Stakeholder-lead, collaborative conservation planning efforts can often be improved by working across geopolitical boundaries to address common conservation goals across larger spatial scales. However, large-scale conservation planning has often been hampered by the lack of empirically-driven, high resolution information on wildlife species distributions and responses to potential landscape changes. To deal with this issue, large-scale conservation planning efforts (e.g., State Wildlife Action Plans) tend to rely on general guidance and coarse data sets that underserve and sometimes misinform land management decisions. Developing species-habitat models based on empirical data from across the full range of each species could help provide higher-resolution data sets for planning and more specific guidance for managers. For species considered to be “at risk”, such empirical efforts are impeded by limited availability of species location data as well as reluctance to report sensitive spatial data identifying species locations. To overcome these hurdles, the “Modeling Species at Risk to Support State Wildlife Action Plans in the Southeast” project will use various empirical means to generate an intermediate resolution data set (i.e., HUC12 watersheds) of species distributions for the Southeast informs large-scale conservation planning efforts while addressing data and data-sharing limitations.
The Post-Doctoral Associate will work closely with Mississippi State University co-investigators, and scientists from the U.S. Fish and Wildlife Service (USFWS), and southeastern state wildlife agencies to carry out the project. The successful candidate for this position will compile distribution data for At-risk Species from various sources (e.g., State Heritage Programs, NatureServe, iNaturalist), develop a HUC12 distribution map for species and species-guilds on the Service’s At-risk Species list for the Southeast, and use this information to modify the existing Southeast Conservation Adaptation Strategy Blueprint map incorporating weighting for habitat quality based on known species presence. This information will also inform an assessment of species sustainability in HUC12 watersheds basted on habitat condition, species presence, and future potential system stressors (e.g., urbanization). The successful candidate will also be responsible for developing and communicating with a project steering committee representing U.S. Fish and Wildlife Service, State Wildlife Diversity coordinators, State Heritage Program coordinators and database managers, and other key conservation partners. The candidate will also be required to publish 2 or more peer-reviewed publications from this work.
The 1-year term limited position will be funded from 2 January 2018 through 31 December 2018. Salary will be $43,000 per year, including a full benefits package, with the possibility of extension pending acquisition of additional extramural funding. The Post-Doctoral Associate will be based out of the Quantitative Ecology and Spatial Technologies Lab in the Department of Wildlife, Fisheries and Aquaculture at Mississippi State University in Starkville, Mississippi.
Application review will begin September 15, 2017 and will continue until the position is filled.
Anticipated Start Date:
January 2, 2018
This position may require some travel to stakeholder meetings and to present research findings at regional and/or national conferences (approximately 2-4 overnight trips during the year).
Applicants may contact Kristine Evans [firstname.lastname@example.org] with any questions prior to application submission.
MSU is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, ethnicity, sex (including pregnancy and gender identity), national origin, disability status, age, sexual orientation, genetic information, protected veteran status, or any other characteristic protected by law. We always welcome nominations and applications from women, members of any minority group, and others who share our passion for building a diverse community that reflects the diversity in our student population.
The Postdoctoral Associate must hold a Ph.D. in wildlife and fisheries science, natural resource management, biological science, environmental science/management, or other related fields. The candidate must have some combination of the following skills: spatially explicit species distribution modeling, landscape conservation, and computer programming. Expertise with geographic information systems (GIS) and other related software applications and technologies is also required, and a general background in quantitative ecology and biostatistics will be viewed favorably. The candidate must also have excellent oral and written communication skills, be self-motivated, and able to work effectively both independently and as part of a cross-agency team.
A Ph.D. in wildlife and fisheries science, natural resource management, biological science, environmental science/management, or other related fields. The preferred candidate will also have experience compiling and conducting QA/QC on state-level wildlife and fisheries datasets, working with sensitive species data (T&E species or Species at Risk), developing large-scale species and ecosystem models, and extrapolating models to watershed-level spatial datasets. The preferred candidate will have an understanding of the Southeast Conservation Adaptation Strategy, U.S. Fish and Wildlife Service At-Risk Species efforts, state wildlife diversity programs, and state natural heritage programs. Additional expertise in other species modeling (e.g., Maxent), conservation planning (e.g., Marxan, GFlow, Zonation), urbanization and climate change predictive modeling, and GIS software applications (e.g., ERDAS Imagine, ENVI, GRASS, QGIS, etc.) is considered a valuable asset for this position.
Applications must include: 1) cover letter, 2) resume or Curriculum Vitae, 3) one-page statement of interest and expertise, 4) contact information for three references, and 5) academic transcripts.
Applicants must complete an application through the MSU HRM website at: http://explore.msujobs.msstate.edu/cw/en-us/job/496078?lApplicationSubSourceID= , but should also email a copy of the cover letter and resume/CV directly to email@example.com.