Figure 3: Change in soil biodiversity in response to environmental stressors associated with (a) climate change, (b) land-use intensification, (c) pollution, and (d) nutrient enrichment. In panel (b), the estimate for macro- and meso-fauna is shown in black, and micro-fauna in grey as body size remained as an additive term in the model. Hedges’ g was used as the effect size in all models. Negative effect sizes indicate that the environmental stressor causes a reduction in biodiversity, and a positive effect size indicates an increase in biodiversity. Error bars indicate 95% confidence intervals. Effect sizes where error bars do not cross the dashed vertical zero line, are significantly different from zero. The values of n indicate the number of cases of each environmental stressor in the model. Grey shading is for enhancing readability only.
For the environmental stressors model investigating different stressors related to land-use intensification, the effect of body size remained in the model, although as an additive effect only. Overall, macro-fauna was more negatively impacted by each of the land-use intensification stressors, while micro-fauna were impacted less (estimate = 0.53; ±95% CIs = 0.22, 0.84; p-value < 0.001). Meso-fauna was not significantly different from macro-fauna, and thus was not presented separately (Figure 3b).
For both macro-/meso- and micro-fauna, the change from an organic system to an inorganic system had the biggest negative impact on biodiversity (estimate = -1.12; ±95% CIs = -1.48, -0.78; p-value <0.0001, for macro-fauna), with the increase in tillage (i.e., comparing reduced tillage practices to conventional tillage) having the second biggest negative impact (estimate = -0.91; ±95% CIs = 1.17, -0.64; p-value < 0.0001, for macro-fauna). The impact of increased fire (intensity or frequency), harvesting, and grazing also had significant negative impacts on biodiversity, although to a lesser extent (and not a significant effect when adjusting environmental stressor estimates for micro-fauna).
Within the model focussed on pollution stressors, the main and interactive effect of body size was removed from the model. The effect of pollutant type was significant, with both pesticides (estimate = -0.41; ±95% CIs = -0.78, -0.04; p-value = 0.03) and metals (estimate = -1.03; ±95% CIs = -1.35, -0.70; p-value < 0.0001) having a significantly negative effect on soil fauna communities (Figure 3c). Further inspection of the raw effect sizes, when accounting for different sources of metals and pesticides (using FAO 2018 categories; ) show that there was variation of the effect sizes within each category (Figure S4). Notably, effect sizes of metals from mining/smelting demonstrate the greatest variation, often being more negative.
For the nutrient enrichment model, as with most of the models, the body size variable was removed as both an interactive and main effect, leaving just the impact of different nutrient enrichment stressors (Figure 3d). Of the 8 different stressors, five did not have any significant impact on biodiversity (synthetic fertilizers, Ca-liming + Wood ash, compost, sludge and multiple fertilizer types) but all trended towards a positive impact, except Ca-liming + Wood ash. The impacts of manure + slurry, other organic fertilizers, and residue + mulch, were all similar, and all significantly positive (estimate = 0.76; ±95% CIs = 0.47, 1.05; p-value < 0.001, estimate = 0.57; ±95% CIs = 0.20, 0.95; p-value = 0.003, estimate = 0.67; ±95% CIs = 0.37; 0.97, p-value < 0.001, respectively).
For the invasive species environmental stressors model, as with the pollution model, both the terms for the body size and the different types of invasive species were removed from the model completely. However, in line with the main model, the overall intercept of the models was not significantly different from zero (estimate = -0.15; ±95% CIs = -0.55, 0.25; p-value = 0.47).