机译:Performance of statistical and machine learning-based methods for predicting biogeographical patterns of fungal productivity in forest ecosystems
Department of Crop and Forest Sciences University of Lleida Av.Alcalde Rovira Roure 191 E-25198 Lleida SpainJoint Research Unit CTFC-AGROTECNIO-CERCA Center Av.Rovira Roure 191 25198 Lleida Spain;
Forest Science and Technology Centre of Catalonia Ctra.Sant Llorençde Morunys km 2 25280 Solsona Spain;
Department of Crop and Forest Sciences University of Lleida Av.Alcalde Rovira Roure 191 E-25198 Lleida SpainJoint Research Unit CTFC-AGROTECNIO-CERCA Center Av.Rovira Roure 191 25198 Lleida Spain;
Forest Advanced Computing and Artificial Intelligence Laboratory Department of Forestry and Natural Resources Purdue University West Lafayette IN 47907 USA;
Department of Crop and Forest Sciences University of Lleida Av.Alcalde Rovira Roure 191 E-25198 Lleida SpainJoint Research Unit CTFC-AGROTECNIO-CERCA Center Av.Rovira Roure 191 25198 Lleida Spain;
Modeling; Regression; Biogeography; Climate; Forest; Fungi; Mushrooms;