| 1. |
- Barnes, Michele L., et al.
(author)
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The social structural foundations of adaptation and transformation in social-ecological systems
- 2017
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In: Ecology and Society. - 1708-3087. ; 22:4
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Journal article (peer-reviewed)abstract
- Social networks are frequently cited as vital for facilitating successful adaptation and transformation in linked social-ecological systems to overcome pressing resource management challenges. Yet confusion remains over the precise nature of adaptation vs. transformation and the specific social network structures that facilitate these processes. Here, we adopt a network perspective to theorize a continuum of structural capacities in social-ecological systems that set the stage for effective adaptation and transformation. We begin by drawing on the resilience literature and the multilayered action situation to link processes of change in social-ecological systems to decision making across multiple layers of rules underpinning societal organization. We then present a framework that hypothesizes seven specific social-ecological network configurations that lay the structural foundation necessary for facilitating adaptation and transformation, given the type and magnitude of human action required. A key contribution of the framework is explicit consideration of how social networks relate to ecological structures and the particular environmental problem at hand. Of the seven configurations identified, three are linked to capacities conducive to adaptation and three to transformation, and one is hypothesized to be important for facilitating both processes. We discuss how our theoretical framework can be applied in practice by highlighting existing empirical examples from related environmental governance contexts. Further extension of our hypotheses, particularly as more data become available, can ultimately help guide the design of institutional arrangements to be more effective at dealing with change.
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| 2. |
- Bodin, Örjan, et al.
(author)
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Theorizing benefits and constraints in collaborative environmental governance : a transdisciplinary social-ecological network approach for empirical investigations
- 2016
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In: Ecology and Society. - 1708-3087. ; 21:1
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Journal article (peer-reviewed)abstract
- When environmental processes cut across socioeconomic boundaries, traditional top-down government approaches struggle to effectively manage and conserve ecosystems. In such cases, governance arrangements that foster multiactor collaboration are needed. The effectiveness of such arrangements, however, depends on how well any ecological interdependencies across governed ecosystems are aligned with patterns of collaboration. This inherent interdisciplinary and complex problem has impeded progress in developing a better understanding of how to govern ecosystems for conservation in an increasingly interconnected world. We argue for the development of empirically informed theories, which are not only able to transcend disciplinary boundaries, but are also explicit in taking these complex social-ecological interdependences into account. We show how this emerging research frontier can be significantly improved by incorporating recent advances in stochastic modeling of multilevel social networks. An empirical case study from an agricultural landscape in Madagascar is reanalyzed to demonstrate these improvements.
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| 3. |
- Koskinen, Johan, et al.
(author)
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Outliers and Influential Observations in Exponential Random Graph Models
- 2018
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In: Psychometrika. - : SPRINGER. - 0033-3123 .- 1860-0980. ; 83:4, s. 809-830
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Journal article (peer-reviewed)abstract
- We discuss measuring and detecting influential observations and outliers in the context of exponential family random graph (ERG) models for social networks. We focus on the level of the nodes of the network and consider those nodes whose removal would result in changes to the model as extreme or central with respect to the structural features that matter. We construe removal in terms of two case-deletion strategies: the tie-variables of an actor are assumed to be unobserved, or the node is removed resulting in the induced subgraph. We define the difference in inferred model resulting from case deletion from the perspective of information theory and difference in estimates, in both the natural and mean-value parameterisation, representing varying degrees of approximation. We arrive at several measures of influence and propose the use of two that do not require refitting of the model and lend themselves to routine application in the ERGM fitting procedure. MCMC p values are obtained for testing how extreme each node is with respect to the network structure. The influence measures are applied to two well-known data sets to illustrate the information they provide. From a network perspective, the proposed statistics offer an indication of which actors are most distinctive in the network structure, in terms of not abiding by the structural norms present across other actors.
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