Research Description The Pennsylvania State University, Pennsylvania Game Commission, and DCNR Bureau of Forestry have been conducting a long-term research project to manipulate the abundance of deer and measure the response of forest vegetation in the context of deer and forest management. Four study areas of approx. 18,000 acres each in a treatment-control context will have deer populations manipulated. Deer populations are monitored with satellite GPS-collared deer and genetic analysis of deer pellets to estimate abundance. In turn, forest vegetation conditions are monitored across each study area as well as intensive vegetation monitoring where forest management activities occur.
The primary goals of this research are to (1) identify the relative importance of the primary factors thought to influence forest vegetation conditions (e.g., deer herbivory, competing vegetation, lack of fire, soil acidification), (2) obtain a better understanding factors that influence the behavior of deer hunters and their motivations for acquiring and using antlerless harvest permits/licenses, and (3) test various measures (e.g., plant indicator species, browse intensity) believed to reflect the effect of deer herbivory on forest vegetation conditions. I am seeking a student interested in developing decision models for deer in the context of meeting forest management goals. This project provides an opportunity for a student to develop integrated population models using survival data, harvest data, and population estimates (genetic spatial capture-recapture and spotlight surveys). These models can be integrated with forest succession models for making deer management decisions. Funding is available for a student to begin summer 2018, but no later than August 2018. Applications will be reviewed as they are received. Qualifications and How to Apply M.S. degree preferred and GRE scores >50th percentile. Strong quantitative skills with an interest in population estimation and modeling is essential. Desirable skills in an applicant include the ability to work in a team setting, supervise technicians, and be well organized to oversee data collection across four study areas. Please send (as a single pdf document) a cover letter describing your research interests, CV, and unofficial copies of transcripts to [email protected]. Please include contact information for 3 references.
