O impacto das mudanças climáticas e de uso do solo sobre a qualidade do habitat para as aves endêmicas da Mata Atlântica

Abstract

Habitat quality is determined by climatic variables, landscape structure, and intrinsic species characteristics. While some studies have been conducted to assess the effects of climate change and land use on habitat quality, identifying high-quality habitats for species in a fine scale requires consideration of their intrinsic characteristics and vulnerabilities to different threats. It is expected that by incorporating this additional complexity layer for the identification of these areas, more narrowly defined suitable areas will be identified compared to models that solely consider climatic data. In this context, the Habitat Quality model from the InVEST software was employed. This model integrates a land-use land-cover map with species threats to identify areas maintaining higher habitat quality for the Atlantic Forest endemic birds both in the present and under a future climate change scenario. The identification of these regions considered bird characteristics such as forest dependence, susceptibility to hunting and trafficking, and habitat preference. The results indicate that, on average, only 35% of the total species distribution area maintains high habitat quality. Furthermore, among these high-quality areas, only 27% are within conservation units (CUs). For the climate change future, the size of high-quality habitat areas within the species' distribution area is projected to decrease by an average of 43% by the year 2050. This reduction is also observed in high-quality habitat areas within CUs, with a projected decrease of 40%. The study findings highlight the severity of the climate change impacts and land-use land-cover transformations. We demonstrate that the method employed in this study yields more robust results compared to most commonly used methods. However, as it requires information about the life history of species, which is often not readily available for biodiversity, applying this method to other taxonomic groups may pose challenges. An alternative approach is to integrate distribution modeling maps with areas containing remnants of natural vegetation within the altitude range where the species occurs. This strategy aligns closely with the robust results obtained from the habitat quality analysis employed in this study. Our results highlight the severe impacts of climate change and land use on the extent of high-quality habitat areas for species, both within and outside of protected areas (PAs). Furthermore, using intrinsic species characteristics for analyzing suitable areas for their persistence yields more robust results compared to other methods. It is clear that there is an urgent need to conserve optimal regions for species persistence identified through robust methods, as this will enhance the resilience of populations against the climate crisis and anthropogenic pressures