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McCoy, K. D. et al. ; Recent observations on the western Antarctic Peninsula have suggested that changing climatic conditions may be increasing pressure on breeding seabirds due to higher exploitation rates by the tick Ixodes uriae. Using data from 8 microsatellite markers and ticks from 6 Pygoscelis spp. colonies, we employed a population genetics approach to specifically test the hypothesis that I. uriae is expanding south-westward along the peninsula from the Subantarctic region. Contrary to expectations, tick genetic diversity was high within all colonies, and no remaining signal of colonisation events was evident. Although significant geographic genetic structure occurred among ticks from different colonies, these ectoparasites tended to belong to 2 major genetic groups, one found principally in south-western locations (Palmer Station area) and the other in more north-eastern areas (South Shetland Islands). More central colonies showed a mixture of ticks from each genetic group, suggesting that this area represents a hybridisation zone of ticks from 2 distinct origins. A subsequent clustering analysis, including ticks from 2 Subantarctic locations, did not reveal the source population for the northern peninsula group. Overall, our data refute the hypothesis of a recent south-westward expansion of I. uriae along the peninsula and suggest that this tick has been present at more southern latitudes for an extended period of time. Further studies on the distribution and genetic characteristics of this ectoparasite around Antarctica are now required to better understand the colonisation process and predict how changing environmental conditions may affect its presence and diversity in seabird colonies. © Inter-Research 2012. ; Financial support was provided by the European Regional Development Fund, the Ministerio de Ciencia e Innovacion from the Spanish Government (Projects POL2006-06635, POL2006-05175, CGL2004-01348, CGL2007-60369, CGL2009-11278/BOS, CMT 2011-24427) and the Agence National de la Recherche, France (ANR-06-JCJC-0095-01). ; Peer Reviewed

In many coastal areas, high water tables are present, complicating installation of some stormwater best management practices (BMPs) that rely on infiltration. Regional estimates of the seasonal high water table (SHWT) often rely on sources such as soil surveys taken over a decade ago; these data are static and do not account for groundwater withdrawals or other anthropogenic impacts. To improve estimates of the SHWT, we developed a GIS-based methodology relying on surface water elevations. Data sources included a 1.5-m (5.0ft) resolution Lidar-derived digital elevation model (DEM), aerial imagery, and publicly available shapefiles of water boundaries. Twenty-six groundwater monitoring wells were screened to eliminate well locations influenced by pumping, yielding 22 wells. In coastal Virginia, tidal water bodies and ditches form terminal boundaries for discharge from the water-table aquifers and permit water table elevations to be fixed at the landward boundaries of surface water bodies. Water table elevations interpolated from well data and boundary elevations were used to create a triangulated irregular network representing the water table elevations for November 2012, which was the date of the DEM. An adjustment factor, calculated from the highest recorded April water table depth from long-term groundwater monitoring data, was added to estimate the SHWT elevation. SHWT elevations were subtracted from the DEM to yield SHWT depth, which was compared with long-term monitoring well data, yielding an R2 value of 0.91. Residual errors were random, although the method underpredicted the highest expected SHWT and overpredicted the median SHWT. The SHWT depth map was validated by using water table depths from 57 soil borings at 10 different sites, and consistently matched observations better than available soil survey estimates. The SHWT depth map could be useful for BMP siting and feasibility studies in similar hydrogeological settings. ; City of Virginia Beach [449263]; Virginia Agricultural Experiment Station; Hatch program of the National Institute of Food and Agriculture, US Department of Agriculture ; The authors express their appreciation to Greg Johnson, Department of Public Works, City of Virginia Beach, Virginia; Kathleen Hancock, Department of Civil and Environmental Engineering, Virginia Tech; and Conrad Heatwole and Durelle Scott, Department of Biological Systems Engineering, Virginia Tech, who facilitated and helped guide this research, and provided constructive comment. Portions of this research were funded by the City of Virginia Beach, Project 449263; however, opinions expressed within are entirely of the authors and reflect no endorsement by the City. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. Funding for this research was also was provided in part by the Virginia Agricultural Experiment Station and the Hatch program of the National Institute of Food and Agriculture, US Department of Agriculture, which also does not imply endorsement of opinions contained herein. ; Public domain authored by a U.S. government employee