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To study the transport of plaice (Pleuronectes platessa L.) eggs and larvae in the eastern Irish Sea, we constructed a 3D-baroclinic physical model and coupled it to a particle-tracking scheme that allowed aspects of larval behaviour to be simulated. Starting positions for eggs were based upon data from a series of ichthyoplankton surveys and final positions were compared with results of settled plaice distributions from two beam trawl surveys conducted on beaches around the eastern Irish Sea. If simulated larval behaviour was limited to passive drift or horizontal swimming, the particles diffused away from the spawning areas but failed to reach nursery grounds in significant numbers (85-90% remaining offshore). In contrast, switching on circatidal vertical swimming significantly increased the numbers of larvae reaching the coast (only 23-30% remained offshore). Particles tended to accumulate in bays and estuaries and this pattern compared well with the distribution of settled plaice from the field surveys. Studies in the southern North Sea (where spawning and nursery grounds are widely separated) have also demonstrated the importance of selective tidal stream transport for successful recruitment of settling plaice to nursery grounds. Although our understanding of the ontogeny of this behaviour is still poor, the model results presented suggest that this aspect of behaviour is a key factor influencing plaice settlement success.

Understanding the key drivers of population connectivity in the marine environment is essential for the effective management of natural resources. Although several different approaches to evaluating connectivity have been used, they are rarely integrated quantitatively. Here, we use a ‘seascape genetics’ approach, by combining oceanographic modelling and microsatellite analyses, to understand the dominant influences on the population genetic structure of two Antarctic fishes with contrasting life histories, Champsocephalus gunnari and Notothenia rossii. The close accord between the model projections and empirical genetic structure demonstrated that passive dispersal during the planktonic early life stages is the dominant influence on patterns and extent of genetic structuring in both species. The shorter planktonic phase of C. gunnari restricts direct transport of larvae between distant populations, leading to stronger regional differentiation. By contrast, geographic distance did not affect differentiation in N. rossii, whose longer larval period promotes long-distance dispersal. Interannual variability in oceanographic flows strongly influenced the projected genetic structure, suggesting that shifts in circulation patterns due to climate change are likely to impact future genetic connectivity and opportunities for local adaptation, resilience and recovery from perturbations. Further development of realistic climate models is required to fully assess such potential impacts.

2018. Managing fishery development in sensitive ecosystems: identifying penguin habitat use to direct management in Antarctica. Ecosphere 9(8):Abstract. In the Southern Ocean, the at-sea distributions of most predators of Antarctic krill are poorly known, primarily because tracking studies have only been undertaken on a restricted set of species, and then only at a limited number of sites. For chinstrap penguins, one of the most abundant krill predators breeding across the Antarctic Peninsula, we show that habitat models developed utilizing the distance from the colony and the bearing to the shelf-edge, adjusting for the at-sea density of Pygoscelis penguins from other colonies, can be used to predict, with a high level of confidence, the at-sea distribution of chinstrap penguins from untracked colonies during the breeding season. Comparison of predicted penguin distributions with outputs from a high-resolution oceanographic model shows that chinstrap penguins prefer nearshore habitats, over shallow bathymetry, with slow-flowing waters, but that they sometimes also travel to areas beyond the edge of the continental shelf where the faster-flowing waters of the Coastal Current or the fronts of the Antarctic Circumpolar Current occur. In the slow-moving shelf waters, large penguin colonies may lead to krill depletion during incubation and chick-rearing periods when penguins are acting as central place foragers. The habitats used by chinstrap penguins are also locations preferentially used by the commercial krill fishery, one of the last under-developed marine capture fisheries anywhere on the planet. As it develops, this fishery has the potential to compete with chinstrap penguins and other natural krill predators. Scaling our habitat models by chinstrap penguin population data demonstrates where overlap with the fishery is likely to be most important. Our results suggest that a better understanding of krill retention and krill depletion in areas used by natural predators and by the krill fishery are needed, and that risk management strategies for the fishery should include assessment of how krill movement can satisfy the demands of both natural predators and the fishery across a range of spatial and temporal scales. Such information will help regional management authorities better understand how plausible ecosystem-based management frameworks could be developed to ensure sustainable co-existence of the fishery and competing natural predators.

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