ENVISION y el modelamiento del paisaje ingles

Document Sample
ENVISION y el modelamiento del paisaje ingles Powered By Docstoc
					www.2010colombia.com
  An Alternative Futures
Approach to Understanding
 Landscape Dynamics and
         Services

              Kellie Vache, PhD.
      Biological & Ecological Engineering
            Oregon State University
             Today’s Discussion
   Overview of alternative futures approach to
    socio-ecological modeling

   Description of one approach using Envision

   Example applications
       Andrews Forest

       Puget Sound
Socio-Ecological Modeling
             To Start - A Definition of
                  Biocomplexity
   Term used to describe complex
    structures, interactions, adaptive
    capabilities and dynamics

   diverse set of biological and
    ecological systems

   multiple spatial and temporal
    scales
   Many Approaches!!! Some focusing on capturing richness of
    system dynamics, some on complex adaptive systems approaches

   Challenge – How to make these operational?
       Alternative Futures Projects
   Examine multiple scenarios of trends and assumptions
    about future conditions, generally using one or more
    models of change,
   Assist in incorporating stakeholder interactions to
    define goals, constraints, trajectories, drivers, outcomes
   Allow visualization of the results
   Ultimately are intended to assist in improving land
    management decision-making
         Software-based Alternative
                  Futures
   A mechanism to include biocomplexity in alternative
    Futures – to do so requires:
       Easy to use interface

       Present results in a format useful to end users
       Spatially and temporally explicit

       Extensible to incorporate evolving “best” science

       Internal feedback
                     Envision Components
                                                 Detailed            Aggregate
Site Selection and          Alternative        Evaluation of        Evaluation of
Characterization         Scenario Selection     Individual          Management
                                                 Services           Alternatives



                         Analysis Framework and Architecture


 Datasets                Alternatives           Landscape         Visualizations
                                               Production
                                               Evaluators
                      Goals       Policies
                                                  Water Quality

                                                     Carbon
                                                      …
                     Stressors     Drivers
                                                  Other ESE’s
    Approach: Multi-Agent Modeling

   Model the behavior and actions agents (actors)
   represents land management decisions of actors
    with authority over parcels of land
   Actor decisions implemented through policies that
    guide & constrain potential actions
   Ecosystem Services (e.g. forest succession, wetland
    function) can be simultaneously modeled
   Envision – Conceptual Structure
                  Multiagent                                          Ecosystem Service Models
               Decision-making                  Landscape
                                                Feedbacks            Generating Landscape Metrics Reflecting
Select policies and generate
                                                                             Landscape Productions
land management decision
affecting landscape pattern
               Actors
     Decision-makers managing the
     landscape by selecting policies
      responsive to their objectives
                                                                                          Landscape
                                                                                            Spatial Container in
                                                                                               which landscape
                                                                                                changes, ES
                                                                                                  Metrics are
           Scenario                                                                                 depicted
           Definition



                  Policies
   Fundamental Descriptors of constraints and                Autonomous Change Processes
     actions defining land use management
                decisionmaking                              Models of Non-anthropogenic Landscape Change
      ENVISION
– Triad of Relationships


                 Goals
            •Economic Services
            •Ecosystem Services
            •Socio-cultural Services
    Provide a common frame of reference
for actors, policies and landscape productions

             Landscapes
                Service Metrics
                       Policy Definition
Landscape policies are
 decisions or plans of
 action for
 accomplishing
 desired outcomes.
from:

   Lackey, R.T. 2006. Axioms of
    ecological policy. Fisheries. 31(6): 286-
    290   .
              Policies in ENVISION
   Policies are a decision or plan of action for accomplishing a
    desired outcome; they are a fundamental unit of computation in
    Envision
   Describe actions available to actors
   Primary Characteristics:
       Applicable Site Attributes (Spatial Query)
       Effectiveness of the Policy at addressing goals
       Outcomes (possible multiple) associated with the selection and
        application of the Policy

   Example: [Purchase conservations easement to allow
    revegetation of degraded riparian areas] in [areas with no built
    structures and high channel migration capacity] when [native fish
    habitat becomes scarce]
            Models in ENVISION
   Models are “plug-ins” of two types:
    1)   Autonomous Processes: Represent processes
         causing landscape changes independent of human
         decision-making – e.g. climate change,
         vegetative succession, fire, flooding, ???
    2)   Evaluative Models – Generate production statistics
         and report back how well the landscape is doing a
         producing metrics of interest – e.g. carbon
         sequestration, habitat production, land
         availability, ???
   Some Examples
From Northwestern US
    Some Examples
 From Northwestern US

Puget Sound




Andrews
Forest
         Example 1. Andrews Forest
                                      MACK (580 ha)



                WS08 (21 ha)                                    WS03 (101 ha)
                 HI15
                                                                WS02 (60 ha)




           HJ Andrews
         (LOOK – 6200 ha)                                       PRIMET

                                                       WS10
                                                      (10 ha)


                                                                         WS09
                                                                         (9 ha)
Photographed by Al Levno Date: 7/91
          Envision Andrews Forest



195 km2

25 year
simulation

Population
growth:
~10,000
~18,500
  Envision Andrews Forest -
          Scenarios
Scenario Name            Key Scenario Features


Conservation – Current   Discourage low-density development,
Climate                  Assume climate is similar to current

Conservation – Warmer    Discourage low-density development,
Climate                  Hotter, drier summers
                         rainier winters.

Development – Current    Allow low density development
Climate                  Assume climate is similar to current.

Development – Warmer     Allow low density development
Climate                  Hotter, drier summers
                         Rainier winters
      Envision Andrews Forest
   Data Sources
                                    Evaluative Models
   Landscape Data
                                     Mean Age at Harvest
    Policy Set(s)

                                     Carbon Sequestration




                        ENVISION
  Agent Descriptors
                                   Forest Products Extraction
Autonomous Process
      Models                          Harvested Acreage

  Rural Residential
     Expansion
                                       Fish Habitat (IBI)
Vegetative Succession

                                   Resource Lands Protection
   Climate Change
         Landcover Over 25 Yrs
Conservation Scenario   Development Scenario
Scenario Results – Forest Carbon
Scenario Results – Forest Product
           Extraction
Scenario Results – Fish IBI
         Example 2. Puget Sound



42,800 km2

60 year simulation

Population growth:
~4.2 million to
~7.0 million in 2060
Envision Puget Sound- Scenarios
               Three Different Scenarios
  Scenario Name          Key Scenario Features


  Status Quo             continue current trends


  Managed Growth         conserving/restoring habitats,
                         protecting resource lands,
                         denser development pattern near urban areas


  Unconstrained Growth   allow lower density patterns
                         less habitat protection
                         less resource land protection
          Envision Puget Sound
    Data Sources
                                       Evaluative Models
    Landscape Data
                                        Impervious Surfaces
     Policy Set(s)
                                       Water Quality/Loading




                          ENVISION
   Agent Descriptors                       (SPARROW)

                                         Nearshore Habitat
Autonomous Process                   (Controlling Factors Model)
      Models
                                       INVEST Tier 1 Carbon
Rural/Urban Development

     Expansion of                    Resource Lands Protection
Nearshore Modifications

   Population Growth                  Residential Land Supply
Puget Sound
Seattle Area
Seattle
Area




          Mt
          Rainier
                 Lessons Learned
   Alternative future assessments are fundamentally place-based
    and client-dependent: Each application is different.

   Commonalities do exist and should be exploited within an
    extensible, adaptable DSS framework

   Interactions between population growth, landscape
    development and ecosystem services drive socio-ecological
    systems, and need to be accommodated

   Engagement with stakeholders is critical to define decision
    processes, desired outcomes endpoints
     Thanks to Dr. John Bolte

and the Envision Development Team
      Muchas Gracias!

        more info at:
http://envision.bioe.orst.edu
www.2010colombia.com

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:7
posted:10/4/2012
language:English
pages:37