Spatial ensemble learning for predicting the potential geographical distribution of invasive species
Author:
Affiliation:
1. National-local Joint Engineering Laboratory of Geospatial Information Technology, Hunan University of Science and Technology, Xiangtan, China
2. School of Geosciences and Info-Physics, Central South University, Changsha, China
Funder
Scientific Research Fund of Hunan Provincial Education Department
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/13658816.2024.2376325
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3. Spatio-temporal variability in the strength, directionality, and relative importance of climate on occupancy and population densities in a philopatric mammal, the American pika (Ochotona princeps);Billman P.D.;Frontiers in Ecology and Evolution,2023
4. Using biodiversity databases to verify and improve descriptions of tree species climatic requirements;Booth T.H.;Forest Ecology and Management,2014
5. Random forests;Breiman L.;Machine Learning,2001
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