Widespread underestimation of rain-induced soil carbon emissions from global drylands
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 by up to 30% during rain-pulse events, which annually contribute 16.9 ± 2.8% of ecosystem respiration and 9.6 ± 2.2% of net ecosystem productivity. We show that the carbon loss intensity correlates most strongly with annual productivity, aridity and soil pH. Finally, we identify a universal decay rate of rain-induced CO2 pulses and use it to bias-correct respiration estimates. Our research highlights the importance of rain-induced carbon emissions for the carbon balance of global drylands and suggests that ecosystem models may largely underrepresent the influence of rain pulses on the carbon cycle of drylands.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- US Department of Energy; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23), Climate and Environmental Sciences Division (SC-23.1 )
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 2587933
- Journal Information:
- Nature Geoscience, Journal Name: Nature Geoscience Journal Issue: 9 Vol. 18
- Country of Publication:
- United States
- Language:
- English
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