Zixuan Wang, Haihua Shen, Aijun Xing, Jingyun Fang. Biotic and abiotic factors jointly drive the temperature sensitivity of soil respiration in forests worldwide[J]. Forest Ecosystems, 2025, 14(1): 100340. DOI: 10.1016/j.fecs.2025.100340
Citation: Zixuan Wang, Haihua Shen, Aijun Xing, Jingyun Fang. Biotic and abiotic factors jointly drive the temperature sensitivity of soil respiration in forests worldwide[J]. Forest Ecosystems, 2025, 14(1): 100340. DOI: 10.1016/j.fecs.2025.100340

Biotic and abiotic factors jointly drive the temperature sensitivity of soil respiration in forests worldwide

  • The sensitivity of soil respiration (Rs) to temperature (Q10) is a key parameter for benchmarking the carbon (C) cycle and climate feedbacks in the context of global warming. However, previous studies on the factors that drive forest soil Q10 have focused mostly on abiotic factors, such as climate and soil, while the role of biotic factors has been less examined. Here, we compiled a global dataset of 766 soil Q10 values and 17 matched biotic and abiotic factors to explore the factors that drive the variability of global forest soil Q10 using a random forest (RF) model. Our findings showed that soil Q10 increased with microbial biomass carbon (MBC), which was the most important predictor. Additionally, soil Q10 was positively correlated with leaf phosphorus content (LPC) but was negatively correlated with leaf N:P, indicating that plant ecological stoichiometry might be a factor that explained soil Q10 variability. All abiotic factors, including climate, soil properties, and elevation, had great predictive power and were significantly related to soil Q10. By comparing the soil Q10 in multispecies forests and monocultures, we found that Q10 in the mixed needle-leaved and broad-leaved forests (NF & BF) was lower than in monocultures. Our study revealed that, in addition to abiotic factors, biotic factors were also strong predictors of forest soil Q10, which can deepen our understanding of soil respiration in response to global warming and provide insights for improving carbon cycle models.
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