Potential planting areas for native tree species in minas gerais state, Brazil, based on environmental variables and wood demand

Abstract Wood production from native tree species in Brazil is primarily limited to exploitation of natural forests. The identification of potential habitats for tree planting may provide new opportunities for natural forest conservation and management and increase the viability of native species plantations for highly valuable wood production. This study aimed to identify potential habitats for native tree planting using a crop-zoning model that combines environmental variables and wood demand modeling. The target region for the study was Minas Gerais (MG) State, Southeast Region, Brazil. The MaxEnt model was used to match environmental variables and the occurrence of 19 economically important tree species. Wood demand modeling was performed through the Grouping Analysis algorithm, using Brazilian consumption records by species. The models generated with MaxEnt were highly accurate (area under the curve [AUC] ≥ 0.77). Apuleia leiocarpa (Vogel) J. F. Macbr., Hymenaea courbaril L., Micropholis venulosa (Mart. & E. ex Miq.) P., P., Pouteria caimito (Ruiz & Pav.) Radlk., Pouteria guianensis Aubl., Simarouba amara Aubl., and Tachigali paniculata Aubl. presented potential cultivation areas occupying 460,881, 572,467, 208,820, 202,989, 118,937, 158,254, and 288,769 km2, respectively. Three classes of wood demand were identified (R2 ≥ 0.82). The Belo Horizonte, Juiz de Fora, Montes Claros, and Uba micro-regions showed high demand for most species studied. The interaction between wood demand and areas with potential for planting each species allowed the specification of priority regions for reforestation. Regions with high demand and high cultivation potential occupied, in km², 19,993.23 for A. leiocarpa, 4,193.8 for H. courbaril, 1,939.6 for M. venulosa, 16,356.3 for P. caimito, 1,623.6 for P. guianensis, 0.8 for S. amara, and 53,566.2 for T. paniculata. Establishing these native tree species near wood-based industries in regions that match the environmental variables of their occurrence area leads to natural forest conservation and economic growth of consumption centers.