be well connected and characterized by closure through a coordinating actor, and this structural aspect is measured by network centralization. Different notions of centralization exist (Bonacich 1987, Freeman 1978–1979,Freeman et al. 1979–1980, Friedkin 1991, Wasserman and Faust 1994). For our purposes, we use the concept of “degree centralization.” Centralization can be explained as a calculation in several steps that starts at the individual level. First, the centrality of each individual actor is examined by counting the number of direct links connecting an actor, ascribing the most connected actor the highest centrality value. Second, the variation in centrality values is determined by summarizing the differences among the most central actor and every other actor in the network. This sum is then divided by a theoretical value reflecting the maximum possible sum of differences (Wasserman and Faust 1994, Scott 2000). Thus, network centralization reflects to what extent one actor is central for the management activities, or how “star-like” the structure is. Network B (Fig. 2) illustrates a network with the highest centralization level possible, i.e., 100%. High density and centralization levels are considered as empirical measures of network closure. Network heterogeneity is captured here by two measures: actors’ diversity and cross-boundary exchange (Sandström and Carlsson 2008). A similar approach was used by Reagans and Zuckerman (2001). Actors’ diversity is calculated by counting the number of organizations represented in the network. The cross-boundary character of the network is examined by calculating the percentage of network ties connecting actors from different organizations. The number of ties connecting actors with different affiliations is divided by the total number of connections in the network. Together, these two measures reflect the diversity of resources available and how these are exchanged. Thus, a network with many links among different types of actors, or actors representing different types of organizations, is perceived as heterogeneous. See, for example, Network C in Fig 2., where different shades of grey reflect different organizations. Closure is a compound measure, determined through density and decentralization. Likewise, heterogeneity is a compound measure, determined by one structural measure, that is, cross-boundary exchange, and one non-structural measure, that is, actors’ diversity. The adaptability of management is determined here by analyzing how the respondents describe the rule- making processes (Appendix 1). The following topics and questions guide the interpretation: (1) Framework of rules: are there rules that regulate access to and appropriation of the resource? If so, are these rules known, used, accepted, and followed by the users? These questions are determined by analyzing the actors’ responses to questions 8–9, 15–19, and 25–28 in Appendix 1. (2) Ecological knowledge: do actors involved in the rule-making process consider the resource system to be complex, non-linear, and characterized by uncertainty? Are observations, experiments, and learning important parts of the rule-making process? These questions are determined by analyzing the actors’ responses to questions 10–14 in Appendix 1. (3) Knowledge and the formulation of rules: are rules continuously changed in reaction to existing ecological knowledge? Do the conditions of the ecosystem constitute criteria for when and how rules are altered? These questions are determined by analyzing the actors’ responses to questions 23–24 in Appendix 1. Affirmative answers to the thematic questions above indicate that the management process is adaptive. Fishing rights in the inland and coastal waters of Sweden are connected to properties and belong to various types of actors: private persons, companies, municipalities, the church, or the state. Often, several property owners have fishing rights in the same waters. To handle these sometimes very complicated ownership patterns, and to enhance the possibility to commonly manage the waters, FCAs can be established (Fishery Conservation Areas Act 1981:533, Dyhre and Edlund 1982). An FCA is a state-regulated management regime that incorporates the fishing rights of all owners within a certain geographical area. The access and appropriation rules are jointly set, formally, during annual summits where fishery-rights owners are entitled to participate. Between those meetings, an elected board is responsible for the operational work (Fishery Conservation Areas Act 1981:533). Thus, in administrative terms, a FCA is a property-based co-management system (Piriz 2005). We conducted a comparative analysis of co- management networks within two FCA situated in the middle and inland parts of Sweden. A co- management network is defined as the social network of actors involved in the ...
Citations
... We visited these occupational groups and interacted with them for possible inclusion in the study. Inclusion of occupational groups in the study was based on: 1) the three occupational sectors of the economy such as agriculture, service and industry; 2) membership ties and activeness of the group, measured by frequency of meetings and payment of membership dues over the last three years (2015-2017), as evidence shows that such groups perform better than groups with fewer ties [30,31]; 3) decentralised communication pattern; and 4) high member heterogeneity, density, and whole-network centrality [32][33][34]. ...
Background
Enrolment of informal sector workers in Ghana’s National Health Insurance Scheme (NHIS) is critical to achieving increased risk-pooling and attainment of Universal Health Coverage. However, the NHIS has struggled over the years to improve enrolment of this subpopulation. This study analysed effect of social capital on enrolment of informal sector workers in the NHIS.
Methods
A cross-sectional survey was conducted among 528 members of hairdressers and beauticians, farmers, and commercial road transport drivers’ groups. Descriptive statistics, principal component analysis, and multinomial logit regression model were used to analyse the data.
Results
Social capital including membership in occupational group, trust, and collective action were significantly associated with enrolment in the NHIS, overall. Other factors such as household size, education, ethnicity, and usual source of health care were, however, correlated with both enrolment and dropout. Notwithstanding these factors, the chance of enrolling in the NHIS and staying active was 44.6% higher for the hairdressers and beauticians; the probability of dropping out of the scheme was 62.9% higher for the farmers; and the chance of never enrolling in the scheme was 22.3% higher for the commercial road transport drivers.
Conclusions
Social capital particularly collective action and predominantly female occupational groups are key determinants of informal sector workers’ participation in the NHIS. Policy interventions to improve enrolment of this subpopulation should consider group enrolment, targeting female dominated informal sector occupational groups. Further studies should consider inclusion of mediating and moderating variables to provide a clearer picture of the relationship between occupational group social capital and enrolment in health insurance schemes.
... Paying attention to the network formed by actors engaged in collaboration, that is, who the actors are and how they interact, is one way to elucidate why some kinds of co-management arrangements seem to be more successful than others (Carlsson and Sandström 2008, Bodin and Crona 2009, Sandström and Rova 2010, Bodin 2017. In turn, network structures can evidence the presence of social capital and leadership proposed as necessary preconditions for collective action (Bodin and Crona 2008, Gutierrez et al. 2011. ...
... The average edge weight was calculated as a first step in the analysis. Only edges equal to or greater than the average weight were considered (Appendix 3) because the reported information's accuracy is improved with the use of stronger ties (Freeman 1977, Wasserman and Faust 1994, Sandström and Rova 2010. The visual representation of the networks was adjusted using the force-directed Fruchterman and Reingold layout algorithm (Fruchterman and Reingold 1991), denoting that nodes closer to each other share more connections among them. ...
... Collaborative governance is one of the most promising ways to address environmental problems (Bodin 2017). Actors' collaboration will determine network structures that would shape different co-management processes and outcomes (Bodin et al. 2006, Carlsson and Sandström 2008, Sandström and Rova 2010). Then, the success or failure of co-management network performance will be associated with how this network is structured (Bodin andCrona 2009, Alexander et al. 2015). ...
... These systems can have structural variations that lead users to exhibit different collaborative responses to specific socio-ecological contexts (Albornoz & Glückler, 2020). At the community level, networks serve as a reliable and flexible structure for collaboration in which user expectations and formal management arrangements interact (Newman & Dale, 2005;Sandström & Rova, 2010;Tompkins & Adger, 2004). Local co-management associations are official organisations because they have formal rules and procedures. ...
By introducing Territorial Use Rights for Fisheries (TURF), the Chilean government has devolved authority over the appropriation of benthic fisheries to local fishers' organisations. Yet there is little evidence of how this local governance works for membership organisations. Drawing on the theory of lateral network governance, the role of legitimacy in governance outcomes is examined by conducting a comparative case study of two TURF networks in northern Chile. Counterintuitively, more effective governance outcomes were found in the TURF network characterised by a less favourable legitimacy structure of decision-making than the case with a better legitimacy structure. Considering context and network evolution, it is suggested that although organisational renewal and high membership turnover potentially fragment legitimacy, they also enable novel collective action and better governance outcomes. The observed divergence of actual legitimacy from formal governance structure underscores the need for dynamic analysis of collective resource governance beyond the formal chart.
... Recent studies have investigated which kinds of social network structures better accommodate collaborative management to deal with uncertainty and change. Sandström and Rova (2010) have argued that adaptability can be expected to be higher in comanagement systems with higher levels of network closure (i.e., high density and/or centralization). Similarly, Oyanedel et al. (2016) found that collective action among heterogeneous stakeholders is facilitated by higher levels of network cohesion, which creates enhanced flows of information and resources (i.e., density; see Bodin et al., 2006) and increased coordination capacity (i.e., centralization; see Crona et al., 2011). ...
... In the face of unprecedented environmental transformations, addressing questions about change, response and adaptation of governance networks within social-ecological systems is a priority. Such an effort implies moving from static to dynamic assessments and gathering longitudinal network data (see Sandström and Rova, 2010;Stein et al., 2011;Bodin et al., 2019). ...
... In this case, these actors imply also higher levels of heterogeneity, which has been considered a determinant feature of co-management adaptability. Higher diversity of players engaged increases the access to more varied sources of knowledge, ideas and resources (Sandström and Rova, 2010). ...
Recent studies have highlighted the relational nature of co-management and investigated which kinds of social network structures define its possibilities to perform, adapt and deal with uncertainty and change. However, there is less understanding about the impacts of disasters and abrupt perturbations on co-management networks. Here we present a social network analysis of the impacts of the 2010 tsunami on co-management in the Chilean fishery. Based on data collected in 21 fisher organizations in the Bio-Bío region, heavily impacted by the tsunami, we assess whether and how co-management facilitating and hindering social relationships have changed after the event, as compared to 16 non-impacted organizations in the Valparaíso region. Baseline data (i.e., 2008) from both regions allows for before-after longitudinal analysis. Our findings show that after the tsunami, co-management networks in Bio-Bío present reduced fragmentation and higher levels of perceived trust among actors in comparison to the non-affected region. A slightly lower tendency towards decentralization was also observed. These findings suggest that post-disaster adjustments have occurred within the same networks. Co-management networks were flexible enough to be rewired as a consequence of abrupt perturbations triggered by the tsunami. Participatory network-based interventions, such as the Chilean MEABR co-management policy, provide a stable and at the same time adaptive setting to respond to coastal disasters.
... As a result, many natural resources are managed through overlapping and co-existing management systems. These systems may include formal policies based on top-down approaches [4,5], adaptive co-management, [6,7], polycentric approaches [8] and/or informal traditional community-based systems [9,10]. If well managed, the co-existence of these systems could provide pathways to sustainability. ...
... Analysis of the nature of actors' interactions in a network is a prerequisite to assessing the effectiveness of the rangeland resource governance network (Bodin and Crona, 2009). The network structures (relational patterns) influence the behavior and actions of actors and the overall effectiveness of the governance system (Sandström & Rova, 2010). These network structural characteristics, which have strong functional implications for the resilience of the network, broadly include number of social ties, degree of cohesion, subgroup inter-linkages network centralization, and actor centrality (Bodin and Crona, 2009). ...
... In shedding light on how each of the network structural characteristics affect the overall performance of natural resource governance, the number of social ties, captured by network density, greatly affects the outcomes of the network governance as the more social ties tend to increase the possibilities of collaboration, mutual trust development and joint action (Sandström & Rova, 2010). The existence of higher network density also facilitates the co-production of knowledge that is useful in SES resilience building (Bodin and Crona, 2009). ...
... To identify actors' structural position, or coordinating actors that would otherwise have limited or no connections, we analyzed parameters of the network centrality. Network centrality measures how central or well-connected an actor is in a network (Sandström & Rova, 2010). It also describes the patterns of power relations and how much an actor has access to the resources in the network (Dkamela et al., 2014;Angst et al., 2018). ...
Effective natural resources governance plays a crucial role in enhancing the resilience of socio-ecological systems (SES) in the face of environmental changes. It is recognized that the ability to adaptively respond to complex environmental change and manage SES resilience resides in actors’ networks. Network forms of governance facilitate both horizontal and vertical interconnection of actors, bring different perspectives and sources of knowledge, and develop shared values and innovative solutions to problems. However, the structural pattern of actors’ collaborative linkages within the network strongly influences actors’ behavior and, hence, delivery and impacts of effective governance. We analyze social networks (SNA) among pastoralists in the Borana rangelands of Ethiopia to identify the structural gaps that result in misfits. Our quantitative SNA revealed a low level of network density with very few horizontal and vertical interactions and linkages among actors in the governance system, which considerably limits flows of knowledge, experiences, and other resources, leading to a failure to establish shared values and undertake joint action. Rangelands governance in Borana is further hampered by the absence of adequate network heterogeneity and solidarity that in turn blocks the building of collaborative planning and efficient use of available resources to address the complex problems of rangeland pastoralism. Our results suggest that a policy environment that can create conditions for greater collaboration, the strengthening of actors’ ties, and the development of trust and social capital enabling the design of effective collective governance should be developed.
... Further study is warranted on the relationship between best practice information and the type of fish, beyond the species level, under management. Second, the diversity raised questions about motivations and abilities that underpin local management, as also illustrated in other studies (e.g., Olsson & Folke, 2001;Sandström & Rova, 2010;Stensland, 2012). ...
... Overall, further studies of what and why local management organizations manage fish resources could reveal and clarify possible leverage points for improving best practice information as well as management in general (Daedlow et al., 2011;Klefoth et al., 2023;Sandström & Rova, 2010). ...
Catch-and-release (C&R) is a popular management tool that can support sustainable development of recreational fisheries, if anglers adopt scientifically informed “best practices.” However, although the role of best practices is widely established in the academic literature, this knowledge is not always disseminated to anglers. In this paper, we investigated if and to what extent local management organizations provided best practice information to anglers. Based on a sample of 331 Swedish organizations, we reviewed the websites through which these organizations sold fishing licenses. Our review demonstrated widespread use of C&R as a management tool yet a general lack of best practice information. Among the small fraction of organizations that mentioned best practices, most mentioned only a single practice, with little consistency among practices that received attention. In addition, best practice information was particularly lacking for pike (Esox Lucius) and perch (Perca fluviatilis), which are by far the most landed and released species nationally. We discovered major knowledge deficiencies that provide insights about where and how to focus efforts for improving best practice information, in the context of local recreational fisheries management.
... O envolvimento de diversos atores em redes de governança colaborativa, tais como proprietários e gestores de terras, funcionários de diferentes níveis de governo, cientistas, ativistas, e representantes de organizações não governamentais (ONG), organizações privadas e grupos comunitários também melhora a eficácia dos esforços de conservação em larga escala permitindo a adaptação das ações às preferências das partes interessadas e às necessidades de conservação em nível de paisagem (e.g., WYBORN;BIXLER, 2013;GUERRERO et al., 2015). Além desses estudos, investigações quantitativas em diferentes regiões costeiras, semiurbanas e rurais revelaram que a ação coletiva na governança se beneficia da existência de colaborações entre atores com diferentes pontos de vista e interesses (e.g., atores locais, empresários, representantes de administrações públicas, organizações sem fins lucrativos, agricultores, pescadores, além de diversos outros setores da sociedade), contribuindo a superar condições desfavoráveis à gestão de ecossistemas (HAHN et al., 2006;HIRSCHI, 2010;ROVA, 2010). ...
Resumo A colaboração inclusiva e equitativa dos atores tem sido cada vez mais reconhecida como elemento essencial para o sucesso da governança na conservação da biodiversidade em larga escala. No entanto, as evidências empíricas sobre o papel dos arranjos de colaboração no estabelecimento e manutenção da governança são ainda limitadas, especialmente em paisagens tropicais megadiversas. Aplicou-se a análise de redes sociais para mapear a rede colaborativa entre os atores envolvidos na governança de um mosaico de áreas protegidas no Brasil e testar se a rede apresentava padrões relacionais favoráveis à boa governança. A rede é densa e diversificada, contendo variedade de atores e arranjos de colaboração horizontal entre os grupos. Esses aspectos estruturais são consistentes com uma rede que promove o engajamento inclusivo e equitativo. A análise também identificou alguns riscos e desafios que oferecem informações úteis para melhorar a eficácia da governança.
... BIXLER, 2013GUERRERO et al., 2015). In addition to these studies, quantitative investigations in different coastal, semi-urban, and rural regions revealed that collective action in governance benefits from collaborations between actors with different points of view and interests (e.g., local actors, entrepreneurs, public administration representatives, non-profit organizations, farmers, fishermen, in addition to several other society sectors), contributing to overcoming unfavorable conditions for the management of ecosystems (HAHN et al., 2006;HIRSCHI, 2010;ROVA, 2010). ...
Inclusive and equitable collaboration of actors has increasingly been recognized as an essential element for successful governance in large-scale biodiversity conservation. However, there is still limited empirical evidence of the role of collaboration arrangements in establishing and maintaining governance, especially in megadiverse tropical landscapes. Social network analysis was applied to map the collaborative network between the actors involved in the governance of a mosaic of protected areas in Brazil and test whether the network displayed relational patterns favorable to good governance. The network is dense and diversified, containing a variety of actors and horizontal collaboration arrangements between groups. These structural aspects are consistent with a network promoting inclusive and equitable engagement. The analysis also identified some risks and challenges that provide useful information to improve governance effectiveness.
... 16,20 A high degree of centralisation can be beneficial, depending on the life stage of the initiative. 17,21 By taking a social network perspective, it is possible to examine the structural configurations of governance networks, to gain insight into how the relational structure may enable or hinder the network, potentially identifying opportunities for improvement. 13,22 These measures are, however, context dependent and interpretations regarding their influence should be based on several social network measures to obtain a comprehensive understanding. ...
... 26 Actors found in central positions are high ranking as they have a significantly higherthan-average number of ties and are considered well connected and influential within the network. 21 17 These networks are also seen as more accountable, as central actors can be held responsible to some degree. 27 While centralised networks are good for information transfer and collective action, they are less appropriate for dealing with complex problems. ...
... Heterogeneity was assessed through node diversity and network homophily measures. 21,32 Network centrality was assessed through the degree of network centralisation, a coreperiphery structure, degree centrality and betweenness centrality. 2,13,47 See Table 2 for more details of network measures. ...
Assessment of social relations, including social network analysis, is central to understanding collaborative processes for environmental decision-making and action. The capacity of network role players to learn and adapt appropriately to uncertainty and change is a critical determinant of the resilience of socialecological systems. Poor social network structure can predispose failure. In this study, we used social network analysis to explore learning capacity and network resilience in a multi-authority conservation initiative on the West Coast of South Africa (Dassenberg Coastal Catchment Partnership). Our analysis focused on structural variables for network learning and resilience, namely connectivity, heterogeneity, and centrality. The governance network was found to be structurally connected, with the interaction between heterogeneous organisations and sectors, and centralised around a core group of actors. The network had good structural features to enable learning. However, the high level of centrality, and dependence on a small number of core actors, rendered the network potentially vulnerable to dealing with complex challenges. We recommend that core actors (1) reflect on their core functions and whether the network can absorb these functions if they were to leave and (2) tap into the knowledge potential of actors on the network periphery or invite new actors to the network when dealing with complex challenges. This may require the network to diverge into decentralised subgroups to deal with complex issues. We further suggest that the Dassenberg Coastal Catchment Partnership network incorporate social network research with qualitative monitoring into a long-term plan to monitor the movement and influence of actors as the initiative evolves.
Significance:
• This study illustrates how social network analysis can help researchers, public-sector organisations, and donor agencies to monitor the structural features of governance networks that enable or disable learning and resilience within landscape-scale conservation initiatives.
• Our results illustrate how social network analysis can assist public-sector actors to reflect on their roles and whether there is redundant competency within the network to maintain its resilience.
