Humidity, low temperature extremes, and space influence floristic variation across an insightful gradient in the Subtropical Atlantic Forest

• Published in: Plant ecology 2015-06, Vol.216 (6), p.759-774
• Main Authors: Rezende, Vanessa Leite, Eisenlohr, Pedro V, Vibrans, Alexander Christian, de Oliveira-Filho, Ary Teixeira
• Format: Article
• Language: English
• Subjects: Analysis; Applied Ecology; autocorrelation; Biodiversity; Biomedical and Life Sciences; Climate change; Community & Population Ecology; Ecology; Environmental gradient; forest types; Global climate; Global temperature changes; Heterogeneity; Humidity; Inflation (Economics); least squares; Life Sciences; Low temperature; Plant Ecology; Plant species; Protection and preservation; Rainforests; Species composition; species diversity; Temperature; Terrestial Ecology; Trees; Tropical forests; Vegetation
• ISSN: 1385-0237; 1573-5052
• DOI: 10.1007/s11258-015-0465-9

The use of well-sampled regions and insightful environmental gradients can provide important theoretical knowledge for understanding the drivers of tropical forest patterns and processes, which are necessary for biological conservation. We investigated the variation in tree species composition across a vegetation gradient in the Subtropical Atlantic Forest, as well as various predictors that could impact such patterns. The exploratory and confirmatory analyses included 178 sampling units distributed among 13 different forest types containing binary occurrence records for 935 species from 25,546 trees. Confirmatory analyses were conducted considering spatial autocorrelation, a well-known factor responsible for type I error inflations. The floristic heterogeneity of the study area was revealed by clear patterns of floristic differentiation between vegetation types, as well as by the significant improvements in local models (GWR—geographically weighted regressions) over global models (OLS—ordinary least squares). We found that the observed floristic variation has most likely been driven by humidity from the Atlantic Ocean, low temperature extremes and geographic distance. The latter was revealed by the high contribution of spatial components to the partial models. These results from a shrinking biological hotspot, particularly those concerning the importance of temperature extremes, represent crucial data for identifying conservation priorities, especially considering the seriousness of the temperature shifts predicted by global climate change scenarios.