Changes in land use alter soil quality and aggregate stability in the highlands of northern Ethiopia

Abstract

Land use change alters biodiversity and soil quality and thus affects ecosystem functions. This study investigated the effects of changes in land use on major soil quality indicators. Soil samples were taken from a depth of 0-10 cm (top soil) under four major land uses (cropland, grassland, area exclosure, eucalyptus plantation) with similar land use change histories for analysis, and soil from a nearby natural forest was used as a reference. Land use change from natural forest to cropland and grassland significantly decreased major soil quality indicators such as soil organic C (SOC), total soil N (TSN), molybdate-reactive bicarbonate-extractable P, and arbuscular mycorrhizal fungi (AMF) spore density, but compared to the cropland, change to area exclosure and eucalyptus plantation significantly improved SOC, TSN and soil aggregate stability (SAS). In addition, we assessed the correlation among indicators and found that SOC, TSN and SAS significantly correlate with many other soil quality indicators. The study highlights that the conversion of natural forest to cropland results in decline of soil quality and aggregate stability. However, compared to cropland, application of area exclosure and afforestation on degraded lands restores soil quality and aggregate stability.

Figure 1

Soil organic C, TSN and extractable P fractions (mean ± SE) in the soils of five different land use types in the highlands of northern Ethiopia. Different letters indicate statistically significant differences (P < 0.05) between land uses according to one-way ANOVA and Tukey’s honest significance test (molybdate-reactive bicarbonate P fraction, molybdate-reactive hydroxide P fraction) or a Kruskal–Wallis test and Mann–Whitney U test (SOC and TSN).

Figure 2

AMF spore density and percent wet soil aggregate stability (mean ± SE) in the soils of five different land use types in the highlands of northern Ethiopia. Different letters indicate significant differences (P < 0.05) between land uses according to one-way ANOVA and Tukey’s honest significance test for wet soil aggregate stability and a Kruskal–Wallis test and Mann–Whitney U test for spore density.

Figure 3

Soil enzyme activities (mean ± SE) in the soils of five different land uses in the highlands of northern Ethiopia. Different letters indicate significant differences (P < 0.05) between different land uses according to a Kruskal–Wallis test and Mann–Whitney U test.

Figure 4

Overall patterns of enzyme activities across five different land uses calculated by principal component analysis (PCA with a biplot function). Two PCA components explain 90.2% of the variance in total enzyme activities. Significant deviations in enzyme activity patterns among different land uses were analyzed by analysis of similarity (ANOSIM). P values are Bonferroni corrected in all cases.

Figure 5

The overall correlation between the chemical, physical and biological indicators of soil quality, where AMF. SD: AM fungal spore density; Gluc: β-glucosidase; Phos: phosphatase; Prot: protease; Chit: chitinase; SAS: soil aggregate stability; SOC: soil organic carbon; Pmo_CO3: molybdate-reactive bicarbonate-extractable P and soil pH. The total soil nitrogen strongly correlated with SOC (ρ = 0.93; P < 0.001) and similarly correlated with SAS, AMF.SD, Phos and Prot. Spearman’s correlation analysis was employed for pairwise comparisons of the three quality indicators; the solid and broken lines show significant positive and negative correlations, respectively.

Figure 6

Map of Ambo Ber District, the study area. The map was produced using ESRI ArcGIS software (version 10.2; http://www.esri.com/software/arcgis/arcgis-for-desktop). The mapping data were acquired from the spatial database of the Global Administrative Areas (GADM) (Global Administrative Areas (2016). GADM database of Global Administrative Areas, version 2.8. www.gadm.org).