MSc or PhD project on the design optimization for private protected areas

Institution: Trent University, Peterborough, Ontario, Canada (www.trentu.ca)

Supervisor: Dennis Murray (http://www.dennismurray.ca)  

We are seeking an MSc student to develop a robust and universal strategy 
for selecting private land parcels for conservation. Using a variety of GIS 
tools, we will develop models for quantifying the conservation value of 
individual land parcels based on natural characteristics, anthropogenic 
effects, zoning, and connectivity, and assess their application using the 
highly fragmented southern Ontario landscape as test case. The models will 
be further tested across a range of restrictions to ultimately provide a 
set of general guidelines to assist NGOs in optimizing their choice of land 
parcels for protection. Ultimately, we aim to optimize procedures for 
designing protected areas networks across southern Ontario and beyond. If 
the position is filled by a PhD candidate, there will be additional 
opportunity to tailor specific research questions within the scope of the 
larger project.


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 a BSc or MSc degree in Biology, Ecology, Geography, or related field, 
with GIS experience and an understanding of basic principles in design of 
protected areas. PhD candidates must demonstrate evidence of peer-reviewed 
publication. The successful candidate must be competitive for scholarship 
funding and will join the Integrative Wildlife Conservation laboratory at 
Trent University (www.dennismurray.ca). 

To apply, send a cover letter, curriculum vitae, unofficial academic 
transcript, and contact information for 3 references, to: Dennis Murray 
([email protected]). The successful candidate will begin enrolment by 
January or May 2018, and we will accept applications until a suitable 
candidate is found, so apply early. 

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