Project: Coastal Wetland Carbon Sequestration in a Warmer Climate
We are seeking a postdoctoral researcher to join our interdisciplinary
team on an exciting new manipulative experiment that examines the
interactions of warming, elevated CO2, and inundation frequency in
coastal wetland marsh ecosystems. The position focuses on the
development, application, and analysis of new computational models that
couple energy, water, carbon, and nutrient dynamics in tidal wetland
systems. This successful candidate will collaborate with an active
modeling team and be expected to interact closely with other research
groups working on field experiments and observations.
The project focuses on a unique manipulative experiment located at the
Smithsonian Environmental Research Center (SERC) in Edgewater, MD. The
manipulative experiment is already underway, and both pre- and post-
treatment results are now available for use by the modeling team. A
broad array of measurements is being gathered routinely, including marsh
elevation, water levels, meteorological conditions, vegetation community
distribution and productivity, plant traits, soil biogeochemistry, and
CO2 and CH4 fluxes. Thanks to a long history of research at the site, a
wealth of observational and experimental data is available to inform
model construction and to evaluate model performance. The primary
objective of the study is to test the hypothesis that warming will
increase both plant production and decomposition, but that the net
effect will be an increase in soil carbon storage.
The candidate will work directly with the land model component of the
new Department of Energy Earth System Model. The full model is known as
ACME (Accelerated Climate Model for Energy), and the land component used
as a starting point for this activity is the ACME Land Model (ALM)
version 1.0. That model includes sophisticated carbon, nitrogen, and
phosphorus biogeochemistry and plant physiology, but has never been
enabled for simulation in a tidal wetland system. New development led by
the candidate will include introduction of redox and pH controls on soil
biogeochemistry (some early work is available as a starting point),
external forcing for water height to mimic tidal variation, and
parameterization of high marsh and low marsh physical environment and
vegetation community.
The new position will have excellent opportunity for creative freedom to
explore alternative approaches and to design the most effective
interactions with observational and experimental project elements.
A strong background in computational modeling is a requirement, with
experience in land, wetland, or tidal system modeling desirable. A
demonstrated record of scientific productivity that includes strong
written and oral communication skills are also required for this
position. Experience collaborating with observationalists and
experimentalists is highly desirable. The ALM v1.0 model uses Fortran90,
and so Fortran experience is desirable, but not necessary.
This is a two-year position funded by SERC, but the successful candidate
will work at the Climate Change Science Institute at Oak Ridge National
Laboratory, located in the lush temperate forest biome near Knoxville,
in eastern Tennessee. Abundant local recreational opportunities include
hiking, biking, camping, and wildlife observation, in the Tennessee
River valley, in the Smoky Mountains to the east, and on the Cumberland
Plateau to west. Numerous rivers and lakes provide abundant opportunity
for all sorts of boating and fishing. Regular visits to interact with
project members and measurement activities at the experimental site in
Maryland will be expected, with all travel expenses covered by the
project.
To apply, please e-mail a short letter of interest that describes your
experience and qualifications (1-2 pages), CV, and list of references to
Dr. Pat Megonigal ([email protected]). Review of applications and
interviews will begin immediately upon receipt and the search will
continue until a suitable applicant is found. The candidate is expected
to start by 1 September 2017. Questions about this position can be
directed to Peter Thornton ([email protected]) or Pat Megonigal.
