Biogeographic variation in temperature sensitivity of decomposition in forest soils

Abstract

Determining soil carbon (C) responses to rising temperature is critical for projections of the feedbacks between terrestrial ecosystems, C cycle, and climate change. However, the direction and magnitude of this feedback remain highly uncertain due largely to our limited understanding of the spatial heterogeneity of soil C decomposition and its temperature sensitivity. Here we quantified C decomposition and its response to temperature change with an incubation study of soils from 203 sites across tropical to boreal forests in China spanning a wide range of latitudes (18°16' to 51°37'N) and longitudes (81°01' to 129°28'E). Mean annual temperature (MAT) and mean annual precipitation primarily explained the biogeographic variation in the decomposition rate and temperature sensitivity of soils: soil C decomposition rate decreased from warm and wet forests to cold and dry forests, while Q_10-MAT (standardized to the MAT of each site) values displayed the opposite pattern. In contrast, biological factors (i.e. plant productivity and soil bacterial diversity) and soil factors (e.g. clay, pH, and C availability of microbial biomass C and dissolved organic C) played relatively small roles in the biogeographic patterns. Moreover, no significant relationship was found between Q_10-MAT and soil C quality, challenging the current C quality-temperature hypothesis. Using a single, fixed Q_10-MAT value (the mean across all forests), as is usually done in model predictions, would bias the estimated soil CO₂ emissions at a temperature increase of 3.0°C. This would lead to overestimation of emissions in warm biomes, underestimation in cold biomes, and likely significant overestimation of overall C release from soil to the atmosphere. Our results highlight that climate-related biogeographic variation in soil C responses to temperature needs to be included in next-generation C cycle models to improve predictions of C-climate feedbacks.

Keywords: Q 10; carbon cycle; carbon cycle modelling; carbon decomposition; climate change; forest; spatial heterogeneity; temperature sensitivity.