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USGS Mendenhall Postdoctoral  Research Fellowship Program

14-40. Hierarchical Modeling of Climate Change Effects: Land Use Impacts on Brook Trout Population Persistence

Forecasting effects of global climate change on biological processes is complicated by multiple connected systems, uncertainty within each of the systems and propagation of uncertainty among systems. We are interested in the development of a novel hierarchical modeling approach to account for sources of uncertainty among multiple scales in forecasts of the effects of global climate change within and among systems. We are interested in the application of such approaches specifically to an examination of the effects of land use/land cover management plans on local population persistence of brook trout (Salvelinus fontinalis) and a community of stream salamanders (in the genus Eurycea, Desmognathus, Gyrinophilus and Pseudotriton) in the context of climate change. Brook trout is a species of major management concern throughout the east coast that is threatened by urban development, riparian corridor management, water withdrawals and habitat fragmentation. Stream salamanders are top predators in streams which are too small for fish, and are likewise sensitive to environmental changes. All of these factors will interact in complex ways with changes in stream temperature and discharge resulting from future climate forcing effects on precipitation and air temperature. These top predators may respond differently to similar factors.

To improve understanding of these complex interactions our team is currently developing a series of original, linked sub-models that will allow estimation of probabilities of population persistence throughout the natural range of the species given climate change, the critical endpoint for management. The critical advance of our approach is explicit accounting for sources of uncertainty/error within and between the sub-models by developing a hierarchical approach with simultaneous parameter and error estimation. The sub-models present major innovations, including 1) linked surface water/groundwater/landuse/landcover hydrologic models, 2) a hierarchical statistical model that generalizes the watershed dynamics for prediction in basins where only geomorphological data are available, 3) a Bayesian characterization of uncertainty associated with downscaled GCM predictions, and 4) a Bayesian model of population processes for stream fish. While we will develop the approach for brook trout and stream salamanders, we anticipate that the key contribution of the project will be the hierarchical modeling framework that will serve as a prototype for effective forecasting of climate change effects across biological systems.

Our overall goal is to provide process-based predictions of population persistence for brook trout under alternate future scenarios. A key component to our approach is the use of hierarchical Bayesian modeling (Clark and Gelfand 2006) for explicit accounting of uncertainty in all modeling steps. The hierarchical approach allows modeling of the uncertainty associated with GCM projections, which can then be propagated through all modeling steps along with the additional sources of model uncertainty that result from parameter estimation and observational error. The result is a robust estimate of uncertainty associated with climate change projections of our primary response variable (population persistence) that can be used for risk assessment and risk management. Explicit accounting for all sources and pathways of uncertainty will indicate both the reliability of the predicted response to future scenarios and which model components need additional study (to reduce component uncertainty).

Hierarchical modeling uncertainty in coupled physical biological systems.—Conceptually, our modeling approach consists of a four-stage hierarchy, where s stands for a specific location, S equals space on the scale of climate, t is time, and | indicates “given.”

Hierarchical dependence

Response variable

Model components

[1] biology(s,t) | hydrology(s,t)

Population persistence

Occupancy, survival, body growth, movement, reproduction

[2] hydrology(s,t) | weather(s,t)

Stream temperature and flow

Coupled surface water/ground water flow (GSFLOW), riparian landcover/landuse, stream temperature, statistical model

[3] weather(s,t) | climate(S,t)

Local air temperature and precipitation

Downscaled projections

[4] climate(S,t)

Broad-scale air temperature and precipitation

Multiple General Circulation Model projection ensemble

There is broad latitude for contributions from the Mendenhall Fellow within this framework. We anticipate that the primary contributions will be 1) linking the biology models with the climate and environmental models and 2) interacting closely with natural resources managers and policy makers to incorporate the models into a structured decision process to identify cost/benefits of alternative management strategies. A lot of the groundwork for the project has already been conducted. The Fellow should be able to focus efforts on the development of the key novel contributions to the science of climate change forecasts, using this project as a template. While the project will be focused within the outlined framework, the Fellow will identify, with team guidance, the specific trajectory of her/his contribution.

REFERENCES.

Clark J.S., and Gelfand, A.E., 2006, A future for models and data in environmental science: Trends in Ecology and Evolution, v. 21, p. 375–380. 

Proposed Duty Station: Turners Falls, MA

Areas of Ph.D.: Ecology, biomathematics, statistics, or related field (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 –Research Fishery Biologist, Ecologist, Research Mathematician.

(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 theposition will be made by the Human Resources specialist).

Research Advisor(s): Ben Letcher, (413) 863-3803, ben_letcher@usgs.gov.; Evan Grant, (413) 863-3854, ehgrant@usgs.gov; Andy Royle, (301) 497-5846, aroyle@usgs.gov.; Keith Nislow (U.S. Forest Service), (413) 545-0357, knislow@fs.fed.us

Human Resources Office Contact: Junell Norris, (303) 236-9557, jlnorris@usgs.gov.


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U.S. Department of the Interior, U.S. Geological Survey
URL: http://geology.usgs.gov/postdoc/opps/2014/14-40 Letcher.htm
Direct inquiries to Rama K. Kotra at rkotra@usgs.gov
Maintained by: Mendenhall Research Fellowship Program Web Team
Last modified: 19:11:04 Tue 23 Jul 2013
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