Fig. 5: Environmental drivers for the geochemistry and associated impacts of soil-dissolved organic matter (DOM). | Nature Communications

Fig. 5: Environmental drivers for the geochemistry and associated impacts of soil-dissolved organic matter (DOM).

From: Spatial patterns and environmental functions of dissolved organic matter in grassland soils of China

Fig. 5

a–c The importance of environmental predictors for a DOM quantity, b size fraction, and c fluorescence composition based on random forest regression analysis. An increase in the mean square error (MSE) denotes the higher importance of environmental variables. All models were significant at P < 0.01. DOC dissolved organic carbon, DON dissolved organic nitrogen, HMW 3.4–25 kDa, LMW <1.2 kDa, MAT mean annual temperature, MAP mean annual precipitation, Srad surface solar radiation, PET potential evapotranspiration, LAI leaf area index, NPP net primary production, GPP gross primary production, SM soil moisture, Clay soil clay fraction, pH soil pH, CEC cation exchange capacity of soil, Na, Mg, and Ca soil exchangeable sodium, potassium, and calcium, respectively, SOC soil organic carbon, TN soil total nitrogen, TP soil total phosphorus. d, e Partial least-squares path model (PLS-PM) showing the relationships between DOM vs d ecosystem carbon exchange and e local cancer incidence and mortality, under the influence of environmental variables. Rs soil respiration, NEP net ecosystem productivity. A detailed description of the latent variables in the model is available in Supplementary Table S2. The purple and red lines in PLS-PM denote significant positive and negative relationships between variables, respectively. PLS-PM are built after 999 bootstraps and only significant (P < 0.05) paths are shown. Numbers in the arrows are standard path coefficients, and the determination coefficients (R2) are the variance explained by the model. GoF goodness of fit. *P < 0.05; **P < 0.01; ***P < 0.001.

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