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Identification and predictability of soil quality indicators from conventional soil and vegetation classifications
Journal article   Open access   Peer reviewed

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

Paul Simfukwe, Paul W. Hill, Bridget A. Emmett and Davey L. Jones
PloS one, Vol.16(10), e0248665
2021
DOI: https://doi.org/10.1371/journal.pone.0248665
PMID: 34679075
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Published1.80 MBDownloadView
CC BY V4.0,  Open Access

Abstract

Multidisciplinary Sciences Science & Technology Science & Technology - Other Topics
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.

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30 Record Views
9 Times Cited - Web of Science

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Collaboration types
Domestic collaboration
International collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.45 Soil Science
3.45.112 Soil Carbon Dynamics
Web Of Science research areas
Soil Science
ESI research areas
Agricultural Sciences
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