Divergent responses of carbon fluxes to elevated temperature and precipitation: A meta-analysis in North Hemisphere grassland ecosystems

Autor: Weikang Zhang, Shan Cong, Zhaogang Liu, Ming Zhao, Zhaoxia Jiang, Congcong Zheng
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Global Ecology and Conservation, Vol 56, Iss , Pp e03289- (2024)
Druh dokumentu: article
ISSN: 2351-9894
DOI: 10.1016/j.gecco.2024.e03289
Popis: The manipulation experiments involving increased precipitation and elevated temperature have elucidated a series of responses to the carbon fluxes (gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP)) in grassland ecosystems. It is still unclear how the duration, magnitude or local climate conditions of these manipulation experiments can affect the response of GEP, ER, and NEP. Here, we conducted a meta-analysis using data from 50 published studies that manipulated precipitation or temperature, while measuring GEP, ER, and NEP in North Hemisphere grassland ecosystems. The results showed that increased precipitation significantly increased the GEP and ER of grassland ecosystems in the Northern Hemisphere, with an average increase of 9.8 % and 12.5 %, respectively. In contrast to increased precipitation, warming did not have a significant effect on GEP and ER. Meantime, there was no significant response of the NEP to both elevated temperature and increased precipitation. Furthermore, we found that the responses of carbon fluxes in North Hemisphere grassland ecosystems were associated with the magnitude and duration of increased precipitation, as well as to local temperature and precipitation changes induced by increased precipitation and elevated temperature. GEP was positively correlated with the local temperature under warming and increased precipitation. These findings emphasize the divergent response of carbon fluxes to climate factors change such as temperature and precipitation in North Hemisphere grassland ecosystems, which helps us better protect grasslands and predict ecosystem functions in the future.
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