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Decision Analysis Shows Scientific and Economic Value of Community-Based Monitoring in Madagascar

Biological Conservation(2025)

University of Florida

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Abstract
Community-based monitoring (CBM) could enable long-term biodiversity monitoring in remote areas and benefit local communities, yet is rarely used to facilitate conservation efforts often due to mistrust in the data collected. We use a multi-criteria decision analysis framework to systematically examine the scientific and socioeconomic values and financial costs associated with biodiversity monitoring for vertebrates by scientists and local community members in six protected areas (PAs) in Madagascar, encompassing diverse ecosystems spanning tropical rainforests to spiny deserts. We compare the number of species observed during scientist and community surveys, identify the ‘ideal’ number of scientist and community surveys that would be required to maximize the scientific and socioeconomic values of monitoring efforts while minimizing financial cost, and compare monitoring plans across several conservation philosophies representing “ecocentric” and “people-centered” perspectives. Scientists generally observed more species than community members. However, including a greater proportion of surveys conducted by community members lowered the financial cost of travel and compensation while maximizing ecological and social objectives associated with diverse conservation philosophies. While the valuation schemes we use are simplistic representations of the complex costs and values associated with CBM, this study indicates the benefits of community monitoring regardless of the conservation philosophy used to anchor valuation and decision-making. Increasing integration of CBM into existing conservation management could therefore offer a financially viable method to consistently monitor biodiversity and benefit local communities in the face of limited funding and global challenges.
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Key words
Biodiversity,Community-based monitoring,Conservation planning,Madagascar,Protected areas,Structured-decision making
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