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Spatial patterns of soil and ecosystem respiration regulated by biological and environmental variables along a precipitation gradient in semi‐arid grasslands in China
Author(s) -
Xu Wenfang,
Li Xianglan,
Liu Wei,
Li Linghao,
Hou Longyu,
Shi Huiqiu,
Xia Jiangzhou,
Liu Dan,
Zhang Haicheng,
Chen Yang,
Cai Wenwen,
Fu Yang,
Yuan Wenping
Publication year - 2016
Publication title -
ecological research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.628
H-Index - 68
eISSN - 1440-1703
pISSN - 0912-3814
DOI - 10.1007/s11284-016-1355-x
Subject(s) - environmental science , ecosystem , precipitation , terrestrial ecosystem , soil respiration , arid , grassland , ecosystem respiration , biomass (ecology) , atmospheric sciences , soil carbon , ecology , primary production , soil science , soil water , geography , biology , geology , meteorology
Precipitation is a key environmental factor in determining ecosystem structure and function. Knowledge of how soil and ecosystem respiration responds to climate change (e.g., precipitation) and human activities (e.g., grazing or clipping) is crucial for assessing the impacts of climate change on terrestrial ecosystems and for improving model simulations and predictions of future global carbon (C) cycling in response to human activities. In this study, we examined the spatial patterns of soil and ecosystem respiration along a precipitation gradient from 167.7 to 398.1 mm in a semi‐arid grassland. Our results showed that soil and ecosystem respiration increased linearly with increasing mean annual precipitation. The trends were similar to those of shoot biomass, litter and soil total C content along the precipitation gradient. Our results indicated that precipitation was the primary controlling factor in determining the spatial pattern of soil and ecosystem respiration in semi‐arid grasslands in China. The linear/nonlinear relationships in this study describing the variations of the ecosystem carbon process with precipitation can be useful for model development, parameterization and validation at the regional scale to improve predictions of how carbon processes in grasslands respond to climate change, land use and grassland management.