Under what conditions do payments for environmental services enable forest conservation in the Amazon? A realist synthesis

Fernando-Esteban Montero-de-Oliveira, Genowefa Blundo-Canto and Driss Ezzine-de-Blas

Ecological Economics, 2023, vol. 205, issue C

Abstract: Payments for environmental services (PES) have been widely studied as one possible way to counter deforestation and support livelihoods. Given the high rates of deforestation in the Amazon region, it is important to study under which conditions PES have positive environmental and social outcomes. We contribute to this debate through a systematic review based on the Realist Evaluation framework. First, we review case studies to identify configurations of social-ecological factors (context), PES design and implementation (resource mechanisms), people's responses (reasoning mechanisms), and the results in terms of forest conservation and people's livelihoods (outcomes). Second, we develop a middle-range theory of how, for whom, and under what conditions PES in the Amazon achieve these results. After screening 972 articles in the SCOPUS, Scielo, and WorldCat databases, we reviewed 13 articles in-depth that contained all the elements (context-mechanism-outcomes) needed to identify these configurations. Our results show that PES in the Amazon generate positive environmental and social outcomes when they: (a) combine cash and in-kind incentives, (b) raise environmental awareness through capacity building, (c) engage socially and ethnically diverse stakeholders through equitable and inclusive approaches, (d) apply transparent spatial targeting, (e) guarantee strong conditionality through robust monitoring of compliance, and (f) guarantee stable delivery of payments.

Keywords: Conservation incentives; Tropical forests; Payments for ecosystem services; Impact; Realist synthesis (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolec:v:205:y:2023:i:c:s0921800922003585

DOI: 10.1016/j.ecolecon.2022.107697

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