Climate change effects on the geographic distribution of specialist tree species of the Brazilian tropical dry forests

The aim of this study was to evaluate the ecological niche models (ENMs) for three specialist trees (Anadenantheracolubrina, Aspidosperma pyrifolium and Myracrodruon urundeuva) in seasonally dry tropical forests (SDTFs) in Brazil, considering present and future pessimist scenarios (2080) of climate change. These three species exhibit typical deciduousness and are widely distributed by SDTF in South America, being important in studies of the historical and evolutionary processes experienced by this ecosystem. The modeling of the potential geographic distribution of species was done by the method of maximum entropy (Maxent). We verified a general expansion of suitable areas for occurrence of the three species in future (c.a., 18%), although there was reduction of areas with high environmental suitability in Caatinga region. Precipitation of wettest quarter and temperature seasonality were the predictor variables that most contributed to our models. Climatic changes can provide more severe and longer dry season with increasing temperature and tree mortality in tropics. On this scenario, areas currently occupied by rainforest and savannas could become more suitable for occurrence of the SDTF specialist trees, whereas regions occupied by Caatinga could not support the future level of unsustainable (e.g., aridity). Long-term multidisciplinary studies are necessary to make reliable predictions of the plant’s adaptation strategies and responses to climate changes in dry forest at community level. Based on the high deforestation rate, endemism and threat, public policies to minimize the effects of climate change on the biodiversity found within SDTFs must be undertaken rapidly.Este estudo tem como objetivo avaliar a modelagem de nicho ecológico (ENMs) para três espécies especialistas (Anadenanthera colubrina, Aspidosperma pyrifolium e Myracrodruon urundeuva) de florestas tropicais secas (FTSs) no Brasil, considerando o cenário de mudanças climáticas: presente e futuro pessimistas (2080). Estas três espécies são decíduas e amplamente distribuídas pelas FTSs na América do Sul, sendo importante em estudos sobre os processos históricos e evolutivos experimentados por este ecossistema. A modelagem da distribuição geográfica potencial das espécies foi construída através do método de máxima entropia (Maxent). Foi observada uma expansão geral de áreas adequadas para a ocorrência das três espécies no futuro (cerca de 18%), embora tenha existido uma redução das áreas com alta adequabilidade ambiental na região da Caatinga. A precipitação do trimestre mais úmido e a sazonalidade da temperatura foram os fatores que mais contribuíram para os nossos modelos. As mudanças climáticas podem gerar períodos secos mais severos e longos, com aumento da temperatura e mortalidade de árvores em regiões tropicais. Neste cenário, as áreas atualmente ocupadas por florestas úmidas e savanas poderiam tornar-se mais adequadas para a ocorrência das árvores especialistas em FTSs, enquanto que as regiões ocupadas por Caatinga não poderiam suportar o nível futuro da não adequabilidade (por exemplo, aridez). Estudos multidisciplinares de longa duração são necessários para fazer previsões confiáveis de estratégias adaptativas das plantas e respostas às variações climáticas em FTS em nível de comunidade. Com base na elevada taxa de desmatamento, endemismo e ameaça, políticas públicas para minimizar os efeitos das mudanças climáticas sobre a biodiversidade encontradas dentro FTSs devem ser realizadas rapidamente

Climate change effects on the geographic distribution of specialist tree species of the Brazilian tropical dry forests

AbstractThe aim of this study was to evaluate the ecological niche models (ENMs) for three specialist trees (Anadenantheracolubrina, Aspidosperma pyrifolium and Myracrodruon urundeuva) in seasonally dry tropical forests (SDTFs) in Brazil, considering present and future pessimist scenarios (2080) of climate change. These three species exhibit typical deciduousness and are widely distributed by SDTF in South America, being important in studies of the historical and evolutionary processes experienced by this ecosystem. The modeling of the potential geographic distribution of species was done by the method of maximum entropy (Maxent).We verified a general expansion of suitable areas for occurrence of the three species in future (c.a., 18%), although there was reduction of areas with high environmental suitability in Caatinga region. Precipitation of wettest quarter and temperature seasonality were the predictor variables that most contributed to our models. Climatic changes can provide more severe and longer dry season with increasing temperature and tree mortality in tropics. On this scenario, areas currently occupied by rainforest and savannas could become more suitable for occurrence of the SDTF specialist trees, whereas regions occupied by Caatinga could not support the future level of unsustainable (e.g., aridity). Long-term multidisciplinary studies are necessary to make reliable predictions of the plant’s adaptation strategies and responses to climate changes in dry forest at community level. Based on the high deforestation rate, endemism and threat, public policies to minimize the effects of climate change on the biodiversity found within SDTFs must be undertaken rapidly

Climate change effects on the geographic distribution of specialist tree species of the Brazilian tropical dry forests

AbstractThe aim of this study was to evaluate the ecological niche models (ENMs) for three specialist trees (Anadenantheracolubrina, Aspidosperma pyrifolium and Myracrodruon urundeuva) in seasonally dry tropical forests (SDTFs) in Brazil, considering present and future pessimist scenarios (2080) of climate change. These three species exhibit typical deciduousness and are widely distributed by SDTF in South America, being important in studies of the historical and evolutionary processes experienced by this ecosystem. The modeling of the potential geographic distribution of species was done by the method of maximum entropy (Maxent).We verified a general expansion of suitable areas for occurrence of the three species in future (c.a., 18%), although there was reduction of areas with high environmental suitability in Caatinga region. Precipitation of wettest quarter and temperature seasonality were the predictor variables that most contributed to our models. Climatic changes can provide more severe and longer dry season with increasing temperature and tree mortality in tropics. On this scenario, areas currently occupied by rainforest and savannas could become more suitable for occurrence of the SDTF specialist trees, whereas regions occupied by Caatinga could not support the future level of unsustainable (e.g., aridity). Long-term multidisciplinary studies are necessary to make reliable predictions of the plant’s adaptation strategies and responses to climate changes in dry forest at community level. Based on the high deforestation rate, endemism and threat, public policies to minimize the effects of climate change on the biodiversity found within SDTFs must be undertaken rapidly

Spatial distribution of aboveground biomass stock in tropical dry forest in Brazil

Climate change is being intensified by anthropogenic emission of greenhouse gasses, highlighting the value of forests for carbon dioxide storing carbon in their biomass. Seasonally dry tropical forests are a neglected, threatened, but potentially critical biome for helping mitigate climate change. In South America, knowing the amount and distribution of carbon in Caatinga seasonally dry vegetation is essential to understand its contribution to the global carbon cycle and subsequently design a strategic plan for its conservation. The present study aimed to model and map the spatial distribution of the potential forest biomass stock across 32 forest fragments of Caatinga, in the state of Bahia, Brazil, using regression kriging and Inverse Square of Distance techniques, building from point measurements of vegetation biomass made on-the-ground in ecological plots. First, a model for estimating biomass was fitted as a function of environmental variables to apply regression kriging, and then applied to the maps of the selected components. Elevation, temperature, and precipitation explained 46% of the biomass variations in the Caatinga. The model residuals showed strong spatial dependence and were mapped based on geostatistical criteria, selecting the spherical semivariogram model for interpolation by ordinary kriging. Biomass was also mapped by the Inverse Square of Distance approach. The quality of the regression model suggests that there is good potential for estimating biomass here from environmental variables. The regression kriging showed greater detail in the spatial distribution and revealed a spatial trend of increasing biomass from the north to south of the domain. Additional studies with greater sampling intensity and the use of other explanatory variables are suggested to improve the model, as well as to maximize the technique’s ability to capture the actual biomass behavior in this newly studied seasonally dry ecosystem