干旱区生态环境知识资源中心(Arid): Forecasting semi-arid biome shifts in the Anthropocene

Arid

DOI	10.1111/nph.16381
	Forecasting semi-arid biome shifts in the Anthropocene
	Kulmatiski, Andrew 1,2; Yu, Kailiang 3,4; Mackay, D. Scott 5,6; Holdrege, Martin C.1,2; Staver, Ann Carla 7; Parolari, Anthony J.8; Liu, Yanlan 9; Majumder, Sabiha 10,11; Trugman, Anna T.12
通讯作者	Kulmatiski, Andrew
来源期刊	NEW PHYTOLOGIST
ISSN	0028-646X
EISSN	1469-8137
出版年	2020
卷号	226 期号:2 页码:351-361
英文摘要	Shrub encroachment, forest decline and wildfires have caused large-scale changes in semi-arid vegetation over the past 50 years. Climate is a primary determinant of plant growth in semi-arid ecosystems, yet it remains difficult to forecast large-scale vegetation shifts (i.e. biome shifts) in response to climate change. We highlight recent advances from four conceptual perspectives that are improving forecasts of semi-arid biome shifts. Moving from small to large scales, first, tree-level models that simulate the carbon costs of drought-induced plant hydraulic failure are improving predictions of delayed-mortality responses to drought. Second, tracer-informed water flow models are improving predictions of species coexistence as a function of climate. Third, new applications of ecohydrological models are beginning to simulate small-scale water movement processes at large scales. Fourth, remotely-sensed measurements of plant traits such as relative canopy moisture are providing early-warning signals that predict forest mortality more than a year in advance. We suggest that a community of researchers using modeling approaches (e.g. machine learning) that can integrate these perspectives will rapidly improve forecasts of semi-arid biome shifts. Better forecasts can be expected to help prevent catastrophic changes in vegetation states by identifying improved monitoring approaches and by prioritizing high-risk areas for management.
英文关键词	carbon metabolism critical threshold early-warning signal ecohydrology ecophysiology lagged mortality machine learning niche partitioning
类型	Review
语种	英语
国家	USA ; Switzerland ; France ; India
收录类别	SCI-E
WOS记录号	WOS:000519790300009
WOS关键词	WOODY PLANT ENCROACHMENT ; DROUGHT-INDUCED TREE ; CLIMATE-CHANGE ; LANDSCAPE HETEROGENEITY ; SLOWING-DOWN ; MORTALITY ; ECOSYSTEMS ; DYNAMICS ; SAVANNA ; VARIABILITY
WOS类目	Plant Sciences
WOS研究方向	Plant Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/315233
作者单位	1.Utah State Univ, Dept Wildland Resources, Logan, UT 84322 USA; 2.Utah State Univ, Ctr Ecol, Logan, UT 84322 USA; 3.Swiss Fed Inst Technol, Dept Environm Syst Sci, Univ Str 16, CH-8092 Zurich, Switzerland; 4.UVSQ, LSCE, IPSL, CEA,CNRS, F-91191 Gif Sur Yvette, France; 5.SUNY Buffalo, Dept Geog, Buffalo, NY 14261 USA; 6.SUNY Buffalo, Dept Environm & Sustainabil, Buffalo, NY 14261 USA; 7.Yale Univ, Dept Ecol & Evolutionary Biol, New Haven, CT 06511 USA; 8.Marquette Univ, Dept Civil Construct & Environm Engn, Milwaukee, WI 53233 USA; 9.Stanford Univ, Dept Earth Syst Sci, Stanford, CA 94305 USA; 10.Indian Inst Sci, Dept Phys, Bengaluru 560012, India; 11.Indian Inst Sci, Ctr Ecol Sci, Bengaluru 560012, India; 12.Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93117 USA
推荐引用方式 GB/T 7714	Kulmatiski, Andrew,Yu, Kailiang,Mackay, D. Scott,et al. Forecasting semi-arid biome shifts in the Anthropocene[J],2020,226(2):351-361.
APA	Kulmatiski, Andrew.,Yu, Kailiang.,Mackay, D. Scott.,Holdrege, Martin C..,Staver, Ann Carla.,...&Trugman, Anna T..(2020).Forecasting semi-arid biome shifts in the Anthropocene.NEW PHYTOLOGIST,226(2),351-361.
MLA	Kulmatiski, Andrew,et al."Forecasting semi-arid biome shifts in the Anthropocene".NEW PHYTOLOGIST 226.2(2020):351-361.