Predição da distribuição de espécies florestais usando variáveis topográficas e de índice de vegetação no leste do Acre, Brasil

摘要: Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge ecological requirements species. The aim this study was to evaluate if use forest inventories can improve estimation occurrence probability, identify limits potential habitat preference a group timber tree environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) height above nearest drainage (HAND). To estimate species we used maximum entropy method (Maxent). In comparison with random distribution, using topographic as features, Maxent predicted an average accuracy 86% geographical studied altitude NDVI were most important variables. There limitations interpolation models non-sampled locations that are outside elevation gradient associated data in approximately 7% basin area. Ceiba pentandra (samauma), Castilla ulei (caucho) Hura crepitans (assacu) is more likely occur nearby water course areas. Clarisia racemosa (guariuba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), parvifolium (amarelao) Astronium lecointei (aroeira) also upland well drained soils. This approach application on other tropical still less studied, especially those under pressure from logging.