ArticleScientific reports2025
Spatial management of poverty-biodiversity interactions in semi-arid ecosystems.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Among the challenges to sustainable development, two primary obstacles stand out: poverty and biodiversity loss. Despite the acknowledged significance of the link between poverty reduction and biodiversity conservation, this relationship remains underexplored due to its complex nature, a lack of integrated data, and the tendency to address poverty and biodiversity separately in research and policy. This study aims to explore the complex relationship between biodiversity conservation and poverty in semi-arid ecosystems in Iran, focusing on the natural, social, economic, and governmental drivers involved. The results revealed a spatially varied relationship between biodiversity conservation and poverty, with both positive and negative outcomes. The structural equation modeling (SEM) indicated that nature (p < 0.001), economy (p < 0.01), society (p < 0.01), and government (p < 0.01), with poverty serving as a mediating factor, significantly influence biodiversity conservation. Further analysis of the SEM revealed that specific factors play key roles: ecosystem production was identified as the most important natural driver (p < 0.001), income as the primary economic driver (p < 0.001), population as the most influential social driver (p < 0.001), and government services as the leading governmental driver (p < 0.01) of biodiversity conservation. Results revealed that ecosystem production and government services positively correlate with biodiversity conservation, while population negatively impacts it. The relationship between income and biodiversity conservation, however, is more complex. This study offers a novel approach for the spatial assessment of both poverty alleviation and biodiversity conservation, using key drivers to inform policy and management decisions.
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