Food web topologies depict the community structure as distributions of feeding interactions across populations. Although the soil ecosystem provides important functions for aboveground ecosystems, data on complex soil food webs is notoriously scarce, most likely due to the difficulty of sampling and characterizing the system. To fill this gap we assembled the complex food webs of 48 forest soil communities. The food webs comprise 89 to 168 taxa and 729 to 3344 feeding interactions. The feeding links were established by combining several molecular methods (stable isotope, fatty acid and molecular gut content analyses) with feeding trials and literature data. First, we addressed whether soil food webs (n = 48) differ significantly from those of other ecosystem types (aquatic and terrestrial aboveground, n = 77) by comparing 22 food web parameters. We found that our soil food webs are characterized by many omnivorous and cannibalistic species, more trophic chains and intraguild‐predation motifs than other food webs and high average and maximum trophic levels. Despite this, we also found that soil food webs have a similar connectance as other ecosystems, but interestingly a higher link density and clustering coefficient. These differences in network structure to other ecosystem types may be a result of ecosystem specific constraints on hunting and feeding characteristics of the species that emerge as network parameters at the food‐web level. In a second analysis of land‐use effects, we found significant but only small differences of soil food web structure between different beech and coniferous forest types, which may be explained by generally strong selection effects of the soil that are independent of human land use. Overall, our study has unravelled some systematic structures of soil food‐webs, which extends our mechanistic understanding how environmental characteristics of the soil ecosystem determine patterns at the community level.

Number of words in manuscript: 6768Number of words in abstract: 260 Number of words in title:14 Curtsdotter et al. Basic and Applied Ecology 2 AbstractThe loss of species from ecological communities can unleash a cascade of secondary extinctions, the risk and extent of which are likely to depend on the traits of the species that are lost from the community. To identify species traits that have the greatest impact on food web robustness to species loss we here subject allometrically scaled, dynamical food web models to several deletion sequences based on species' connectivity, generality, vulnerability or body mass. Further, to evaluate the relative importance of dynamical to topological effects we compare robustness between dynamical and purely topological models. This comparison reveals that the topological approach overestimates robustness in general and for certain sequences in particular. Top-down directed sequences have no or very low impact on robustness in topological analyses, while the dynamical analysis reveals that they may be as important as high-impact bottom-up directed sequences.Moreover, there are no deletion sequences that result, on average, in no or very few secondary extinctions in the dynamical approach. Instead, the least detrimental sequence in the dynamical approach yields an average robustness similar to the most detrimental (non-basal) deletion sequence in the topological approach. Hence, a topological analysis may lead to erroneous conclusions concerning both the relative and the absolute importance of different species traits for robustness.The dynamical sequential deletion analysis shows that food webs are least robust to the loss of species that have many trophic links or that occupy low trophic levels. In contrast to previous studies we can infer, albeit indirectly, that secondary extinctions were triggered by both bottom-up and topdown cascades.

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Most ecosystem functions and related services involve species interactions across trophic levels, for example, pollination and biological pest control. Despite this, our understanding of ecosystem function in multitrophic communities is poor, and research has been limited to either manipulation in small communities or statistical descriptions in larger ones. Recent advances in food web ecology may allow us to overcome the trade-off between mechanistic insight and ecological realism. Molecular tools now simplify the detection of feeding interactions, and trait-based approaches allow the application of dynamic food web models to real ecosystems. We performed the first test of an allometric food web model's ability to replicate temporally nonaggregated abundance data from the field and to provide mechanistic insight into the function of predation. We aimed to reproduce and explore the drivers of the population dynamics of the aphid herbivore Rhopalosiphum padi observed in ten Swedish barley fields. We used a dynamic food web model, taking observed interactions and abundances of predators and alternative prey as input data, allowing us to examine the role of predation in aphid population control. The inverse problem methods were used for simultaneous model fit optimization and model parameterization. The model captured >70% of the variation in aphid abundance in five of ten fields, supporting the model-embodied hypothesis that body size can be an important determinant of predation in the arthropod community. We further demonstrate how in-depth model analysis can disentangle the likely drivers of function, such as the community's abundance and trait composition. Analysing the variability in model performance revealed knowledge gaps, such as the source of episodic aphid mortality, and general method development needs that, if addressed, would further increase model success and enable stronger inference about ecosystem function. The results demonstrate that confronting dynamic food web models with abundance data from the field is a viable approach to evaluate ecological theory and to aid our understanding of function in real ecosystems. However, to realize the full potential of food web models, in ecosystem function research and beyond, trait-based parameterization must be refined and extended to include more traits than body size.