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Performance of statistical and machine learning-based methods for predicting biogeographical patterns of fungal productivity in forest ecosystems

Albert Morera Juan Martínez de Aragón José Antonio Bonet Jingjing Liang Sergio de-Miguel

森林生态系统（英文版）2021，Vol.8Issue(2)：278-291,14.

Performance of statistical and machine learning-based methods for predicting biogeographical patterns of fungal productivity in forest ecosystems

Albert Morera ¹Juan Martínez de Aragón ²José Antonio Bonet ³Jingjing Liang ¹Sergio de-Miguel²

作者信息

1. Department of Crop and Forest Sciences, University of Lleida, Av. Alcalde Rovira Roure 191, E-25198 Lleida, Spain
2. Joint Research Unit CTFC-AGROTECNIO-CERCA Center, Av. Rovira Roure 191, 25198 Lleida, Spain
3. Forest Science and Technology Centre of Catalonia, Ctra. Sant Lloren? de Morunys km 2, 25280 Solsona, Spain
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摘要

关键词

Modeling/Regression/Biogeography/Climate/Forest/Fungi/Mushrooms

Key words

Modeling/Regression/Biogeography/Climate/Forest/Fungi/Mushrooms

引用本文复制引用

Albert Morera,Juan Martínez de Aragón,José Antonio Bonet,Jingjing Liang,Sergio de-Miguel..Performance of statistical and machine learning-based methods for predicting biogeographical patterns of fungal productivity in forest ecosystems[J].森林生态系统（英文版）,2021,8(2):278-291,14.

基金项目

This work was supported by the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund.This work was partially supported by the Spanish Ministry of Science,Innovation and Universities(Grant No.RTI2018–099315-A-I00).J.A.B.benefitted from a Serra-Húnter Fellowship provided by the Government of Catalonia. （Grant No.RTI2018–099315-A-I00）

森林生态系统（英文版）

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ISSN：2095-6355

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