文献类型：期刊文献

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

作者：Zhou, Xiao[1] Fu, Liyong[2,3] Sharma, Ram P.[4] He, Peng[5] Lei, Yuancai[2,3] Guo, Jinping[1]

第一作者：Zhou, Xiao

通信作者：Guo, JP[1]

机构：[1]Shanxi Agr Univ, Coll Forestry, Taigu 030801, Shanxi, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[3]Natl Forestry & Grassland Adm, Key Lab Forest Management & Growth Modeling, Beijing 100091, Peoples R China;[4]Tribhuwan Univ, Inst Forestry, Kathmandu 44600, Nepal;[5]Natl Forestry & Grassland Adm, Cent South Inventory & Planning Inst, Changsha 410014, Peoples R China

年份：2021

卷号：32

期号：6

起止页码：2447-2458

外文期刊名：JOURNAL OF FORESTRY RESEARCH

收录：;Scopus(收录号：2-s2.0-85103353247);WOS:【SCI-EXPANDED(收录号:WOS:000633271700001)】；

基金：The work was supported by the National Natural Science Foundations of China (No. 31971653).

语种：英文

外文关键词：Base models; Regional mortality models; Mixed-effects modeling; Model validation; Forest management

摘要：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.