Population dynamics of cod Gadus morhua in the North Sea region: biological density-dependent and climatic density-independent effects

Abstract

Through the statistical modeling of monitoring data, we assess the ecological interlinkages between cod Gadus morhua L. in the North Sea, Skagerrak and Kattegat -regions which typically have been considered separate management units. The model includes both within-population density dependence (within and between age classes), as well as density-dependent effects of migration between the North Sea, Skagerrak and Kattegat. Further, the model incorporates the effects of environmental features (such as temperature and the North Atlantic Oscillation). The obtained results are discussed, both with reference to general ecological principles as well as with respect to management implication. Altogether our analysis suggests a unified management regime for the entire region including the North Sea, the open Skagerrak and Kattegat.KEY WORDS: GAM · NAO · North Sea-Skagerrak-Kattegat system · Time-series modeling · Transport effect Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 302: [219][220][221][222][223][224][225][226][227][228][229][230][231][232] 2005 density dependence within and between cohorts) and extrinsic processes (such as climate dependence). We apply a time-series approach to deduce the underlying forms of dynamics and interactions of the populations. We analyze data on cod Gadus morhua L. from the International Bottom Trawl Survey (IBTS) monitoring surveys coordinated by the ICES, together with environmental data, in order to arrive at a joint model for the North Sea, Skagerrak and Kattegat populations. Using this approach we are able to demonstrate the effect of transport between the areas, and show that almost identical models can be used to represent the dynamics of the cod populations in the 3 areas.The overall perspective of our study is a general one focusing on the density-dependent and densityindependent structure of populations (see, e.g., Stenseth et al. 2002), where climate is seen as the main density-dependent factor. A key focus of our paper is the interlinkage of various sub-units of the overall population (North Sea, Kattegat and Skagerrak), where each of these sub-units may affect each other in a density-dependent manner. As a platform for our analyses, we provide in the following section a synoptic account of the Skagerrak system with its neighboring waters. The North Sea-Skagerrak-Kattegat systemCurrents in the North Sea, as in any continental shelf sea, occur in response to forcing by tides, winds, density gradients (arising from freshwater input) and pressure gradients. For most of the North Sea the dominant motion is tidal, with the next most significant motion generator being wind forcing (Howarth 2001). About 70% of the water entering the North Sea is assumed to pass through the Skagerrak before leaving for the North Sea again (Danielssen et al. 1996). The general circulation pattern in the Skagerrak is counterclockwise. After passing by the northern tip of Denmark, the highly saline North Atlantic water (entering from the ...

Inter- and intra-annual trends and status indicators of nektobenthic elasmobranchs off the Balearic Islands (northwestern Mediterranean)

“…Ciannelli et al 2004, Chen et al 2005. GAMs were implemented in the R package, using variations of GAM formulations, as implemented in the mgcv library (Wood 2004).…”

Oil sardine (Sardinella longiceps) off the Malabar Coast: density dependence and environmental effects

“…Direct and indirect effects of density dependence and external variables have been reported for other marine fish populations (Chen et al. , 2005; Dingsor et al.…”

“…Direct and indirect effects of density dependence and external variables have been reported for other marine fish populations (Chen et al, 2005;Dingsor et al, 2007). Stenseth et al (1999) illustrated how density dependence and stochastic forces are crucial in shaping the dynamics of Atlantic cod populations.…”

Challenges and Opportunities of Local Fisheries Management: Pikeperch, Sander Lucioperca (Actinopterygii: Perciformes: Percidae), in Pärnu Bay, Northern Gulf of Riga, Baltic Sea

“…Incorporating environmental variables can enhance the performance of stock-recruitment models (Fiksen and Slotte 2002, Marjomäki 2004, Keyl and Wolff 2008 and GAM models are a flexible tool for incorporating non-linear environmental effects (Daskalov 1999, Chen et al 2005, Megrey et al 2005, Keyl and Wolff 2008. Even though the pikeperch stock-recruitment model presented here performs well, with most data points within the 95% confidence limit of the model (Fig.…”