Generalized or general mixed-effect modelling of tree morality of Larix gmelinii subsp. principis-rupprechtii in Northern China

Tree mortality models play an important role in predicting tree growth and yield, but existing mortality models for Larix gmelinii subsp. principis-rupprechtii, an important species used for regeneration and afforestation in northern China, have overlooked potential regional influences on tree morta...

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Bibliographic Details
Published in:Journal of forestry research 2021-12, Vol.32 (6), p.2447-2458
Main Authors: Zhou, Xiao, Fu, Liyong, Sharma, Ram P., He, Peng, Lei, Yuancai, Guo, Jinping
Format: Article
Language:English
Subjects:
Afforestation
Analysis
Area
Biomedical and Life Sciences
Data acquisition
Forestry
Forests
Health aspects
Larix gmelinii
Life Sciences
Model forms
Morality
Mortality
Mountain forests
Mountains
Original Paper
Random variables
Regeneration
Trees
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Summary:Tree mortality models play an important role in predicting tree growth and yield, but existing mortality models for Larix gmelinii subsp. principis-rupprechtii, an important species used for regeneration and afforestation in northern China, have overlooked potential regional influences on tree mortality. This study used data acquired from 102 temporary sample plots (TSPs) in natural stands of Prince Rupprecht larch in the state-owned Guandi Mountain Forest ( n  = 67) and state-owned Boqiang Forest ( n  = 35) in northern China. To model stand-level tree mortality, we compared seven model forms of county data. Three continuous (dominant height, plot mean diameter, and basal area per hectare) and one dummy variable with two levels (region) were used as fixed effects variables. Tree morality variations caused by forest blocks were accounted for using forest blocks as a random effect in selected models. Results showed that tree mortality significantly positively correlated with stand basal area and dominant height, but negatively correlated with stand mean diameter. Incorporating both the dummy variables and random effects into the tree mortality models significantly increased the fitting improvements, and Hurdle Poisson mixed-effects model showed the most attractive fit statistics (largest R 2 and smallest RMSE) when employing leave-one-out cross-validation. These mixed-effects dummy variable models will be useful for accurately predicting Larix tree mortality in different regions.
ISSN:1007-662X
1993-0607
DOI:10.1007/s11676-021-01302-2