Climate influence on Baltic cod, sprat, and herring stock–recruitment relationships

• Published in: Progress in Oceanography
• Main Authors: Margonski, Piotr, Hansson, Sture, Tomczak, Maciej, Grzebielec, Ryszard
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2010
• Subjects: /dk/atira/pure/sustainabledevelopmentgoals/climate_action; SDG 13 - Climate Action; Gotland Basin; North Atlantic; North Atlantic oscillation
• Online Access: https://orbit.dtu.dk/en/publications/60daf9aa-8f78-40f1-b5ac-1b1c671a185d; https://doi.org/10.1016/j.pocean.2010.08.003

A wide range of possible recruitment drivers were tested for key exploited fish species in the Baltic Sea Regional Advisory Council (RAC) area: Eastern Baltic Cod, Central Baltic Herring, Gulf of Riga Herring, and sprat. For each of the stocks, two hypotheses were tested: (i) recruitment is significantly related to spawning stock biomass, climatic forcing, and feeding conditions and (ii) by acknowledging these drivers, management decisions can be improved. Climate impact expressed by climatic indices or changes in water temperature was included in all the final models. Recruitment of the herring stock appeared to be influenced by different factors: the spawning stock biomass, winter Baltic Sea Index prior to spawning, and potentially the November–December sea surface temperature during the winter after spawning were important to Gulf of Riga Herring, while the final models for Central Baltic Herring included spawning stock biomass and August sea surface temperature. Recruitment of sprat appeared to be influenced by July–August temperature, but was independent of the spawning biomass when SSB > 200,000 tons. Recruitment of Eastern Baltic Cod was significantly related to spawning stock biomass, the winter North Atlantic Oscillation index, and the reproductive volume in the Gotland Basin in May. All the models including extrinsic factors significantly improved prediction ability as compared to traditional models, which account for impacts of the spawning stock biomass alone. Based on the final models the minimum spawning stock biomass to derive the associated minimum recruitment under average environmental conditions was calculated for each stock. Using uncertainty analyses, the spawning stock biomass required to produce associated minimum recruitment was presented with different probabilities considering the influence of the extrinsic drivers. This tool allows for recruitment to be predicted with a required probability, that is, higher than the average 50% estimated from the models. Further, this approach ...