Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below-and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se.

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Soil degradation is a worsening global phenomenon driven by socio‐economic pressures, poor land management practices and climate change. A deterioration of soil structure at timescales ranging from seconds to centuries is implicated in most forms of soil degradation including the depletion of nutrients and organic matter, erosion and compaction. New soil–crop models that could account for soil structure dynamics at decadal to centennial timescales would provide insights into the relative importance of the various underlying physical (e.g. tillage, traffic compaction, swell/shrink and freeze/thaw) and biological (e.g. plant root growth, soil microbial and faunal activity) mechanisms, their impacts on soil hydrological processes and plant growth, as well as the relevant timescales of soil degradation and recovery. However, the development of such a model remains a challenge due to the enormous complexity of the interactions in the soil–plant system. In this paper, we focus on the impacts of biological processes on soil structure dynamics, especially the growth of plant roots and the activity of soil fauna and microorganisms. We first define what we mean by soil structure and then review current understanding of how these biological agents impact soil structure. We then develop a new framework for modelling soil structure dynamics, which is designed to be compatible with soil–crop models that operate at the soil profile scale and for long temporal scales (i.e. decades, centuries). We illustrate the modelling concept with a case study on the role of root growth and earthworm bioturbation in restoring the structure of a severely compacted soil.

Under favourable conditions, soil ingestion by earthworm populations can be equivalent to approximately 5-10% of the topsoil mass per year. This suggests that for contaminants that are strongly bound to soil, earthworm 'bioturbation' may be a more important transport mechanism than water-borne advection dispersion. It is therefore quite surprising that few modelling studies to date have explicitly considered the effects of biological processes on contaminant transport in soil. In this study, we present a general model that incorporates the effects of both 'local' and 'non-local' biological mixing into the framework of the standard physical (advective-dispersive) transport model. The model is tested against measurements of the redistribution of caesium-137 ( 137 Cs) derived from the Chernobyl accident, in a grassland soil during 21 years after fallout. Three model parameters related to biological transport were calibrated within ranges defined by measured data and literature information on earthworm biomasses and feeding rates. Other parameters such as decay half-life and sorption constant were set to known or measured values. A physical advective-dispersive transport model based on measured sorption strongly underestimated the downward displacement of 137 Cs. A dye-tracing experiment suggested the occurrence of physical non-equilibrium transport in soil macropores, but this was inadequate to explain the extent of the deep penetration of 137 Cs observed at the site. A simple bio-diffusion model representing 'local' mixing worked reasonably well, but failed to reproduce the deep penetration of Cs as well as a dilution observed close to the soil surface. A comprehensive model including physical advectivedispersive transport, and both 'local' and 'non-local' mixing caused by the activities of both endogeic and anecic earthworms, gave an excellent match to the measured depth profiles of 137 Cs, with predictions mostly lying within confidence intervals for the means of measured data and model efficiencies exceeding 0.9 on all sampling occasions but the first.

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