Difference between revisions of "MAPSS"

From COST Action FP0804: FORSYS
Jump to: navigation, search

Warning: require(): Unable to allocate memory for pool. in /data/home/fp0804/www/wiki/includes/AutoLoader.php on line 1191
(Spatial analysis capabilities)
(Abilities to address interdisciplinary, multi-scaled, and political issues)
Line 99: Line 99:
  
 
=== Abilities to address interdisciplinary, multi-scaled, and political issues  ===
 
=== 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
+
MAPSS cannot be used of itself to evaluate interactions between different basic information types (biophysical, economic, social). MAPSS will provide information for the biophysical aspects of questions involving ecosystems and climate change; and it can be used as one source of information for other tools that can do this kind of integration.
  
 
== System ==
 
== System ==

Revision as of 23:49, 1 September 2010

General System description

System name: Map Atmosphere Plant Soil System

Acronym: MAPSS

Brief overview

MAPSS (Mapped Atmosphere-Plant-Soil System) is a landscape- to global-scale vegetation distribution model that was developed to simulate the potential biosphere impacts and biosphere-atmosphere feedbacks from climatic change.


Scope of the system

System origin

MAPSS was originally developed in the early 1990's by Ron Neilson at the Environmental Protection Agency laboratory in Corvallis, Oregon; and he subsequently refined it after moving to the U.S. Forest Service Pacific Northwest Research Laboratory. It was developed as a response to the need for a process-based capability to simulate the potential changes in the distribution of the world's major biotic regions under climate change. The MAPSS model was constructed under a philosophy of ecosystem constraints and it combines a process-based water balance model with a physiologically conceived rule-based model to simulate both thermal and water balance constraints on vegetation life-form (e.g., tree. shrub, or grass: evergreen or deciduous: broadleaf or needleleaf) and biome physiognomy (e.g., forest. savanna, or shrub-steppe). The fundamental assumption under which MAPSS calculates water-limited vegetation type and density is that the vegetation leaf area will find a maximum that just utilizes the available soil water. Fire has been incorporated in the MAPSS model as a disturbance factor that can alter the equilibrium state of the ecosystem. Grass-tree competition has also been incorporated in the model.

MAPSS has been used as a research tool and has not been developed as a commercial product. MAPSS was used in the second assessment of the the Intergovernmental Panel on Climate Change (IPCC) for regional and global assessments of climate change impacts on vegetation, and was also included in the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP).

Support for specific issues

MAPSS has been used for predictions of biome redistribution, habitat loss and migration rates, changes in forest productivity, changes in surface runoff, and changes in forest stress areas under different scenarios of climate change.

Support for specific thematic areas of a problem type

  • Vegetation Distribution
  • Biodiversity
  • Conservation
  • Volatile Organic Compound Emissions
  • Climate Change
  • Site Water Balance
  • Carbon Sequestration

Capability to support decision making phases

The MAPSS model potentially can contribute to a variety of different topics (eg. vegetation distributions, wildlife conservation, water availability, carbon managemente). The contribution of the MAPSS model to decision making phases depends in part on which topic is under consideration.

  • Intelligence. The following are examples of problem identification questions that the MAPSS model can be used to answer: How likely is it that the vegetation type that currently is at my site will still be viable in the future under climate change? Can I expect drought-induced die-offs? Will my current set of nature preserves still be able to provide habitat for an endangered species? Will more or less water be available for stream-flows under future climates? Will US forests still prove to be carbon sinks 100 years from now?
  • Design.
  • Choice.
  • Monitor.

Related systems

The MC1 dynamic vegetation model is an off-shoot of the MAPSS biogeography model. It is a linking of a MAPSS-like biogeography model with the CENTURY biogeochemistry model and with a fire model. This means that it also has the ability to simulate vegetation type changes under future climates, hydrology, as well as carbon storage dynamics, and fire.

Data and data models

Typical spatial extent of application

MAPSS has been run: 1) Globally at a half degree grid, 2) Over the conterminous United States at a half degree grid, and 3) Over the conterminous USA at a 10 kilometer grid.

Forest data input

For input MAPSS requires: 12-month average climate data (precipitation, temperature, wind, vapor pressure). Soil data for 3 depths (%sand, %clay, %rockiness).

As output MAPSS produces maps of vegetation type, leaf area index, and surface runoff (more to be listed).

Type of information input from user (via GUI)

NA

Models

Forest models

MAPSS is a general ecosystem model which includes 11 forest classes, 9 tree savanna classes, as well as shrubland and grassland classes.

Social models

NA

Decision Support

Definition of management interventions

As described in the Decision Making Phases section above. MAPSS mostly provides information for the intelligence phase of decision making.

Typical temporal scale of application

MAPSS is an equilibrium model, which means that it simulates the long term ecosystem response to long term average climate.

Types of decisions supported

MAPSS is probably most appropriately used for long term strategic decision-making.

Decision-making processes and models

MAPSS is a deterministic simulation model. No randon processes are included.

Output

Types of outputs

MAPSS produces average annual maps of leaf area, vegetation type, broad vegetation classes (deciduous vs evergreen, broadleaf vs needle leaf), fire occurence, evaporative demand, snowpack, runoff, as well as other output variables.

MAPSS produces average monthly maps of leaf area, evaporative demand, runoff, snow pack, as well as other output variables.

Spatial analysis capabilities

MAPSS outputs are in Network Common Data Form (NetCDF). NetCDF is a set of software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. It is frequently used by climate modelers. The data is gridded and can be loaded into GIS software for overlays and other analyses, but the data needs to be converted to a format the GIS can read. C, Fortran, C++, and Java all have software libraries for working with NetCDF data, and other interfaces to NetCDF data can be found in MATLAB, Objective-C, Perl, Python, R, Ruby, and Tcl/Tk. More information on NetCDF and the tools that can be used to read it can be found at https://www.unidata.ucar.edu/software/netcdf/.

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

MAPSS cannot be used of itself to evaluate interactions between different basic information types (biophysical, economic, social). MAPSS will provide information for the biophysical aspects of questions involving ecosystems and climate change; and it can be used as one source of information for other tools that can do this kind of integration.

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