Résumé: Ecological indicators are increasingly used to examine the evolution of natural ecosystems and the impacts of human activities. Assessing their trends to develop comparative analyses is essential. We introduce the analysis of convergence, a novel approach to evaluate the dynamic and trends of ecological indicators and predict their behavior in the long-term. Specifically, we use a non-parametric estimation of Gaussian kernel density functions and transition probability matrix integrated in the R software. We validate the performance of our methodology through a practical application to three different ecological indicators to study whether Mediterranean countries converge towards similar fisheries practices. We focus on how distributions evolve over time for the Marine Trophic Index, the Fishing in Balance Index and the Expansion Factor during 1950–2010. Results show that Mediterranean countries persist in their fishery behaviors throughout the time series, although a tendency towards similar negative effects on the ecosystem is apparent in the long-term. This methodology can be easily reproduced with different indicators and/or ecosystems in order to analyze ecosystem dynamics.

Résumé: Anticipating future changes in marine social-ecological systems (MSES) several decades into the future is essential in the context of accelerating global change. This is challenging in situations where actors do not share common understandings, practices, or visions about the future. We introduce a dedicated scenario method for the development of MSES scenarios in a participatory context. The objective is to allow different actors to jointly develop scenarios which contain their multiple visions of the future. The method starts from four perspectives: “fisheries management,” “ecosystem,” “ocean climate,” and “global context and governance” for which current status and recent trends are summarized. Contrasted scenarios about possible futures are elaborated for each of the four single perspectives before being integrated into multiple-perspective scenarios. Selected scenarios are then developed into storylines. Focusing on individual perspectives until near the end allows actors with diverse cultures, interests and horizons to confront their own notions of the future. We illustrate the method with the exploration of the futures of the Barents Sea MSES by 2050. We emphasize the following lessons learned: first, many actors are not familiar with scenario building and attention must be paid to explaining the purpose, methodology, and benefits of scenarios exercises. Second, although the Barents Sea MSES is relatively well understood, uncertainties about its future are significant. Third, it is important to focus on unlikely events. Fourth, all perspectives should be treated equally. Fifth, as MSES are continuously changing, we can only be prepared for future changes if we collectively keep preparing.

Résumé: Spatial indicators are widely used to monitor species and are essential to management and conservation. In the present study, we tested the ability of 11 spatial indicators to quantify changes in species' geographic patterns: (1) spatial displacement of a patch of biomass ('shift'), (2) a spatial decrease in a patch, accompanied either by a loss of biomass ('shrink0') or (3) a relocation of the same biomass ('shrink1'), and (4) splitting of a patch into smaller patches ('split'). The geographic changes were simulated by manipulating the spatial distributions of the demersal species (observed during bottom trawl surveys). Hence, the spatial distributions of the latter being used as input data on which the manipulations were done. Additionally, other aspects of the indicators affecting the responses to the geographic changes were also tested, (1) homogeneous increase in biomass throughout the patch and (2) different sample sizes. The center of gravity (defined by latitude and longitude) was the only indicator that accurately detected the 'shift' in biomass. The index of aggregation identified a decrease in the area and biomass of the main biomass patch ('shrink0'), while the Gini index, equality area and spreading area were accurately identified a decrease in the area of the main biomass patch when total biomass did not decreased ('Shrink1'). Inertia and isotropy responded to all geographic changes, except for those in biomass or distribution area. None of the indicators successfully identified 'split' process. Likewise, one of the indicators were sensitive to a homogeneous increase in biomass or the type of spatial distribution. Overall, all indicators behaved similarly well when sample sizes exceeded 40 stations randomly located in the area. The framework developed provides an accessible and simple approach that can be used to evaluate the ability of spatial indicators to identify geographic processes using empirical data and can be extended to other indicators or geographic processes. We discuss perspectives of the development of spatial indicators especially within the application of EU's Marine Strategy Framework Directive.