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Regressions underestimate the direct effect of soil moisture on land carbon sink variability

Zhen Wang, Dan Zhu, Xuhui Wang, Yao Zhang, Shushi Peng

2022Global Change Biology11 citationsDOI

Abstract

Multiple linear regression (MLR) is widely used to attribute causes of the interannual variability (IAV) of land carbon uptake, yet, parameter estimation in MLR can be problematic if the predictors are strongly inter-correlated. Recently, Humphrey et al., (2021) used MLR method to conclude that the indirect effect of soil moisture (SM) via land-atmosphere coupling, rather than direct effect of SM on photosynthesis and respiration, controls the IAV of NBP. Here we assess the validity of MLR and find that the direct effect of SM on NBP-IAV is greatly underestimated by MLR, which may undermine their main conclusion.

Topics & Concepts

Environmental scienceLinear regressionIndirect effectCarbon sinkWater contentSoil scienceAtmospheric sciencesSoil respirationSoil carbonAgronomySoil waterMathematicsStatisticsEcosystemEcologyBiologyLawGeotechnical engineeringPolitical scienceEngineeringGeologyPlant Water Relations and Carbon DynamicsClimate variability and modelsSoil and Unsaturated Flow
Regressions underestimate the direct effect of soil moisture on land carbon sink variability | Litcius