An investigation of the spatial influences and governance implications of social-ecological heterogeneity, connectivity, and scale on landscape change

Sivee Chawla has operationalised Ostrom's design principles for terrestrial social-ecological systems (SESs) using dynamic simulation models. Her work has given new insights into the spatial interplay between governance and landscape change from the systems perspective. The research contributes to extending SES theory to better understand spatially explicit feedbacks and cross-scale interactions

Insights from twenty years of comparative research in Pacific Large Ocean States

Under global environmental change, understanding the interactions between people and nature has become critical for human survival. Comparative research can identify trends within social-ecological systems providing key insights for both environmental and developmental research. Island systems, with clear land boundaries, have been proposed as ideal case studies for comparative research, but it is unclear to what extent their potential has been fulfilled. To summarize existing research and identify potential gaps and new directions, we reviewed comparative environmental and developmental research on Pacific Large Ocean States. A diversity of case study locations and research themes were addressed within the sample of reviewed studies. Within the reviewed literature climate change, energy infrastructure, trade and fisheries were key themes of environmental and developmental research compared between island systems. Research was biased towards wealthier Pacific Large Ocean States and those with a relatively higher degree of socio-economic development. Our review highlights the potential value of a stronger a priori inclusion of spatial scale and conceptual frameworks, such as spatial resilience, to facilitate generalization from case studies

The Problem of Institutional Fit: Uncovering Patterns with Boosted Decision Trees

Complex social-ecological contexts play an important role in shaping the types of institutions that groups use to manage resources, and the effectiveness of those institutions in achieving social and environmental objectives. However, despite widespread acknowledgment that “context matters”, progress in generalising how complex contexts shape institutions and outcomes has been slow. This is partly because large numbers of potentially influential variables and non-linearities confound traditional statistical methods. Here we use boosted decision trees – one of a growing portfolio of machine learning tools – to examine relationships between contexts, institutions, and their performance. More specifically we draw upon data from the International Forest Resources and Institutions (IFRI) program to analyze (i) the contexts in which groups successfully self-organize to develop rules for the use of forest resources (local rulemaking), and (ii) the contexts in which local rulemaking is associated with successful ecological outcomes. The results reveal an unfortunate divergence between the contexts in which local rulemaking tends to be found and the contexts in which it contributes to successful outcomes. These findings and our overall approach present a potentially fruitful opportunity to further advance theories of institutional fit and inform the development of policies and practices tailored to different contexts and desired outcomes

The problem of institutional fit : uncovering patterns with boosted decision trees

Unidad de excelencia María de Maeztu CEX2019-000940-MComplex social-ecological contexts play an important role in shaping the types of institutions that groups use to manage resources, and the effectiveness of those institutions in achieving social and environmental objectives. However, despite widespread acknowledgment that "context matters", progress in generalising how complex contexts shape institutions and outcomes has been slow. This is partly because large numbers of potentially influential variables and non-linearities confound traditional statistical methods. Here we use boosted decision trees - one of a growing portfolio of machine learning tools - to examine relationships between contexts, institutions, and their performance. More specifically we draw upon data from the International Forest Resources and Institutions (IFRI) program to analyze (i) the contexts in which groups successfully self-organize to develop rules for the use of forest resources (local rulemaking), and (ii) the contexts in which local rulemaking is associated with successful ecological outcomes. The results reveal an unfortunate divergence between the contexts in which local rulemaking tends to be found and the contexts in which it contributes to successful outcomes. These findings and our overall approach present a potentially fruitful opportunity to further advance theories of institutional fit and inform the development of policies and practices tailored to different contexts and desired outcomes

A framework for conceptualizing and modeling social-ecological systems for conservation research

As conservation biology has matured, its scope has expanded from a primarily ecological focus to recognition that nearly all conservation problems involve people. At the same time, conservation actions have been increasingly informed by ever more sophisticated quantitative models. These models have focused primarily on ecological and geographic elements of conservation problems, such as mark-recapture methods, predicting species occurrences, and optimizing the placement of protected areas. There are many off-the-shelf ecological models for conservation managers to draw upon, but very few that describe human-nature interactions in a generalizable manner. We address this gap by proposing a minimalistic modeling framework for human-nature interactions, combining well-established ideas in economics and social sciences (grounded in Ostrom's social-ecological systems framework) and accepted ecological models. Our approach begins with a systems breakdown consisting of an ecosystem, resource users, public infrastructure, and infrastructure providers; and interactions between these system elements, which bring together the biophysical context, the relevant attributes of the human society, and the rules (institutions, such as protected areas) currently in use. We briefly review the different disciplinary building blocks that the framework could incorporate and then illustrate our approach with two examples: a detailed analysis of the social-ecological dynamics involved in managing South African protected areas and a more theoretical analysis of a general system. We conclude with further discussion of the urgent need in conservation biology for models that are genuinely designed to capture the complexities of human socioeconomic behavior, rather than the more typical approach of trying to adapt an ecological model or a stochastic process to simulate human agency and decision-making. Our framework offers a relatively simple but highly versatile way of specifying social-ecological models that will help conservation biologists better represent critical linkages between social and ecological processes when modeling social-ecological dynamics

Drivers of compliance monitoring in forest commons

Lasting community-based governance of common-pool resources depends on communities self-organizing to monitor compliance with rules. Monitoring serves an important function in community-based governance by establishing conditions for long-term cooperation, but the factors that foster its provision are poorly understood. We have analysed data from 177 forest user groups to assess the relative importance of 15 potential drivers of compliance monitoring, as well as the direction and form of their relationships. The results suggest that user groups are most likely to successfully self-organize to monitor compliance when rules are designed by local user groups (local rulemaking), and when those user groups are located close to or far from markets for forest products and have a larger number of members. Additionally, local leadership plays an important role in certain contexts, such as groups that are smaller in size and located near markets for forest products