Institution: Trent University, Peterborough, Ontario, Canada (www.trentu.ca)
Supervisor: Dennis Murray (Lab webpage: http://www.dennismurray.ca)
We are seeking a PhD student to assess the statistical limitations and biological inference of contemporary long-term ecological monitoring study designs and datasets, to help reveal the extent that existing approaches may be limited in guiding wildlife conservation programs or documenting broader patterns of environmental change. Currently, few robust long-term datasets of wildlife abundance exist, and there is the need to evaluate both the optimal design of long-term monitoring studies and the reliability of surrogate datasets (e.g., harvest statistics, habitat loss timeseries) in population analysis. Indeed, our previous work on carnivores and waterfowl (e.g., Murray et al. 2010, Ecology 91: 571-581; Murray et al. 2008 J. Wildl. Manage. 72: 1463-1472) revealed shortcomings that call into question the broader utility of existing approaches in population analysis and management. Through timeseries analysis, statistical power analysis, and simulation modeling, the project will address questions such as: 1) population timeseries attributes that are needed to reliably detect a numerical decline or increase; 2) the most robust statistical methods for assessing cyclicity and attenuation in fluctuating animal populations; 3) optimal design of wildlife surveys in heterogenous and changing landscapes; and 4) forecasting population viability using limited or biased data. The student will have the opportunity to develop specific research questions within the scope of the larger project, and our lab-based model system (i.e., Chlamydomonas, see Borlestean et al. 2015 Frontiers in Ecology and Evolution doi: 10.3389/fevo.2015.00037) is available to test specific model predictions in an empirical context.
The funding package includes a competitive stipend, foreign tuition waiver (if the student is not a Canadian citizen or permanent resident) as well as coverage of all research/travel expenses. The successful candidate will have an MSc degree in Ecology, Mathematics, Statistics, or related field, evidence of peer-reviewed publications, and very strong quantitative skills. The student will join the Integrative Wildlife Conservation laboratory at Trent University (www.dennismurray.ca) and be part of an interdisciplinary team addressing innovative solutions to environmental change (www.create-enviro.ca).
To apply, send a cover letter, curriculum vitae, unofficial academic transcript, and contact information for 3 references, to: Dennis Murray (email@example.com). Application deadline is Feb 16th, but review of applications will begin immediately and continue until a suitable candidate is found. Applicants are strongly encouraged to apply early.