Spatio-temporal analysis of dynamics and future scenarios of anthropic pressure on biomes in Brazil
Anthropogenic transformations, which have become intensified by land use and land cover changes and industrialization, have contributed to increased anthropogenic pressure on biodiversity. These disturbances contribute toward fragmentating habitats at different scales and putting species at risk, in addition to compromising the main biogeochemical cycles. To better understand the spatiotemporal dynamics of anthropogenic pressure on Brazilian biomes, this study sought to develop a composite index to identify and analyze the degree and distribution of anthropogenic-based pressure on biodiversity, and identify internally homogeneous and heterogeneous regions regarding the dynamics of this pressure in different scenarios.
To that end, we carried out an analysis of the impact of select anthropogenic factors. Specifically, we analyzed future scenarios involving land use and land cover changes in line with the global structure Shared Socio-Economic Pathways (SSPs) and Representative Concentration Pathways (RCPs), according to the narratives SSP1/RCP 1.9, SSP2/ RCP 4.5 and SSP3/RCP 7.0. We used cluster and spatial analyses to determine the spatial dynamics of the index and, consequently, the regions most susceptible to anthropogenic pressure.
The results demonstrate intensified pressure on biodiversity in areas that have already been subject to a considerable degree of disturbances, especially the Cerrado, Caatinga, and Atlantic Forest biomes. In all scenarios, the region with the highest average pressure index, i.e., Region 4, which has an average pressure index of 0.57, corresponds to 30% of Brazilian territory. This method made it possible to determine the level of pressure in each region and, subsequently, identify the regions that have been most affected by human actions in an effort to guide priority actions and local policies. However, it should be noted that this approach should be complemented with additional information, such as soil erosion, field recognition, and socioeconomic information.
Research news | 2023-03-20
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