Assessing landscape impacts of potential bioenergy production scenarios

using spatially explicit STSMsJennifer Costanza

Robert C. Abt, Alexa McKerrow, Jaime CollazoSeptember 17, 2014

Biomass for energy

Best alternative for society and the environment?Landscape and species impacts have not been fully addressed

Assume impacts will be negative

Recent studies

(Evans et al. 2013 NWF Report)

2nd generation biofuel feedstocks Wood pellets

How will biofuels affect the NC landscape?

2. “Purpose-grown crops” on marginal ag and forest lands

1. Increased “conventional” forest management

• Sweet sorghum• Switchgrass• Short-rotation loblolly pine based on supply chain (Gonzalez et al. 2011, 2012)

How will potential biomass production scenarios for biofuels affect landscapes in North Carolina?1. Create scenarios of land use change2. Map initial conditions in NC: 20093. Model vegetation dynamics: conventional forest

management and associated land use changes4. Model conversion of marginal ag and forest land to

purpose-grown crops5. Incorporate urban growth 6. Simulate landscape change with ST-Sim: 2010 - 20507. Summarize results, especially in forests8. Translate to species impacts

Overview

1. Our past experience and model infrastructure 2. Existing LANDFIRE VDDT models3. Ability to simulate major types of change

expected from biofuels production4. Ability to incorporate output from timber supply

model5. Spatial simulation capability so we can model

resulting species impacts

Why STSMs (ST-Sim)?

Biomass production scenarios for NC

ScenarioConv.

forestsOther 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%

NC vegetation and land use types

CurrentForests: 55%Agriculture: 23%Urban: 10%

Initial conditions: NC vegetation and land use typesCirca 2009

Spatial conditions based on GAP 2001 Land coverupdated with 2009 urban60 m resolution

73 vegetation and land use types59 have state and transition models

Modeling vegetation dynamicsExample: Longleaf pine woodlands

Modeling vegetation dynamicsExample: Longleaf pine woodlands

Conventional forest management added

To other vegand land uses

Initial conditions: state classes, ages

States: Based on 2008 LANDFIRE S-class, NLCD canopy coverAges: Based on FIA data

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

Modeling conventional forest management:Thinning, harvest, land use change

Result: Annual areas thinned, harvested, converted to and from broad forest types and age classes

Modeling purpose grown crops onmarginal agricultural and forest land

Based on soil and land useExcludes protected areas

Based on life cycle analysis

Series of spatial multipliers

Urban growth through time: 2010 - 2050

Terando et al. 2014 PLOS ONE

How will potential biomass production scenarios for bioenergy affect landscapes in North Carolina?1. Create scenarios of land use change2. Map initial conditions in NC: 20093. Model vegetation dynamics: conventional forest

management and associated land use changes4. Model conversion of marginal ag and forest land to

purpose-grown crops5. Incorporate urban growth 6. Simulate landscape change with ST-Sim: 2010 - 20507. Summarize results, especially in forests8. Translate to species impacts

Overview

Results: Simulated land use and vegetationBaseline scenario

2009

2050

Results: Simulated land use and vegetationBaseline scenario

2009

Fayetteville, NC

Spatial results: Conventional biomass scenario

2020

Fayetteville, NC

Spatial results: Conventional biomass scenario

2030

Fayetteville, NC

Spatial results: Conventional biomass scenario

2040 Spatial results: Conventional biomass scenario

Fayetteville, NC

2050

Fayetteville, NC

Spatial results: Conventional biomass scenario

Results: General statewide trends

Forests

Agriculture

Urban areas

2050 Proportion difference from Baseline Scenario

2050 Proportion difference from Baseline Scenario

2050 Proportion difference from Baseline Scenario:Seral Stage, All Forests

2050 Proportion difference from Baseline Scenario:Seral Stage, Lowland Hardwoods

2050 Proportion difference from Baseline Scenario:Seral Stage, Pine plantations

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.

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

Wildlife species we modeled

Birds (12)Brown-headed NuthatchCerulean WarblerGrasshopper SparrowHairy WoodpeckerKentucky WarblerLoggerhead ShrikePrairie WarblerProthonotary WarblerRed-headed WoodpeckerSwainson’s WarblerWood ThrushYellow-breasted Chat

Amphibians (4)Eastern tiger salamanderGopher frogOak toadMole salamander

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

Acknowledgements

People:Todd EarnhardtMatt RubinoNathan TarrAshton DrewSteve WilliamsRonalds GonzalezDennis Hazel

Funding: