• Address a pressing conservation challenge
• Stipend and tuition included, support provided primarily through research assistantships
• Live in an affordable, safe, and friendly university town
• Gain experience that will prepare the student for a diverse range of career options
Background: Many ungulates migrate to access key resources and avoid harsh weather. Despite the importance of ungulate migration for many ecosystems, the traditional migration corridors used by populations around the world face unprecedented change from the expanding footprint of human development. To conserve ungulate migration in the face of rapid environmental change and anthropogenic disturbance, an important first step is mapping the migration corridors. The successful applicant will develop methods to map key movement corridors and landscape linkages for species that exhibit "atypical migrations" (i.e., wide-ranging but less predictable movement patterns). The successful applicant will also investigate the ecological drivers and benefits of atypical migrations. The taxonomic focus of this effort may include pronghorn, elk, moose, and potentially other species. Currently, methodology exists to map corridors of migratory taxa with high fidelity to their migration routes and seasonal ranges (i.e., “typical migration”). However, when these approaches are applied to atypical migrants, the results are often less than desirable – identifying areas that are too large for realistic landscape-scale prioritization or failing to capture key areas used outside the data collection window. The goal of this work is to derive generalizable and scalable methods to prioritize areas critical for maintaining connectivity for atypical migrants and to advance our ecological understanding of such wide-ranging movements.
The PhD student will be supervised by Dr. Ellen O. Aikens and will work closely with the west-wide corridor mapping team, which includes researchers and wildlife managers from across the western USA.
Project Goals and Deliverables:
• Build a better understanding of the ecological drivers of atypical ungulate migrations.
• Test the efficacy of existing migration mapping tools for atypical migrants.
• Refine existing approaches or develop new methods to prioritize landscape-scale conservation for atypical migrants.
• Build software and tools to facilitate the use of new methods.
To apply, please send a single PDF containing the following information to Dr. Aikens (Ellen.Aikens@sdstate.edu) with the subject line “Atypical migration mapping PhD application”:
1. A cover letter highlighting the research interests, qualifications, and motivation of the applicant
2. CV or resume
3. A writing sample (e.g., a peer-reviewed publication, proposal, thesis, popular science article)
4. Contact information for 3 references
Applications will be reviewed on a rolling basis and preference will be given to applications received by October 31st, 2022. If this timeline does not work for you, contact Dr. Aikens.
- A strong work ethic, positive attitude, and a desire to conduct research that bridges science and management
- Excellent communication skills
- Experience conducting scientific research
- Works well independently and as part of a team
- Programming experience in R or python
- A bachelor’s degree in Ecology, Natural Resource Management, Geography, Data Science, or a related field. Candidates with degrees in computer science or other related quantitative fields who have a strong interest in wildlife ecology and conservation are also encouraged to apply.
- A Master’s degree in Ecology, Natural Resource Management, Geography, Data Science, Statistics, or a related field. Candidates with degrees in computer science or other related quantitative fields who have a strong interest in wildlife ecology and conservation are also encouraged to apply.
- Experience publishing in peer-reviewed scientific journals
- Strong programming skills in R or python
- Strong analytical skills, especially managing and analyzing large, spatially-explicit datasets
- Familiar with emerging approaches in spatial analysis, animal movement modeling and remote sensing
- Experience with Shiny app development or other related tools
The GRE is NOT required.