Dynamics and controls of carbon use efficiency across China’s grasslands

• Autorzy: Hou G. , Sun J. , Wang J.
• Języki publikacji: EN

Abstrakty

EN

China’s grasslands play a significant role in the carbon cycle. Accurately evaluating carbon use efficiency (CUE) of grassland ecosystems is of great importance. Therefore, we adopted moderate resolution imaging spectroradiometer documents to explore dynamics and controls of CUE across grasslands of China from 2001 to 2010. Results demonstrated that CUE presented an increasing trend (0 to 0.0067 year⁻¹) in the most studies regions except for desert steppe (-0.0046 to 0 year⁻¹). At spatial scale, the precipitation, temperature, and aridity index significantly regulated the dynamics of CUE in alpine grasslands. Furthermore, the different mechanisms are explored at the transect scale, and CUE revealed the positive correlation with aridity index (R² = 0.92, P<0.0001) and precipitation (R² = 0.88, P<0.0001), but a negative correlation with temperature (R² = 0.92, P<0.0001) in alpine grasslands. However, in temperate grasslands, CUE exposed the negative correlation with aridity index (R² = 0.40, P<0.0001) and precipitation (R² = 0.54, P<0.0001), but a positive correlation with temperature (R² = 0.56, P<0.0001). Moreover, precipitation was decreasing with the increased temperature in the alpine grasslands (R² = 0.85, P<0.0001) and temperature of grasslands (R² = 0.19, P<0.0001). In conclusion, CUE had a slight increased trend across grasslands in China, with higher precipitation, aridity index, and lower temperature promoting CUE in the alpine region – nevertheless restraining the CUE variations in grassland temperature. The better heat and water conditions in temperate grasslands than in alpine grasslands resulted in higher CUE in temperate grasslands.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2018
• Tom: 27
• Numer: 4
• Opis fizyczny: p.1541-1550,fig.,ref.

Twórcy

autor

Hou G.

• Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, P.R. China
• School of Earth Science and Resources, Chang’an University, Xian, P.R.China

autor

Sun J.

• Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, P.R. China

autor

Wang J.

• Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, P.R. China

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Identyfikatory

DOI

10.15244/pjoes/76912