Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewedConventional

Effects of land use and soil properties on taxon richness and abundance of soil assemblages

Burton, V. J. et al

Eur. J. Soil Sci. 74, e13430 (2023) · 2023

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Summary

This global analysis, combining soil biodiversity data from the PREDICTS project with soil characteristics, quantifies how land-use change affects soil organism communities. The work calculates—for the first time—a Biodiversity Intactness Index specific to soil biodiversity, finding that cropland has reduced soil BII to approximately one-third of baseline levels, whilst grazed pastures show less severe declines. Soil properties mediate these responses but inconsistently across land uses, highlighting the need to explicitly consider soil biota in global biodiversity assessments.

Regional applicability

The global findings are applicable to United Kingdom farming and land-use policy, particularly regarding the comparative impacts of arable cropping versus pasture management on soil biodiversity. The study's demonstration that UK croplands likely harbour substantially impoverished soil communities relative to undisturbed baselines aligns with domestic concerns about agricultural soil health and supports evidence for soil-focused conservation priorities.

Key measures

Soil taxon richness, total abundance of soil organisms, Biodiversity Intactness Index (BII), soil properties across different land-use types

Outcomes reported

The study modelled how taxon richness and total abundance of soil organisms respond to different land uses using global biodiversity data, and calculated the Biodiversity Intactness Index (BII) for soil biodiversity for the first time. Relative to undisturbed vegetation, soil organism abundance and taxon richness were reduced in all land uses except pasture, with cropland showing particularly severe declines.

Theme
Farming systems, soils & land use
Subject
Soil biology & microbiology
Study type
Research
Study design
Observational analysis using global dataset (PREDICTS project)
Source type
Peer-reviewed study
Status
Published
Geography
Global
System type
Mixed farming
DOI
10.1111/ejss.13430
Catalogue ID
IRmoq83nfn-98ed25

Topic tags

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