USDI - Geological Survey Pre-proposal for Integrated Science in Direct Assistance to National Wildlife Refuge Managers and Biologists Working in the Greater Yellowstone Area of the Northern Rocky Mountains

---

Adaptive Management, Advanced Technologies,
and Montane Wetlands

Justification
Refuge managers find it very challenging to develop annual schedules of management practices reflecting the actual dynamics of their wetland systems because almost no information exists about the ecology of montane wetlands in the Northern Rockies. Typically, the best information on palustrine wetlands is based on work done in the Prairie Pothole Region. Extrapolating such information to montane areas in the Intermountain West can be extremely misleading because such ecological basics as climate, soils, and water regimes are so different. By the same token, refuge managers cannot simply put their management on hold for the next several decades while researchers gather the specifics needed. To overcome this problem, an approach is needed that is based on adaptive management and decision analysis. One requirement for managing montane wetlands is a thorough understanding of the uncertainties related to various parameters. Some parameters may be based on scientific field studies and empirical, predictive modelling, and others on more qualitative, expert knowledge. Approaches are needed that blend these types of data and information in ways that help refuge managers in the annual process of making decisions.

A comprehensive decision support system, drawing from different databases and knowledge sources, can organize far more information than humans can typically process in making subjective decisions. Furthermore, decision support systems can often be used effectively to communicate and explain the basis for management recommendations. In this fashion, the refuge manager can assess the quality of the logic and also gain the advantage of having others? expertise available to them via the system.

A structured, systematic approach based on simulating the primary controlling factors should enable refuge managers to recognize and effectively manipulate those factors to create optimal conditions for migratory birds and other wetland wildlife. By modelling such systems using artificial intelligence methods and Bayesian analysis, we propose to incorporate what is now known, describe the uncertainties associated with that knowledge, and revise our knowledge and models in an adaptive fashion. We believe that this strategy is a realistic and effective way to assist natural resource managers.

Addressing a Specific Purpose in Support of Four Very Specific Questions?
This decision support research is designed to address four questions as articulated by refuge biologists and managers:

• What seasonal water level recommendations can be annually developed that would best contribute to migratory bird objectives for certain individual species as well as groups of species when considered together?
• On an annual basis, what combination of muskrat population levels and vegetation conditions are desirable in conjunction with the dynamics of long-term wetland processes and hemi-marsh conditions?
• What effects do optimal water levels in the semi-permanent emergent marsh (PEMF) have on adjacent wet meadow (PEMA; PEMB; PEMC) plant communities?
• When there are direct economic costs involved with acquiring or retaining water, what is the predicted value of that additional water both to a given year?s objectives and to management of long-term vegetation cycles?

Integrated Science and Decision Support
To address these questions, information is needed from a variety of disciplines: ecology, climatology, hydrology, geology, geomorphology, remote sensing, GIS, computer science, and decision theory. Each of the USGS divisions has a great deal to offer in developing an innovative approach to better understanding montane wetlands and providing that information to land managers. From a research perspective, original and synthesis work is needed to develop a new modelling and decision support approach that will not only be applicable at the refuges being studied, but will contribute to a more generalized model that might be applied to palustrine wetlands throughout the Northern Rockies. Such models must be fueled by a wide variety of ecological, spatial, and related monitoring data. National wildlife refuges throughout the country are developing comprehensive conservation plans. From their perspective, the decision support tools we will provide to simulate wetland management scenarios will be an important method for development and evaluation of alternatives within the planning process. In addition, the gathering of the monitoring data will provide significant baseline data necessary for other aspects of the planning process. The key will be cooperation between the two separate but complementary processes, research and management.

Goals and Objectives
The overall goal of this research is to provide decision support that will allow refuge managers to simulate water level management and ecological response to this management as a way to explore the most satisfactory ways of reaching long term refuge wetland objectives, while satisficing short term needs. The following are more specific research objectives to be addressed:

• To improve the refuge manager?s capability to manage water levels for attainment of optimal vegetative conditions and migratory bird objectives by providing a more thorough understanding of wetland system dynamics.
• To provide decision analysis and support for managing montane wetlands on national wildlife refuges, specifically addressing the four questions delineated in this proposal.
• To assess the value of artificial intelligence methods for modelling ecological relationships and wetland dynamics in a decision support context.
• To quantitatively evaluate what baseline data are ultimately necessary for building effective decision support systems for montane wetland management on national wildlife refuges.
• To evaluate what remote sensing techniques and data are both available and useful to refuge managers for monitoring bathymetry, vegetation types, water levels, and muskrat populations in montane wetlands, and for assessing periodic changes in these parameters.
• To quantitatively assess how an understanding of the geologic framework contributes to modelling surface and groundwater interactions in wetlands.

Model development and field work will be targeted at national wildlife refuges in the Northern Rockies, and specifically the Greater Yellowstone Area when possible. Grays Lake, Benton Lake, and Red Rock Lakes NWRs are the areas currently under consideration by the FWS as partners in this project.

Figure 2. Views at Red Rock Lakes NWR, 11 June 1999.

System Modelling: This team will build the overall model, as well as all individual submodels, except for the hydrologic submodel. They will be responsible for working with the other teams to determine what additional submodels might be necessary, as well as what inputs and outputs are necessary for each submodel. They will also build the user interface. They will be responsible for overall system verification and validation, the latter specifically in relation to the four management questions working closely with the Ecology Team. They will build and maintain a web page for the project, which will provide a way for team members to exchange data and information as well as a way for refuge managers to provide interpretive information to their audiences.

Remote Sensing: This team will provide, to the extent technology will allow, DEM?s of bathymetry; and will provide monitoring inputs as developed collaboratively with the Ecology Team related to vegetation, water levels, and muskrats. In the final year of the project, they will provide a report to each national wildlife refuge delineating detailed procedures for gathering necessary monitoring data so that the system can be used in an adaptive management fashion. This team will be responsible for preparing metadata for all parts of the project, as appropriate.

Ecology: This team will be responsible for gathering necessary information about wetland vegetation, bird communities, and muskrat populations, specifically to fuel the individual submodels. The focus will be on understanding wetland processes, involving both long and short term dynamics, especially of vegetation cycles. Specific concepts generally accepted for low elevation, inland palustrine wetlands will be examined in relation to variables such as growing season length, water sources, soils, and short and long-term climatic patterns. Investigations will specifically provide the ability for the system to address the four management questions. This team will delineate, for the Systems Modelling Team, the inputs and outputs required for model development, and will work with them throughout iterative model and submodel development. The Ecology Team will be responsible for ecological validation of the overall model working closely with the Systems Modelling Team to do so.  Because ecological aspects of this research will determine the success of the system, this team will have responsibility for conceptual design of simulations necessary to address the four management questions.

Geologic Framework and Geohydrology: This team will develop procedures that provide information regarding: (1.) Basin development and geomorphologic landscape history as it relates to understanding plant response and water level management, especially through soils; (2.) Wetland history as determined from patterns of the past few hundred years; (3.) Characterization of geochemical relationships to water quality as they affect wetland functions such as emergent and submergent plant germination and growth, or as outright contaminants. This includes characterization of catchment mineralogy, understanding element pathways (sources and sinks), and documenting present and historic baselines for biologically critical elements. (4.) Origin of springs, discharge areas, and recharge areas; (5.) Tectonics as pertinent to wetland management, including impacts on hydrology, as well as an assessment of any risk.

A general framework for a hydrologic budget (submodel) will be developed that can be used by refuge staff as part of this system. Minimum hydrologic information and data requirements for future use of the system will be made. A water table or potentiometric surface map will be generated. Detailed descriptions of how to gather that information will be provided. An existing model developed for Bowdoin National Wildlife Refuge (Kendy 1999) will be used as a basis from which to proceed. The existing procedural approach will be extended through artificial intelligence methods such as Bayesian belief networks. Close coordination with the Systems Modelling Team will be necessary.

Climatic Patterns: This team will explore existing data and information to provide an understanding of the frequency of extreme and average precipitation and evapotranspiration patterns, along with an assessment of the reliability of that information. The focus will be on spatial and temporal climate patterns as they relate to understanding wetland dynamics, namely drought and flooding periodicity and duration. They will provide recommendations for what information inputs and outputs are needed for this submodel to function in relation to the hydrologic model. They will also provide information and analysis related to winter severity as needed for a better understanding of muskrat population dynamics, as suggested by the Ecology Team.

Oversight: A team consisting of Fish and Wildlife Service representatives will review each of the projects on an annual basis to assess whether the specific project continues to hold promise in addressing the four wetland management questions. If any effort appears unsatisfactory, they will provide recommendations to the team leader(s) about how to remedy the situation. They will provide an annual assessment of the project to each regional office of the Fish and Wildlife Service and Geological Survey. They will be available to all other teams as a vehicle by which these teams can explore and ensure the applicability of their approaches to wetland management on national wildlife refuges, and will encourage interaction among teams to do so. They will foster working relationships with individual national wildlife refuges and will try to ensure that researchers have appropriate access to refuge data, records, facilities, staff, etc. They will organize anonymous peer review of specific research proposals during the project initiation stage as requested by each investigator. They will work with each team, suggesting specific scientific papers that might be prepared, and will be available to assist in the preparation of those papers, as requested by team leaders. During Year 5 of the project, a workshop will be held for land managers and researchers throughout the Northern Rockies and other montane areas to demonstrate various aspects of the system, highlight new knowledge about montane wetlands, and describe problems encountered.

Further Information
An on-line slide show about this project was developed to stimulate discussion among all partners and is available at http://swan.msu.montana.edu/wetlands . In addition, this document is available there to view in web (html) format as well as in postscript format

Literature Cited

Carter, G. M., M. P. Murray, R. G. Walker, and W. E. Walker. 1992. Building organizational decision support systems. Economic Press Inc. San Diego, CA. 358 pages.

Return to home page for Adaptive Management, Advanced Technologies, and Montane Wetlands