Transdisciplinary science for improved conservation outcomes

Margules, Chris, Boedhihartono, Agni K., Langston, James D., Riggs, Rebecca A., Sari, Dwi Amalia, Sarkar, Sahotra, Sayer, Jeffrey A., Supriatna, Jatna, and Winarni, Nurul L. (2020) Transdisciplinary science for improved conservation outcomes. Environmental Conservation, 47 (4). pp. 224-233.

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Abstract

[Extract] Major advances in biology and ecology have sharpened our understanding of what the goals of biodiversity conservation might be, but less progress has been made on how to achieve conservation in the complex, multi-sectoral world of human affairs. The failure to deliver conservation outcomes is especially severe in the rapidly changing landscapes of tropical low-income countries. We describe five techniques we have used to complement and strengthen long-term attempts to achieve conservation outcomes in the landscapes and seascapes of such regions; these are complex social-ecological systems shaped by interactions between biological, ecological and physical features mediated by the actions of people. Conservation outcomes occur as a result of human decisions and the governance arrangements that guide change. However, much conservation science in these countries is not rooted in a deep understanding of how these social-ecological systems work and what really determines the behaviour of the people whose decisions shape the future of landscapes. We describe five scientific practices that we have found to be effective in building relationships with actors in landscapes and influencing their behaviour in ways that reconcile conservation and development. We have used open-ended inductive enquiry, theories of change, simulation models, network analysis and multi-criteria analysis. These techniques are all widely known and well tested, but seldom figure in externally funded conservation projects. We have used these techniques to complement and strengthen existing interventions of international conservation agencies. These five techniques have proven effective in achieving deeper understanding of context, engagement with all stakeholders, negotiation of shared goals and continuous learning and adaptation.

Item ID: 66620
Item Type: Article (Research - C1)
ISSN: 1469-4387
Keywords: inductive research, landscape, multi-criteria analysis, network analysis, simulation models, theories of change, transdisciplinary
Copyright Information: © The Author(s), 2020. Published by Cambridge University Press on behalf of Foundation for Environmental Conservation
Funders: Critical Ecosystem Partnership Fund (CEPF), Centre for Tropical Environmental and Sustainability Sciences at JCU
Date Deposited: 24 May 2021 05:30
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410401 Conservation and biodiversity @ 100%
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