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Latest revision as of 07:59, 14 October 2012
General System description
System name: SIMulating Patterns and Processes at Landscape ScaLEs
Acronym: SIMPPLLE
Brief overview
SIMPPLLE is a spatially-explicit, dynamic landscape modeling system for projecting temporal changes in the spatial distribution of vegetation in response to insects, disease, wildland fire and other natural and management caused disturbances. SIMPPLLE is designed to provide a balance between incorporating enough complexity and interactions in modeling ecosystem processes to provide an acceptable level of realism while making simplifications in the choices on required data input requirements, required computer platforms and computing time to be a management tool useful in collaborative planning processes.
Contents
Scope of the system
SIMPPLLE is designed to serve as a decision support system to help managers and resource specialists quantify and incorporate concepts that are often difficult to interpret for specific landscapes. Managers can use SIMPPLLE to help define and evaluate desired future conditions at landscape scales, to identify what parts of a landscape are more prone to disturbance processes over a given time frame, and to help design and evaluate different strategies for achieving desired future conditions.
SIMPPLLE is implemented with ecological knowledge associated with geographic zones. Currently all the geographic zones are within the United States:
Geographic zones: Forest Service – Westside Region One, Montana and Idaho; Forest Service – Eastside Region One, Montana and Idaho; Sierra Nevada - Yosemite National Park, CA; Southern California; South Central Alaska - Kenai Peninsula, AK; Gila National Forest, NM; South West Utah; Michigan; Colorado Front Range; Colorado Plateau; Western Great Plains Steppe; Mixed Grass Prairie; Great Plains Steppe; Teton – Northwest Wyoming; Northern Central Rockies;
However the underlying object design of the system makes it possible to create new geographic zones for other ecosystems throughout the world.
System origin
SIMPPLLE was developed by Jim Chew, USDA Forest Service, as a management tool for the Northern Region of the Forest Service(Chew 1995, Chew and others 2004). Through the Joint Fire Sciences program (http://www.firescience.gov/) it was expanded into eight other geographic areas to test it and other models’ capabilities to design and evaluate fuel treatments at landscape scales (Weise and others 2006). Additional work with the FRAME project in Mesa Verde National Park (Turner and others 2008) has expanded the system into the Colorado Plateau. Work with the Ecosystem Management Research Institute (http://www.emri.org/) has expanded SIMPPLLE into grassland ecosystems.
The initial release of version 1.0 was in 1997. The current version available is 2.5. Version 3.0 is under development with USGS and Northern Arizona University, “Regional Dynamic Vegetation Model for the Colorado Plateau: A Species- Specific Approach”, http://www.niccr.nau.edu/cobb_abs.html
SIMPPLLE has been used for Forest Service project planning (Slaughter and others 2004), resource management planning on both National Forests (USDA 2008) and Bureau of Land Management lands (USDI 2005), for ecosystem assessments on National Grasslands (Haufler and others 2009) and in State wildlife management plans (State of South Dakota 2006). SIMPPLLE was utilized by a group of timber companies and conservation organizations to prepare a land management approach for the Beaverhead-Deerlodge National Forest (Ecosystem Resource Group 2006).
Support for specific issues
SIMPPLLE has been used to quantify possible historic ranges of variability, desired future conditions, and levels of treatments for project planning (Slaughter and others 2004), resource management planning on both National Forests (USDA 2008) and Bureau of Land Management lands. (USDI 2005), for ecosystem assessments on National Grasslands (Haufler and others 2009) and in State wildlife management plans (State of South Dakota 2006).
Within the flexibility that SIMPPLLE offers to address a range of issues, it offers some common elements:
• Disturbance processes are simulated as stochastic occurrences in time and space. • Spatially explicit vegetation patterns interact with disturbance processes. • Multiple simulations of stochastic processes help managers view scenarios as a range of possible outcomes.
Access to system knowledge through the user interface, the common computer platforms used, and the rapid simulation time all make SIMPPLLE useful in collaborative planning processes (Turner and others 2008).
Support for specific thematic areas of a problem type
- Silvicultural
- Conservation
- Restoration
- Development choices / land use zoning
- Policy/intervention alternatives
- Sustainability impact assessment (SIA)
A wide range of types of problems are supported such as designing and testing silvicultural, restoration, and conservation strategies. Long simulations of hundreds of years can be utilized to address sustainability assessments.
Capability to support decision making phases
(NOTE I do not quite know what to do with this, as I do not understand it myself, although it seems related to system use)
(Click here to see a more detailed explanation)
- Intelligence (+ explicit description of the support given by the DSS)
- Design (+ explicit description of the support given by the DSS)
- Choice (+ explicit description of the support given by the DSS)
- Monitor (+ explicit description of the support given by the DSS)
Related systems
Results from the use of stand level models such as the Forest Vegetation Simulator (FVS) can be incorporated into the vegetation pathways. Output from SIMPPLLE has been used with the optimization and scheduling model, MAGIS. Output of changing vegetation conditions has been used as input into USGS’s hydrologic response model, Precipitation Runoff Modeling System (PRMS).
Data and data models
Typical spatial extent of application
The spatial extent varies as SIMPPLLE is designed for simulating vegetation patterns and processes at a range of spatial scales. The user can chose the size to represent plant communities and the extent of the landscape that is needed to address specific issues. Only the available RAM on the computers used limits the spatial extent. For project level planning and watershed assessments of landscapes that are 1000’s of acres, users often use plant communities of the size of 30 meters to 1 to 5 acres. For multiple watershed assessments of millions of acres the size of plant communities may vary from 10 to 20 acres.
Forest data input
The basic vegetation information required is an ecological stratification, cover type, size class – structure, and density for each plant community in the landscape. These plant communities can be represented by irregular polygons or rasters. Optional information can be provided on current and past disturbance processes and treatments. The plant communities can be described with multiple lifeforms if desired; trees, shrubs, and herbaceous. For those geographic zones that include logic to predict the probability of invasive species the percent of invasives in a plant community can be added. In grassland zones the percent of species by cover has to be identified. The specific values for these input variables are different for each geographic zone. All data is input through ESRI’s ArcGIS system. Specific input variables for optional landscape units such as land, aquatic and roads and trails are identified in the user’s manual. All landscape components have to be feature classes in file geodatabases in ESRI’s ArcGIS 9.3. A SIMPPLLE tool box for all the necessary processing of input data is provided with the installation executable.
Type of information input from user (via GUI)
Through the system’s user interface a user can identify the input files to build new landscape area files, select simulation parameters, lock in disturbance processes, schedule management treatments, choose options for outputs, and make changes in system knowledge on vegetation pathways and disturbance process probability. Each geographic zone comes with “default” system knowledge. However, all of the system knowledge is accessible through the user interface and changes can be made to reflect new research results or updates in expert opinion.
Individual vegetation unit attributes can be edited through the user interface.
The simulation results can be examined by summaries for the entire landscape or by individual plant communities.
The selection of the geographic zone “zone builder” is intended to give a user the ability to create a new geographic zone through the user interface without the involved of the system developers. However this capability is not fully available in version 2.5.
Models
Forest models
The simulation of processes of succession, regeneration and disturbance of fire, insects and disease by individual plant communities enables one to address growth, yield, biodiversity and habitat suitability, environmental and external effects in both forest and grassland ecosystems. Climate change in version 2.5 is handled through a “regional climate” variable. Version 3.0 under development will incorporate downscaled climate model output and climate envelope modeling for individual species.
Social models
Optional fields for vegetation units can be used to identify areas of a landscape that have historic or cultural values. This enables the changes in vegetation conditions and the occurrence of disturbance processes that may affect these values to be tracked over time.
Decision Support
Definition of management interventions
Simulations can be made with or without fire suppression. The user interface screens allow a user to define various levels of fire suppression.
Vegetation management activities can be scheduled that can change the combination of species, size class and density of individual vegetation units. The user interface screens allow a user to modify the logic that identifies the changes made by a treatment and to define new treatments.
Treatments can be scheduled by the user for specific plant communities or the acres of desired treatments can be identified and the system will find units that meet the vegetation conditions that are necessary for specific treatments to be applied. Treatment reports will identify when future treatments are no longer feasible because of changing conditions due to stochastically simulated disturbance processes.
Typical temporal scale of application
The system has been used for the full range of temporal scales associated with land use planning. It has been used for individual project planning, identifying levels of management activities to achieve desired future conditions, designing and testing long term management scenarios, and defining levels of sustainable resources.
Types of decisions supported
SIMPPLLE can be used to support the following types of decisions:
- Management level
- strategic decisions
- administrative decisions
- Management function
- planning decisions
- coordination decisions
- decision making situation
- Bargaining / participative decision making
Decision-making processes and models
SIMPPLLE, whether it is used for the quantification of historic conditions to help design desired future conditions, an evaluation of current trends, or an evaluation of different proposed management scenarios, enables users to make many choices on system knowledge and simulation parameters. A set of single simulations is usually not sufficient for any analysis purpose. An iterative process employs the use of multiple simulations and is best handled as a collaborative effort. Managers, resource specialists and stakeholders must decide what sets or subsets of simulations provide the best integration of the most appropriate science and knowledge that will be of the greatest use in the decision-making process.
Output
Types of outputs
Output consists of the acres of individual vegetation characteristics of species, size class and density; acres of unique combinations of the vegetation attributes; acres of disturbance processes; and acres of management treatments. This output can be summarized by various levels of the landscapes simulated and by the individual plant communities. Output can be viewed within the user interface; in reports and interpretations, and in GIS displays. Two Excel spreadsheets with macros provide the means to summarize and plot system outputs. These outputs vary depending on whether a single simulation or multiple simulations are made. The multiple simulations provide the basis of quantifying a range of outcomes and the probability of vegetation conditions and processes occurring for a given scenario. An Excel spreadsheet with a statistical test, Multiple Response Permutation Procedures (Mielke 1967) can be used to evaluate differences between management scenarios.
Spatial analysis capabilities
All of the changes in vegetation attributes and the location of disturbance processes by simulation time steps can be joined to the original GIS feature classes. A broad range of spatial analysis software can be utilized.
Abilities to address interdisciplinary, multi-scaled, and political issues
The flexibility in building and testing management scenarios that can reflect differences in biophysical, economic and social issues does facilitate SIMPPLLE being used in collaborative planning efforts (Turner and others 2008).
System
System requirements
Two installation executables are available from the SIMPPLLE website for Windows operating systems: http://www.fs.fed.us/rm/missoula/4151/SIMPPLLE/. One executable is for Microsoft’s 64 bit operating system, Vista ,XP, and Windows 7 (simpplle-2.5.10-install-x64.msi). The second is for Microsoft’s XP 32 bit operating system (simpplle-2.5.10-install-x32.msi. The Java Runtime Environment is included in the installation. Executables for Mac OS X, AIX, Solaris, Linux, and HP-UX can be provided upon request.
There is no cost for the system.
SIMPPLLE makes an initial assignment of a computer system’s memory to the “Java Max Heap Size” when the installation is made. On 64 bit operating systems the default is set to 90 percent of the available memory. On 32 bit operating systems, the default is set 1100 MB. Development of the required input files requires ESRI’s ArcGIS 9.3.
Version 2.5 is available. Version 3.0 that offers increased capabilities for addressing climate change is under development.
Architecture and major DSS components
SIMPPLLE is implemented in Java for desktop computers with Windows operating systems. Executables for Mac OS X, AIX, Solaris, Linux, and HP-UX can be provided upon request. The approach to linking to other decision support components is to provide output files in text formatted files that can be incorporated into other systems. Work with the MAGIS optimization and scheduling model represents this type of linkage (Chew and others 2000, Jones and others 1999a, 1999b, 2003)
Usage
SIMPPLLE is being used by the US Department of Agriculture Forest Service, US Department Interior Bureau of Land Management and Geologic Survey, private contractors, Universities, and nonprofit environmental organizations.
SIMPPLLE has been used for Forest Service project planning (Slaughter and others 2004), resource management planning on both National Forests (USDA 2008) and Bureau of Land Management lands (USDI 2005), for ecosystem assessments on National Grasslands (Haufler and others 2009) and in State wildlife management plans (State of South Dakota 2006). SIMPPLLE was utilized by a group of timber companies and conservation organizations to prepare a land management approach for the Beaverhead-Deerlodge National Forest (Ecosystem Resource Group 2006).
Computational limitations
The only computational limitation is the amount of RAM required. The amount of RAM needed is a function of the number of units simulated; vegetation units, land units, aquatic units and roads and trails. The more units and the greater the number of time steps, the more RAM is required. Project level analyses with landscapes of 1000 of acres can be easily accomplished with 32 bit computers and 2 GBs of RAM. Applications that deal with millions of acres and vegetation units as small as 15 to 30 meters have required using 64 bit architecture computers with 64 operating systems such as Vista to utilize as much as 20 GBs of RAM.
User interface
The system has a well developed user interface that provides access to the system knowledge such as vegetation pathways, disturbance process probability, fire type and spread logic, and treatment logic. Various components of the system knowledge can be changed and saved in files that the user can reload. Interface screens provide access to view the simulation results as a summary for the entire landscape or by individual vegetation units.
Documentation and support
All available documentation, the current users’ guide and powerpoints displaying how the system has been used are available on the system’s web site. The system developer is available for assistance. Contact information is available on the web site. http://www.fs.fed.us/rm/missoula/4151/SIMPPLLE/.
Installation
Two executables for installing SIMPPLLE version 2.5 can be obtained from the SIMPPLLE website - http://www.fs.fed.us/rm/missoula/4151/SIMPPLLE/. One executable is for Microsoft’s 64 bit operating system, Vista ,XP, and Windows 7 (simpplle-2.5.10-install-x64.msi). The second is for Microsoft’s XP 32 bit operating system (simpplle-2.5.10-install-x32.msi. Executables for Mac OS X, AIX, Solaris, Linux, and HP-UX can be provided upon request. To install SIMPPLLE from the executable after downloading it to your computer, execute the appropriate *msi file, and follow the instructions, accepting the defaults recommended.
There is no cost for the system.
References
Cited references
Chew, J.D. 1995, Development of a system for simulating vegetative patterns and processes at landscape scales. Missoula: University of Montana;182 p. Ph.D. dissertation.
Chew, Jimmie D., 2003. Comparing Two Methods of Identifying Ecological Restoration Opportunities. In: Omi, Philip N.; Joyce, Linda A. technical editors. 2003. Fire, Fuel Treatments, and Ecological Restoration: Conference Proceedings; 2002 April 16-18 Fort Collins, CO. Proceedings RMRS-P-29. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 475 p.
Chew, Jimmie D.; Stalling, Christine; Moeller, Kirk. 2004. Integrating Knowledge for Simulating Vegetation Change at Landscape Scales. Western Journal of Applied Forestry 19(2) pp102-108.
Chew, J.; Jones, J.G.; Stalling, Christine; Sullivan, Janet; Slack, S. 2000. Combining Simulation and Optimization for Evaluating the Effectiveness of Fuel Treatments for Four Different Fuel Conditions at Landscape Scales. In Systems Analysis in Forest Resources, Proceedings of the Eight Symposium, Sept. 27-30, 2000, Snowmass Village, Colorado.
Ecosystem Resource Group, Partnership Strategy for the Beaverhead-Deerlodge National Forest. April 14, 2006 Available: http://www.ecosystemrg.com/beaverhead-deerlodge/press/Draft%20Partnership%20Strategy.pdf [last accessed January 2010]
Haufler, Jonathan, Carolyn Mehl, Amy Ganguli, and Scott Yeats. 2009 Ecological Assessment of Terrestrial Ecosystems, Thunder Basin Wyoming Available: http://www.emri.org/PDF%20Docs/Adobe%20files/TB_Doc_final_0908_web.pdf [last accessed January 2009]
Jones, J. Greg, Jimmie D. Chew, and Hans R. Zuuring. 1999A. Applying Simulation and Optimization to Plan Fuel Treatments at Landscape Scales. In Proceedings of the Symposium on Fire Economics, Planning, and Policy: Bottom Lines, April 5-9, 1999. San Diego, California, General Technical Report PSW-GTR-173
Jones, J.G.; Chew, J.D. 1999B. Applying simulation and optimization to evaluate the effectiveness of fuel treatments for different fuel conditions at landscape scales. In: Volume II, Proceedings of The Joint Fire Science Conference and Workshop, Crossing the Millennium: Integrating Spatial Technologies and Ecological Principles to a New Age in Fire Management; 1999 June 15-17; Boise, ID. p. 89-96.
Jones, Greg, Jim Chew, Robin Silverstein, Chris Stalling, Janet Sullivan, Judy Troutwine, David Weise, and Don Garwood. 2003. Spatial Analysis of Fuel Treatment Options for Chaparral on the Angeles National Forest. USDA Forest Service Gen. Tech. Rep PSW-GTR-xxx.
Mielke, P.W.; Berry, K.; Johnson, E.S. 1976. Multiple response permutation procedures for a priori classifications. Communications in Statistics—Theory and Methods. A5: 1409-1424.
Slaughter, Steve, Laura Ward, Jim Chew, and Rebecca McFarlan. 2003. A Collaborative Fire Hazard Reduction/Ecosystem Restoration Stewardship Project in a Montana Mixed Ponderosa Pine/Douglas-Fir/Western Larch Wildland Urban Interface. National Silviculture Proceedings, Granby, Colorado. September 7-11, 2003
State of South Dakota, Department of Game, Fish and Parks. South Dakota Comprehensive Wildlife Conservation Plan, May 2006 Available: http://www.emri.org/PDF%20Docs/Adobe%20files/TB_Doc_final_0908_web.pdf [last accessed January 2009]
Turner, C. E., W. H. Romme, J. Chew, M. E. Miller, G. Leavesley, L. Floyd-Hanna, G. San Miguel, N. S. Cobb, R. Zirbes, R. Viger, and K. E. Ironside. 2008. The FRAME Project—A Collaborative Modeling Approach to Natural Resource Management at Mesa Verde National Park, Colorado. Van Riper, C., III, and M. K. Sogge, editors. The Colorado Plateau III: Integrating Research and Resources Management for Effective Conservation, University of Arizona Press, Tucson, AZ. P 23-41
United States Department of Agriculture, Beaverhead-Deerlodge National Forest, Revised Forest Plan, Final Environmental Impact Statement. 2008 Available:http://www.fs.fed.us/r1/b-d/forest-plan/index-plan-document-maps.shtml [Last accessed January, 2009]
United States Department of Interior, Bureau of Land Management Proposed Dillon Resource Management Plan and Final Environmental Impact Statement 2005 Available: http://www.blm.gov/mt/st/en/fo/dillon_field_office/rmp/Final.html [Last accessed January 2009]
Weise, David R., Richard Kimberlin, Mike Arbaugh, Jim Chew, Greg Jones, Jim Merzenich, Marc Wiitala, Robert Keane, Mar Schaaf, and Jan Van Wagtendonk. 2000. Comparing Potential Fuel Treatment Trade-Off Models, Initial Results. In Systems Analysis in Forest Resources, Proceedings of the Eight Symposium, Sept. 27-30, 2000, Snowmass Village, Colorado.
