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Postdoctoral Scholar In Modeling Climate Impacts On Conifer Reproduction

University of California - Merced
United States, California, Merced
5200 Lake Road (Show on map)
Nov 17, 2024
Position overview
Position title:
Postdoctoral Scholar
Salary range:
See Table 23 for the salary range for this position. A reasonable estimate for this position is $66,727 - $80,034.
Percent time:
100%
Anticipated start:
Start date is negotiable between December 10, 2024 and January 20, 2024.
Position duration:
2 year appointment


Application Window


Open date: October 23, 2024




Next review date: Tuesday, Nov 26, 2024 at 11:59pm (Pacific Time)

Apply by this date to ensure full consideration by the committee.




Final date: Tuesday, Dec 31, 2024 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.



Position description

A postdoc position researching climate impacts on conifer reproduction is available at UC Merced in the Moran lab . Our research focuses on the ecological and evolutionary responses of forests to climate change.

This position will make use of the Mast Inference and Forecasting (Mastif) model , and the associated global network of forest monitoring plots. This network of research collaborations has already yielded multiple high-impact papers*. The Moran lab is currently participating in an NSF-funded grant^ that aims to build on this work by linking data on seed production to consumer/disperser activity and seedling growth and establishment, and a UC climate change research initiative for a project^^ that, among other things, aims to use this model framework to better target seed collection efforts for reforestation.

Duties of the postdoc would include:



  • Assisting with collection (fieldwork) of cone count and seed trap data from across California and beyond. This will include mentoring undergraduate research assistants.
  • Analyzing California tree fecundity data and seedling data using the Mastif framework to test relationships between seed production and seedling regeneration, and how investment in cone size affects size and variability of seed crop.

  • Collaborating with UC Davis team-members to improve a web-based tool to share fecundity predictions with forest managers.
  • Participating in meetings with research teams and stakeholders.
  • Taking active part in manuscript preparation. At least one manuscript will be the primary responsibility of the postdoc as first author. The postdoc will also give at least one presentation on this research at a professional meeting.
  • The postdoc would also be encouraged to propose additional independent analyses using these datasets that match their research interests.


*Prior papers include:



  • V. Journe et al. 2024. The Relationship between Maturation Size and Maximum Tree Size from Tropical to Boreal Climates. Ecology Letters. 27:e14500
  • T. Qiu et al. 2023. Masting is uncommon in trees that depend on mutualist dispersers in the context of global climate and fertility gradient. Nature Plants 9, 1044-1056.
  • M. Bogdziewicz et al. 2023. Linking seed size and number to trait syndromes in trees. Global Ecology & Biogeography 32(5), 683-694.
  • S. Sharma et al. 2022. North American tree migration paced by climate in the West, lagging in the East. PNAS. 119(3): e2116691118


^ Collaborative research: Continent-wide forest recruitment change: the interactions between climate, habitat, and consumers (NSF, DEB-2211767)

^^ Increasing publicly available tools for climate-smart seed sourcing and forest restoration (UCOP Climate Action Award R02CP6995)

Funding sources:

UCOP project: 8.5 months Jan-Sept'25

Mastif project: 15.5 months Oct'25-Jan'27


Qualifications
Basic qualifications

Candidates must have completed a PhD in biology, ecology, mathematical modeling, or similar discipline, and have substantial experience with R. The candidate must be creative, self-disciplined, and motivated (as evidenced by reference letters, prior research productivity, and any research questions suggested in communication with PI).

Preferred qualifications

Qualifications that would be desirable but not strictly required include experience with Bayesian modeling, coding for Shiny apps, and/or fieldwork experience.


Application Requirements
Document requirements
  • Curriculum Vitae - Your most recently updated C.V.


  • Cover Letter - Please explain your interest in the position, how you match the qualifications, and how the position aligns with your future goals.


Reference requirements
  • 3 required (contact information only)

Apply link:
https://aprecruit.ucmerced.edu/JPF01828

Help contact: snspersonnel@ucmerced.edu



About UC Merced

The University of California, Merced, is the newest of the University of California system's 10 campuses. With over 9,000 undergraduate and graduate students (https://cie.ucmerced.edu/analytics-hub/student-statistics), UC Merced is committed to interdisciplinary excellence in research and teaching as well as to diversity, equity and inclusion. Ranked as one of the best public universities in the nation by U.S. News and World Report, UC Merced provides outstanding educational opportunities to highly qualified students from the heart of California, the nation, and abroad. The campus has special connections to nearby Yosemite National Park; is on the cutting edge of sustainability in construction and design; and supports the economic development of Central California. The Merced 2020 Project doubled the physical capacity of the campus, and enhanced academic distinction, student success, and research excellence (https://merced2020.ucmerced.edu/).

The University of California, Merced is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.

Please refer to the University of California's Affirmative Action Policy and the University of California's Anti-Discrimination Policy.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements. This includes the University of California Policy on Vaccination Programs: https://policy.ucop.edu/doc/5000695/VaccinationProgramsPolicy.


Job location
Merced, CA
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