Postdoc: Adaptive Management for Black Rails, Maryland

Agency
USGS Eastern Ecological Science Center at Patuxent Research Refuge
Location
Laurel, MD
Job Category
Post Doctoral Appointments
Salary
GS-12
Start Date
07/05/2021
Last Date to Apply
05/19/2021
Website
https://www.usgs.gov/centers/pwrc
Description
Project Title: Adaptive Management for Eastern Black Rails Position Title: Post-doctoral Research Associate Salary: GS-12 salary (approximately $87K annually) and benefits Location: USGS Eastern Ecological Science Center at Patuxent Research Refuge, Laurel, MD Performance Period: 24 months (anticipate start date July 2021) Application Deadline: 14 May 2021 Position Summary: To identify effective management practices for Eastern Black Rails, the USGS Eastern Ecological Science Center at Patuxent Research Refuge (formerly Patuxent Wildlife Research Center) is seeking a post-doctoral research associate with interest in adaptive management and population modeling for a collaboration with the Atlantic Coast Joint Venture. This project will develop an adaptive management framework to reduce uncertainty about management practices for Eastern Black Rails and provide managers with tools and information that will help them implement best management practices for creating and enhancing habitat for this species, which is listed as endangered in five states along the Atlantic Coast and as Threatened under the Endangered Species Act. In collaboration with the ACJV Eastern Black Rail Working Group, which includes biologists and land managers from NJ to FL, this project will combine data about wetland management (e.g., timing and depth of water levels, burning, etc.) with Black Rail occupancy or abundance and vegetation response across many different project sites. The data will be used to build predictive models of rail population responses to management actions. The models will be updated over time to test assumptions and improve predictions about which management techniques result in high quality habitat. Specific duties will be to conduct statistical power analyses for management experiments, develop a Bayesian decision model to predict consequences of management actions and reduce uncertainty about best management practices, and create a decision-making framework that links management objectives, actions, and predictive models to guide habitat management and inform recovery planning for Eastern Black Rails. This position is a 2-year appointment located in Laurel, MD.
Qualifications
Minimum Requirements: 1. Ph.D. in biology (wildlife), ecology, or related field, with a focus on quantitative methods in population ecology. 2. Applicant must be within 5 years of receiving PhD. 3. Applicant must be a US citizen. 4. Demonstrated familiarity with statistical modeling and concepts of decision analysis. 5. Demonstrated proficiency with computing platforms such as R or MATLAB. 6. Demonstrated desire and ability to publish in the peer-reviewed literature. Desired Abilities: Competitive candidates will have a strong background in statistics, quantitative ecology, and decision analysis. Strong programming skills are desired including proficiency with R for data manipulation and statistical modeling and Bayesian networks or other frameworks for predictive modeling. The successful candidate will have excellent written and personal communication skills and demonstrated success in working closely with management agencies on applied questions in wildlife conservation. Applicants should email: (1) a letter describing your background and interests – the letter should address specifically how the applicant meets both the minimum requirements and the desired abilities, (2) curriculum vitae, and (3) the names and contact information for 3 references to Dr. Jim Lyons (jelyons@usgs.gov). Please include “Black Rail postdoc” in the subject line. For further information, contact: Jim Lyons (jelyons@usgs.gov), USGS Eastern Ecological Science Center at Patuxent Research Refuge, 12100 Beech Forest Road, Laurel, MD 20708.
Contact Person
Dr. Jim Lyons
Contact eMail
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