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Water balance creates a threshold in soil pH at the global scale

Nature volume 540, pages 567–569 (2016)Cite this article

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Abstract

Soil pH regulates the capacity of soils to store and supply nutrients, and thus contributes substantially to controlling productivity in terrestrial ecosystems1. However, soil pH is not an independent regulator of soil fertility—rather, it is ultimately controlled by environmental forcing. In particular, small changes in water balance cause a steep transition from alkaline to acid soils across natural climate gradients2,3. Although the processes governing this threshold in soil pH are well understood, the threshold has not been quantified at the global scale, where the influence of climate may be confounded by the effects of topography and mineralogy. Here we evaluate the global relationship between water balance and soil pH by extracting a spatially random sample (n = 20,000) from an extensive compilation of 60,291 soil pH measurements. We show that there is an abrupt transition from alkaline to acid soil pH that occurs at the point where mean annual precipitation begins to exceed mean annual potential evapotranspiration. We evaluate deviations from this global pattern, showing that they may result from seasonality, climate history, erosion and mineralogy. These results demonstrate that climate creates a nonlinear pattern in soil solution chemistry at the global scale; they also reveal conditions under which soils maintain pH out of equilibrium with modern climate.

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Figure 1: Soil pH at 0.5 m depth versus annual water balance.
Figure 2: Outliers from the global relationship between pH and MAP minus PET.

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Acknowledgements

We thank P. Vitousek, S. Fendorf, X. Feng and C. Kouba for guidance and comments. Soil data were provided by multiple contributing organizations (Extended Data Table 1). Funding for E.W.S. was provided by a Graduate Research Fellowship from the United States National Science Foundation.

Author information

Author notes

  1. J. E. Johnson

    Present address: †Present address: Department of Global Ecology, Carnegie Institution for Science, Stanford, California, USA.,

Authors and Affiliations

  1. Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, California, USA

    E. W. Slessarev & J. P. Schimel

  2. Department of Environmental Science, Policy and Management, University of California, Berkeley, California, USA

    Y. Lin

  3. Department of Geography, University of California, Santa Barbara, California, USA

    N. L. Bingham & O. A. Chadwick

  4. Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA

    J. E. Johnson

  5. School of Atmospheric Sciences, Sun Yat-Sen University, Guangzhou, Guangdong, China

    Y. Dai

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Contributions

Research was conceived by E.W.S., O.A.C., Y.L., N.L.B., J.P.S. and J.E.J. Data aggregation and processing tasks were shared by E.W.S., Y.L. and Y.D. Statistical analysis and chemical calculations were performed by E.W.S. The manuscript was written by E.W.S. with input from all authors.

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Correspondence to E. W. Slessarev.

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The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks R. Merckx, S. Porder and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Soil pH versus calcite and exchangeable aluminium.

Transparent points show a spatial sample of 20,000 measurements from the NCSS database. a, The relationship between soil pH at 0.5 m and CaCO3 equivalents as a mass percentage. The yellow line shows the calculated pH of a solution in equilibrium with calcite and atmospheric CO2 (345 parts per million) at 25 °C. b, The relationship between soil pH at 0.5 m and the log-ratio of exchangeable calcium (CaX) to exchangeable aluminium (AlX), which is thought to control the pH of gibbsite-buffered soils. The yellow line is the fit by least-squares regression (b0 = 4.96, b1 = 0.32, R2 = 0.36, P < 0.01).

Extended Data Figure 2 Results of spatial resampling.

Transparent points show a spatial sample of 20,000 measurements (a and b) and a random sample of 20,000 measurements (c and d). a, c, pH at 0.5 m depth versus MAP minus PET. b, d, The geographic distribution of measurements in the Americas.

Extended Data Figure 3 Soil pH at 0.5 m depth versus alternative water-balance models.

Transparent points show a spatial sample of 20,000 measurements of soil pH at 0.5 m depth. a, Soil pH versus MAP. b, Soil pH versus MAP minus PET estimated using the Priestley–Taylor method driven by CERES radiation data. c, MAP minus AET, from the LandFlux-EVAL synthesis. d, MAP minus PET estimated using the Priestley–Taylor method driven by GEWEX radiation data.

Extended Data Figure 4 Soil pH at 0.1 m depth versus MAP minus PET.

Transparent points show a spatial sample of 20,000 measurements of soil pH at 0.1 m depth. Side panels show histograms of MAP minus PET and soil pH, and yellow lines show predicted pH values of CaCO3-buffered soils (8.2) and Al(OH)3-buffered soils (5.1).

Extended Data Figure 5 Calcite and exchangeable aluminium versus MAP minus PET.

Transparent points represent a spatial sample of 20,000 measurements from the NCSS database. a, Calcite (CaCO3) equivalents as mass percentage versus MAP minus PET. b, Exchangeable aluminium as a percentage of the effective cation exchange capacity versus MAP minus PET. These data are not reported for all samples in the NCSS database, and so points on the plot represent only the subset of the data with reported values.

Extended Data Figure 6 Dry-climate soil pH versus seasonality, relief and carbonates.

Transparent points show soil pH at 0.5 m depth in the driest quartile of MAP minus PET (n = 5,000). a, Soil pH versus the coefficient of variation (CV) of precipitation. b, Soil pH versus local relief. c, Violin plots showing soil pH versus carbonate lithology. Panels d and e show the proportion of the observations with pH < 6.5, binned into deciles of the variable on the x axis; panel f shows the proportion in each lithologic category. Black lines show logistic regression fits, with associated chi-squared (χ2) statistics and P values from likelihood ratio tests for precipitation CV (χ2 = 167.65, P < 0.01), local relief (χ2 = 76.5, P < 0.01) and carbonate lithology (χ2 = 91.42, P < 0.01). Dashed lines show the proportion of observations with pH < 6.5.

Extended Data Figure 7 Wet-climate soil pH versus seasonality, relief and carbonates.

Transparent points show soil pH at 0.5 m depth in the wettest quartile of MAP minus PET (n = 5,000). a, Soil pH versus the coefficient of variation of precipitation. b, Soil pH versus local relief. c, Violin plots showing soil pH versus carbonate lithology. Panels d and e show the proportion of the observations with pH >6.5, binned into deciles of the variable on the x axis; panel f shows the proportion in each lithologic category. Black lines show logistic regression fits, with associated χ2 statistics and P values from likelihood ratio tests for precipitation CV (χ2 = 3.5, P = 0.06), local relief (χ2 = 61.29, P < 0.01) and carbonate lithology (χ2 = 156.41, P < 0.01). Dashed lines show the proportion of observations with pH > 6.5.

Extended Data Table 1 Soil profile data sets
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Extended Data Table 2 Gridded Environmental Data sets
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Slessarev, E., Lin, Y., Bingham, N. et al. Water balance creates a threshold in soil pH at the global scale. Nature 540, 567–569 (2016). https://doi.org/10.1038/nature20139

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