Estuaries and coastal waters are essential nursery habitats for many marine species, and especially for flatfishes. Thus, investigating how anthropogenic disturbances affect the quality of these habitats is of major importance to understand their consequences on the population renewal of marine species.The aim of the present study was to analyse the effects of estuarine habitat degradation on the population of the common sole in the Eastern Channel, a key species in the fish community and fisheries in this area. We especially focused on the drastic drop in the surface area and on the low water quality of the Seine estuary, the main river of the Eastern Channel.

For many marine fish species, recruitment is strongly related to larval survival and dispersal to nursery areas. Simulating larval drift should help assessing the sensitivity of recruitment variability to early life history. An individual‐based model (IBM) coupled to a hydrodynamic model was used to simulate common sole larval supply from spawning areas to coastal and estuarine nursery grounds at the population scale in the eastern Channel on a 14‐yr time series, from 1991 to 2004. The IBM allowed each particle released to be transported by currents from the hydrodynamic model, to grow with temperature, to migrate vertically giving stage development, and possibly to die according to drift duration, representing the life history from spawning to metamorphosis. Despite sensitivity to the larval mortality rate, the model provided realistic simulations of cohort decline and spatio‐temporal variability of larval supply. The model outputs were analysed to explore the effects of hydrodynamics and life history on the interannual variability of settled sole larvae in coastal nurseries. Different hypotheses of the spawning spatial distribution were also tested, comparing homogeneous egg distribution to observation and potential larval survival (PLS) maps. The sensitivity analyses demonstrated that larval supply is more sensitive to the life history along larval drift than to the phenology and volume of spawning, providing explanations for the lack of significant stock–recruitment relationship. Nevertheless, larval supply is sensitive to spawning distribution. Results also suggested a very low connectivity between supposed different sub‐populations in the eastern Channel.

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.