Identification and predictability of soil quality indicators from conventional soil and vegetation classifications

Simfukwe, Paul; Hill, Paul W.; Emmett, Bridget A. ORCID: https://orcid.org/0000-0002-2713-4389; Jones, Davey L.. 2021 Identification and predictability of soil quality indicators from conventional soil and vegetation classifications. PLoS ONE, 16 (10), e0248665. 22, pp. https://doi.org/10.1371/journal.pone.0248665

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Abstract/Summary

The physical, chemical and biological attributes of a soil combined with abiotic factors (e.g. climate and topography) drive pedogenesis and some of these attributes have been used as proxies to soil quality. Thus, we investigated: (1) whether appropriate soil quality indicators (SQIs) could be identified in soils of Great Britain, (2) whether conventional soil classification or aggregate vegetation classes (AVCs) could predict SQIs and (3) to what extent do soil types and/ or AVCs act as major regulators of SQIs. Factor analysis was used to group 20 soil attributes into six SQI which were named as; soil organic matter (SOM), dissolved organic matter (DOM), soluble N, reduced N, microbial biomass, DOM humification (DOMH). SOM was identified as the most important SQI in the discrimination of both soil types and AVCs. Soil attributes constituting highly to the SOM factor were, microbial quotient and bulk density. The SOM indicator discriminated three soil type groupings and four aggregate vegetation class groupings. Among the soil types, only the peat soils were discriminated from other groups while among the AVCs only the heath and bog classes were isolated from others. However, the peat soil and heath and bog AVC were the only groups that were distinctly discriminated from other groups. All other groups heavily overlapped with one another, making it practically impossible to define reference values for each soil type or AVC. The two-way ANOVA showed that the AVCs were a better regulator of the SQIs than the soil types. We conclude that conventionally classified soil types cannot predict the SQIs defined from large areas with differing climatic and edaphic factors. Localised areas with similar climatic and topoedaphic factors may hold promise for the definition of SQI that may predict the soil types or AVCs.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1371/journal.pone.0248665
UKCEH and CEH Sections/Science Areas:	Soils and Land Use (Science Area 2017-)
ISSN:	1932-6203
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
NORA Subject Terms:	Agriculture and Soil Science
Date made live:	02 Nov 2021 12:51 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531334

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