DISPLACE: a dynamic, individual-based model for spatial fishing planning and effort displacement: Integrating underlying fish population models
Publication: Research › Conference abstract for conference – Annual report year: 2012
We previously developed a spatially explicit, individual-based model (IBM) evaluating the bio-economic efficiency of fishing vessel movements between regions according to the catching and targeting of different species based on the most recent high resolution spatial fishery data. The main purpose was to test the effects of alternative fishing effort allocation scenarios related to fuel consumption, energy efficiency (value per litre of fuel), sustainable fish stock harvesting, and profitability of the fisheries. The assumption here was constant underlying resource availability. Now, an advanced version couples the vessel model to selected size-based population models and considers the underlying resource dynamics in the distribution and density patterns of the targeted stocks for the cases of Danish and German vessels harvesting the North Sea and Baltic fish stocks. The stochastic fishing process includes direct and local depletion by stock that is specific to the vessel catching power, which is proportional to the encountered size-based population on the visited ground and is based on stock assessment and research survey data. The impact of the potential fishing effort displacement by vessels on the fish stocks, with resulting fishing mortality, and the vessels’ economic consequences are evaluated on high spatial and seasonal disaggregation levels by simulating different individual choices of vessel speed, fishing grounds and ports. All tested scenarios led to increased overall energy efficiency, except for the fishing closures that increased fuel consumption and costs for most of the vessels due to increased travel distance. On an individual scale, the simulations led to gains and losses due to either the technical interactions between vessels exploiting the same stocks or to the alteration of individual fishing patterns. We demonstrate that integrating the spatial activity of vessels and local fish stock abundance dynamics allow for interactions and more realistic predictions of fishermen behaviour, revenues and stock abundance
|State||Published - 2012|
|Country||Tanzania, United Republic of|
|City||Dar es Salaam|
|Period||16/07/2012 → 20/07/2012|
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