Weather patterns are changing across the globe, and these changes may affect populations of animals. For coastal seabirds, it seems likely that associated changes in precipitation levels and wind characteristics could impact their ability to find and locate prey, and therefore feed themselves and chicks. For example, variations in precipitation change levels of freshwater input, causing rapid alterations in water temperature and salinity, with consequences on prey behaviour and distribution. Changes in wind direction and strength influence the energetic costs of movement, with consequences on foraging efficiency. Whilst local and daily variations in weather conditions could have considerable impacts on population dynamics, responses of animals to such variation is poorly understood. To meet this important knowledge gap, this project asks whether daily and local variations in weather conditions influences a species abundance/distribution, activity budgets and demographics. To do so, the project applies traditional and modern approaches to a population of European shags Phalacrocorax aristotellis occupying Conwy Bay, Wales, UK. Shore and vessel-based observations will record the abundance and distribution of the population within the Bay. Camera-traps, GPS loggers and DSLR time-lapse will monitor the activity budgets of individual animals at the breeding colony. Long-term ringing and nest monitoring data will provide insights into productivity and survival rates. These biological data will then be combined with physical data from in-situ instrumentation, 3D hydrodynamic models and historical measurements to (1) identify influential meteorological conditions and (2) assess how these conditions influence population dynamics. The successful applicant will divide their time between the performance of fieldwork and the processing/analysis of large data. Alongside generic research training, the successful applicant will receive specialist training in ornithological fieldwork (observations, ringing, nest-monitoring, tagging), analytical software (Matlab, R), population models and advanced statistics (GLM, GAM, GLMM).
Applicants should hold a minimum of a UK Honours degree at 2:1 level (or equivalent) in a relevant subject including Biology, Ecology or Zoology. A valid driving license is also required.
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