Widespread underestimation of rain-induced soil carbon emissions from global drylands.

ABSTRACT: Dryland carbon fluxes, particularly those driven by ecosystem respiration, are highly sensitive to water availability and rain pulses. However, the magnitude of rain-induced carbon emissions remains unclear globally. Here we quantify the impact of rain-pulse events on the carbon balance of global drylands and characterize their spatiotemporal controls. Using eddy-covariance observations of carbon, water and energy fluxes from 34 dryland sites worldwide, we produce an inventory of over 1,800 manually identified rain-induced CO₂ pulse events. Based on this inventory, a machine learning algorithm is developed to automatically detect rain-induced CO₂ pulse events. Our findings show that existing partitioning methods underestimate ecosystem respiration and photosynthesis b

SUBMITTER: Nguyen NB 

PROVIDER: S-EPMC12422978 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature