文献类型：期刊文献

英文题名：Environmental Response of Tree Species Distribution in Northeast China with the Joint Species Distribution Model

作者：Yong, Juan[1,2] Duan, Guangshuang[3] Chen, Shaozhi[1] Lei, Xiangdong[4]

第一作者：Yong, Juan

通信作者：Chen, SZ[1];Lei, XD[2]

机构：[1]Chinese Acad Forestry, Res Inst Forestry Policy & Informat, Beijing 100091, Peoples R China;[2]China Forestry Grp Corp, Beijing 100036, Peoples R China;[3]Xinyang Normal Univ, Coll Math & Stat, Xinyang 464000, Peoples R China;[4]Chinese Acad Forestry, State Key Lab Efficient Prod Forest Resources, Key Lab Forest Management & Growth Modelling, Inst Forest Resource Informat Tech,Natl Forestry &, Beijing 100091, Peoples R China

年份：2024

卷号：15

期号：6

外文期刊名：FORESTS

收录：;EI(收录号：20242616511186);Scopus(收录号：2-s2.0-85197112332);WOS:【SCI-EXPANDED(收录号:WOS:001257729700001)】；

基金：This research was funded by National Key R&D Program of China (Grant No. 2022YFD2200501).

语种：英文

外文关键词：joint species distribution model; niche; environmental factors; Tjur R-2

摘要：The composition, distribution, and growth of native natural forests are important references for the restoration, structural adjustment, and close-to-nature transformation of artificial forests. The joint species distribution model is a powerful tool for analyzing community structure and interspecific relationships. It has been widely used in biogeography, community ecology, and animal ecology, but it has not been extended to natural forest conservation and restoration in China. Therefore, based on the 9th National Forest Inventory data in Jilin Province, combined with environmental factors and functional traits of tree species, this study adopted the joint species distribution model-including a model with all variables (model FULL), a model with environmental factors (model ENV), and a model with spatial factors (model SPACE)-to examine the distribution of multiple tree species. The results show that, in models FULL and ENV, the environmental factors explaining the model variation were ranked as follows, climate > site > soil. The explanatory power was as follows: model FULL (AUC = 0.8325, Tjur R-2 = 0.2326) > model ENV (AUC = 0.7664, Tjur R-2 = 0.1454) > model SPACE (AUC = 0.7297, Tjur R-2 = 0.1346). Tree species niches in model ENV were similar to those in model FULL. Compared to predictive power, we found that the information transmitted by environmental and spatial predictors overlaps, so the choice between model FULL and ENV should be based on the purpose of the model, rather than the difference in predictive ability. Both models can be used to study the adaptive distribution of multiple tree species in northeast China.