Best of both worlds: Combining ecological and social research to inform conservation decisions in a Neotropical biodiversity hotspot - Ferraz, Katia Maria Paschoaletto Micchi de Barros; Marchini, Silvio; Bogoni, Juliano A.; Paolino, Roberta Montanheiro; Landis, Mariana; Fusco-Costa, Roberto; Magioli, Marcelo; Munhoes, Leticia Prado; Saranholi, Bruno H.; Ribeiro, Yuri Geraldo Gomes; Domini, Juan Andrea de; Magezi, Gabriel Shimokawa; et al. (Elsevier, 2022)
Conservation decision is a challenging and risky task when it aims at prioritizing species or protected areas (PAs) to prevent extinction while ensuring fair treatment of all stakeholders. Better conservation decisions are those made upon a broader evidence base that includes both ecological and social considerations. However, in some of the most biodiverse ecosystems on Earth — tropical forests, for instance — multicriteria decision-making has been constrained by the following (i) ecological and social datasets available have been obtained in an independent, non-integrated manner, with social data typically more scarce than ecological ones, and (ii) capacity in social and/or interdisciplinary data analysis among decision-maker is limited. We describe a conservation prioritization exercise that combined findings from independent ecological and social research conducted in the Brazilian Atlantic Forest, and propose methods to integrate, analyze and visualize data. We found that the outcomes based on combined ecological and social research findings were, in some cases, different from those based on any of these lines of evidence alone. Indeed, the input from relatively basic social research significantly changed the outcomes of decision-making based on the results of ecological research. Results corroborate the importance and cost-effectiveness of broadening the interdisciplinary evidence base for conservation decision-making, even when social data is scarce and analytical capacity is limited.
Keywords: Atlantic Forest; Conservation planning; Interdisciplinary research; Mammal diversity; Multi-criteria decision-making; Social research