Abstract. Given the great overfishing of the demersal resources in the Northern Adriatic Sea (geographical sub-area [GSA] 17), along with the fishing pressure in marine habitats, evidence strongly supports the need to evaluate appropriate management approaches. Several fishing activities operate simultaneously in the area, and the need to minimize conflicts among them is also a social concern. We applied a spatially and temporally explicit fish and fisheries model to assess the impact of a suite of spatial plans suggested by practitioners that could reduce the pressure on the four demersal stocks of high commercial interest in the GSA 17 and that could promote space sharing between mutually exclusive activities. We found that excluding trawlers from some areas has lowered the effective fishing effort, resulting in some economic losses but providing benefit to the set netters. Not every simulated fishing vessel is impacted in the same way because some fishing communities experienced different economic opportunities, particularly when a 6-nautical mile buffer zone from the coast was implemented in the vicinity of important fishing grounds. Along this buffer zone, the four stocks were only slightly benefiting from the protection of the area and from fewer discards. In contrast, assuming a change in the ability of the population to disperse led to a large effect: Some fish became accessible in the coastal waters, therefore increasing the landings for rangelimited fishers, but the discard rate of fish also increased, greatly impairing the long-term biomass levels. Our evaluation, however, confirmed that no effort is displaced onto vulnerable benthic habitats and to grounds not suitable for the continued operation of fishing. We conclude that the tested spatial management is helpful, but not sufficient to ensure sustainable fishing in the area, and therefore, additional management measures should be taken. Our test platform investigates the interaction between fish and fisheries at a fine geographical scale and simulates data for varying fishing methods and from different harbor communities in a unified framework. We contribute to the development of effective science-based inputs to facilitate policy improvement and better governance while evaluating trade-offs in fisheries management and marine spatial planning.
Knowledge of connectivity among subpopulations is fundamental in the identification of the appropriate geographical scales for stock status evaluation and management, the identification of areas with greater retention rates, and space‐based fisheries management. Here, an integration of hydrodynamic, biological, and habitat models results is used to assess connectivity and support the definition of essential fish habitats (EFH) in the Adriatic Sea, with reference to Nephrops norvegicus, an important benthic commercial resource, the recruitment of which is strongly related to larval dispersal from spawning to recruitment areas. We explored oceanographic and biological connectivity in the Adriatic Sea under a wide and representative variety of oceanographic conditions (winters 2006–2012) by tracking 3D trajectories of larvae released from different areas. We used a Lagrangian model that features a specific larval behavior module with explicit dependence on environmental parameters (i.e., temperature and sediment type) and that is driven by high‐resolution hydrodynamic and meteorological data. The results were used to partition the area in which Nephrops was observed into 20 homogenous management subareas; to assess the connection between spawning, recruitment, and harvesting grounds; and to identify potential subpopulation boundaries as well as the connectivity among the potential subpopulations. The results suggest the presence of at least three distinct subpopulations, which need to be independently managed and conserved, and confirms that the Jabuka‐Pomo pit is the most important spawning area, but alone it cannot sustain Nephrops populations throughout the Adriatic Sea. The results also show the importance to move from particle‐tracking to approaches based on integrated models.
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