Shifts in the dynamics of productivity signal ecosystem state transitions at the biome-scale

doi:10.1111/ele.13126

CORC > 地理科学与资源研究所 > 中国科学院地理科学与资源研究所 > 生态系统研究网络观测与模拟重点实验室 > CERN水分分中心

	Shifts in the dynamics of productivity signal ecosystem state transitions at the biome-scale
	Hu, Zhongmin 1,2,3; Guo, Qun 2,3; Li, Shenggong 2,3; Piao, Shilong 4; Knapp, Alan K.5,6; Ciais, Philippe 7; Li, Xinrong 8; Yu, Guirui 2,3
刊名	ECOLOGY LETTERS
	2018-10-01
卷号	21 期号:10 页码:1457-1466
关键词	Climate change grassland resilience state transition tipping point variability
ISSN号	1461-023X
DOI	10.1111/ele.13126
通讯作者	Guo, Qun(guoq@igsnrr.ac.cn) ; Li, Shenggong(lisg@igsnrr.ac.cn)
英文摘要	Understanding ecosystem dynamics and predicting directional changes in ecosystem in response to global changes are ongoing challenges in ecology. Here we present a framework that links productivity dynamics and ecosystem state transitions based on a spatially continuous dataset of above-ground net primary productivity (ANPP) from the temperate grassland of China. Across a regional precipitation gradient, we quantified spatial patterns in ANPP dynamics (variability, asymmetry and sensitivity to rainfall) and related these to transitions from desert to semi-arid to mesic steppe. We show that these three indices of ANPP dynamics displayed distinct spatial patterns, with peaks signalling transitions between grassland types. Thus, monitoring shifts in ANPP dynamics has the potential for predicting ecosystem state transitions in the future. Current ecosystem models fail to capture these dynamics, highlighting the need to incorporate more nuanced ecological controls of productivity in models to forecast future ecosystem shifts.
资助项目	National Key R&D Program of China[2017YFA0604801] ; National Natural Science Foundation of China[31570437] ; National Natural Science Foundation of China[31400425] ; National Natural Science Foundation of China[31420103917] ; Startup Foundation for Talented Scholars in South China Normal University ; Youth Innovation Promotion Association, CAS[2015037] ; Youth Innovation Research Team Project[LENOM2016Q0003]
WOS关键词	EARLY-WARNING SIGNALS ; REGIME SHIFTS ; CATASTROPHIC SHIFTS ; USE EFFICIENCY ; INTERANNUAL VARIABILITY ; GRASSLAND PRODUCTIVITY ; RAINFALL VARIABILITY ; CLIMATE VARIABILITY ; MESIC GRASSLAND ; PRECIPITATION
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	WILEY
WOS记录号	WOS:000444413300001
资助机构	National Key R&D Program of China ; National Natural Science Foundation of China ; Startup Foundation for Talented Scholars in South China Normal University ; Youth Innovation Promotion Association, CAS ; Youth Innovation Research Team Project
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/52925]
专题	地理科学与资源研究所_生态系统研究网络观测与模拟重点实验室_CERN水分分中心
通讯作者	Guo, Qun; Li, Shenggong
作者单位	1.South China Normal Univ, Sch Geog, Shipai Campus, Guangzhou 510631, Guangdong, Peoples R China 2.Chinese Acad Sci, Synth Res Ctr Chinese Ecosyst Res Network, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China 4.Peking Univ, Coll Urban & Environm Sci, Key Lab Earth Surface Proc, Dept Ecol,Minist Educ, Beijing 100871, Peoples R China 5.Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA 6.Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA 7.Lab Sci Climatet Environm, Gif Sur Yvette, France 8.Chinese Acad Sci, Shapotou Desert Res & Expt Stn, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Hu, Zhongmin,Guo, Qun,Li, Shenggong,et al. Shifts in the dynamics of productivity signal ecosystem state transitions at the biome-scale[J]. ECOLOGY LETTERS,2018,21(10):1457-1466.
APA	Hu, Zhongmin.,Guo, Qun.,Li, Shenggong.,Piao, Shilong.,Knapp, Alan K..,...&Yu, Guirui.(2018).Shifts in the dynamics of productivity signal ecosystem state transitions at the biome-scale.ECOLOGY LETTERS,21(10),1457-1466.
MLA	Hu, Zhongmin,et al."Shifts in the dynamics of productivity signal ecosystem state transitions at the biome-scale".ECOLOGY LETTERS 21.10(2018):1457-1466.