Model uncertainty and simulated multispecies fisheries management advice in the Baltic Sea

Different ecosystem models often provide contrasting predictions (model uncertainty), which is perceived to be a major challenge impeding their use to support ecosystem-based fisheries management (EBFM). The focus of this manuscript is to examine the extent of model disagreements which could impact...

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Veröffentlicht in:PloS one 2019-01, Vol.14 (1), p.e0211320-e0211320
Hauptverfasser: Bauer, Barbara, Horbowy, Jan, Rahikainen, Mika, Kulatska, Nataliia, Müller-Karulis, Bärbel, Tomczak, Maciej T, Bartolino, Valerio
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container_issue 1
container_start_page e0211320
container_title PloS one
container_volume 14
creator Bauer, Barbara
Horbowy, Jan
Rahikainen, Mika
Kulatska, Nataliia
Müller-Karulis, Bärbel
Tomczak, Maciej T
Bartolino, Valerio
description Different ecosystem models often provide contrasting predictions (model uncertainty), which is perceived to be a major challenge impeding their use to support ecosystem-based fisheries management (EBFM). The focus of this manuscript is to examine the extent of model disagreements which could impact management advice for EBFM in the central Baltic Sea. We compare how much three models (EwE, Gadget and a multispecies stock production model) differ in 1) their estimates of fishing mortality rates (Fs) satisfying alternative hypothetical management scenario objectives and 2) the outcomes of those scenarios in terms of performance indicators (spawning stock biomasses, catches, profits). Uncertainty in future environmental conditions affecting fish was taken into account by considering two seal population growth scenarios and two nutrient load scenarios. Differences in the development of the stocks, yields and profits exist among the models but the general patterns are also sufficiently similar to appear promising in the context of strategic fishery advice. Thus, we suggest that disagreements among the ecosystem models will not impede their use for providing strategic advice on how to reach management objectives that go beyond the traditional maximum yield targets and for informing on the potential consequences of pursuing such objectives. This is especially true for scenarios aiming at exploiting forage fish sprat and herring, for which the agreement was the largest among our models. However, the quantitative response to altering fishing pressure differed among models. This was due to the diverse environmental covariates and the different number of trophic relationships and their functional forms considered in the models. This suggests that ecosystem models can be used to provide quantitative advice only after more targeted research is conducted to gain a deeper understanding into the relationship between trophic links and fish population dynamics in the Baltic Sea.
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The focus of this manuscript is to examine the extent of model disagreements which could impact management advice for EBFM in the central Baltic Sea. We compare how much three models (EwE, Gadget and a multispecies stock production model) differ in 1) their estimates of fishing mortality rates (Fs) satisfying alternative hypothetical management scenario objectives and 2) the outcomes of those scenarios in terms of performance indicators (spawning stock biomasses, catches, profits). Uncertainty in future environmental conditions affecting fish was taken into account by considering two seal population growth scenarios and two nutrient load scenarios. Differences in the development of the stocks, yields and profits exist among the models but the general patterns are also sufficiently similar to appear promising in the context of strategic fishery advice. 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subjects Animals
Baltic States
Biology and Life Sciences
Biomass
Commercial fishing
Computer simulation
Earth sciences
Ecology
Ecology and Environmental Sciences
Ecosystem management
Ecosystem models
Ecosystems
Ekologi
Environment models
Environmental aspects
Environmental conditions
Environmental quality
Eutrophication
Fish
Fish populations
Fisheries
Fisheries management
Fishery management
Fishes - growth & development
Fishing
Management
Models, Economic
Nutrient loading
Objectives
Oceans and Seas
Pollution load
Population biology
Population dynamics
Population growth
Profits
Spawning
Trophic relationships
Uncertainty
title Model uncertainty and simulated multispecies fisheries management advice in the Baltic Sea
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