Impacts of climate change on the potential distribution of epiphytic cacti in the Caatinga biome, Brazil.

The Caatinga biome is the largest dry tropical forest region in South America as well as one of the most vulnerable regions in the world to the climate changes forecast for this century. Climate forecasts for the biome include increased air temperature, reduced rainfall and aridization. This biome does not have a homogeneous landscape; instead it has several rainforest enclaves. This article describes a study to model the potential distribution of four epiphytic cactus species (Epiphyllum phyllanthus (L.) Haw., Rhipsalis floccosa Salm-Dyck ex Pfeiff., Rhipsalis lindbergiana K. Schum and Rhipsalis russellii Britton & Rose.) in the biome under future climate scenarios and traces out a prognosis for the enclaves and the biome. For that purpose, we used the MaxEnt modeling method, considering two future time intervals (2041-2060 and 2061-2080) and the interval 1961-1990 for the current situation, with the RCP4.5 and 8.5 scenarios. The projections for future potential distribution showed a spatial contractions greater than 88% found in the areas of high potential presence for the target species throughout the biome and in all the scenarios. The results strengthen the expectation of aridization in the Caatinga biome, with the loss or shrinkage of rainforest enclaves as time progresses.

Modeling the potential distribution of Epiphyllum phyllanthus (L.) Haw. under future climate scenarios in the Caatinga biome.

The climate change projections for the Caatinga biome this century are for an increase in temperature and reduction in rainfall, leading to aridization and plant cover dominated by Cactaceae. The objective of this study was to model the potential distribution of Epiphyllum phyllanthus (L.) Haw., a cactus that is native to the Caatinga biome, considering two possible future climate scenarios, to assess this species' spatio-temporal response to these climate change, and thus to evaluate the need or not for conservation measures. For this purpose, we obtained biogeographic information on the target species from biodiversity databases, choosing nine environmental variables and applying the MaxEnt algorithm. We considered the time intervals 2041-2060 and 2061-2080, centered on 2050 and 2070, respectively, and the greenhouse gas scenarios RCP4.5 and 8.5. For all the scenarios considered, the models generated for 2050 and 2070 projected drastic contraction (greater than 80%) for the areas of potential occurrence of the species in relation to the present potential. The remaining areas were found to be concentrated in the northern portion of the biome, specifically in the northern part of the state of Ceará, which has particular characteristics.