A model-based evaluation of Marine Protected Areas: the example of eastern Baltic cod (Gadus morhua callarias L.)

The eastern Baltic cod stock collapsed as a consequence of climate-driven adverse hydrographic conditions and overfishing and has remained at historically low levels. Spatio-temporal fishing closures [Marine Protected Areas (MPAs)] have been implemented since 1995, to protect and restore the spawning stock. However, no signs of recovery have been observed yet, either suggesting that MPAs are an inappropriate management measure or pointing towards suboptimal closure design. We used the spatially explicit fishery simulation model ISIS-Fish to evaluate proposed and implemented fishery closures, combining an age-structured population module with a multifleet exploitation module and a management module in a single model environment. The model is parameterized based on (i) the large amount of biological knowledge available for cod and (ii) an analysis of existing spatially disaggregated fishery data. As the population dynamics of eastern Baltic cod depend strongly on the climate-driven hydrographic regime, we considered two production regimes of the stock. MPAs were only effective for stock recovery when they reduced overall fishing effort. The performance of MPAs needs to be evaluated relative to environmental regimes, especially for stocks facing strong environmental variability.

[1]  C. Möllmann,et al.  Food consumption by clupeids in the Central Baltic: evidence for top-down control? , 1999 .

[2]  Robert L. Heilbroner,et al.  Growth and Survival , 1972 .

[3]  A. Lehmann.  A three-dimensional baroclinic eddy-resolving model of the Baltic Sea , 1995 .

[4]  R. Voss,et al.  Spatial and temporal heterogeneity of the cod spawning environment in the Bornholm Basin, Baltic Sea , 2007 .

[5]  K. Radtke.  Evaluation of the exploitation of Eastern Baltic cod (Gadus morhua callarias L.) stock in 1976-1997 , 2003 .

[6]  Michael J. Fogarty,et al.  Effort distribution and catch patterns adjacent to temperate MPAs , 2005 .

[7]  Stéphanie Mahévas,et al.  Spatially explicit fisheries simulation models for policy evaluation , 2005 .

[8]  Watson,et al.  A dynamic mass‐balance model for marine protected areas , 2000 .

[9]  Hilaire Drouineau,et al.  Assessing the impact of different management options using ISIS-Fish : the French Merluccius merluccius - Nephrops norvegicus mixed fishery of the Bay of Biscay , 2006 .

[10]  O. Bagge,et al.  The Baltic cod , 1994 .

[11]  B. MacKenzie,et al.  Baltic cod recruitment – the impact of climate variability on key processes , 2005 .

[12]  Ransom A. Myers,et al.  What can be learned from the collapse of a renewable resource? Atlantic cod, Gadus morhua, of Newfoundland and Labrador , 1994 .

[13]  J. Tomkiewicz,et al.  Fish stock development in the Central Baltic Sea (1976-2000) in relation to variability in the environment , 2003 .

[14]  B. MacKenzie,et al.  Quantifying environmental heterogeneity : habitat size necessary for successful development of cod Gadus morhua eggs in the Baltic Sea , 2000 .

[15]  C. Möllmann,et al.  Biophysical modeling of larval Baltic cod (Gadus morhua) growth and survival , 2002 .

[16]  Stéphanie Mahévas,et al.  ISIS-Fish, a generic and spatially explicit simulation tool for evaluating the impact of management measures on fisheries dynamics , 2004 .

[17]  J. Tomkiewicz,et al.  Maturation processes and spawning time of cod in the Bornholm Basin of the Baltic Sea: Preliminary results , 1999 .

[18]  C. Humborg,et al.  Second Assessment of Climate Change for the Baltic Sea Basin , 2008 .

[19]  R. Tol,et al.  Testing the implications of a permanent or seasonal marine reserve on the population dynamics of Eastern Baltic cod under varying environmental conditions , 2007 .

[20]  Jesper Boje,et al.  Report of the Baltic Fisheries Assessment Working Group (WGBFAS), 10-17 April 2013, ICES Headquarters, Copenhagen , 2011 .

[21]  Michel J. Kaiser,et al.  Are marine protected areas a red herring or fisheries panacea , 2005 .

[22]  M. Tundi Agardy,et al.  Advances in marine conservation: the role of marine protected areas , 1994 .

[23]  A. Nissling,et al.  Variation in egg buoyancy of Baltic cod Gadus morhua and its implications for egg survival in prevailing conditions in the Baltic Sea , 1994 .

[24]  B. Halpern,et al.  Review Paper. Matching marine reserve design to reserve objectives , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[25]  Villy Christensen,et al.  Ecospace: Prediction of Mesoscale Spatial Patterns in Trophic Relationships of Exploited Ecosystems, with Emphasis on the Impacts of Marine Protected Areas , 1999, Ecosystems.

[26]  Julia L. Blanchard,et al.  Aggregation and removal of weak-links in food-web models: system stability and recovery from disturbance , 2005 .

[27]  H. Gislason.  Effect of Changes in Recruitment Levels on Multispecies Long-term Predictions , 1993 .

[28]  F. Walters.  Sequential Simplex Optimization - An Update , 1999 .

[29]  H. Hinrichsen,et al.  Identifying eastern Baltic cod nursery grounds using hydrodynamic modelling: knowledge for the design of Marine Protected areas , 2009 .

[30]  Serge M. Garcia,et al.  When can marine reserves improve fisheries management , 2004 .

[31]  G. Turner,et al.  The mbuna cichlids of Lake Malawi: a model for rapid speciation and adaptive radiation , 2005 .

[32]  C. Roberts,et al.  Effects of marine reserves on adjacent fisheries. , 2001, Science.

[33]  W. Matthäus,et al.  Characteristics of major Baltic inflows—a statistical analysis , 1992 .

[34]  V. Mohrholz,et al.  The impact of exceptionally warm summer inflow events on the environmental conditions in the Bornholm Basin , 2006 .