About the Project
Although theoretically apparent, there is scant empirical evidence of relationships between animal energy budgets and ecosystem processes (2,3). So far, the scientific community has been poorly equipped to determine instantaneous space- and time-specific energy expenditures of wild animals. Recent technological advances in animal-borne logger hardware and software mean that we can now measure the activity patterns of wild animals and use this variable as a proxy both for energy expenditure and behaviour.
Within mammal guilds, certain species seem to be particularly vulnerable to energetic constraints and are consequently in rapid decline. Large mammals are a case-in-point. This can be because their distributions are limited and/or because biotic conditions restrict their food intake. Other concerns also highlight the effects of disease and climate change.
To ensure future sustainable wildlife populations, we must understand the impact that each population stressor and the interactions between stressors have on wild animal ecology. Drivers such as habitat loss and human-wildlife conflict are widely accepted and easily demonstrable. However, subtle and multiplicative interactions between altered behaviours and energy expenditures in response to differences in habitat characteristics, disease status, presence of prey, conspecifics, humans, and/or other environmental perturbations including changes in climate are less well explored. Such interactions therefore warrant more attention for mitigation planning and species conservation.
The student will be trained in analytical techniques used to measure activity and energy expenditure in wild animals. Valuable experience will be acquired through working with the CASE partner (Wildbyte Technologies, see below) on the research and development of data analytics, including multidimensional visualisation and filtering mechanisms, and algorithms/parameters to enhance the existing in-house software. There is also potential to work on interfacing with other software packages such as R or MatLab for extra statistical analysis. Interfacing the primary software with external software packages would expand the in-house software capabilities immensely. No single software tool can do everything if it does not allow the user full control over their analysis. Existing datasets will be used to develop the skills required and then a research protocol will be designed to collect additional field data. The student will be required to travel to Aberdeen University for training in the doubly labelled water technique. QUB/ UoA and the QUADRAT scheme have comprehensive training courses in data handling, statistics, presentation skills and career development, which the student will be required to undertake.
More project details are available here: https://www.quadrat.ac.uk/projects/case-links-between-energetics-and-disease-in-mammals-use-of-biolgging-and-remote-sensing-to-assess-behaviour-and-movement/
How to apply: https://www.quadrat.ac.uk/how-to-apply/
Note that applications should NOT be submitted directly to Queen’s.
Before applying please check full funding and eligibility information: View Website
(2) Nisbet, R.M. et al. 2000. J. Anim. Ecol. 69: 913-926
(3) Martin, B.T. et al. 2012. Methods Ecol. Evol. 3: 445-449
Why not add a message here
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.
QUADRAT DTP CASE: Salmonid conservation in American rivers in the wake of proliferative kidney disease outbreaks: using functional genomics to understand climate-change driven disease emergence