Exploring the use of learning techniques for relating the site index of radiata pine stands with climate, soil and physiography

Forest Ecology and Management(2020)

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摘要
•Stepwise, LAR and IFSR approaches do not perform an effective variable selection.•LASSO and PLS show a significant regression to the mean.•MARS approach models SI more effectively than purely linear approaches.•Heat variables, such as the sum of degree-days, have a positive influence on SI.•Frost and hydric stress variables have a negative influence on SI.
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关键词
Site index,Pinus radiata,Stand growth modelling,Machine learning,Climate change
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