How does the Net primary productivity respond to the extreme climate under elevation constraints in mountainous areas of Yunnan, China?

(a)-(d) represent the correlation between NPP estimated by CASA model and MOD17A3H data, the maximum control point of NPP at each grid point, the proportion of correlation between extreme climate indices and NPP, and the q value of NPP by the synergistic effect of extreme climate indices, respective...

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Veröffentlicht in:Ecological indicators 2022-05, Vol.138, p.108817, Article 108817
Hauptverfasser: He, Yunling, Yan, Wenbo, Cai, Ya, Deng, Fuying, Qu, Xinxing, Cui, Xilin
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Sprache:eng
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Zusammenfassung:(a)-(d) represent the correlation between NPP estimated by CASA model and MOD17A3H data, the maximum control point of NPP at each grid point, the proportion of correlation between extreme climate indices and NPP, and the q value of NPP by the synergistic effect of extreme climate indices, respectively. [Display omitted] •Exploring the relationship between extreme climate and NPP with altitude constraint.•Extreme precipitation was the main controlling factor of NPP at lower elevations.•The extreme temperature was the main controlling factor of NPP at higher elevations.•NPP is more susceptible to the interaction of extreme climate indices below 3000 m. Mountain ecosystems regulate global terrestrial carbon dynamics and are sensitive to changes of extreme climate. To discuss extreme climate’s impact on productivity of vegetation by using the elevation change as a binding force can provide a new reference for carbon sink management of ecosystem in alpine regions. The CASA model and Rclimdex1.0 were used to calculate NPP and 16 climate extremes indices, respectively, from 1982 to 2019 in Yunnan. The response characteristics of regional NPP to climate extremes were calculated using unary regression analysis, correlation analysis, geographic detector, and relative importance analysis. The results are as follows: (1) The turning point of NPP for various vegetation types appeared in the late 1980s in Yunnan. (2) The correlation between extreme precipitation index and NPP is more dependent on elevation than on extreme temperature indices. (3) Extreme climate indices are more sensitive in middle and high-elevation areas. As a result, NPP of alpine vegetation increased by more than 10% after the turning point compared with that before the turning point. (4) In the elevation range Ⅰ-IV (76–4000 m), the proportion of double-factor increase on NPP was more than 30%, while in the range of 4000–5000 m, the proportion of double-factor increase on NPP was
ISSN:1470-160X
1872-7034
DOI:10.1016/j.ecolind.2022.108817