Trade-off and synergies among ecosystem services of the Atlantic Forest biome
Year: 2026
Type: article
Abstract: • ES were mapped across the Atlantic Forest, a highly diverse and threatened biome. • Trade-offs were found between provisioning and regulating services • Three ES bundles were identified, varying in composition and spatial distribution. • Spatial patterns of ES associations reflect socio-ecological gradients in the biome. • ES bundles contribute to policy decisions and environmental management. Assessing ecosystem service interactions helps identify unique ecosystem service bundles across biologically relevant areas. These efforts can identify critical areas for providing services and are crucial to the planning and management of ecosystems. In this study, we identified ecosystem services interactions and bundles across the entire megadiverse and threatened Brazilian Atlantic Forest. We quantified and mapped 9 ecosystem services on provision, regulation, and supporting services associated with 2,255 plant species, in 3039 municipalities covering more than 148 million hectares in Brazil, using national official datasets. We identified ecosystem service interactions (trade-offs or synergies) with pairwise Pearson’s correlations and ecosystem service bundles with K-means cluster analysis. We identified significant trade-offs between provisioning and regulating services and three ecosystem service bundles that varied in composition and were spatially clustered in the biome. The composition and distribution of ecosystem services bundles evidence how land management and biophysical characteristics act in the landscape. These results are essential to support conservation planning and ecosystem management to mitigate potential trade-offs and create more synergies among ecosystem services and biodiversity.
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: diamond
Awards: G6629423732, G6633645745, G7718916411
OpenAlex ID: W7125517023
