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Bob McKane, USEPA Western Ecology Division
Marc Stieglitz and Feifei Pan, Georgia Tech
Adam Skibbe, Kansas State University
Kansas State UniversitySeptember 25, 2008
A Multi-Model Ecosystem Simulator for Predicting the Effects of Multiple Stressors on
Great Plains Ecosystems
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ORD Corvallis – Dr. Bob McKane Region 7 – Brenda Groskinsky and others
A Collaborative EffortA Collaborative Effort
Dr. Marc SteiglitzDr. Feifei Pan
Dr. Ed RastetterBonnie Kwiatkowski
Adam SkibbeDr. John Blair
Dr. Loretta JohnsonMany others…
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Agenda
1. Seminar (45 minutes)• Project overview – McKane
• GIS database – Skibbe
• Model description and results to date – Stieglitz
2. Open discussion of collaborative opportunities (45 minutes…)• Calibration & analysis of spatial and temporal controls on:
• Plant biomass & NPP• Soil C & N dynamics• Fuel load dynamics • Hillslope hydrology & biogeochemistry• Stream water quality & quantity
• Linkage of ecohydrology and air quality modeling• Air quality models (BlueSkyRAINS, others?)• Spatial domain for regional assessments• Scenarios: burning strategies, land use, climate • Ecological and air quality endpoints• Collaboration among KSU, EPA, GT researchers
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Modeling Goals
Woody Encroachment Air Quality
Rangeland Productivity Water Quality & Quantity
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Modeling Approach
Environmental Effects
InteractingStressors
Biogeochemisty(PSM, Plant Soil Model)
Air Quality(BlueSkyRAINS)
Hydrology(GTHM, Georgia Tech
Hydrology Model)
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Stressors
Vegetation change
Climate change
Management• Fire• Grazing• Pesticides• Fertilizers
Terrestrial Effects
Vegetation change
Plant productivity
Carbon storage
Fuel loads (input for fire & air quality models)
Aquatic Effects Water quality &
quantity
Biogeochemisty(PSM, Plant Soil Model)
Air Quality(BlueSkyRAINS)
Hydrology(GTHM, Georgia Tech
Hydrology Model)
Modeling Approach
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Stressors
Vegetation change
Climate change
Management• Fire• Grazing• Pesticides• Fertilizers
Terrestrial Effects
Vegetation change
Plant productivity
Carbon storage
Fuel loads (input for fire & air quality models)
Aquatic Effects Water quality &
quantity
Biogeochemisty(PSM, Plant Soil Model)
Air Quality(BlueSkyRAINS)
Hydrology(GTHM, Georgia Tech
Hydrology Model)
Modeling Approach
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Fire effects modeling: a collaborative effort involving EPA (ORD & Region 7), KSU, Georgia Tech
http://www.emporia.edu/earthsci/student/lee1/gis.html
Fires (red) andsmoke plume (white)
Flint Hills Ecoregion
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Mean Annual Plant Productivity
Total Grass Forbs0
100
200
300
400
500
annually burned
unburned
*
*
*
Abo
vegr
ound
Pro
duct
ion
(g ·
m-2
· yr
-1)
Effect of Fire on Biomass Production
Slide courtesy of John Blair
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Rangeland Fires:What are the ecological and air quality tradeoffs?
remove litter… and increase plant productivity & diversity…
Fires prevent woody invasion…
but, are a source of particulates and ozone
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Need to simulate how water controls ecosystem structure and function across multiple scales,
Sala et al. 1988Sala et al. 1988
R2 = 0.90
ANNUAL PRECIPITATION (mm)
Central Great Plains
PR
OD
UC
TIO
N (
g m
-2 y
r-1)
Ojima and Lackett 2002Ojima and Lackett 2002
Precip (in.)
from region…
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Heisler & Knapp 2008Heisler & Knapp 2008
Konza Prairie
PR
OD
UC
TIO
N (
g m
-2 y
r-1)
snobear.colorado.edu/IntroHydro/hydro.gif
…to hillslopes
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Photo credit: http://www.konza.ksu.edu/gallery/landscape3.JPG
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Correlation of Soil & Geology
Hydrogeomorphic surfaces, Konza Prairie
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Linked H2O, Carbon & Nitrogen Cycles
Low productivity sites
High productivity sites
Low productivity sites
High productivity sites
Daily outputs of water & nutrients to streams
30 x 30 m pixels
With adequate spatial data, GTHM-PSM simulates the cycling & transport of water & nutrients within watersheds
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Flint Hills Ecoregion, Kansas~10,000 mi2
Current Landcover of Kansas
TopographyVegetation
SoilClimate
GIS Data Layers
Land Use
30 x 30 mpixels
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Ecosystem Simulator
Dynamic Vegetation & Soils Alternative Futures
TopographyVegetation
SoilClimate
GIS Data Layers
Land Use
30 x 30 mpixels
Current Landcover of Kansas
Stressor Scenarios
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Ecosystem Simulator
Dynamic Vegetation & Soils Alternative Futures?
Current Landcover of Kansas
Simulated fuel loads provide link to
air quality models
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• Data • Collection• Analysis• Management
• Collaboration
• Communication• Web• Metadata• Visualization• “jack of all data”
• Explorer
““GIS Support”GIS Support”
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GIS Coverages (30 x 30 m)GIS Coverages (30 x 30 m)
• Elevation• Slope, aspect, etc.
• Climate• Precipitation• Temperature• Solar radiation• Relative humidity
• Land Use / Land Cover• Vegetation type• Grazing, cropland, etc.
• Stream flow
• Stream chemistry
• Soils• Horizons• Texture, bulk density• Hydraulic conductivity• Total C, N, P
• Geology• Bedrock• Impervious surfaces• Permeability
• Boundaries• Watersheds• Political
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Data IssuesData Issues
• Identifying gaps• Finding workarounds
• Soils example• All variables not part of
SSURGO• Append SCD pedon
data• Surrogates for missing
soil types
• Regional vs. local climate• Worldclim vs. weather stations
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• Diffuse research team with variedbackgrounds
• They cannot see the landscape…
• How to show them in wayseveryone understands…• Maps• Videos• 3D• KML
CommunicationCommunication
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• Web-site to distributeall information related to project
• Archive of all maps, data, metadata, presentations, etc.
• Always available for access by collaborators
• Hosted .KML files
Knowledge DistributionKnowledge Distributionhttp://epa.adamskibbe.com/
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Phase I: Konza Prairie calibration / validation
Phase II:Flint Hills extrapolation
Konza Prairie
Work Plan
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Incorporating Ecological Modeling in Incorporating Ecological Modeling in a Decision-Making Frameworka Decision-Making Framework (ENVISION) (ENVISION)
John Bolte, Oregon State University
Landscape Evaluators:
Generate landscape metrics reflecting scarcity
Landscape:Spatial Domain in which land use changes are depicted
Autonomous Change Processes:
Models of nonhuman change
Actions
Policies:Constraints and actions
defining land use management
decisionmaking
PolicySelection
Actors:Decisionmakers making landscape change by selecting
policies responsive to their objectives
Landscape Feedback
Evoland – General Structure
(ES Maps)
Update
Input
Landscape GIS:Maps of current
land use, vegetation, soils,
climateetc.
Human Actions
Policy Selection
Landscape Feedback
Modified from John Bolte, Oregon State University
Changes in Ecological Processes
Ecological Models (GTHM-
PSM)
LandscapeEvaluators:
Generate landscape metrics to assess
outcomes
Actors:Land managers
implement policies responsive to their
objectives
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2. Open discussion of collaborative opportunities
• Calibration & analysis of spatial and temporal controls on:
• Plant biomass & NPP
• Soil C & N dynamics
• Fuel load dynamics
• Hillslope hydrology & biogeochemistry
• Stream water quality & quantity
• Linkage of ecohydrology and air quality modeling
• Air quality models (BlueSkyRAINS, others?)
• Spatial domain for regional assessments
• Scenarios: burning strategies, land use, climate
• Ecological and air quality endpoints
• Collaboration among KSU, EPA, GT researchers
Agenda
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Kings Creek Watershed, 11 kmKings Creek Watershed, 11 km22