In this study, we have analyzed the relationships of four manageable soil properties, soil texture, and climate variables on the scores of visual indicators of 132 soils across Europe and China. Correlations differed in acid-to-neutral and alkaline soils, both in strength and direction, which gave rise to the different rankings of the importances of the explanatory variables for each visual indicator. In alkaline soils, higher soil pH values significantly affected the score of the visual indicators and dominated other variables for most visual indicators; in acid soils, only the "presence of a tillage pan" was affected by pH, and, for most visual indicators, soil organic matter (SOM) and labile organic carbon (LOC) dominated other manageable variables. In both soil reaction groups, climate variables covaried similarly in terms of direction but with different significances for different indicators; the dominance of the variables was dependent on soil reaction. Eight out of 16 visual indicators (eight per reaction group) had a statistically significant dominant explanatory variable (soil property or climate variable). The soil pH must be accounted for when interpreting visual indicators of soils with more extreme pH (both acid and alkaline).
Citation: Fernando Teixeira. Determining the relative importance of climate and soil properties affecting the scores of visual soil quality indicators with dominance analysis[J]. AIMS Geosciences, 2024, 10(1): 107-125. doi: 10.3934/geosci.2024007
In this study, we have analyzed the relationships of four manageable soil properties, soil texture, and climate variables on the scores of visual indicators of 132 soils across Europe and China. Correlations differed in acid-to-neutral and alkaline soils, both in strength and direction, which gave rise to the different rankings of the importances of the explanatory variables for each visual indicator. In alkaline soils, higher soil pH values significantly affected the score of the visual indicators and dominated other variables for most visual indicators; in acid soils, only the "presence of a tillage pan" was affected by pH, and, for most visual indicators, soil organic matter (SOM) and labile organic carbon (LOC) dominated other manageable variables. In both soil reaction groups, climate variables covaried similarly in terms of direction but with different significances for different indicators; the dominance of the variables was dependent on soil reaction. Eight out of 16 visual indicators (eight per reaction group) had a statistically significant dominant explanatory variable (soil property or climate variable). The soil pH must be accounted for when interpreting visual indicators of soils with more extreme pH (both acid and alkaline).
| [1] | Peerlkamp P (1959) A visual method of soil structure evaluation. Meded vd Landbouwhogeschool en Opzoekingsstations van deStaat te Gent 24: 216–221. |
| [2] | Shepherd T (2000) Visual Soil Assessment. Field guide for cropping and pastoral grazing on flat to rolling country. horizons.mw & Landcare Research, Palmerston North. Available from: https://orgprints.org/30582/1/VSA_Volume1_smaller.pdf. |
| [3] |
Ball B, Batey T, Munkholm L (2007) Field assessment of soil structural quality—a development of the Peerlkamp test. Soil Use Manage 23: 329–337. https://doi.org/10.1111/j.1475-2743.2007.00102.x doi: 10.1111/j.1475-2743.2007.00102.x
|
| [4] |
Karlen D, Mausbach M, Doran J, et al. (1997) Soil quality: a concept, definition, and framework for evaluation (a guest editorial). Soil Sci Soc Am J 61: 4–10. https://doi.org/10.2136/sssaj1997.03615995006100010001x doi: 10.2136/sssaj1997.03615995006100010001x
|
| [5] |
Zeraatpisheh M, Ayoubi S, Mirbagheri Z, et al. (2021) Spatial prediction of soil aggregate stability and soil organic carbon in aggregate fractions using machine learning algorithms and environmental variables. Geoderma Reg 27: e00440. https://doi.org/10.1016/j.geodrs.2021.e00440 doi: 10.1016/j.geodrs.2021.e00440
|
| [6] |
Budescu DV (1993) Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression. Psychol Bull 114: 542–551. https://doi.org/10.1037/0033-2909.114.3.542 doi: 10.1037/0033-2909.114.3.542
|
| [7] | Tongway D, Hindley N (1995) Manual for Soil Condition Assessment of Tropical Grasslands. Csiro. Australia. Available from: https://publications.csiro.au/rpr/download?pid = procite: fa79052c-07eb-4345-a001-43e68c86ec4a & dsid = DS1. |
| [8] | Weil RR, Islam KR, Stine MA, et al. (2003) Estimating active carbon for soil quality assessment: A simplified method for laboratory and field use. Am J Alternative Agric 18: 3–17. |
| [9] | Alaoui A, Schwilch G (2016) Soil quality and agricultural management practices inventory at case study sites. Available from: https://www.isqaper-is.eu/soil-quality/visual-soil-assessment/77-labile-organic-carbon. |
| [10] | McLean EO (1983) Soil pH and lime requirement, Methods of soil analysis: Part 2 Chemical and microbiological properties 9: 199–224. https://doi.org/10.2134/agronmonogr9.2.2ed.c12 |
| [11] | Food and Agriculture Organization of the United Nations, Locate Climate Estimator (New_LocClim). 2005. Available from: http://www.fao.org/land-water/land/land-governance/land-resources-planning-toolbox/category/details/en/c/1032167/. |
| [12] |
Slessarev E, Lin Y, Bingham N, et al. (2016) Water balance creates a threshold in soil pH at the global scale. Nature 540: 567–569. https://doi.org/10.1038/nature20139 doi: 10.1038/nature20139
|
| [13] | Yang H, Wong WH, Bradley KD, et al. (2017) Partial and semi-partial correlations for categorical variables in educational research: addressing two common misconceptions. Gen Linear Model J 43: 1–45. |
| [14] |
Bhatt R, Singh P, Sharma S (2023) Changes in Soil Organic Pool and Carbon Preservation Capacity of Macro- and Micro-aggregates in Response to Land-Use Change in North-Western India. J Soil Sci Plant Nutr 23: 2849–2867. https://doi.org/10.1007/s42729-023-01239-x doi: 10.1007/s42729-023-01239-x
|
| [15] |
Malik AA, Puissant J, Buckeridge KM, et al. (2018) Land use driven change in soil pH affects microbial carbon cycling processes. Nat Commun 9: 3591. https://doi.org/10.1038/s41467-018-05980-1 doi: 10.1038/s41467-018-05980-1
|
| [16] |
Tajik S, Ayoubi S, Lorenz N (2020) Soil microbial communities affected by vegetation, topography and soil properties in a forest ecosystem. Appl Soil Ecol 149: 103514. https://doi.org/10.1016/j.apsoil.2020.103514 doi: 10.1016/j.apsoil.2020.103514
|
| [17] |
Kölbl A, Kögel-Knabner I (2004) Content and composition of free and occluded particulate organic matter in a differently textured arable Cambisol as revealed by solid-state 13C NMR spectroscopy. J Plant Nutr Soil Sci 167: 45–53. https://doi.org/10.1002/jpln.200321185 doi: 10.1002/jpln.200321185
|
| [18] |
Chenu C, Hassink J, Bloem J (2001) Short-term changes in the spatial distribution of microorganisms in soil aggregates as affected by glucose addition. Biol Fertil Soils 34: 349–356. https://doi.org/10.1007/s003740100419 doi: 10.1007/s003740100419
|
| [19] | Virto I, Antón R, Apesteguía M, et al. (2018) Role of Carbonates in the Physical Stabilization of Soil Organic Matter in Agricultural Mediterranean Soils. Soil Manage Clim Change, 121–136. https://doi.org/10.1016/b978-0-12-812128-3.00009-4 |
| [20] |
Alessandro O, Nyman P (2017) Aridity indices predict organic matter decomposition and comminution processes at landscape scale. Ecol Indic 78: 531–540. https://doi.org/10.1016/j.ecolind.2017.03.049 doi: 10.1016/j.ecolind.2017.03.049
|
| [21] |
Longepierre M, Widmer F, Keller T, et al. (2021) Limited resilience of the soil microbiome to mechanical compaction within four growing seasons of agricultural management. ISME Commun 1: 1–13. https://doi.org/10.1038/s43705-021-00046-8 doi: 10.1038/s43705-021-00046-8
|
| [22] |
Chenu C, Le Bissonnais Y, Arrouays D (2000) Organic Matter Influence on Clay Wettability and Soil Aggregate Stability. Soil Sci Soc Am J 64: 1479–1486. https://doi.org/10.2136/sssaj2000.6441479x doi: 10.2136/sssaj2000.6441479x
|
| [23] |
Prieto B, Silva B, Lantes O (2004) Biofilm quantification on stone surfaces: comparison of various methods. Sci Total Environ 333: 1–7. https://doi.org/10.1016/j.scitotenv.2004.05.003 doi: 10.1016/j.scitotenv.2004.05.003
|
| [24] |
Teixeira F (2023) The effects of climate and soil properties on the magnitude of the visual soil quality indicators: a logistic regression approach. AIMS Geosci 9: 492–512. https://doi.org/10.3934/geosci.2023027 doi: 10.3934/geosci.2023027
|
| [25] |
Teixeira F, Lemann T, Ferreira C, et al. (2023) Evidence of non-site-specific agricultural management effects on the score of visual soil quality indicators. Soil Use and Manage 39: 474–484. https://doi.org/10.1111/sum.12827 doi: 10.1111/sum.12827
|
| [26] |
Azizsoltani E, Honarjoo N, Ayoubi S (2019) How Soil Pore Distribution Could Help in Soil Quality Studies as an Appropriate Indicator. Eurasian Soil Sc 52: 654–660. https://doi.org/10.1134/S1064229319060036 doi: 10.1134/S1064229319060036
|
| [27] |
Lou Y, Xu M, Wang W, et al. (2011) Return rate of straw residue affects soil organic C sequestration by chemical fertilization. Soil and Tillage Res 113: 70–73. https://doi.org/10.1016/j.still.2011.01.007 doi: 10.1016/j.still.2011.01.007
|
| [28] | Golia, EE (2023) The impact of heavy metal contamination on soil quality and plant nutrition. Sustainable management of moderate contaminated agricultural and urban soils, using low cost materials and promoting circular economy. Sustainable Chem Pharm 33: 101046. https://doi.org/10.1016/j.scp.2023.101046 |
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Fernando Teixeira. Determining the relative importance of climate and soil properties affecting the scores of visual soil quality indicators with dominance analysis[J]. AIMS Geosciences, 2024, 10(1): 107-125. doi: 10.3934/geosci.2024007
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