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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
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…
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
Modeling Goals
Woody Encroachment Air Quality
Rangeland Productivity Water Quality & Quantity
Modeling Approach
Environmental Effects
InteractingStressors
Biogeochemisty(PSM, Plant Soil Model)
Air Quality(BlueSkyRAINS)
Hydrology(GTHM, Georgia Tech
Hydrology Model)
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
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
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
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
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
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…
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
Photo credit: http://www.konza.ksu.edu/gallery/landscape3.JPG
Correlation of Soil & Geology
Hydrogeomorphic surfaces, Konza Prairie
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
Flint Hills Ecoregion, Kansas~10,000 mi2
Current Landcover of Kansas
TopographyVegetation
SoilClimate
GIS Data Layers
Land Use
30 x 30 mpixels
Ecosystem Simulator
Dynamic Vegetation & Soils Alternative Futures
TopographyVegetation
SoilClimate
GIS Data Layers
Land Use
30 x 30 mpixels
Current Landcover of Kansas
Stressor Scenarios
Ecosystem Simulator
Dynamic Vegetation & Soils Alternative Futures?
Current Landcover of Kansas
Simulated fuel loads provide link to
air quality models
• Data • Collection• Analysis• Management
• Collaboration
• Communication• Web• Metadata• Visualization• “jack of all data”
• Explorer
““GIS Support”GIS Support”
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
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
• Diffuse research team with variedbackgrounds
• They cannot see the landscape…
• How to show them in wayseveryone understands…• Maps• Videos• 3D• KML
CommunicationCommunication
• 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/
Phase I: Konza Prairie calibration / validation
Phase II:Flint Hills extrapolation
Konza Prairie
Work Plan
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
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
Kings Creek Watershed, 11 kmKings Creek Watershed, 11 km22