We built a classification tree （CT） model to estimate climatic factors controlling the cold temperate coniferous forest （CTCF） distributions in Yunnan province and to predict its potential habitats under the curre...We built a classification tree （CT） model to estimate climatic factors controlling the cold temperate coniferous forest （CTCF） distributions in Yunnan province and to predict its potential habitats under the current and future climates, using seven climate change scenarios, projected over the years of 2070-2099. The accurate CT model on CTCFs showed that minimum temperature of coldest month （TMW） was the overwhelmingly potent factor among the six climate variables. The areas of TMW〈-4.05 were suitable habitats of CTCF, and the areas of -1.35 〈 TMW were non-habitats, where temperate conifer and broad-leaved mixed forests （TCBLFs） were distribute in lower elevation, bordering on the CTCF. Dominant species of Abies, Picea, and Larix in the CTCFs, are more tolerant to winter coldness than Tsuga and broad-leaved trees including deciduous broad-leaved Acer and Betula, evergreen broad- leaved Cyclobalanopsis and Lithocarpus in TCBLFs. Winter coldness may actually limit the cool-side distributions of TCBLFs in the areas between -1.35℃ and -4.05℃, and the warm-side distributions of CTCFs may be controlled by competition to the species of TCBLFs. Under future climate scenarios, the vulnerable area, where current potential （suitable ＋ marginal） habitats （80,749 km^2） shift to non-habitats, was predicted to decrease to 55.91% （45,053 km^2） of the current area. Inferring from the current vegetation distribution pattern, TCBLFs will replace declining CTCFs. Vulnerable areas predicted by models are important in determining priority of ecosystem conservation.展开更多
基金supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the EnvironmentJapan and JSPS KAKENHI Grant Numbers 15H02833
文摘We built a classification tree （CT） model to estimate climatic factors controlling the cold temperate coniferous forest （CTCF） distributions in Yunnan province and to predict its potential habitats under the current and future climates, using seven climate change scenarios, projected over the years of 2070-2099. The accurate CT model on CTCFs showed that minimum temperature of coldest month （TMW） was the overwhelmingly potent factor among the six climate variables. The areas of TMW〈-4.05 were suitable habitats of CTCF, and the areas of -1.35 〈 TMW were non-habitats, where temperate conifer and broad-leaved mixed forests （TCBLFs） were distribute in lower elevation, bordering on the CTCF. Dominant species of Abies, Picea, and Larix in the CTCFs, are more tolerant to winter coldness than Tsuga and broad-leaved trees including deciduous broad-leaved Acer and Betula, evergreen broad- leaved Cyclobalanopsis and Lithocarpus in TCBLFs. Winter coldness may actually limit the cool-side distributions of TCBLFs in the areas between -1.35℃ and -4.05℃, and the warm-side distributions of CTCFs may be controlled by competition to the species of TCBLFs. Under future climate scenarios, the vulnerable area, where current potential （suitable ＋ marginal） habitats （80,749 km^2） shift to non-habitats, was predicted to decrease to 55.91% （45,053 km^2） of the current area. Inferring from the current vegetation distribution pattern, TCBLFs will replace declining CTCFs. Vulnerable areas predicted by models are important in determining priority of ecosystem conservation.
