<p>The spatiotemporal dynamics of fragmentation in the Caatinga biome reflect complex interactions between natural processes and human-induced land-use change. This study investigated fragmentation and land-use/land-cover dynamics across the Caatinga biome from 1985 to 2024. Land-use and land-cover data were obtained from the MapBiomas Project, and landscape ecology metrics were calculated using the FRAGSTATS methodology implemented in Python. Landscape fragmentation was assessed by quantifying multiple dimensions of landscape structure, including habitat amount, patch subdivision, edge development, and spatial aggregation. The evaluated metrics included class area (CA), percentage of landscape (PLAND), number of patches (NP), largest patch index (LPI), mean patch area (AREA-MN), mean shape index (SHAPE-MN), mean Euclidean nearest-neighbor distance (ENN-MN), and patch density (PD). The results revealed substantial changes in landscape structure, marked by intense fragmentation of forested areas and the expansion of anthropogenic land uses, particularly sugarcane cultivation. These changes indicate progressive structural degradation of the biome and suggest negative implications for habitat integrity and biodiversity conservation. The integrated analysis of landscape metrics proved effective in characterizing long-term changes in forest structure and fragmentation patterns. Overall, native vegetation in the Caatinga became increasingly fragmented between 1985 and 2024, with the strongest intensification occurring in forested areas.</p> Graphical Abstract <p></p> <p>This visual summary serves as a pivotal entry point into the research, offering a concise overview of the study’s core findings and methodologies. The graphical abstract synthesizes the investigation of landscape fragmentation and land-use change in the Caatinga biome between 1985 and 2024. It first identifies the study region and temporal scope, then illustrates the analytical workflow based on MapBiomas data and FRAGSTATS-derived landscape metrics. The visual comparison highlights the decline in native vegetation, represented primarily by savanna formation, and the marked expansion of pasture over the study period. It also summarizes the behavior of the key fragmentation indicators, showing increases in the number of patches and total edge, a decrease in the percentage of the landscape occupied by native vegetation, and a slight increase in the aggregation index. In addition, the maps of degraded and recovered areas and the core-area graph demonstrate that degradation was spatially more extensive and that native vegetation core habitats became progressively smaller under stronger edge-effect thresholds. As a quick and visually appealing summary of the research, the graphical abstract provides readers with a rapid understanding of the main findings without requiring them to read the entire manuscript. In this way, it improves accessibility, attracts attention, and strengthens the communication and impact of the study.</p>

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Landscape Fragmentation and Land-use Change in the Caatinga Biome: A Spatiotemporal Analysis from 1985 to 2024

  • Gregory Lira da Silva,
  • Danilo Henrique da Silva Santana,
  • Leonardo Vidal Batista,
  • Richarde Marques da Silva,
  • Celso Augusto Guimarães Santos

摘要

The spatiotemporal dynamics of fragmentation in the Caatinga biome reflect complex interactions between natural processes and human-induced land-use change. This study investigated fragmentation and land-use/land-cover dynamics across the Caatinga biome from 1985 to 2024. Land-use and land-cover data were obtained from the MapBiomas Project, and landscape ecology metrics were calculated using the FRAGSTATS methodology implemented in Python. Landscape fragmentation was assessed by quantifying multiple dimensions of landscape structure, including habitat amount, patch subdivision, edge development, and spatial aggregation. The evaluated metrics included class area (CA), percentage of landscape (PLAND), number of patches (NP), largest patch index (LPI), mean patch area (AREA-MN), mean shape index (SHAPE-MN), mean Euclidean nearest-neighbor distance (ENN-MN), and patch density (PD). The results revealed substantial changes in landscape structure, marked by intense fragmentation of forested areas and the expansion of anthropogenic land uses, particularly sugarcane cultivation. These changes indicate progressive structural degradation of the biome and suggest negative implications for habitat integrity and biodiversity conservation. The integrated analysis of landscape metrics proved effective in characterizing long-term changes in forest structure and fragmentation patterns. Overall, native vegetation in the Caatinga became increasingly fragmented between 1985 and 2024, with the strongest intensification occurring in forested areas.

Graphical Abstract

This visual summary serves as a pivotal entry point into the research, offering a concise overview of the study’s core findings and methodologies. The graphical abstract synthesizes the investigation of landscape fragmentation and land-use change in the Caatinga biome between 1985 and 2024. It first identifies the study region and temporal scope, then illustrates the analytical workflow based on MapBiomas data and FRAGSTATS-derived landscape metrics. The visual comparison highlights the decline in native vegetation, represented primarily by savanna formation, and the marked expansion of pasture over the study period. It also summarizes the behavior of the key fragmentation indicators, showing increases in the number of patches and total edge, a decrease in the percentage of the landscape occupied by native vegetation, and a slight increase in the aggregation index. In addition, the maps of degraded and recovered areas and the core-area graph demonstrate that degradation was spatially more extensive and that native vegetation core habitats became progressively smaller under stronger edge-effect thresholds. As a quick and visually appealing summary of the research, the graphical abstract provides readers with a rapid understanding of the main findings without requiring them to read the entire manuscript. In this way, it improves accessibility, attracts attention, and strengthens the communication and impact of the study.