A guide to qualitative attribution methods for evaluation in conservation

Author:

Zavaleta Cheek Jennifer12ORCID,Eklund Johanna3ORCID,Merten Nikolas24ORCID,Brooks Jeremy5ORCID,Miller Daniel C.26ORCID

Affiliation:

1. Department of Natural Resources South Dakota State University Brookings South Dakota USA

2. Department of Natural Resources and Environmental Sciences University of Illinois at Urbana–Champaign Urbana Illinois USA

3. Global Development Studies, Faculty of Social Sciences University of Helsinki Helsinki Finland

4. John Glenn College of Public Affairs The Ohio State University Columbus Ohio USA

5. School of Environment and Natural Resources Ohio State University Columbus Ohio USA

6. Keough School of Global Affairs University of Notre Name Notre Dame Indiana USA

Abstract

AbstractKnowledge of what conservation interventions improve biodiversity outcomes, and in which circumstances, is imperative. Experimental and quasi‐experimental methods are increasingly used to establish causal inference and build the evidence base on the effectiveness of interventions, but their ability to provide insight into how and under what conditions an intervention should be implemented to improve biodiversity outcomes faces limitations. A suite of attribution methods that leverage qualitative methods for causal inference is available but underutilized in conversation impact evaluation. This article provides a guide to 5 such qualitative attribution methods: contribution analysis, process tracing, realist evaluation, qualitative comparative analysis, and most significant change. It defines and introduces each method and then illustrates how they could be applied through a case study of community conservancies in Namibia. This guide provides examples of how qualitative attribution methods can advance knowledge of what works, in which contexts, and why in biodiversity conservation.

Funder

John D. and Catherine T. MacArthur Foundation

Publisher

Wiley

Subject

Nature and Landscape Conservation,Ecology,Ecology, Evolution, Behavior and Systematics

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