ML4WX

Climate analysis & attribution

Greening of the earth does not compensate for rising soil heterotrophic respiration under climate change

Dilip G. T. Naidu, Sumanta Bagchi

Global Change Biology ·

Paper

In one sentence. Machine learning on 2001-2019 global NPP, heterotrophic respiration and climate data finds soil carbon losses likely as precipitation drives warming-related vulnerability.

Abstract

Abstract Stability of the soil carbon (C) pool under decadal scale variability in temperature and precipitation is an important source of uncertainty in our understanding of land–atmosphere climate feedbacks. This depends on how two opposing C‐fluxes—influx from net primary production (NPP) and efflux from heterotrophic soil respiration (Rh)—respond to covariation in temperature and precipitation. There is scant evidence to judge whether field experiments which manipulate both temperature and precipitation align with Earth System Models, or not. As a result, even though the world is generally greening, whether the resultant gains in NPP can offset climate change impacts on Rh, where, and by how much, remains uncertain. Here, we use decadal‐scale global time‐series datasets on NPP, Rh, temperature, and precipitation to estimate the two opposing C‐fluxes and address whether one can outpace the other. We implement machine‐learning tools on recent (2001–2019) and near‐future climate scenarios (2020–2040) to assess the response of both C‐fluxes to temperature and precipitation variation. We find that changes in C‐influx may not compensate for C‐efflux, particularly in wetter and warmer conditions. Soil‐C loss can occur in both tropics and at high latitudes since C‐influx from NPP can fall behind C‐efflux from Rh. Precipitation emerges as the key determinant of soil‐C vulnerability in a warmer world, implying that hotspots for soil‐C loss/gain can shift rapidly and highlighting that soil‐C is vulnerable to climate change despite widespread greening of the world. The direction of covariation between change in temperature and precipitation, rather than their magnitude, can help conceptualize highly variable patterns in C‐fluxes to guide soil‐C stewardship.

Labels

Topic
Climate analysis & attribution
Type
Application study
Method
Classical ML (trees, GP, linear, kernels)
Time scale
Climate projections / centennial
Domain
Global
Data
Other
Status
Research
Identifiers
DOI:10.1111/gcb.15531 OpenAlex:W3121222644
Added
2026-10-22

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