Performance of soil condition indicators across taxonomic groups and land uses
Abstract
Information on soil conditions in New Zealand is needed to assess soil quality at a national scale. We tested a standard set of 16 primary indicators at 29 sites (0–10 cm depth) across nine soil great groups with matched examples of indigenous forest, plantation forest, pastures, and crops. Soils under indigenous forest were acidic (pH 5.5–5.7), low in Olsen P (5–14 μg cm −3 ), with high microbial C (814–1228 μg cm −3 ), respiration (1.1–1.4 μg C cm −3 h −1 ), total C (31.8–52.9 mg cm −3 ), macroporosity (9.6–11.7% v/v), and total available water (29.2–31.5% v/v). Plantation forest soils had generally similar characteristics. Pasture soils were less acidic (pH 5.3–6.9) than forest soils, but with more available P (5.5–43.0 μg cm −3 ), higher total C (30.7–141.5 mg cm −3 ), total N (2.7–9.0 mg cm −3 ), and mineralizable N (68–175 μg cm −3 ). The physical condition was similar to forest soils. Cropped soil had low total C (20–34 mg cm −3 ), microbial C (160–956 μg cm −3 ), respiration (0.29–1.33 μg C cm −3 h −1 ), and total available water (6.7–30.1% v/v), but high pH (5.8–7.2), Olsen P (11.2–199 μg cm −3 ), and bulk density (0.96–1.3 g cm −3 ). Principal component analysis identified outlier sites and grouped land uses independently of soil great groups. Some indicators were less useful because of high variability (unsaturated hydraulic conductivity), correlation to other indicators (microbial C) or interpretation difficulties (respiration). Overall, the standardized approach provided useful information about soil conditions on a national scale.
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Subsequently, statistical data reduction by multivariate techniques such as principal component analysis, redundancy analysis and discriminant analysis, and multiple regression, became more common for selecting minimum datasets.
“Subsequently, statistical data reduction by multivariate techniques such as principal component analysis (PCA), redundancy analysis (RDA) and discriminant analysis (e.g. Andrews and Carroll, 2001; Lima et al., 2013; Schipper and Sparling, 2000; Shukla et al., 2006), and multiple regression (Kosmas et al., 2014) became more common.”
From Soil quality – A critical review (2018) · cites this paper as Schipper and Sparling, 2000
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- Authors
- Schipper, L. A., & Sparling, G. P.
- Affiliations
- Landcare Research Private Bag 3127 Hamilton New Zealand
- Corresponding author
- Sparling, G. P.
- ORCID
- Schipper, L. A.
- Venue
- Soil Science Society of America Journal
- Publisher
- Wiley
- Published
- 2000-01
- Volume
- 64
- Issue
- 1
- Pages
- 300-311
- ISSN
- 0361-5995 (ISSN-L)
- 1435-0661
- OpenAlex
- W2088708205
- Cited by
- 144
- References
- 43
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 5 · 2023: 4 · 2022: 7 · 2021: 9 · 2020: 3 · 2019: 5 · 2018: 6 · 2017: 5 · 2016: 8 · 2015: 5 · 2014: 5 · 2013: 9 · 2012: 4
- FWCI
- 11.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Soil Science Society of America Journal (publishedVersion)
- Funders
- New Zealand Ministry for the Environment Sustainable Management Fund
- Foundation for Research, Science, and Technology (C09629)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil Carbon and Nitrogen Dynamics
- 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
- Keywords
- soil quality assessment, land use, pasture soils, agricultural soils, soil pH, Olsen phosphorus, microbial biomass carbon, soil respiration, soil organic carbon, soil nitrogen, macroporosity, available water capacity, unsaturated hydraulic conductivity, bulk density, New Zealand soils
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