China ranks fifth in the world in terms of forest area, covering a wide climate gradient from cold temperate to tropical regions, and playing an important role in the global carbon cycle. In the past two decades, research on forest soil respiration (Rs) in China has rapidly increased, but the resulting Rs data needs to be summarized. Based on this, this dataset compiles a comprehensive dataset of undisturbed forest ecosystem Rs in China from literature published up to December 31, 2018, including monthly Rs and simultaneously measured soil temperature (N=8317), monthly average Rs (N=5003), and annual Rs (N=634). In addition, detailed plot information was recorded, such as geographic location, climatic factors, forest characteristics, and measurement descriptions. Studied some aspects of the dataset - the Rs equation fitted to soil temperature, temperature sensitivity (Q10), monthly variations, and annual outflows in cold temperate, temperate, subtropical, and tropical regions. I hope this dataset can be used by the scientific community to better understand the carbon cycle of China's forest ecosystems and reduce the uncertainty of large-scale carbon budget assessments.
This dataset is sourced from the PANGAEA website（ https://doi.org/10.1594/PANGAEA.943617 ）.
This dataset selects commonly used measurement methods, namely infrared gas analyzer (Li-6400, Li-8100, Li-8150 models (LI-COR company, Lincoln, Nebraska, USA) and gas chromatography. At the same time, relevant information was also recorded, such as geographical location (province, research site, latitude, longitude, and altitude), climatic factors (annual average temperature and annual average precipitation), forest stand description (forest type, origin, age, density, average tree height, and diameter at breast height), measurement system (method, time, frequency, territorial area, height, and quantity).
The data quality is good.
This work is licensed under a
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Commons Attribution 4.0 International License.
CSTR:11738.11.NCDC.PANGAEA.DB6811.2025
10.1594/PANGAEA.943617