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ABSTRACT – The U.S. Geological Survey (USGS) is the science agency of the Department of Interior (DOI) and provides science in support of resource-management needs. Identifying the science needs and framing the right science questions, together with developing and delivering tools that make the science information useable, are crucial to linking science to decision making. The FRAME (Framing Research to support Adaptive Management of Ecosystems) project integrates: • Collaborative approaches to framing the appropriate science questions to meet resource-management needs • Adaptive modeling tools to develop and deliver scientific information that accommodates the interrelationships of landscape parameters and their variability with changing environmental and management circumstances • Capacitybuilding to enhance the abilities of scientists to work in collaborative problem-solving environments, and the abilities of resource managers to effectively use adaptive-modeling tools. • The ultimate goal is to bring together collaborative approaches to framing science questions with modeling tools applicable to multi-objective management needs across a wide range of ecosystems. Development of this strategy requires a multi-year effort; however, we have begun development of the approach and tools with an initial focus on selected management issues in a single geographic region. We selected the Colorado Plateau because it is an area dominated by federal lands, and DOI and USDA agencies are currently re-evaluating land-management strategies because they face fundamental changes in ecosystems in this region http://www.mpcer.nau.edu/direnet/. The initial focus of FRAME is the management of pinyon-juniper ecosystems at Mesa Verde National Park. Capacity Building Adaptive Modeling Tools Models are an essential means of incorporating science into adaptive ecosystem management (Christensen et al. 1996). In the FRAME project, the modeling process has enabled managers and scientists to engage in a constructive dialogue about natural resource-management objectives. The interaction begins with the identification of critical resource-management issues. The managers and scientists then collaboratively frame the appropriate science questions to address the issues. Research and model development are then conducted to provide the tools and techniques necessary to Database-Centered Decision Support System Toolbox Resource Planning and Management Resource-management models are linked to vegetation-dynamics models and physical-process models using a common resource database and system-supported data-management interfaces (DMIs). Simulated changes in vegetation conditions that result from disturbances such as fire, insect infestation, disease, harvesting, and thinning can be used to estimate parameters for physical-process models to assess the effects of alternative management strategies on a variety of hydrological and ecological responses. Analysis and visualization tools provide measures for use in these assessments. The modular toolbox design enables the immediate integration of advances in physical and biological sciences, GIS technology, computer technology, and data resources into the toolbox. Quantification of historic cycles Resource Management Issues Research and Model Development Adaptive Management Text to be added to describe general concept of linked models Resource Management Alternatives Collaborative Framing of Science Questions DMI Object User Interface Interface for data visualization and modeling DMI evaluate alternative management strategies. Selected management strategies can be implemented. A fundamental component of adaptive resource management is a monitoring program designed to gather data for evaluating the success of management actions in promoting desired conditions. Simulation models also can aid in the selection of monitoring attributes that will provide effective feedback to managers and enable them to adjust management strategies in relation to changing conditions. DMI Resource Database DMI DMI Modular Modeling System Physical Process Models Model development has facilitated the explicit specification of assumptions that underlie the comparative analysis of fire-management-plan alternatives for pinyon-juniper ecosystems and the uncertainties attributable to limited scientific information. This process provides transparency and enables the critical examination of assumptions by fire-management-plan stakeholders. Spatially explicit simulation models will generate hypotheses concerning future trajectories of pinyon-juniper ecosystems and valued ecosystem attributes. The integration of simulation modeling into management planning will allow participants to examine and compare potential outcomes of proposed management alternatives in relation to management objectives and desired conditions. SIMPPLLE Vegetation Dynamics Models SIMulating Patterns and Processes at Landscape scaLEs (SIMPPLLE) Potential to Maintain Existing Old Growth Collaborative Approach: SIMPPLLE is a spatially explicit landscape-scale system for simulating vegetation changes caused by the disturbance processes of wildfire, insects, and diseases. An important component of the system is the interaction between disturbance processes and spatial patterns of vegetation. Output is provided for both individual vegetation units and the entire landscape modeled. For individual units, the system provides the disturbance processes modeled, their occurrence probabilities, the changes in vegetation conditions, and whether a process originated within a unit or spread to a unit. The acres of vegetation conditions, acres of each disturbance process, and acres of treatments are displayed by yearly or decade time steps for the entire landscape. These results can be used by managers to quantify current trends in vegetation conditions and disturbance processes; to create a representation of historic conditions; to quantify the range of variability for both vegetation conditions and disturbance processes; and to test the impact of management actions. These capabilities can help managers design and evaluate management strategies in the context of dynamic landscapes. Existing Old Growth and the simulated probability of stand replacing fire in the next 10 years Framing of the specific science questions that derive from pinyon-juniper management issues is accomplished collaboratively through a focus group of resource managers and scientists (the FRAMErs) with an emphasis on the decision context. These science questions are used to develop the modeling tools. Collaborative identification of issues and framing the questions helps overcome the common pitfalls of attempts to link science to resource management and ensures a focus on the decision context. Collaboration goes beyond consultation--all parties learn from each other in the process. • FRAME enhances the capacity of scientists to work in collaborative problem-solving environments, and of resource managers to effectively use adaptive-modeling tools to address complex resource management issues . The Future of FRAME Probability of Stand Replacing Fire Existing Old Growth The FRAME effort in Mesa Verde National Park is a pilot project to develop a collaborative approach to integrating science into resource management through modeling that can be expanded to other regions and other resource management issues on the Colorado Plateau. Mesa Verde FRAME project: Resource managers at Mesa Verde National Park were very receptive to the idea of modeling pinyon-juniper woodlands to guide critical decision making in the coming years. Managers of national parks are required to use the best available scientific information in making management decisions. At Mesa Verde, research is encouraged, and the staff takes pride in facilitating scientific investigations. Managers believe that a focus on pinyon-juniper research, monitoring, and conservation management can succeed in maintaining this community and its biodiversity. Another important issue involves the park’s archeological treasures. Sustaining a natural vegetative ground cover may be an important factor in retaining artifacts and archeological sites. Geographic Future: To adequately model pinyon-juniper within Mesa Verde National Park, it is desirable to model pinyon-juniper woodlands in a series of scenarios based on nested Minimum Dynamic Areas (MDA’s) for this system type. The concept of nested MDA’s allows us to begin with one that would include the Park boundary with a ¼ mile buffer, and expand ultimately to the Colorado Plateau. Participatory Future: It is also desirable to expand the collaboration to include participation by citizen and stakeholder groups. Modular Modeling System (MMS) Model Builder MMS is a modeling framework that supports the integration of models and tools at a variety of levels of modular design. Design levels include individual process models, tightly coupled models, loosely coupled models, and fully integrated decision support systems. A geographic information system (GIS) interface, the GIS Weasel, has been integrated with MMS to enable spatial delineation and characterization of basin and ecosystem features, and to provide objective parameter-estimation methods for selected models using available digital data coverages and landscape model outputs. Optimization and sensitivity-analysis tools are provided to analyze model parameters and evaluate the extent to which uncertainty in model parameters affects uncertainty in simulation results. A variety of visualization and statistical tools are also provided. Thematic Future: The management of pinyon-juniper (PJ) woodlands was selected as the initial focus for the development of our approach. PJ woodlands are abundant in the Colorado Plateau region (25 million ha). PJ management involves a number of cross-cutting management issues, such as grazing, OHV use, soil erosion, ecosystem restoration, fire management, urban/wildland interface, woodcutting, invasive species, coal-bed methane development, and recreational tourism. MMS Interface With a new Fire Management Plan in progress, the park quickly needed a better way to evaluate the long-term consequences of different management alternatives under different environmental circumstances. The unique natural and scientific values of the park’s old-growth pinyon-juniper woodlands are at risk due to recent ecological changes driven by drought. About half of the park’s stands have been eliminated by high intensity wildfires in just a matter of a few decades. Many of the surviving but drought-stressed pinyon pines were succumbing to bark beetle infestations. Major concerns regarding sustainability and regeneration include climate variability, wildfire frequency, invasive alien plants, effects of fuels treatments, and the relatively small size of the park, which does not meet the minimum dynamic area required to sustain the full range of natural variability of pinyon-juniper woodlands by natural processes alone. Mesa Verde's rapidly changing woodlands are likely to provide a responsive environment to study and measure the effects of environmental change, an important theme in interpreting the prehistoric and modern use of the Four Corners area. The information obtained from these studies is crucial in developing long-term land-management plans with old-growth pinyon-juniper woodland conservation as a stated goal. The Object User Interface (OUI) is a map-based interface for acquiring, organizing, browsing, and analyzing spatial and temporal data, and for executing models and analysis tools. OUI is the key component of MMS for developing loosely coupled models and DSSs. The functional components of the OUI are a hierarchical data tree, a map window for display of, and interaction with, one or more data-tree themes. The spatial data layers are stored in an ESRI shape-file format. The display and data tree provide action buttons to initiate model applications, evaluate model results using a variety of statistical and graphical tools, analyze associated spatial and temporal data, and generate a 3-D animation of simulated model states. The contents of the data tree and pull-down menus are specified using the eXtensible Markup Language (XML). George Leavesley, USGS, Denver Federal Center, george@usgs.gov; Jim Chew, USDA Forest Service, jchew@fs.fed.us; Christine Turner, Central Energy Resources Team, USGS, cturner@usgs.gov; Richard Zirbes, USGS, Denver Federal Center, rjzirbes@usgs.gov; William Romme, Colorado State University,romme@cnr.colostate.edu; Mark Miller, Southwest Biological Service Center, mark_miller@usgs.gov; Allan Loyallan.loy@nps.gov and George San Miguel, Mesa Verde National Park, george_san_miguel@nps.gov; Lisa Floyd-Hanna, Prescott College,lfloyd-hanna@prescott.edu; Neil Cobb, Northern Arizona University, Neil.Cobb@nau.edu Integrating Science with Resource Management through Collaborative Approaches and Adaptive Modeling Systems: Project FRAME (Framing Research to support Adaptive Management of Ecosystems) Literature Cited Christensen, N. L., A. M. Bartuska, J. H. Brown, S. Carpenter, C. M. D'Antonio, R. Francis, J. F. Franklin, J. A. MacMahon, R. F. Noss, D. J. Parsons, C. H. Peterson, M. G. Turner, and R. G. Woodmansee. 1996. The report of the Ecological Society of America Committee on the scientific basis for ecosystem management. Ecological Applications 6: 665-691.