Using case study data to understand SES interactions: a model-centered meta-analysis of SES framework applications
Sergio Villamayor-Tomas
Christoph Oberlack
Graham Epstein
Stefan Partelow
Matteo Roggero
Elke Kellner
Maurice Tschopp
Michael Cox
Abstract
Studying social–ecological interactions systematically is difficult when dealing with case study data. The methodological flexibility inherent in case studies facilitates the discovery of complex relationships between social and ecological variables; however, it also poses problems for knowledge accumulation given the diverse ways that variables are measured, as well as the descriptive approaches to causal inference that are typically employed. This article builds on the Social-Ecological Systems Framework (SESF) to systematically compare interactions among variables across case studies. We adopt a ‘model-centered’ meta-analysis of existing SESF case studies, in which the units of analysis are causal explanations including sets of variables and their effects on outcomes (i.e. ‘models’). Our analysis encompassed 30 studies and resulted in the formalization of 125 models. The analysis illustrates opportunities to assess interactions at different levels of detail. The paper concludes by proposing strategies to advance the study and reporting of interactions in case studies to foster a better understanding of dynamics and outcomes of environmental sustainability.
Villamayor-Tomas S., Oberlack C., Epstein G., Partelow S., Roggero M., Kellner E., Tschopp M. and Cox M. (2020) Using case study data to understand SES interactions: a model-centered meta-analysis of SES framework applications. Current Opinion in Environmental Sustainability 44: 48-57. 10.1016/j.cosust.2020.05.002
@article{Villamayor-Tomas2020,
Title = {Using case study data to understand SES interactions: a model-centered meta-analysis of SES framework applications},
Author = {Villamayor-Tomas, Sergio and Oberlack, Christoph and Epstein, Graham and Partelow, Stefan and Roggero, Matteo and Kellner, Elke and Tschopp, Maurice and Cox, Michael},
Editor = {},
Journal = {Current Opinion in Environmental Sustainability},
Year = {2020},
Pages = {48-57},
Volume = {44},
Doi = {10.1016/j.cosust.2020.05.002},
Abstract = {Studying social–ecological interactions systematically is difficult when dealing with case study data. The methodological flexibility inherent in case studies facilitates the discovery of complex relationships between social and ecological variables; however, it also poses problems for knowledge accumulation given the diverse ways that variables are measured, as well as the descriptive approaches to causal inference that are typically employed. This article builds on the Social-Ecological Systems Framework (SESF) to systematically compare interactions among variables across case studies. We adopt a ‘model-centered’ meta-analysis of existing SESF case studies, in which the units of analysis are causal explanations including sets of variables and their effects on outcomes (i.e. ‘models’). Our analysis encompassed 30 studies and resulted in the formalization of 125 models. The analysis illustrates opportunities to assess interactions at different levels of detail. The paper concludes by proposing strategies to advance the study and reporting of interactions in case studies to foster a better understanding of dynamics and outcomes of environmental sustainability.},
}
TY - JOUR
AU - Villamayor-Tomas, Sergio
AU - Oberlack, Christoph
AU - Epstein, Graham
AU - Partelow, Stefan
AU - Roggero, Matteo
AU - Kellner, Elke
AU - Tschopp, Maurice
AU - Cox, Michael
TI - Using case study data to understand SES interactions: a model-centered meta-analysis of SES framework applications
T2 - Current Opinion in Environmental Sustainability
PY - 2020
SP - 48-57
VL - 44
DO - 10.1016/j.cosust.2020.05.002
AB - Studying social–ecological interactions systematically is difficult when dealing with case study data. The methodological flexibility inherent in case studies facilitates the discovery of complex relationships between social and ecological variables; however, it also poses problems for knowledge accumulation given the diverse ways that variables are measured, as well as the descriptive approaches to causal inference that are typically employed. This article builds on the Social-Ecological Systems Framework (SESF) to systematically compare interactions among variables across case studies. We adopt a ‘model-centered’ meta-analysis of existing SESF case studies, in which the units of analysis are causal explanations including sets of variables and their effects on outcomes (i.e. ‘models’). Our analysis encompassed 30 studies and resulted in the formalization of 125 models. The analysis illustrates opportunities to assess interactions at different levels of detail. The paper concludes by proposing strategies to advance the study and reporting of interactions in case studies to foster a better understanding of dynamics and outcomes of environmental sustainability.
ER -
