Difference between revisions of "SIMPPLLE"

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=== Decision-making processes and models ===
 
=== Decision-making processes and models ===
*Logic modeling
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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 single set of 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.
*Operations research modeling
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**Direct approaches
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**Heuristic manipulation of simulation models
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*Business modeling
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*Simulation (with and without stochasticity)
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*Multiple criteria/ranking
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*Other
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== Output ==
 
== Output ==

Revision as of 00:11, 2 February 2010

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.

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

  • 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 single set of 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

Types of outputs produced (tables, maps, 3-D visualizations, pre-programmed summaries, etc)

Spatial analysis capabilities

  • integrated capabilities
  • facilitates links to GIS (wizards, etc.)
  • provides standard data import/export formats
  • allows spatial analysis (e.g. topology overlays (e.g. multi layering of different maps, selection of objects based on selection criteria, aggregation by attributes (e.g. areas of similar characteristics), Linking by logical means, Statistics by area, analysis with digital terrain model)

Abilities to address interdisciplinary, multi-scaled, and political issues

Evaluate interactions between different basic information types (biophysical, economic, social). Produce coordinated results for decision makers operating at different spatial scales facilitate social negotiation and learning

System

System requirements

  • Operating Systems: (Windows, Macintosh, Linux/UNIX, Web-based, Others)
  • Other software needed (GIS, MIP packages, etc...)
  • Development status

Architecture and major DSS components

Describe the basic architecture of the system in software and hardware. Desktop client-server, web based, as well as the integration with available systems. Basic data flow, focusing on retrieval of required input and propagation and implementations of decisions. Mention its modular and scalability capabilities.

Usage

Describe the level of use: Research level use, Industry use, Government use

Computational limitations

Describe the system limitations: e.g. number of management units, number of vehicles, time horizon

User interface

Describe the quality of user interface and the Prerequisite knowledge for using the system

Documentation and support

Describe the connection to Help-system and possibilities for assistance, as well as the required training and user support levels

Installation

  • Prerequisite knowledge: Level of effort to become functional
  • Cost: (purchase price, development costs, demonstrated return on investment, cost of use, training costs, licence and maintenance costs)
  • Demo: allows the download/utilization of a trial version. If yes, where is it available and what are the trial conditions.

References

Cited references


External resources