Overview of simulation modeling to assess landscape impacts of biomass production for bioenergy in North Carolina. This is a talk I gave at the 2nd State-and-Transition Simulation Modeling Conference in Ft. Collins, CO. http://www.stsm2014.org/index.php?title=Home

1. Assessing landscape impacts of potential
bioenergy production scenarios
using spatially explicit STSMs
Jennifer Costanza
Robert C. Abt, Alexa McKerrow, Jaime Collazo
September 17, 2014

2. Biomass for energy
Best alternative for society and
the environment?
Landscape and species impacts
have not been fully addressed
Recent studies
Assume impacts
will be negative
(Evans et al. 2013 NWF Report)
2nd generation biofuel feedstocks
Wood pellets

3. How will biofuels affect the NC landscape?
1. Increased “conventional” forest management
• Sweet sorghum
• Switchgrass
• Short-rotation loblolly pine
based on supply chain (Gonzalez et al. 2011, 2012)
2. “Purpose-grown crops” on
marginal ag and forest lands

4. Overview
How will potential biomass production scenarios for
biofuels affect landscapes in North Carolina?
1. Create scenarios of land use change
2. Map initial conditions in NC: 2009
3. Model vegetation dynamics: conventional forest
management and associated land use changes
4. Model conversion of marginal ag and forest land to
purpose-grown crops
5. Incorporate urban growth
6. Simulate landscape change with ST-Sim: 2010 -
2050
7. Summarize results, especially in forests
8. Translate to species impacts

5. Why STSMs (ST-Sim)?
1. Our past experience and model infrastructure
2. Existing LANDFIRE VDDT models
3. Ability to simulate major types of change
expected from biofuels production
4. Ability to incorporate output from timber supply
model
5. Spatial simulation capability so we can model
resulting species impacts

6. Biomass production scenarios for NC
Scenario
Conv.
forests
Other forest
products
Marg. ag to
purpose
grown
Marg. forest to
purpose grown
Portion of NC
Fuel
Baseline None BAU No No 0%
Ag No BAU Yes No 10%
Ag-Forest No BAU Some Some 10%
Conventional Yes Reduced No No 1.5%
Conventional-
Ag
Yes Reduced Yes No 10%
Conventional-
Ag-Forest
Yes Reduced Some Some 10%

7. NC vegetation and land use types
Current
Forests: 55%
Agriculture: 23%
Urban: 10%

8. Initial conditions: NC vegetation and land use types
Circa 2009
Spatial conditions based on GAP 2001 Land cover
updated with 2009 urban
60 m resolution
73 vegetation and land use types
59 have state and transition models

9. Modeling vegetation dynamics
Example: Longleaf pine woodlands

10. Modeling vegetation dynamics
Example: Longleaf pine woodlands
Conventional forest management added
To other veg
and land uses

11. Initial conditions: state classes, ages
States: Based on 2008 LANDFIRE S-class, NLCD canopy cover
Ages: Based on FIA data

12. Modeling conventional forest management:
Thinning, harvest, land use change
SRTS timber supply model (Abt et al. 2009 For. Prod. J.)
Not all demand is met by increased harvest
Estimates timber supply based on
• Inventory: how much timber exists? (FIA data;
economic land use change model)
• Demand:
1. Empirical harvests (FIA data)
2. Annual demand in NC increases to 4 million
green tons biomass by 2018
• Forest residues harvested
• Other products displaced

13. Modeling conventional forest management:
Thinning, harvest, land use change
Result: Annual areas thinned, harvested, converted to
and from broad forest types and age classes
Harvest Thinning
200,000
100,000
0
2010 2020 2030 2040 20502010 2020 2030 2040 2050
Year
Hectares
Scenario
Baseline
Conventional

14. Modeling purpose grown crops on
marginal agricultural and forest land
Based on soil and land use
Excludes protected areas
Based on life cycle analysis

15. Urban growth through time: 2010 - 2050
Series of spatial multipliers
Terando et al. 2014 PLOS ONE

16. Overview
How will potential biomass production scenarios for
bioenergy affect landscapes in North Carolina?
1. Create scenarios of land use change
2. Map initial conditions in NC: 2009
3. Model vegetation dynamics: conventional forest
management and associated land use changes
4. Model conversion of marginal ag and forest land to
purpose-grown crops
5. Incorporate urban growth
6. Simulate landscape change with ST-Sim: 2010 -
2050
7. Summarize results, especially in forests
8. Translate to species impacts

17. Results: Simulated land use and vegetation
Baseline scenario
2009

18. Results: Simulated land use and vegetation
2050
Baseline scenario

19. 2009
Spatial results: Conventional biomass scenario
Fayetteville, NC

20. 2020
Spatial results: Conventional biomass scenario
Fayetteville, NC

21. 2030
Spatial results: Conventional biomass scenario
Fayetteville, NC

22. 2040 Spatial results: Conventional biomass scenario
Fayetteville, NC

23. 2050
Spatial results: Conventional biomass scenario
Fayetteville, NC

24. 8,000,000
6,000,000
4,000,000
2,000,000
0
2010 2020 2030 2040 2050
Year
Area (ha)
Results: General statewide trends
Forests
Agriculture
Urban areas

25. Agriculture Forest Urban
0%
−5%
−10%
−15%
Scenario
Proportion Difference
Scenario
Ag
Ag−Forest
Conventional
Conventional−Conventional−2050 Proportion difference from Baseline Scenario
Mixed pine hardwood Natural pine
Upland hardwood
Scenario
Ag
Ag−Forest
Conventional
Conventional−Ag
Conventional−Ag−Forest

26. 2050 Proportion difference from Baseline Scenario
Lowland hardwood Mixed pine hardwood Natural pine
Planted pine Upland hardwood
10%
5%
0%
−5%
−10%
10%
5%
0%
−5%
−10%
Scenario
Proportion Difference
Scenario
Ag
Ag−Forest
Conventional
Conventional−Conventional−Mixed pine hardwood Natural pine
Upland hardwood
Scenario
Ag
Ag−Forest
Conventional
Conventional−Ag
Conventional−Ag−Forest

27. Early Mid Late
10%
5%
0%
Scenario
Proportion Difference
Scenario
Ag
Ag−Forest
Conventional
Conventional−Conventional−2050 Proportion difference from Baseline Scenario:
Seral Stage, All Forests
Upland hardwood
Scenario
Scenario
Ag
Ag−Forest
Conventional
Conventional−Ag
Conventional−Ag−Forest

28. 2050 Proportion difference from Baseline Scenario:
Seral Stage, Lowland Hardwoods
Upland hardwood
Scenario
Scenario
Ag
Ag−Forest
Conventional
Conventional−Ag
Conventional−Ag−Forest

29. 2050 Proportion difference from Baseline Scenario:
Seral Stage, Pine plantations
Scenario
Ag
Ag−Forest
Conventional
Conventional−Ag
Conventional−Ag−Forest

30. Translating landscape results to potential species habitat
State classes Suitable/unsuitable
habitat
• Deductive modeling based on literature
• Pixels in the current species range classified as
suitable or unsuitable: potential habitat
• Not considering species interactions, etc.

31. Example results:
Brown-headed Nuthatch
- Affinity: open, mature pine forests
- Recent sharp declines due to pine
plantations Photo: David Bell
% Change in potential habitat from 2009 Difference in area compared to baseline

32. Wildlife species we modeled
Birds (12)
Brown-headed Nuthatch
Cerulean Warbler
Grasshopper Sparrow
Hairy Woodpecker
Kentucky Warbler
Loggerhead Shrike
Prairie Warbler
Prothonotary Warbler
Red-headed Woodpecker
Swainson’s Warbler
Wood Thrush
Yellow-breasted Chat
Amphibians (4)
Eastern tiger salamander
Gopher frog
Oak toad
Mole salamander

33. Summary
• The STSM framework is useful for assessing change
through time
• Biomass demand, especially in conventional forests,
helps keep some forests on the landscape
• Remaining forest tends to have more area in early
succession state
• In some cases, species could be positively impacted
by biomass production
• There remains much uncertainty regarding landscape
and species impacts
• This famework can be applied to assess potential
positive and negative impacts of other bioenergy and
forest management scenarios

34. Acknowledgements
People:
Todd Earnhardt
Matt Rubino
Nathan Tarr
Ashton Drew
Steve Williams
Ronalds Gonzalez
Dennis Hazel
Funding: