Objectives
- Compare effects of climate and land use on fluxes within the same climate zone and among the mesic and semi-arid regions
- Combine multi-scale observations (satellite, flux sites, inventories, tall towers) in neural networks to determine how current climate, land-use and land cover influence processes
- Modify CLM to reduce uncertainties in simulated effects of land use and land cover on biogeochemical and biophysical processes (crops, poplar)
- Investigate future climate variability, and effects of changes in land use and land cover on terrestrial processes
2. Carbon cycle dynamics within Oregon’s urban-suburban-forested-
agricultural landscapes Part 1: Current Land-Use/Land-Cover
PI: B.E. Law, CoIs: C. Still, T. Hilker, A. Schmidt
Objective
• Multi-scale observations and
neural networks to determine
how current climate and
LC/LUC influence ecosystem
processes
Approach
• Establish flux sites in major
crops and poplar
• Compare seasonal and annual
fluxes among cover types
Project # OREZFES-867
5. Annual Carbon Budget for Oregon
Initial Estimates
Source
Sector
Fossil Fuels Forest NECB Crop NECB
TgCO2yr-1
-30
-20
-10
0
10
20
30
40
Land-based carbon sink
is ~30% of the equivalent
of Oregon’s FFE
(Inventories, Flux sites, Ancillary Plots, Satellite Land Cover & Fire Emissions)
6. Carbon cycle dynamics within Oregon’s urban-suburban-forested-
agricultural landscapes: Part 2 Future Climate & Land-Use/Land-Cover
PI: B.E. Law, CoIs: C. Still, T. Hilker, A. Schmidt (Oregon State University), Collaborator: T. Hudiburg (UI)
Objective
• Investigate future climate
variability and effects of land
cover and land use changes on
terrestrial processes
Approach
• Reduce uncertainties in CLM
projections
• Simulate future climate effects on
ecosystem processes
• Simulate thinning of vulnerable
forests, LUC non-forage crop to
poplar
Project # OREZFES-868
Model underestimated NEP in high biomass forests
L: Difference between prior and posteriori NEP
R: Current non-forage grass crops
7. Land Cover Willamette Valley
Vegetation Type / Crops
Alfalfa
Apples
Barley
Barren
Blueberries
Broccoli
Buckwheat
Cabbage
Caneberries
Cauliflower
Cherries
Christmas Trees
Clover/Wildflowers
Corn
Cucumbers
Dbl Crop WinWht/Corn
Deciduous Forest
Developed/High Intensity
Developed/Low Intensity
Developed/Med Intensity
Developed/Open Space
Dry Beans
Evergreen Forest
Fallow/Idle Cropland
Flaxseed
Garlic
Grapes
Grass/Pasture
Greens
Herbaceous Wetlands
Herbs
Hops
Mint
Misc Vegs & Fruits
Mixed Forest
Mustard
Oats
Onions
Open Water
Other Crops
Other Hay/Non Alfalfa
Other Tree Crops
Peaches
Pears
Peas
Peppers
Perennial Ice/Snow
Plums
Potatoes
Pumpkins
Radishes
Rape Seed
Rye
Shrubland
Sod/Grass Seed
Sorghum
Spring Wheat
Squash
Strawberries
Sugarbeets
Sunflower
Sweet Corn
Triticale
Turnips
Vetch
Walnuts
Winter Wheat
Woody Wetlands
8. Conversion from Coal to Bioenergy – Oregon
~3 Tg torrefied biomass per year needed to
run 518 MW power plant at base load
Optimize for minimizing impacts on forests,
sustainable supply
9. Future C Stocks and Emissions – Oregon
In progress:
NECB and C stocks in forests post-thinning
NECB and C stocks on agr land if convert
150K ha non-forage grass to poplar (100%
conversion unlikely).
Maximum potential supply of biomass to
electric facility, and uncertainties
Refine Life Cycle Assessment of emissions
from land post-harvest, transport,
torrefaction, pelletization, fossil fuel
displacement
Assessment of effects of LUC to poplar on
carbon and water cycle
10. Forest Die-off, Climate Change, and Human Intervention in Western
North America
PI: P. Mote, Co-lead PI: B.E. Law (OSU) Co-Is: A. Plantinga (UC-SB), J. Hicke (UI)
Objectives
• Improve ability to predict mortality
• Map vulnerability of forests to mortality
under present and future climate
• Assess & reduce uncertainty in forecast
Approach
• CLM: Drought- and beetle-related
mortality
• Economic model to optimize thinning of
vulnerable forests
• Life Cycle Assessment
Project #:OREW-2013-00628
(Berner et al. in rev)
NASA fellowship
11. Forest Biomass Mortality – Western US (2002-2012)
Negative water balance is the dominant
driver of mortality in the W US
Dry ecoregions were exposed to below-
average water availability for longer duration
(Berner & Law 2015)
Water
availability
Biomass
density
12. (Berner et al. BGD 2016)
Water Availability Mean Over Western US (1985-2014)
13. Mean Magnitude (kg * m-1 s-1)
60 70 80 90 100 110 120 130
LocationofMaximumMoistureTransport(latitudeN)
36
38
40
42
44
46
11 Yr Mean
Perturbed Physics
Default Physics setting
1 Standard Deviation
Reanalysis Datasets
Simulated Moisture Transport over NE Pacific
Aim: Parameterize global model to
bring correct amount of moisture into
western boundary of regional model
Default: Location of the jet is too far
N and not enough moisture
Several parameter sets improve jet
location and moisture transport