Beyond the green: Socioeconomic and climatic pressures on native vegetation in the Araguaia Biodiversity Corridor

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Abstract

This study examines how climatic and socioeconomic variables influence native vegetation cover across 108 municipalities within the Araguaia Biodiversity Corridor (ABC), an ecologically strategic region in central Brazil that connects Amazonian and Cerrado biomes and supports habitat continuity for wide-ranging species such as jaguars (Panthera onca). The corridor was defined as a 40 km-wide buffer along the Araguaia River (20 km each side), based on ecological connectivity principles and recent legislative proposals (e.g., PL 909/2024). We first characterized municipalities using land use, climate, and socioeconomic indicators. On average, 55.3% of municipal territory lies within the corridor, and native vegetation covers 46.5% of municipal land, ranging from less than 15% to over 90%. Using linear modeling, we assessed the effects of annual precipitation, Gross Domestic Product (GDP), human population density, number of rural properties, and average property size. Results indicate that precipitation and GDP are positively associated with vegetation cover, while population density shows a strong negative relationship. Additionally, municipalities with larger and more numerous rural properties tend to retain greater native vegetation. To translate these dynamics into policy-relevant metrics, we developed a Socioenvironmental Pressure Index (SPI) based on model residuals. The SPI highlights municipalities where vegetation cover is significantly lower or higher than expected. High-SPI areas may require targeted restoration, land-use regulation, or enforcement, whereas low-SPI areas may reflect resilience or effective local governance. These findings support place-based conservation planning and inform legislative efforts to formalize the ABC, emphasizing the need to integrate climatic and socioeconomic data into biodiversity policy.
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Abstract

This study examines how climatic and socioeconomic variables influence native vegetation cover across 108 municipalities within the Araguaia Biodiversity Corridor (ABC), an ecologically strategic region in central Brazil that connects Amazonian and Cerrado biomes and supports habitat continuity for wide-ranging species such as jaguars (Panthera onca). The corridor was defined as a 40 km-wide buffer along the Araguaia River (20 km each side), based on ecological connectivity principles and recent legislative proposals (e.g., PL 909/2024). We first characterized municipalities using land use, climate, and socioeconomic indicators. On average, 55.3% of municipal territory lies within the corridor, and native vegetation covers 46.5% of municipal land, ranging from less than 15% to over 90%. Using linear modeling, we assessed the effects of annual precipitation, Gross Domestic Product (GDP), human population density, number of rural properties, and average property size. Results indicate that precipitation and GDP are positively associated with vegetation cover, while population density shows a strong negative relationship. Additionally, municipalities with larger and more numerous rural properties tend to retain greater native vegetation. To translate these dynamics into policy-relevant metrics, we developed a Socioenvironmental Pressure Index (SPI) based on model residuals. The SPI highlights municipalities where vegetation cover is significantly lower or higher than expected. High-SPI areas may require targeted restoration, land-use regulation, or enforcement, whereas low-SPI areas may reflect resilience or effective local governance. These findings support place-based conservation planning and inform legislative efforts to formalize the ABC, emphasizing the need to integrate climatic and socioeconomic data into biodiversity policy. DOI https://doi.org/10.32942/X2ZM0H Subjects Biology

Keywords

Ecological corridor, Conservation strategy, environmental governance, land use, landscape connectivity, Socioenvironmental pressure, spatial analysis Dates Published: 2025-09-15 13:49 Last Updated: 2025-09-15 13:49 License No Creative Commons license Additional Metadata Language: English

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