Loop analysis quantifying important species in a marine food web

Improving the predictive power of food web analysis is a major challenge. Identifying the relationships that link topological and dynamical features may help. We used the predictions of loop analysis about the effect of perturbations targeted to the components of Barents sea food web to quantify their sensitivity and community impact, that we summarized in two new indices, and . Using a multivariate analysis we interpreted the meaning of these indices in a benchmarking exercise using several well recognized indices of species topological (positional) importance. Our findings suggest that the information the two indices proposed here provides does not overlap with that of more diffused topological indices of positional importance (i.e. centrality indices). The former are express the dynamic consequences of the topology in which species are embedded, whereas for the latter such dynamical consequences are mostly hypothesized on a topological base. The indices of loop analysis are based on the effective role a species plays in passing the impacts to other species ( ) and their role as sinks of the perturbations entering anywhere in the system ( ). These two indices, in the end, reveal how the topology of the network affects the response of the species to perturbations and thus emphasize the interaction between topology and dynamics. Based on our results, the question related to conservation is whether to prioritize sensitive species, that can be more strongly influenced when others are perturbed, or species of high impact, that can more strongly influence the rest of the community if perturbed. • The predictive power of food web theory needs to be improved • We develop a method to quantify keystone species, based on predictions of loop analysis • We study the relatioships between the novel and earlier indices of species importance • The new approach is illustrated on the Barents Sea food web • We support the community importance of haddock and capelin