Ecosphere (Mar 2024)
Nonsignificant elevational trends of soil microbial respiration and temperature sensitivity in a subtropical forest
Abstract
Abstract Soil carbon (C) cycling plays a critical role in regulating global C budget and atmospheric CO2 concentrations. The ongoing global warming potentially accelerates soil C loss induced by microbial respiration (MR) and makes soil a large C source to the atmosphere. Quantifying the drivers of MR and its response to rising temperature (also called temperature sensitivity, Q10) should be a high priority to improve the modeling and prediction of terrestrial C cycle under global warming. In this study, we applied a standardized soil sampling along nine gradients from 410 to 1080 m in a subtropical forest in southern China. All soil samples were incubated at varying temperature gradients (10–15–20–25–20–15°C) to measure MR and Q10 every day for three weeks. Then all the measured MR was adjusted by the field temperature of each elevation gradient. Our objectives were to examine the response of MR and Q10 to the environmental change induced by elevational gradients in the subtropical forest and then quantify their main drivers. We totally collected 54 abiotic and biotic factors relative to the MR and Q10. Our results showed that the incubated MR increased from low to high elevation. However, a significant elevation trend of the adjusted MR was not examined after adjusting the field temperature of sampling sites, due to the trade‐off between increasing soil C concentration and declining temperature as elevation increased. We further found that the elevational gradients did not cause significant change in Q10. The variation in Q10 was negatively dominated by soil C quality, which declined nonlinearly along the elevation gradients. This study highlights the trade‐off between environment and biotic factors in determining soil C decomposition along elevational gradients. The uncertainty of MR measurements caused by unifying incubated temperature should not be ignored in future model development.
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