Abstract

Soil respiration is an important process in maintaining global carbon balance. Taking the Pangquangou Nature Reserve as the research area, based on the field measurement of soil respiration (Rs) data combined with altitude (ELE), soil temperature (T), soil moisture (SWC), normalized vegetation index (NDVI), slope (slope), soil total carbon (C), total nitrogen (N), and soil bulk density (BD), we analyzed the main driving forces and interactions of Rs spatial differentiation by using the geographic detector model. The results showed that:① the spatial variation of Rs and its influencing factors in the study area was moderate. The Rs was significantly positively correlated with NDVI, T, and N (P<0.01) and negatively with ELE, slope, and SWC (P<0.01). The Rs was significantly correlated with BD(P<0.05) but not with C(P>0.05). ② The multivariate linear model composed of NDVI and T explained 64.3% of Rs spatial variation. ③ ELE, T, and NDVI were the dominant driving forces of Rs spatial differentiation in the study area, which could explain 64%, 59%, and 48% of the spatial variability. ④ The interaction of the two factors enhanced the explanatory power of Rs spatial differentiation, and the maximum interaction factors were ELE∩BD (q=0.73), and T∩slope (q=0.74), respectively. Therefore, in the process of Rs estimation, combined with topographical and environmental conditions, the interaction between multiple factors should be considered.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.