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Identification and predictability of soil quality indicators from conventional soil and vegetation classifications
Paul Simfukwe1, Paul W Hill2, Bridget A Emmett3
1Department of Agricultural Biotechnology and Biosciences, School of Agriculture and Natural Resources, Mulungushi University, Kabwe, Central Province, Zambia.
Plos One
|October 22, 2021
Summary
Soil quality indicators (SQIs) were identified using factor analysis. Aggregate vegetation classes (AVCs) better regulated SQIs than soil types, suggesting localized studies for effective SQI prediction.
Area of Science:
- Soil Science
- Environmental Science
- Ecology
Background:
- Soil quality indicators (SQIs) are crucial for understanding soil health, often derived from physical, chemical, and biological attributes.
- Abiotic factors like climate and topography significantly influence pedogenesis and soil quality.
Purpose of the Study:
- To identify appropriate SQIs in Great Britain's soils.
- To determine if conventional soil classification or aggregate vegetation classes (AVCs) can predict SQIs.
- To assess the regulatory role of soil types and AVCs on SQIs.
Main Methods:
- Factor analysis was employed to group 20 soil attributes into six SQIs: soil organic matter (SOM), dissolved organic matter (DOM), soluble N, reduced N, microbial biomass, and DOM humification (DOMH).
- Two-way ANOVA was used to compare the regulatory effects of soil types and AVCs on SQIs.
Main Results:
- Soil organic matter (SOM) emerged as the most significant SQI for discriminating soil types and AVCs.
- Only peat soils and heath/bog AVCs were distinctly identified; other groups showed considerable overlap, hindering reference value definition.
- Aggregate vegetation classes (AVCs) demonstrated a stronger regulatory influence on SQIs compared to conventional soil types.
Conclusions:
- Conventional soil classification is insufficient for predicting SQIs across large areas with diverse environmental conditions.
- Aggregate vegetation classes offer a more promising framework for predicting soil quality indicators.
- Future research focusing on localized areas with similar climatic and topoedaphic factors may lead to more effective SQI definitions and predictions.
