Increased interannual precipitation variability enhances the carbon sink in a semi‐arid grassland

Ru, Jingyi; Wan, Shiqiang; Hui, Dafeng; Song, Jian; Jing, Wang

doi:10.1111/1365-2435.14011

Cited by 21 publications

(1 citation statement)

References 71 publications

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“…In particular, it is necessary to clarify whether the state-dependent, nonlinear responses of productivity to climate change and variability are specific to cold and water-limited drylands, such as Mongolia. In addition, global-scale manipulative experiments incorporating climatic extremes ( 49 – 51 ) and model simulations ( 9 , 22 ) are required to elucidate the fundamental mechanisms underlying the observed patterns in dryland sensitivity to climate. Another consideration is the need for an explicit statistical test on the synergistic causal effects of temperature and precipitation on productivity under further methodological development, as the CCM permits the identification of causal relationships between two time-series variables ( 16 , 17 , 52 ).…”

Section: Resultsmentioning

confidence: 99%

Dryland sensitivity to climate change and variability using nonlinear dynamics

Sasaki,

Collins,

Rudgers

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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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.

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