Emma F. Young

Prediction and analysis of long-term variability of temperature and salinity in the Irish Sea

[1] The variability of temperature and salinity in the Irish Sea over the 40 year period 1960–1999 is investigated using a free-running fine-resolution local area model. The skill of the model to represent observed temperature and salinity variability is assessed using conductivity-temperature-depth survey data (3397 profiles) and a long time series of measurements from Cypris station (southwest of Isle of Man). This clearly demonstrates that the model can reproduce the observed seasonal and longer-term cycles in temperature, with mean and RMS errors of � 0.01C and 0.78C. Particularly apparent is the long-term warming trend at Cypris station and throughout the model domain. Model estimates of salinity are less accurate and are generally too saline (mean and RMS errors are 0.79 and 0.98 practical salinity units). Inaccuracies are likely to arise from boundary conditions and forcing (riverine and surface). However, while absolute values are not particularly well represented, the model reproduces many of the trends in the salinity variability observed at Cypris station, suggesting that the dominant physical processes in the Irish Sea, with timescales up to � 3 years, are well represented. The model is also used to investigate the variability in temperature stratification. While stratification is confined to approximately the same geographical area in each year of the simulation, there is significant variability in the timing of the onset and breakdown of stratification and in the peak surface to bed temperature difference. Together, these results suggest that a local area model with limited boundary conditions may be sufficiently accurate for climatic investigation of some (locally forced) parameters. Citation: Young, E. F., and J. T. Holt (2007), Prediction and analysis of long-term variability of temperature and salinity in the Irish Sea, J. Geophys. Res., 112, C01008, doi:10.1029/2005JC003386.

Oceanography and life history predict contrasting genetic population structure in two Antarctic fish species

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.

Variability in transport pathways on and around the South Georgia shelf, Southern Ocean: Implications for recruitment and retention

[1]xa0The waters around South Georgia are among the most productive in the Southern Ocean, with zooplankton populations close to the island, in particular Antarctic krill, supporting vast colonies of higher predators. However, our understanding of the processes governing variability in the supply of these food resources is limited by the poor spatial and temporal resolution of available data. Here, we use a numerical modeling approach to examine the underlying physical processes driving the recruitment and retention of zooplankton to the South Georgia shelf. Variability in the magnitude and spatial distribution of recruitment was dominated by the proximity and orientation of the southern Antarctic Circumpolar Current front to the shelf edge. Shelf retention was highest for source sites on the southwest shelf, with the main transport routes off the shelf to the north and northwest. Retention was lowest in the austral summer and winter; in summer increased glacial melt drives stronger off-shelf near-surface currents, while in winter, stronger winds lead to an increase in off-shelf transport. Of particular note was the prediction of a significant increase in retention for particles released throughout the shelf in April and July 2000. This period coincided with the development of pronounced anticlockwise shelf flows, associated with horizontal density gradients due to reduced wind mixing of shelf waters, and differences between shelf and oceanic waters, which significantly reduced off-shelf transport rates. Such findings are crucial for understanding the influence of variability in physical processes on the ecosystem at South Georgia.

Stepping stones to isolation: Impacts of a changing climate on the connectivity of fragmented fish populations

In the marine environment, understanding the biophysical mechanisms that drive variability in larval dispersal and population connectivity is essential for estimating the potential impacts of climate change on the resilience and genetic structure of populations. Species whose populations are small, isolated and discontinuous in distribution will differ fundamentally in their response and resilience to environmental stress, compared with species that are broadly distributed, abundant and frequently exchange conspecifics. Here, we use an individual‐based modelling approach, combined with a population genetics projection model, to consider the impacts of a warming climate on the population connectivity of two contrasting Antarctic fish species, Notothenia rossii and Champsocephalus gunnari. Focussing on the Scotia Sea region, sea surface temperatures are predicted to increase significantly by the end of the 21st century, resulting in reduced planktonic duration and increased egg and larval mortality. With shorter planktonic durations, the results of our study predict reduced dispersal of both species across the Scotia Sea, from Antarctic Peninsula sites to islands in the north and east, and increased dispersal among neighbouring sites, such as around the Antarctic Peninsula. Increased mortality modified the magnitude of population connectivity but had little effect on the overall patterns. Whilst the predicted changes in connectivity had little impact on the projected regional population genetic structure of N. rossii, which remained broadly genetically homogeneous within distances of ~1,500 km, the genetic isolation of C. gunnari populations in the northern Scotia Sea was predicted to increase with rising sea temperatures. Our study highlights the potential for increased isolation of island populations in a warming world, with implications for the resilience of populations and their ability to adapt to ongoing environmental change, a matter of high relevance to fisheries and ecosystem‐level management.