气候变化领域集成服务门户(CCPortal): Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates

CCPortal

DOI	10.1016/j.foreco.2020.118498
	Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates
	Keane R.E.; Holsinger L.M.; Loehman R.
发表日期	2020
ISSN	0378-1127
卷号	477
英文摘要	Land managers need new tools for planning novel futures due to climate change. Species distribution modeling (SDM) has been used extensively to predict future distributions of species under different climates, but their map products are often too coarse for fine-scale operational use. In this study we developed a flexible, efficient, and robust method for mapping current and future distributions and abundances of vegetation species and communities at the fine spatial resolutions that are germane to land management. First, we mapped Potential Vegetation Types (PVTs) using conventional statistical modeling techniques (Random Forests) that used bioclimatic ecosystem process and climate variables as predictors. We obtained over 50% accuracy across 13 mapped PVTs for our study area. We then applied future climate projections as climate input to the Random Forest model to generate future PVT maps, and used field data describing the occurrence of tree and non-tree species in each PVT category to model and map species distribution for current and future climate. These maps were then compared to two previous SDM mapping efforts with over 80% agreement and equivalent accuracy. Because PVTs represent the biophysical potential of the landscape to support vegetation communities as opposed to the vegetation that currently exists, they can be readily linked to climate forecasts and correlated with other, climate-sensitive ecological processes significant in land management, such as fire regimes and site productivity. © 2020
英文关键词	Climate offsets; Constancy; Habitat types; Random forests; Statistical modeling; WXFIRE
语种	英语
scopus关键词	Climate change; Decision trees; Ecosystems; Forestry; Land use; Population distribution; Random forests; Vegetation; Bioclimatic models; Future climate projections; Random forest modeling; Species distribution modeling; Species distribution models; Species distributions; Statistical modeling; Vegetation community; Climate models; climate effect; environmental modeling; forest fire; landscape change; spatial distribution; vegetation mapping; vegetation type; Distribution; Ecosystems; Forestry; Land Use; Maps; Plants; Trees
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154970
作者单位	USDA Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory, 5775 Hwy 10 West, Missoula, MT 59808, United States; U.S. Geological Survey, Alaska Science Center, 4210 University Drive, Anchorage, AK 99508, United States
推荐引用方式 GB/T 7714	Keane R.E.,Holsinger L.M.,Loehman R.. Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates[J],2020,477.
APA	Keane R.E.,Holsinger L.M.,&Loehman R..(2020).Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates.Forest Ecology and Management,477.
MLA	Keane R.E.,et al."Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates".Forest Ecology and Management 477(2020).