Estimation of Soil Respiration by Its Driving Factors Based on Multi-Source Data in a Sub-Alpine Meadow in North China

Soil respiration (Rs) in high-altitude areas are normally sensitive to varying climatic conditions. The objective of this research was mainly to explore temporal variations in Rs rates and the corresponding controlling factors for the establishment of appropriate fitting models in a sub-alpine meadow of north China. The data was obtained through field measuring and extraction of the Moderate Resolution Imaging Spectroradiometer (MODIS) in the geographical unit of the study site over the period of 2007 to 2015. The main results were as follows: (1) seasonal variations in Rs rates, soil temperature (Ts), land surface temperature (LST), and normalized difference vegetation index (NDVI) all produced symmetrical bell type patterns, while soil moisture (Ms) showed a fluctuating pattern, (2) a Ts-exponential model could greatly capture seasonal variations of Rs rates in the study site, reflecting the role of temperature as a dominant driving factor in determining Rs temporal variations in alpine meadow areas, (3) there was no significant difference between the performing indicators evaluating the proposed Ts-exponential model and the LST-exponential model. This indicated great potential for applying remote sensing products to estimate seasonal Rs rates and 4) seasonal variations in Rs rates towards temperature sensitivity (Q10) showed a concave curve and dramatically decreased as the temperature increased from −1 to 11 °C. Overall, the results indicated that attention to significant effects of climatic conditions on Rs, particularly in areas of low temperature, should be warranted. Also, applicability of remote sensing products for estimating Rs was reflected and demonstrated.