Cited by 240Soil Management and Crop YieldSoil Science and Environmental ManagementSustainable Agricultural Systems Analysis

GISQ, a multifunctional indicator of soil quality

Velasquez, Elena, Lavelle, Patrick, Andrade, Mercedes·2007·Soil Biology and Biochemistry

Abstract

We present here an indicator of soil quality that evaluates soil ecosystem services through a set of 5 subindicators, and further combines them into a single general Indicator of Soil Quality (GISQ). We used information derived from 54 properties commonly used to describe the multifaceted aspects of soil quality. The design and calculation of the indicators were based on sequences of multivariate analyses. Subindicators evaluated the physical quality, chemical fertility, organic matter stocks, aggregation and morphology of the upper 5 cm of soil and the biodiversity of soil macrofauna. A GISQ combined the different subindicators providing a global assessment of soil quality. Research was conducted in two hillside regions of Colombia and Nicaragua, with similar types of land use and socio-economic context. However, soil and climatic conditions differed significantly. In Nicaragua, soil quality was assessed at 61 points regularly distributed 200 m apart on a regular grid across the landscape. In Colombia, 8 plots representing different types of land use were arbitrarily chosen in the landscape and intensively sampled. Indicators that were designed in the Nicaragua site were further applied to the Colombian site to test for their applicability. In Nicaragua, coffee plantations, fallows, pastures and forest had the highest values of GISQ (1.00; 0.80; 0.78 and 0.77, respectively) while maize crops and eroded soils (0.19 and 0.10) had the lowest values. Examination of subindicator values allowed the separate evaluation of different aspects of soil quality: subindicators of organic matter, aggregation and morphology and biodiversity of macrofauna had the maximum values in coffee plantations (0.89; 0.72 and 0.56, respectively on average) while eroded soils had the lowest values for these indicators (0.10; 0.31 and 0.33, respectively). Indicator formulae derived from information gained at the Nicaraguan sites were not applicable to the Colombian situation and site-specific constants were calculated. This indicator allows the evaluation of soil quality and facilitates the identification of problem areas through the individual values of each subindicator. It allows monitoring of change through time and can guide the implementation of soil restoration technologies. Although GISQ formulae computed on a set of data were only valid at a regional scale, the methodology used to create these indices can be applied everywhere.

Integrity signals

Registry

Crossref · 10.1016/j.soilbio.2007.06.013

Cites

52 of 52 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Velasquez et al. summed the contributions of each of five sub-indicators (hydraulic properties, chemical fertility, aggregation, organic matter and biodiversity) to derive the general indicator of soil quality (GISQ).

    “Velasquez et al. (2007) summed the contributions of each of fi ve sub-indicators (hydraulic properties, chemical fertility, aggregation, organic matter and biodiversity) to derive the general indicator of soil quality (GISQ).”

    From Soil quality – A critical review (2018) · cites this paper as Velasquez et al. (2007)

  • L'indicateur d'état du sol est un proxy de l'Indicateur Biologique de Qualité du Sol (IBQS), inspiré de Velasquez et al. (2007) et Ruiz et al. (2011), composite de 54 variables reliant macrofaune et composantes physiques, chimiques et biologiques des sols.

    “La variable indicatrice de l'état du sol est un proxy de l'Indicateur Biologique de Qualité du Sol (IBQS) inspiré de Velasquez et al. (2007) et Ruiz et al. (2011).”

Cites

Flagged first, then by citations

1 of the 53 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Ruiz-Camacho, N., 2004. Mise au point d’un système de bioindication de la qualité du sol base sur l’étude des peuplements de macro-invertébrés. Doctorate Dissertation, Université Paris VI, Paris, 270pp.

Cited by

Sorted by citations

Authors
Velasquez, E., Lavelle, P., & Andrade, M.
Affiliations
Institut de Recherche pour le Développement (FR)
Venue
Soil Biology and Biochemistry
Publisher
Elsevier BV
Published
2007-12
Volume
39
Issue
12
Pages
3066-3080
ISSN
0038-0717 (ISSN-L)
OpenAlex
W1973952688
Cited by
240
References
53
Citations by year
2026: 5 · 2025: 13 · 2024: 16 · 2023: 11 · 2022: 23 · 2021: 31 · 2020: 22 · 2019: 8 · 2018: 23 · 2017: 12 · 2016: 12 · 2015: 5 · 2014: 19 · 2013: 9 · 2012: 12
FWCI
8.17
Type
journal article
Language
en
Open access
closed
Locations
  • Soil Biology and Biochemistry (publishedVersion)
  • HAL (submittedVersion)
  • CentAUR (University of Reading) (submittedVersion)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil Management and Crop Yield
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil Science and Environmental Management
  • Physical Sciences › Environmental Science › Environmental Chemistry › Sustainable Agricultural Systems Analysis
Keywords
soil quality indicators, soil ecosystem services, soil physical quality, soil chemical fertility, soil organic matter, soil aggregation, soil morphology, land use, soil erosion, coffee plantations, soil restoration, soil quality monitoring

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review