Aug 2026· Global Change Biology· Vol 32· 0 citations· 66 references
Medicine
Abstract
Ecosystem respiration (ER) is the largest source of biogenic CO2 to the atmosphere, and its temperature sensitivity (Q10) before reaching maximum values is crucial for understanding land–climate feedback. However, despite decades of studies showing that Q10 varies considerably across space, time, and biomes, the mechanisms underlying this variability remain unresolved. Here we demonstrate that global variation in Q10 can be reconciled within a unified hydrothermal framework. Using data from 142 eddy covariance sites around the world, we show that Q10 exhibits unimodal responses to soil moisture. At each site, Q10 first increases with soil moisture, peaks at a threshold (SMth), and then declines. This SMth is ecosystem‐specific, which consistent with mechanisms involving plant–soil–microbial interactions, shaped by long‐term hydroclimatic regimes and soil physical constraints. Global mapping of SMth shows that about 25% of the planet's vegetated land currently operates above SMth, including many carbon‐rich peatlands and tropical forests, where moderate drying may amplify temperature sensitivity and accelerate carbon loss. By identifying soil moisture thresholds as a first‐order control on Q10, our study provides a unifying mechanism that links hydrological state to the thermal sensitivity of carbon fluxes. This framework offers a predictive basis for anticipating respiration responses to climate change by explicitly resolving whether shifts in soil moisture move ecosystems toward or away from these critical thresholds.
The temperature sensitivity of soil carbon (C) and nitrogen (N) mineralization commonly expressed as the Q
10
coefficient, plays a pivotal role in regulating soil–atmosphere greenhouse gas exchanges in temperate ecosystems. This review synthesizes findings from 181 peer-reviewed studies (1960–2025) to evaluate how soil properties, substrate quality, microbial traits, and land-use history interact to shape Q
10
dynamics under climatic warming. Using a structured, thematically coded literature review, we identify mechanistic pathways that govern mineralization responses across major temperate soil orders. Clay-rich soils with high short-range ordered (SRO) minerals consistently exhibit low Q
10
values (1.3–2.0) due to mineral protection of soil organic matter (SOM). In contrast, coarse-textured and disturbed soils exhibit elevated thermal sensitivity (> 3.0). Microbial C use efficiency (CUE), enzyme activity, and functional group composition further modulate mineralization responses, especially under seasonal freeze–thaw or rewetting events. Land-use transitions, including tillage, afforestation, and organic amendments, significantly alter Q
10
by altering aggregation, SOM accessibility, and microbial community structure. Despite advances, Earth system models often overlook the spatiotemporal heterogeneity of Q
10
, limiting prediction accuracy. We highlight the need for integrating depth-resolved mineralogical traits, microbial acclimation, and management history into climate–soil feedback frameworks. This synthesis advances a mechanistic foundation for improving biogeochemical models and informing soil-based climate mitigation strategies.
K. N. Sheuly, Khalid Syfullah, Z. Solaiman· Biogeochemistry· 0 citations
Understanding how the spatiotemporal variability of precipitation affects ecosystem respiration (RE) is central to carbon–climate feedback in climate-smart agriculture, yet remains unresolved for the alpine agricultural region of the southern Qinghai–Tibet Plateau, where flux observations are sparse. Using 25 years (2000–2024) of monthly gridded climate and remote sensing data for the Yarlung Zangbo River Basin and Its Two Tributaries Basin, we developed a flux tower-constrained reference–respiration (Rref) environment-matching model in which Rref varies with the enhanced vegetation index (EVI) and land surface temperature (LST) to correct the Lloyd–Taylor parameterization. The correction reduced the RE root mean square error by 54.8% (1.04 → 0.47 gC·m−2·month−1) and eliminated systematic bias (+0.80 → −0.001) relative to an independent gridded RECO product. We then constructed a multidimensional index of precipitation variability (intra-annual concentration, interannual variability, long-term trend, spatial clustering) and combined random forest, spatial regression, lag analysis, and structural equation modeling (SEM) to disentangle direct and indirect pathways from precipitation variability to RE. The central finding is an indirect-conduction mechanism: precipitation concentration (PCI) affects RE almost entirely through vegetation productivity (PCI → GPP → RE, indirect effect −0.676) rather than directly (direct effect +0.076, opposite in sign), because low temperature and high soil water holding capacity buffer the immediate soil moisture response. The basin functions as a net carbon source (mean NEP = −0.550 gC·m−2·month−1) with a significant warming-driven interannual RE increase (Sen’s slope = 0.0025 yr−1, p = 0.022) that is independent of the stable precipitation total. The framework offers a transferable paradigm for carbon flux attribution in alpine regions under sparse observation.
