Synergies and Trade‐Offs Between Biodiversity Conservation, Human Well‐Being, and Agricultural Production: Lessons From the Southern Atlantic Forest of Brazil

ABSTRACT Aims We evaluate the complex interplay between biodiversity conservation, agricultural production, and socioeconomic development in the Southern Brazilian Atlantic Forest, under both current and projected future conditions. Specifically, we aim to understand (1) the spatial distribution of woody plant biodiversity (species richness, phylogenetic richness, and functional richness) and agricultural revenue (from temporary and permanent crops), (2) the potential synergies and trade‐offs between biodiversity, agricultural revenue, and socioeconomic metrics, and (3) how associations between biodiversity and agricultural revenue may shift under projected climate scenarios by 2040. Our findings provide decision‐makers with insights to balance biodiversity conservation with agricultural sustainability, offering a framework applicable to similar regions globally. Location Santa Catarina, Brazil. Methods We used machine learning ensemble models to predict woody plant biodiversity and agricultural revenue based on climate, topography, soil, and spatial structure. Biodiversity data were compiled from 480 forest inventory plots (4000 m 2 each), while socioeconomic indicators and agricultural production data were obtained from governmental databases. Soil and environmental data were sourced from open‐access global databases. Results Temperature, precipitation, and topography were primary predictors of biodiversity, highlighting climate and terrain influences on species richness. In contrast, spatial structure emerged as the main predictor of crop revenue, emphasizing the role of local infrastructure and biophysical factors in agriculture. Projections for 2040 indicate stable biodiversity levels in most municipalities, with localized shifts in biodiversity and crop yields driven by climate‐induced changes. Our findings reveal synergies between biodiversity and agricultural revenue but also underscore trade‐offs, particularly between permanent crop revenue and forested area. Conclusions Our results support prioritizing conservation efforts in regions projected to maintain or increase biodiversity while promoting climate‐smart agriculture for sustainable production. This framework, adaptable to other biodiverse, agriculturally reliant regions, provides a tool for policymakers to balance biodiversity conservation with sustainable agricultural practices under shifting climate conditions.

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Publication Details

Journal
Applied Vegetation Science
Published
2025-10-01
DOI
https://doi.org/10.1111/avsc.70047
Citations
1
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
1.84

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article

Synergies and Trade‐Offs Between Biodiversity Conservation, Human Well‐Being, and Agricultural Production: Lessons From the Southern Atlantic Forest of Brazil

Vinícius Marcilio‐Silva, Alexander Christian Vibrans, Márcia C. M. Marques, Andrea Paz et al.
1 citations
Applied Vegetation Science
Species Distribution and Climate Change
1.84
article

Synergies and Trade‐Offs Between Biodiversity Conservation, Human Well‐Being, and Agricultural Production: Lessons From the Southern Atlantic Forest of Brazil

Vinícius Marcilio‐Silva, Alexander Christian Vibrans, Márcia C. M. Marques, Andrea Paz, Jeannine Cavender‐Bares, Ana Carolina Carnaval
article en
1 citations

Abstract

ABSTRACT Aims We evaluate the complex interplay between biodiversity conservation, agricultural production, and socioeconomic development in the Southern Brazilian Atlantic Forest, under both current and projected future conditions. Specifically, we aim to understand (1) the spatial distribution of woody plant biodiversity (species richness, phylogenetic richness, and functional richness) and agricultural revenue (from temporary and permanent crops), (2) the potential synergies and trade‐offs between biodiversity, agricultural revenue, and socioeconomic metrics, and (3) how associations between biodiversity and agricultural revenue may shift under projected climate scenarios by 2040. Our findings provide decision‐makers with insights to balance biodiversity conservation with agricultural sustainability, offering a framework applicable to similar regions globally. Location Santa Catarina, Brazil. Methods We used machine learning ensemble models to predict woody plant biodiversity and agricultural revenue based on climate, topography, soil, and spatial structure. Biodiversity data were compiled from 480 forest inventory plots (4000 m 2 each), while socioeconomic indicators and agricultural production data were obtained from governmental databases. Soil and environmental data were sourced from open‐access global databases. Results Temperature, precipitation, and topography were primary predictors of biodiversity, highlighting climate and terrain influences on species richness. In contrast, spatial structure emerged as the main predictor of crop revenue, emphasizing the role of local infrastructure and biophysical factors in agriculture. Projections for 2040 indicate stable biodiversity levels in most municipalities, with localized shifts in biodiversity and crop yields driven by climate‐induced changes. Our findings reveal synergies between biodiversity and agricultural revenue but also underscore trade‐offs, particularly between permanent crop revenue and forested area. Conclusions Our results support prioritizing conservation efforts in regions projected to maintain or increase biodiversity while promoting climate‐smart agriculture for sustainable production. This framework, adaptable to other biodiverse, agriculturally reliant regions, provides a tool for policymakers to balance biodiversity conservation with sustainable agricultural practices under shifting climate conditions.

Applied Vegetation ScienceVol. 28(4)
The Graduate Center, CUNY (US), City College of New York (US), University of Minnesota (US), Harvard University (US), Universidade Regional de Blumenau (BR), Universidade Federal do Paraná (BR), North Dakota State University (US), Université de Montréal (CA)
National Science Foundation, Universidade Regional de Blumenau, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina, Division of Biological Infrastructure
Openalex Percentile: Top 11%
Species Distribution and Climate Change
1.84
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