Development of Polymorphic Index Model for Assessing Subtropical Secondary Natural Oak Forest Site Quality Under Complex Site and Climate Variables DOI Open Access
Lang Huang, Guangyu Zhu, Guoqi Chen

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(11), P. 1867 - 1867

Published: Oct. 24, 2024

Site and climate conditions are the key determinants controlling dominant height growth forest productivity, both independently interactively. Secondary natural oak forests a typical type in China, especially Hunan Province, but little is known about site index of this under complex variables subtropics. Based on survey data trees from 101 plots secondary obtained using spatial interpolation, we used random method, correlation analysis, analysis variance to determine main factors affecting proposed modeling method an based effect site–climate interaction type. Of variables, elevation affected stand most, followed by slope direction position. Winter precipitation summer mean maximum temperature had greatest impact height. To develop created 10 popular base models found low performance (R2 ranged 0.1731 0.2030). The optimal model was Mitscherlich form M3 = 0.1940) parameter significance tests. Since affect curve, were combined into types types, respectively, nonlinear mixed-effects approach simulate different their combinations as effects. Site–climate factor enhanced (M3.4) prediction accuracy 0.1940 0.8220) compared optimum model. After clustering 62 three, five, eight groups hierarchical clustering, with effects improved 0.8265) applicability. developed study could be assess regional evaluate productivity.

Language: Английский

Development of Polymorphic Index Model for Assessing Subtropical Secondary Natural Oak Forest Site Quality Under Complex Site and Climate Variables DOI Open Access
Lang Huang, Guangyu Zhu, Guoqi Chen

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(11), P. 1867 - 1867

Published: Oct. 24, 2024

Site and climate conditions are the key determinants controlling dominant height growth forest productivity, both independently interactively. Secondary natural oak forests a typical type in China, especially Hunan Province, but little is known about site index of this under complex variables subtropics. Based on survey data trees from 101 plots secondary obtained using spatial interpolation, we used random method, correlation analysis, analysis variance to determine main factors affecting proposed modeling method an based effect site–climate interaction type. Of variables, elevation affected stand most, followed by slope direction position. Winter precipitation summer mean maximum temperature had greatest impact height. To develop created 10 popular base models found low performance (R2 ranged 0.1731 0.2030). The optimal model was Mitscherlich form M3 = 0.1940) parameter significance tests. Since affect curve, were combined into types types, respectively, nonlinear mixed-effects approach simulate different their combinations as effects. Site–climate factor enhanced (M3.4) prediction accuracy 0.1940 0.8220) compared optimum model. After clustering 62 three, five, eight groups hierarchical clustering, with effects improved 0.8265) applicability. developed study could be assess regional evaluate productivity.

Language: Английский

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