Résumé: The benthic fauna of European continental shelves is a severely impacted community, mostly due to intense bottom trawling activity. Trawling effect may be dependent on the spatial and temporal distribution of abrasion, the habitat type including natural perturbation intensity and the fishing gear used. Nonetheless, there is an urgent need to identify or develop indices likely to measure the effect of trawling. For this purpose benthic fauna by-catch monitored in scientific trawl surveys carried out in all European waters in the frame of the Common Fishery Policy Data Collection Multiannual Program may be used. Benthic invertebrates data used in this study were collected during scientific bottom trawl surveys covering the English Channel, the North Sea and the North-West Mediterranean. Swept area ratios derived from VMS data were used to quantify the intensity of fishery induced abrasion on the seabed. Fifteen indices were investigated: taxonomic diversity metrics, functional di-versity indices and functional indices, the two later based on sensitivity traits to physical abrasion. Their properties, such as their capacity to detect trawling effect, their statistical behavior or their ability to inform on community structure, were investigated. Among them, fours indices specific to fishery effect detection based on biological traits appeared to be the best performing benthic indices regarding these requirements: Trawling Disturbance Index (TDI), modified-Trawling Disturbance Index (mTDI), partial-Trawling Disturbance Index (pTDI), modified sensitivity index (mT). Maps of the distribution pattern of seabed sensitivity captured through each of these four indices were produced. This work has highlighted the need to use specific indices to monitor the effect of trawling on benthic communities but also that the use of different indices may be necessary to carry out this monitoring in all European waters.

Résumé: The state of marine systems subject to natural or anthropogenic impacts can be generally summarized by suites of ecological indicators carefully selected to avoid redundancy. Length-based indicators capture the status of fish community structure, fulfilling the Marine Strategy Framework Directive (MSFD) requirement for Descriptor 3 (status of commercial fish species). Although the MSFD recommends the development of regional indicators, a comparison among alternative length-based indicators is so far missing for the Mediterranean Sea. Using principal component analysis and dynamic factor analysis, we identified the most effective subset of length-based indicators, whether or not based on maximum length. Indicator trends and lime series of fishing effort and environmental variables are also compared in order to highlight the individual and combined capability of indicators to track system changes across geographical sub-areas. Two indicators, typical length and mean maximum length, constitute the smallest set of non-redundant indicators, capturing together 87.45% of variability. Only in combination can these indicators disentangle changes in the fish community composition from modifications of size structure. Our study supports the inclusion of typical length among the regional MSFD Descriptor 3 indicators for the Mediterranean Sea. Finally, we show dissimilarity between the western and eastern-central Mediterranean, suggesting that there are sub-regional differences in stressors and community responses.

Résumé: Multivariate autoregressive (MAR) models are an increasingly popular technique to infer interaction strengths between species in a community and to predict the community response to environmental change. The most commonly employed MAR(1) models, with one time lag, can be viewed either as multispecies competition models with Gompertz density dependence or, more generally, as a linear approximation of more complex, nonlinear dynamics around stable equilibria. This latter interpretation allows for broader applicability, but may come at a cost in terms of interpretation of estimates and reliability of both short- and long-term predictions. We investigate what these costs might be by fitting MAR(1) models to simulated 2-species competition, consumer-resource and host–parasitoid systems, as well as a larger food web influenced by the environment. We review how MAR(1) coefficients can be interpreted and evaluate how reliable are estimates of interaction strength, rank, or sign; accuracy of short-term forecasts; as well as the ability of MAR(1) models to predict the long-term responses of communities submitted to environmental change such as PRESS perturbations. The net effects of species j on species i are usually (90%-95%) well recovered in terms of sign or rank, with the notable exception of overcompensatory dynamics. In actual values, net effects of species j on species i are not well recovered when the underlying dynamics are nonlinear. MAR(1) models are better at making short-term qualitative forecasts (next point going up or down) than at predicting long-term responses to environmental perturbations, which can be severely over- as well as underestimated. We conclude that when applying MAR(1) models to ecological data, inferences on net effects among species should be limited to signs, or the Gompertz assumption should be tested and discussed. This particular assumption on density-dependence (log-linearity) is also required for unbiased long-term predictions. Overall, we think that MAR(1) models are highly useful tools to resolve and characterize community dynamics, but we recommend to use them in conjunction with alternative, nonlinear models resembling the ecological context in order to improve their interpretation in specific applications.