Regional Consequences of Climate and Land Use Change on Ecosystem Services in Pennsylvania
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Regional Consequences of Climate and Land Use Change on Ecosystem Services in Pennsylvania
Benjamin Felzer
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Outline of Talk
• Introduction: Environmental Stresses and Ecosystem Services• Description of Tools: Models and Data• Model Validation• Role of climate and land use change in PA• Future climate extremes and flooding in the Lehigh Valley• Historical Multiple Factorial Effects in the Mid-Atlantic
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Environmental Stresses
• Rising atmospheric CO2
• Climate variability and change• Land use cover and change• Nitrogen deposition and fertilizer• Ozone near surface
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CO2 and Climate
(Raich et al., 1991)
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Forest RegrowthPoplar, WI
Pine, FL
(Pan et al., 2002)
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Nitrogen and Ozone
(Magnani et al., 2007) (Lombardozzi et al., 2012)
Tulip Poplar
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Carbon Accounting
Net Ecosystem Productivity (NEP) = NPP – rh
where NPP = Net Primary Productivity
rh = heterotrophic respiration
Net Carbon Exchange (NCE) = NEP – ec – ep
where ec = carbon lost due to conversion
ep = carbon lost due to decomposition of products
Positive NEP, NCE means land is carbon sink
Generally neutral (Odum, 1969) or small sink (Luyssaert et al., 2008) or small source (Law et al. 2004) for mature forest.
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Description of Tools: Models and Data
• Biogeochemical Model (TEM-Hydro)• Climate Data• Land Cover Data
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Vegetation
Carbon
Nitrogen
GPP Rg Rm
CarbonNitrogenSoil
LTRC
LTRNN uptake
Rh
Carbon
Atmosphere
Water
Water
Precip.
Soil Evap.
Transp.
Runoff
TEM-Hydro Model
(Felzer et al, 2009, 2011)
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Disturbance
• Cohort Approach• Slash: input to soils• Residue: to atmosphere• Product Pools (1, 10, 100 years): decomposition rates
Open Nitrogen
• Inputs: N fixation, N deposition, N fertilizer• Outputs: Leaching of Dissolved Organic
Nitrogen (DON) and Dissolved Inorganic Nitrogen
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Inputs and Calibration
• Climate (Cloud or Radiation, Temperature, Precipitation, ozone, carbon dioxide (global annual value))
• Vegetation Cohorts• Soil and Elevation (static)• Calibration of carbon and nitrogen parameters to target values
of carbon and nitrogen stocks and fluxes
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Climate Data
Dataset Spatial Res.
Temporal Res.
Time Period
Scenario
CRU 0.5o Monthly 1901-2009 historical
PRISM 1/24o Monthly 1890-2013 historical
CMIP3(Maurer)
1/8o Monthly 1950-2099 A2, A1B, B1
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Hurtt Dataset
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Model Validation
• Streamflow at Watersheds• Eddy Covariance (Ameriflux) NEE (Net Ecosystem
Exchange) and ET (Evapotranspiration)• Gridded Datasets combining Eddy Covariance and Remote
Sensing (EC-MOD, Fluxnet-MTE)
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(Felzer et al., 2009)
Eastern U.S. Forests
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(a) (b)
(c) (d)
Willow Creek, WI
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Felzer and Sahagian, Climate Research, in review
Validation: without land use disturbance
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Trend Comparison: Evapotransporation
Accounting for significant, 72% grids Not accounting for significant, 60% grids
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Felzer and Sahagian, Climate Research, in review
Seasonal Validation
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(Felzer et al., 2012)
PA Study
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Note: Future is A2
Forest Urban Crops Pasturerunoff
(kg(H2O)/m2/yr)303 555 440 413
DIN Leach
(gN/m2/yr)383 492 4060 941
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Rodale-based Dairy Farm Parameterization
(Jiang and Zhang, in prep.)
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25
GPP: 1020 g C yr-1 m-2 NPP: 466 g C yr-1 m-2
Ra: 554 g C yr-1 m-2 Rh: 1685 g C yr-1 m-2
Available N: 3.3 g N m-2 Soil C: 2559 g C m-2 Soil N: 360 g N m-2
Vegetation C: 922 g C m-2
Vegetation N: 57.8 g N m-2
Measured Rodale dairy pasture targeting values
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Historical NCDC storm statistic
Future bias-corrected NCAR CESM storm statistic
HEC-HMS peak stream discharge
Monocacy Creek
HEC-RASFlood Profiles
Flooding in Lehigh Valley
(Felzer, Schneck, Withers, and Holland in preparation)
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24 Hour Storm Event (inches)
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(Dangal et al., 2013)
Effects of Human Disturbance on Carbon: Eastern U.S.
1700 1750 1800 1850 1900 1950 2000-30000
-25000
-20000
-15000
-10000
-5000
0
5000
10000
year
Cum
ulati
ve N
CE (T
g C)
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000-4000
-2000
0
2000
4000
6000
8000
10000
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(Table from Dangal et al., 2013)
Net Ecosystem Productivity (NEP) Validation
Site ID EC NEE Biometric
DIST NEP UND NEP
% diff.
RMSE NC
DUK 489 NA 321 140 -34 54 -0.67WLK 750 252 360 180 -52 62 0.50WIL 360 106 150 50 -58 59 0.60UMBS 170 73 189 80 11 61 0.51
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Multifactorial Experimental Design for MidAtlantic
LULC CO2 Climate O3 Ndep
S0
S1 X
S2 X X
S3 X X X
S4 X X X X
S5 X X X X X
S1-S0 = LULCS2-S1 = CO2
S3-S2 = ClimateS4-S3 = O3
S5-S4 = Ndep
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Net Carbon Exchange from 1700
year
1700 1750 1800 1850 1900 1950 2000
Cum
ula
tive
NC
E (
gC
/m2
)
-14000
-12000
-10000
-8000
-6000
-4000
-2000
0
2000
4000
LULC CO2 Climate O3 NDep year vs LULC
Net Carbon Exchange from 1900
year
1900 1920 1940 1960 1980 2000
Cum
ula
tive
NC
E (
gC
/m2
)
-2000
-1000
0
1000
2000
3000
LULC CO2 Climate O3 Ndep year vs Total
Cumulative NCE from1929
year
1940 1960 1980 2000
Cum
ula
tive
NC
E (
gC
/m2
)
-1000
0
1000
2000
3000
4000
LULC CO2 Climate O3 Ndep year vs Total
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Photosynthesis Transpiration
ElevatedCO2
Nitrogenlimitation
Ozoneexposure
Runoff
Feedbacks of Carbon on Water
gc = gmin LAI + ga (GPP) (RH) / [CO2]Ball-Berry Model:
positive coupling: amplifying
negative coupling: dampening
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Key Results• Increased urbanization and climate change in PA results in more
runoff while increased urbanization results in more DIN leaching• Useful to use future storm scenarios to determine enhanced
flooding in local watersheds• Comparing models to eddy covariance data requires accounting
for forest disturbance• Carbon storage has decreased due to LULC, climate, and ozone,
but increased due to CO2 and Ndep in the Mid-Atlantic since 1700
• Runoff has increased due to LULC and slightly due to CO2 and ozone
• Model underestimating carbon sink?
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Thanks!
M.S. Students: Shree Dangal
Ph.D. Students: Mingkai Jiang, Jien Zhang, Travis Andrews
Postdoc: Eungul Lee
Research Associate: Zavareh Kothavala
Undergraduates: Lauren Schneck, Cathy Withers, David Kolvek, Trista Barthol, Peter Phelps, Jonathan Chang
Co-Authors: T. Cronin, J. Melillo, D. Kicklighter, A. Schlosser, D. Sahagian, M. Hurteau
Assistance: B. Hargreaves, D. Morris, D. Sahagian
Funding Agencies: MIT, Westwind Foundation, Lehigh University, DOE (Basic Research and Modeling to Support Integrated Assessment), NSF (Macrosystems Biology).
Computational Time: NSF Yellowstone supercluster at Computational and Information Systems Laboratory (CISL)
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EXTRA
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(Felzer et al., 2012)
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SOC
SOC
SON
DOC DON
VEGC
AvailN
Rh
DOCprod DONprod
LeachDOC LeachDON LeachDIN
VegNup
LtrC VEGNLtrN
NetNmin
Soil Organic Matter
Ndep
Fert.
GPP Ra
SymbioticNfix
NonSymbioticNfix
(Felzer et al., 2012)
TEM-Hydro Reduced Form Open Nitrogen
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TEM Inputs
Transient Datasets• Cloud or Radiation, Temperature, Precipitation, ozone,
carbon dioxide (global annual value)• Vegetation cohorts
Static Datasets• soil texture, elevation
Parameter Files• soil, rooting depth, vegetation, vegetation mosaics, leaf,
microbe, agriculture, calibrated biome files
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TEM Calibration
Stocks• Vegetation Carbon, Vegetation Nitrogen, Soil Organic Carbon,
Soil Organic Nitrogen, Soil Inorganic Nitrogen
Fluxes• NPP, N-saturated NPP, GPP, Plant Nitrogen Uptake
Parameters• CMAX (photosynthesis), NMAX (N uptake), KD (heterotrophic
respiration), NUP (Net N mineralization), KR (autotrophic respiration)
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Climate Data
Historical 20th century• CRU (Climatic Research Unit) 0.5o, monthly,1901-2009• PRISM (Parameter-elevation Regressions on Independent
Slopes) 1/24o, monthly, 1890-2013
Future IPCC Scenarios• AR4: A2, (A1B, B1)• Downscaled/Bias-Corrected Surface Temperature and
Precipitation CMIP3 (Maurer): 1/8o, monthly, 1950-2099• Delta/Ratio downscaling of Vapor Pressure and Net Irradiance
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Carbon
Vegetation
Labile Pool
GPP Rg Rm
Soil
LTRC
Rh
Atmosphere
Allocation
Leaf
Active Stem
Inactive StemRoot
Senescence
(Felzer et al, 2009, 2011)
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Nitrogen
Vegetation
Labile Pool
VNUP
Soil
LTRN
Allocation
Leaf
Active Stem
Inactive StemRoot
Senescence
OrganicMineralImmobilization
Mineralization
Nresorb
(Felzer et al, 2009, 2011)
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Vegetation
Atmosphere
Precip.
Soil Evap.
Transp.
Runoff
Water
WiltingPoint
Field Capacity
Soil: Bucket Model
stomatalresistance
leaf-to-canopyaerodynamic resistance
soil internal resistance
soil-to-canopyaerodynamicresistance
canopy-to-screen heightaerodynamic resistance
Soil Evap.
Transp.
Shuttleworth-Wallace method
Screen height, known T, VPRCanopy airspace, in contact with leaves and soilSurface of “big leaf”
Soil Surface
(Felzer et al, 2009, 2011)