文献类型：期刊文献

英文题名：A climate sensitive mixed-effects diameter class mortality model for Prince Rupprecht larch (Larix gmelinii var. principis-rupprechtii) in northern China

作者：Zhou, Xiao[1,2,3] Chen, Qiao[3] Sharma, Ram P.[4] Wang, Yihao[5] He, Peng[6] Guo, Jinping[2] Lei, Yuancai[3] Fu, Liyong[1,3]

第一作者：Zhou, Xiao

通信作者：Fu, LY[1]

机构：[1]Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China;[2]Shanxi Agr Univ, Coll Forestry, Taigu 030801, Shanxi, Peoples R China;[3]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[4]Tribhuwan Univ, Inst Forestry, Kathmandu 44600, Nepal;[5]Chongqing Normal Univ, Coll Geog & Tourism, Chongqing 401331, Peoples R China;[6]Natl Forestry & Grassland Adm, Cent South Inventory & Planning Inst, Changsha 410014, Peoples R China

年份：2021

卷号：491

外文期刊名：FOREST ECOLOGY AND MANAGEMENT

收录：;EI(收录号：20212910661186);Scopus(收录号：2-s2.0-85110457203);WOS:【SCI-EXPANDED(收录号:WOS:000647735500008)】；

基金：We would like to thank the the Thirteenth Fiveyear Plan Pioneering project of High Technology Plan of the National Department of Technology (No. 2017YFC0503906) and the National Natural Science Foundations of China (No. 31971653) for the financial support of this study. We are thankful to two anonymous reviewers for the insightful comments and suggestions that helped improve the article.

语种：英文

外文关键词：Stand mortality; Basic model; Mixed-effects modeling; Climate change; Forest management

摘要：Forest mortality is an important variable commonly included as one of the predictors in the growth and yield models that are the fundamental decision-making tools in forest management. The existing forest mortality models for Larch (Larix gmelinii var. principis-rupprechtii) forest, which plays key roles in maintaining forest ecosystem functions and reducing atmospheric carbon concentration through the sequestration, are based on the traditional modeling methods, and these models do not account for the effects of climate on the forest mortality. Developing climate sensitive mortality models are useful for formulating effective forest management strategies in the context of climate change. We developed the diameter class mortality models using the data of 102 temporary sample plots distributed across the Guandi Mountain National Forest Park and Wutai Mountain Boqiang State-owned Forest Farm in the Shanxi Province of northern China. Four commonly used mortality functions were used to fit the data. Among many climatic and dendrometric variables evaluated, number of trees per diameter class (NC), mean annual precipitation (MAP); median diameter class (MDC), and mean temperature difference (DT) contributed significantly highly to the mortality variations. Then, these variables were selected as predictors to develop the two-level nonlinear mixed-effects mortality models applicable to the diameter class levels. The random effects at the levels of both the sample plots and stands with different site quality (blocks) were taken into account to build the models. Compared to other three models derived from the Poisson; Zeroinflated Poisson; Hurdle Poisson functions, the two-level Logistic mixed-effects mortality model better explained the effects of climate variables on the forest mortality of Larch. Tree mortality increased with increasing NC and MAP, however, MDC and DT had the opposite effects with diameter class increasing. Modeling the random effects at the block-level alone led to significantly high correlations among the residuals, and correlations were significantly reduced when the random effects were modeled at both the block- and sample plotlevels. Excessive rain during the growing season decreased the rate of tree mortality, especially for diameter classes with high number of trees. Findings from this study can be combined with the knowledge of the adaptive management to reduce the risks and uncertainties associated with forest management decision.