干旱区生态环境知识资源中心(Arid): Dryland sensitivity to climate change and variability using nonlinear dynamics

Arid

DOI	10.1073/pnas.2305050120
	Dryland sensitivity to climate change and variability using nonlinear dynamics
	Sasaki, Takehiro; Collins, Scott L.; Rudgers, Jennifer A.; Batdelger, Gantsetseg; Baasandai, Erdenetsetseg; Kinugasa, Toshihiko
通讯作者	Sasaki, T
来源期刊	PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
ISSN	0027-8424
EISSN	1091-6490
出版年	2023
卷号	120 期号:35
英文摘要	Primary productivity response to climatic drivers varies temporally, indicating state-dependent interactions between climate and productivity. Previous studies primarily employed equation -based approaches to clarify this relationship, ignoring the state-dependent nature of ecological dynamics. Here, using 40 y of climate and productivity data from 48 grassland sites across Mongolia, we applied an equation-free, nonlinear time-series analysis to reveal sensitivity patterns of productivity to climate change and variability and clarify underlying mechanisms. We showed that productivity responded positively to annual precipitation in mesic regions but negatively in arid regions, with the opposite pattern observed for annual mean temperature. Furthermore, productivity responded negatively to decreasing annual aridity that integrated precipitation and temperature across Mongolia. Productivity responded negatively to interannual variability in precipitation and aridity in mesic regions but positively in arid regions. Overall, interannual temperature variability enhanced productivity. These response patterns are largely unrecognized; however, two mechanisms are inferable. First, time-delayed climate effects modify annual productivity responses to annual climate conditions. Notably, our results suggest that the sensitivity of annual productivity to increasing annual precipitation and decreasing annual aridity can even be negative when the negative time-delayed effects of annual precipitation and aridity on productivity prevail across time. Second, the proportion of plant species resistant to water and temperature stresses at a site determines the sensitivity of productivity to climate variability. Thus, we highlight the importance of nonlinear, state-dependent sensitivity of productivity to climate change and variability, accurately forecasting potential biosphere feedback to the climate system.
英文关键词	aridification climate extreme convergent cross-mapping drought legacy empirical dynamic modeling
类型	Article
语种	英语
开放获取类型	hybrid, Green Published
收录类别	SCI-E
WOS记录号	WOS:001115836500001
WOS关键词	PRECIPITATION VARIABILITY ; VEGETATION ; VULNERABILITY ; PRODUCTIVITY ; TEMPERATURE ; ECOSYSTEMS ; GRASSLANDS ; STABILITY ; RESPONSES ; MONGOLIA
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/398166
推荐引用方式 GB/T 7714	Sasaki, Takehiro,Collins, Scott L.,Rudgers, Jennifer A.,et al. Dryland sensitivity to climate change and variability using nonlinear dynamics[J],2023,120(35).
APA	Sasaki, Takehiro,Collins, Scott L.,Rudgers, Jennifer A.,Batdelger, Gantsetseg,Baasandai, Erdenetsetseg,&Kinugasa, Toshihiko.(2023).Dryland sensitivity to climate change and variability using nonlinear dynamics.PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,120(35).
MLA	Sasaki, Takehiro,et al."Dryland sensitivity to climate change and variability using nonlinear dynamics".PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 120.35(2023).