http://geology.usgs.gov/postdoc/2013/opps/opp36.html
USGS Mendenhall Research Fellowship Program, FY 2013 Announcement
36. Understanding Effects of Climate and Land Use
Change on Grizzly Bear Demographics
Dynamic forces, including climate and land use
change, increasingly constrain wildlife
populations. Consequently, new tools are required
for adaptively monitoring and managing wildlife
in the face of this uncertainty. In northwestern
Montana, both bottom-up (food) and top-down
(mortality) processes control grizzly bear
abundance (Graves and others, in press), and
climate change will likely influence both.
Climate change will likely lead to increased
human development (Samson and others, 2011),
increasing the potential for human-bear
conflictsand, thus, higher bear mortality.
Increased temperature and variability in weather,
along with changes in timing of precipitation,
will shift ecosystem-shaping processes such as
wildfire, avalanches, insects, disease, and
invasive species outbreaks and also directly
influence bear food sources. For example,
increased weather variability will especially
influence fruiting food species that require
specific combinations of temperature and
precipitation conditions over multiple years.
Shifts in phenology may also cause both local and
broad shifts in activity and occurrence.
Bear-human conflicts fluctuate with food
availability, so if food decreases, more
conflicts are likely (Nielsen and McLellan,
2011). Bears may enter dens later or emerge
earlier with warmer climate (Haroldson and
others, 2002). Along with lower and less
predictable food availability, greater spatial
and temporal exposure to humans greatly increases
the potential for human-bear conflicts and resulting mortalities.
The population in the Northern Continental Divide
Ecosystem (NCDE) in northwestern Montana is
currently healthy (N~765; ~1.03), and efforts are
underway to develop a conservation strategy to
begin the delisting process. However, given
potential changes, monitoring strategies must be
able to identify not only population trend but
also the source of any decreases in the
population. Combining spatially explicit adaptive
monitoring strategies and integrated population
monitoring may meet this need while identifying
the most economically feasible means of maintaining high data quality.
Recently, two concurrent programs have evaluated
the ability of different methods (genetic
mark-recapture and telemetry-based known fate
models) to monitor population trend. Other
records also exist, including
spatial-capture-recapture data, human-caused
mortality locations, human-bear conflict details,
and sighting information. Each method has
different strengths and weaknesses, including
costs, degree of training required, ease of
back-country monitoring, risk to animals, ability
to meet assumptions, detection bias, and
precision. The NCDE includes Glacier National
Park (GNP), where security and bear abundance are
high, non-invasive monitoring is preferred, and
management options are limited primarily to
managing human behavior. The spatial distribution
of mortality and reproduction is unknown, but
higher abundance in the park is likely due in
part to higher survival, the most elastic of bear
vital rates (see Harris and others, 2011, for
citations). Most human-caused mortality occurs on
mixed-use and private lands where greater
opportunity for management of people and habitat exists.
A new class of hierarchical toolsintegrated
population modelsprovides an exciting new
approach to jointly analyze multiple datasets and
estimate plural demographic parameters, including
reproduction and survival, with improved
precision over separate analyses. No research has
been conducted on optimal sample design with this
class of models, although simultaneously
maximizing precision and minimizing monitoring
costs are a highly practical outcome of this
approach. This highly flexible approach permits
inclusion of variables that may drive demographic
parameters, including food indices, population
density, and winter severity. Method development
opportunities include finding appropriate model
selection techniques and incorporating spatially
and temporally repeated counts within the
integrated population model (Schaub and Abadi, in
press). Ideally, monitoring would also be
adaptive, permitting a balance of cost savings
and precision (Hooten and others, 2009).
Combining optimal adaptive monitoring designs
with integrated population models offers another frontier of method advances.
Applicants to this Opportunity are invited to
propose postdoctoral research to (1) develop a
spatially explicit, adaptive monitoring design
for grizzly bears that simultaneously estimates
trend, reproduction, and survival while
optimizing cost, precision, and feasibility and
(2) evaluate the ability of those models to
identify the causes of threats to the population
through simulations linking habitat, human
development, and human behavior to bear demographics.
References
Graves, T.A., Kendall, K., Royle, J.A., Beier,
P., Stetz, J., and MacLeod, A., in press, Multi-
scale assessment of landscape characteristics
influencing local grizzly bear abundance: Ecography.
Harris, R.B., Schwartz, C.C., Mace, R.D., and
Haroldson, M.A., 2011, Study design and sampling
intensity for demographic analyses of bear populations: Ursus, v. 22, p. 2436.
Haroldson, M.A., Ternent, M.A., Gunther, K.A.,
and Schwartz, C.C., 2002, Grizzly bear denning
chronology and movements in the greater
Yellowstone Ecosystem: Ursus, v. 13, p. 2937.
Hooten, M.B., Wikle, C.K., Sheriff,S., and
Rushin, J., 2009, Optimal spatio-temporal hybrid
sampling designs for ecological monitoring:
Journal of Vegetation Science,v. 20, p. 639649.
Nielsen, S., and McLellan. B., 2011, Potential
implications of climate change on brown bears in
North America: Ottowa, 20th International
Conference on Bear Research and Management, July 1723, 2011.
Samson, J., Berteaux, D., McGill, B.J., and
Humphries, M.M., 2011, Geographic disparities and
moral hazards in the predicted impacts of climate
change on human populations: Global Ecology and
Biogeography, v. 20, p. 532544.
Schaub, M., and Abadi, F., in press, Integrated
population models: A novel analysis framework for
deeper insights into population dynamics: Journal of Ornithology
Proposed Duty Station: West Glacier, MT
Areas of Ph.D.: Ecology, biology (candidates
holding a Ph.D. in other disciplines but with
knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet one of the
following qualifications:
<http://geology.usgs.gov/postdoc/2013/qualifications.html#res_biol>Research
Biologist,
<http://geology.usgs.gov/postdoc/2013/qualifications.html#res_ecol>Research
Ecologist
(This type of research is performed by those who
have backgrounds for the occupations stated
above. However, other titles may be applicable
depending on the applicant's background,
education, and research proposal. The final
classification of the position will be made by the Human Resources specialist.)
Research Advisors: Kate Kendall, (406) 888-7994,
<mailto:[email protected]>[email protected]; J.
Andy Royle, (301) 497-5846,
<mailto:[email protected]>[email protected]; Mevin
Hooten, (970) 491-1415,
<mailto:[email protected]>[email protected]
Human Resources Office Contact: Candace Azevedo,
(916) 278-9393, <mailto:[email protected]>[email protected]
