LA 510/410 Climate Change Planning and DesignFinal Project

Scenario Planning Using Envision Modeling Software:Defining Policies & Attributes for GHG Reductions on the Landscape

byTeam 5: Ryan Bellinson, Ben Farrell, Gayathry L

March 18th, 2013

“ENVISION is a GIS­based tool for scenario­based community and regional planning andenvironmental assessments. ENVISION combines a spatially­explicit polygon­basedrepresentation of a landscape, a set of application­define policies (decision rules) that aregrouped into alternative scenarios, landscape change models, and models of ecological, socialand economic services to simulate land use change and provide decision­makers, planners, andthe public with information about resulting effects on indices of valued products of thelandscape.”­ John Bolte ­ http://envision.bioe.orst.edu

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Table of Contents

Executive Summary­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 3

Introduction­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 3

Methodology­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 5

Selection of Scenario­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 6

Selection of Site attribute­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 6

Selection of Policy­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 7

Hypothesis­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 9

Key findings­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 9

Results/Analysis­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 10

Conclusions­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 15

Recommendations­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 15

Appendix A­ Scope of work­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 16

Appendix B­ Maps­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 17

Appendix C­ Graphs­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 22

Appendix D­ Charts­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 23

Appendix E­ Policy (xml) ­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 24

Appendix F­ Site attributes (xml)­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 27

Works Cited­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­ 28

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Executive Summary

Our team has chosen to test our policies under two scenarios. These two scenarios

include High climate impacts with Compact development with Mixed fuels treatment and Low

climate impacts with Compact development with Mixed fuels treatment. The type of

development has been left constant due to the emphasis of the project on compact development

planning. The type of fuels treatment has been left constant at Mixed fuels due to the emphasis

of the project being on increasing forest carbon storage by decreasing the chance of major fire

through mixed methods of fire hazard reduction on the landscape.

The HCM and LCM scenario simulations were run 3 times each for a time period of 50

years. A control simulation was also run for a time period of 50 years. The analysis compares

the two experimental scenarios to each other and then to the control scenario.

Introduction

Envision is a wonderful tool that allows us asking large questions about the landscape

around us. It enables manipulation of agents that interact with the landscape and compare

multiple scenarios that show what the future could look like based upon probabilistically models.

When mulling over what future scenarios to examine, our group decided to focus on a general

theme of examining reductions greenhouse gasses (GHGs) and how that impact fire on the

landscape. Oregon has some of the nation’s strictest self imposed carbon reduction laws; a

reduction of CO2 emissions levels to 1990 levels by 2020.1

The first conjecture for this paper is addressed through a specific set of target policies,

that will project a clear and visible reduction in GHGs. To address this question, a specific set of

indicator variables such as vehicle miles traveled, biomass, and disturbance were selected. The

later part of the paper discusses the reason for the selection of these variables and their in depth

description.

The next hypothesis was focused on reducing GHGs through the target policies, that will

subsequently lead to a reduction in catastrophic fires. In order to address this an understanding

of what catastrophic fire is essential . According to Dr. Jack Cohen, a catastrophic fire is one 2

1 Dodson, Mark, and Jane Lubchenco. "Oregon Strategy for Greenhouse Gas Reduction." (2004): 8­13.2 Cohen, J. 2008. The wildland­urban interface fire problem: A consequence of the fire exclusion paradigm

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that ignites homes over the course of its path. A catastrophic fire also is stand replacing which is

very important to our first hypothesis because if a fire is stand replacing, it destroys tree stands

that capture large amounts of carbon.

Compact development was one major area of focus as it can greatly reduce GHGs. Land

use conversion is one of the largest producers of GHGs and because modifying the landscape is

an extremely energy intensive process. When we thought about incorporating compact

development into our policy sets, we considered Oregon’s strict land use policy.

Oregon’s land use policy is some of the strictest in the country. The Urban Growth 3

Boundary is a unique policy tool only two states (OR and MN) currently use and when creating

policies we wanted to think outside of the like the Oregon Legislature does when considering

new land use planning policy. The compact development we hoped our policies would capture 4

were developed with the intent of creating a similar effect as the UGB. We hoped our compacted

development policies would act like a UGB, placing intensive development in a centralized

location and leaving more available surrounding land for agriculture, natural resources, and

general intrinsic value. The more compact and condensed development is, fewer GHGs are

emitted in both the processes in developing the infrastructure as well as running the subsequent

infrastructure once it is operational.

Another policy area targeted was protecting old growth forests. The older, larger trees on

the landscape are the most efficient vegetation on the landscape at absorbing carbon in the

study area. When we have a large group of these trees in a clustered area on the landscape, 5

they act as a carbon sink, or net absorber of carbon. Carbon sinks are extremely important 6

when considering our overall goal of lower GHGs so protecting these valuable commodities is

pivotal to our goal.

The reasons for addressing GHG emissions as the project goal are numerous.Primary

3 Nielsen­Pincus, Max. "Agent Based Actors in Envision." 22 Feb. 2013. Lecture.4 Nielsen­Pincus, M., R. G. Ribe, and B. R. Johnson. 2011. The sociology of landowner interest in restoring fire­adapted,biodiverse habitats in the wildland­urban interface of Oregon's Willamette Valley Ecoregion. Pages 58­66 in Proceedings of thesecond conference on the Human Dimensions of Wildland Fire. U.S. Department of Agriculture, Forest Service, NorthernResearch Station.5 PNW Research Station Science Update. January 2004. Western Forests, Fire Risk, and Climate Change.6 PNW Research Station Science Update. January 2004. Western Forests, Fire Risk, and Climate Change.

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one is that Oregon as state, has chosen to tackle the issue of climate change and thus GHGs

much more aggressively than most other states. Oregon has chosen to tackle climate change 7

through both land use planning as well as incentive based policies. We wanted to mimic 8

Oregon’s commitment to lowering GHGs and wanted to incorporate similar tactics.

The Kyoto Protocol and other international climate change mitigation reduction policies is

another reason we wanted to address climate change. Even though the United States never 9

ratified the Kyoto Protocol, we feel it is an important and monumental treaty that will spur new

policy and discussion moving into the future. We feel international treaties will become more

prevalent in term of GHG reduction in the future so we felt it would be appropriate and prevalent

to address these through our policies.

Most importantly, as a group we feel strongly about climate change and mitigating its

effects so reducing GHGs was a topic of great interest for all of us. The issue of carbon and

GHG reduce is something that is talked about regularly but often not examined passed face

value. We wanted to use this opportunity to dive into the issue and really examine what could be

accomplished when trying to address the issue head on. Envision might not be designed to

directly address how GHGs impact climate change, but based upon the indicator variables, we

feel that the emphasis we put into compact climate change also has made reduction of wildfire

on the landscape.

Methodology

There are three components that are key in conducting the envision runs, to get the

necessary data to validate the hypothesis. These are Scenarios, Attributes and Policies. Each

one of these components have a wide range from which choices are to be made in order to

favour the set of assumptions made for a particular project.

7 Dodson, Mark, and Jane Lubchenco. "Oregon Strategy for Greenhouse Gas Reduction." (2004): 8­13.8 Nielsen­Pincus, M., R. G. Ribe, and B. R. Johnson. 2011. The sociology of landowner interest in restoring fire­adapted,biodiverse habitats in the wildland­urban interface of Oregon's Willamette Valley Ecoregion. Pages 58­66 in Proceedings of thesecond conference on the Human Dimensions of Wildland Fire. U.S. Department of Agriculture, Forest Service, NorthernResearch Station.9 Summary for Policymakers: A Report of Working Group I of the Intergovernmental Panel on Climate Change.

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Selection of scenario:

Initially, the scenarios selected for testing were based on keeping the mixed fuels

treatment component as constant due to the emphasis of the project being on increasing forest

carbon storage by decreasing the chance of major fire through mixed methods of fire hazard

reduction on the landscape that is High climate impact Compact development Mixed fuel

treatment (HCM), Low climate impact Compact development Mixed fuel treatment (LCM), High

climate impact Dispersed development Mixed fuel treatment (HDM) and Low climate impact

Dispersed development Mixed fuels treatment (LDM). At the end of the preliminary runs, trends

showed that the development was majorly compact and hence for the next set of multi runs we

chose the two scenarios that had mixed fuels treatment and compact development as constant

components, that is HCM and LCM.

Selection of Site attributes:

The first policy attribute selected to achieve the goal is the Nearest UGB for site selection.If

the site for development is closer to the urban growth boundary then the vehicle miles travel

necessary to commute for basic services like hospitals, entertainment, office etc. is reduced. In

this project the nearest UGB were selected to be Lowell, Creswell, Veneta and Eugene and also

specified the distance to the nearest UGB, D_UGB to be a maximum of 3000 m or 1.8 miles

approximately. This preference will also make it easier and possible to connect these

developments by public transportation.

Slope is the second important policy adopted for a variety of factors. The primary idea

was to keep slopes of development under 10%. Land use conversion is a large contributor to

GHG emissions. It is critical to ensure severe grading doesn’t takes place in rural development

projects. Land management strategies should use land as productively and sustainably as

possible. Limiting construction activities helps in minimizing contamination by equipment as well

as carbon emissions. Building on flatter land eliminates the need for excavation of high quality

soils as well as saves money in construction costs.

The next attribute altered was the distance to roads. It was kept at less than 600 meters.

This policy will put the development a short distance from paved roads, meaning fewer vehicle

miles traveled, in which transportation contributes heavily to GHGs emissions, in addition the

policy will help limit dust particles resulting from unpaved roads. We hope a policy such as this

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will put the development close enough to transit as well as encourage pedestrian and bicycle

use on the roadways to get to the city. Due to the fact we are developing rural land, we do not

want the development too close to major roads, this may actually encourage vehicle miles

traveled as access would then be too easy for cars. In addition, people choose to move into rural

areas to get away from the city.

Vehicle miles traveled is a great indicator of GHG emissions and a cities approach to global

climate change. In order to reduce vehicle miles traveled and reduce overall emissions by

utilities we implemented a distance to the nearest Urban Growth Boundary of 3000 meters. In

limiting distance to the UGB, there is a reduction in vehicle miles traveled, cost and benefit both

ecologically and financially by expansive utilities and helps keep a tight border around the WUI.

Floodplains are very sensitive habitats and it is best to avoid any and all development in

these biodiverse habitats. Not only does this eliminate the risk of multiple land use changes due

to flooding but it also preserves a valuable natural buffer against floods and preserved

endangered habitat. Hence, development was contained outside floodplains.

Selection of Policy

The first policy addressed to facilitate the runs was Conservation status.When

addressing rural development policy was set up to create a conservation easement where

landowners or developers can selectively thin or create oak woodlands on their property and

receive a tax credit. By creating more oak woodlands, the moisture content of surface fuels

increases because of the dense oak canopy. This policy helps in creating a more fire resistance

environment. Oak trees are also a great source for storing carbon because the sequester

carbon in their root systems and surrounding soils as well as in the hardwood trunks which is

critical when many conifers only store carbon in aboveground structures that are much more

susceptible to fire.

The next policy selected was the disturbance policy. For this, the area immediately

around new structures is to be converted into oak savanna. This causes a decrease in fuel loads

around structures and act as a buffer zone. By decreasing fuel loads around structures,

homeowners are helping firefighters protect structures and helping to mitigate fire risks.

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Another GHG and fire reduction policy selected for implementation was ensuring that

management status is set to high quality savanna restoration(agricultural land) / fire hazard

reduction(forest land). Savannas sequester high amounts of carbon in their root systems, which

run deep into moist soils. Savannas are natural to the Willamette Valley and act as a strong fire

hazard reduction strategy. Another benefit to the strategy is that savannas are not only more

impervious to fire than conifer forests, but sequester carbon in a safer form­underground.

The new development policy strategy of limiting densities from 1­30 units was also

selected. This development strategy encourages compact development. Compact

development allows for population density, reduces transportation, and limits the installation of

new infrastructure such as water, sewer, and roads. Vehicle miles traveled will be constricted

within a dense development, therefore GHG emissions will be less than they would be if the

population is traveling far distances. Compact development will also limit land disturbance and

preserve natural areas. This development policy will also act as a mitigation strategy against

wildfires.

Several policy changes were made to the envision .envx file. These incentivized

policies represent options that may be implemented through top­bottom or bottom up

mechanisms. The set of policies altered are:10

FT4.(if)Fuels reduction treatment blocks outside WUI­ off

FT14a.(ir) Oak woodland restoration within fire hazard zones­on

FT14d.(if) Extreme makeover inside WUI­off

FT15. Post fire Douglas­fir plantation establishment­ off

FT17b(ir). Wetland prairie conservation reserve program­on

LM1.3. Conventional timber harvest by rural residents and rural ranchette owners­off

The primary focus of editing these policies was :

reducing disturbance of landscape outside WUI

promote structural savannah restoration and oak woodland restoration

encourage fuels reduction treatment within WUI

oak woodland restoration within fire hazard zone

control timber harvest by locals

10 Bart Johnson, available envision policies and options

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Hypothesis

H1 Through a set of specific target policies and attributes, there will be a noticeable reduction of GHGs based upon a set of indicating variables; population density, number of new dwellings, expansion area of UGB, land use/disturbance, stand replacing fire.H2 By targeting to reduce GHGs through our target policies, there will subsequently be a reduction in catastrophic fires.H3 In creating policy specifically targeted to reduce catastrophic fire in High climatscenariosos, there will be subsequent reduction to catastrophic fire in Low climate scenarios.

Key Findings

H1 In both the high and low climate scenarios, there have been noticeable reductions ofGHGs based upon the indicator variables; population density, number of new dwellings,expansion area of UGB, land use/disturbance, stand replacing fire. In the low climate model, ourmodel did a worse job of preventing stand replacing fires than the control runs but in the othercategories our model did a better job of reducing GHGs based upon the indicator variables.Overall our hypothesis was confirmed.

H2 Our policies clearly reduced GHGs and there was a curious reduction in fire as well. Inthe high climate model, our model reduced stand replacing fire in comparison to the control run.The low climate scenario in our model had more stand replacing fire than the control run,showing our policies weren’t effective in this area. Our hypothesis was partially confirmed.

H3 When compared with a control of unaltered Envision policies, our high climate scenarioreduced the amount of catastrophic fires or stand replacing fires on the landscape. The lowclimate scenario in the control runs did a better job of reducing stand replacing fire than ouraltered model. This is somewhat foreseeable because our model was intended to reduce standreducing in extreme climate change scenarios rather than lesser climate change scenarios. Ourhypothesis was disproved.

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ResultsGraph 1: Oak Habitat ­ Run (0) vs Run (2) vs Control Run

Graph 2: Management ­ Run (0) vs Run (2) vs Control

AnalysisThe overall oak habitat, as per our policy, increases over time There is no significant differencein the oak restoration area between the simulations.Fire hazard reductions apply to the greatest amount of land in all scenarios. High QualityWoodland Restoration is more prevalent in the HCM scenario, in particular Run 2. Structuralwoodland and High Quality Savanna follow in area that is restored on the landscape.Restorations generally peak around year 30.

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Graph 3: Fire ­ Run (0) vs Run (2) vs Control

Graph 4: Restoration, Harvest, Thinning ­ Run (0) vs Run (2) vs Control

AnalysisThe highest amount of burned area from a stand replacing fire occurred in the HCM run 2 inwhich 900 hectares were affected in year 46. In addition, a surface fire of 500 hectares hit inyear 22. The HCM control run, however, had the highest amount of burned area from surface firethat affected 1200 hectares in year 25. In the LCM run 2, a larger than normal stand replacing firehit in year 27 which affected 210 hectares. Overall, the HCM experimental scenarios performedbetter than the control at reducing large fires, while the LCM control performed better than theexperimental run at reducing large fires. Fuels treatments were held constant at ‘mixed’ thereforethe scenarios were relatively similar in this category.

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Graph 5: Burned Area ­ Run (0) vs Run (2) vs Control

Graph 6: Budget Allocation ­ Run (0) vs Run (2) vs Control

AnalysisThe number of burned residences were lower in the HCM experimental runs versus the control.The number of burned residences in the LCM control run were lower than in the experimentalruns. The fuels treatment budget correlates with the major fire incidents. Each scenario had alarger percentage of the budget geared towards restoration, which is to be expected.

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Graph 9: Land Use Trends ­ LCM MultiRun ­ Run (0) vs Run (1) vs Run (2)

Graph 10: Land Use Trends ­ HCM MultiRun ­ Run (0) vs Run (1) vs Run (2)

AnalysisThe HCM and LCM scenario land use trends are similar over each multi­run. The land usetrends in the LCM and HCM scenario showed declines in mixed forest area. This is a results ofthe thinning and burning of mixed forest lands as a fuels treatment method. The area of openforest increased for both scenarios but more so in the HCM scenario. Hay/pasture/fallowshowed slight declines in area in each scenario.

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Graph 11: Land Management Trends ­ LCM MultiRun ­ Run (0) vs Run (1) vs Run (2)

Graph 12: Land Management Trends ­ HCM MultiRun ­ Run (0) vs Run (1) vs Run (2)

AnalysisLand management is mostly comprised of fire hazard reduction treatments and high qualitywoodland restoration. Structural woodland restoration and high quality savanna restoration areevenly distributed throughout the landscape. The HCM scenario better distributes restorationthroughout the landscape as woodland and savanna restorations comprise 8,000 hectares at 50years while in the LCM scenario fire hazard reduction comprises 6,000­7,00 hectares of 50years. HCM scenario 1 is preferred since less restoration and fire hazard reductions whereneeded.

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Conclusions

Our findings were fairly inconclusive. Envision does not have any clear way of showing

GHGs so it is very difficult to assess whether or not our policies made any significant differences

in this area. GHGs are constantly shifting, moving about in the atmosphere like a grain of sand in

an ocean current. This makes it difficult to take a small portion of the global and assess its

specific values in a very complex, vast system.

Based upon our indicator variables it appears as if there are some reductions for certain

variables but it is quite sporadic and it is hard to assess where these reductions come at the

result of our policies or simply a result of stochastic variability in Envision. Because of the

stochastic variability, it would be reaching to assume the inconsistent findings were a direct

result of our policies and not of some other unseen reason.

Recommendations

It would be a beneficial tool for Envision to have some type of tangible output category

that calculated CO2, an easy way to calculate biomass on the landscape, or some other way to

examine GHGs. In accordance with Oregon’s land use policy, it would be a valuable tool to be

able to see what types of landscape act as carbon sinks, or GHGs impact fire. This would be a

complicated tool to create but if there were a way to easily view and assess GHGs on the

landscape it would be a positive addition to Envision already vast arsenal of capabilities.

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Appendices

Appendix A: Scope of Work

Team 5 MembersRyan BellinsonBen FarrellGayathry L

Objective:The objective of the project is to develop and test policies and scenarios in Envision. Our

team will create a list of attributes that will be used to identify IDUs suitable for new ruraldevelopment through zoning changes: 1) Land currently zoned for agriculture and 2) Landcurrently zoned for forestry. We will implement the attributes in the Envision code and test thepolicy strategies.

Team Goals:In creating an Envision scenario we wanted to implement policy that would favor a

reduction in greenhouse gas (GHG) emissions. In doing so, we targeted attributes that would reduce vehicle miles traveled, reduce land use changes, and implement agricultural and forestry planning that will favor vegetation strategies that will act as net carbon sinks as well as reduce fire fuel loadings. Our goal is to develop policy strategies to address the challenging issue of climate change by reducing GHG emissions and retaining and enhancing natural areas. The policy initiatives will reduce GHG emissions primarily through minimizing vehicle trips, increasing the availability of alternative transportation such as walking or biking into the City, minimizing land disturbance, encouraging conservation initiatives and supporting an increase in density in areas where there is infrastructure to support it or in areas in which soils are low quality. Our policies should also address adaptation to climate change, such as wildfire management and protection, biological preservation, and water use and supply.

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Appendix B: MapsMapsMap 1: Fine Articulated Land Use – LCM Scenario – 50 Year

Map 2: Fine Articulated Land Use – HCM Scenario – 50 Year

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Map 3: New Dwellings ­ LCM Scenario ­ 50 year

Map 4: New Dwellings ­ HCM Scenario ­ 50 year

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Map 5: Population Density ­ Scenario LCM ­ 50 year

Map 6: Population Density ­ HCM Scenario ­ 50 year

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Map 7: Urban Growth Boundaries ­ LCM Scenario ­ 50 year

Map 8: Urban Growth Boundaries ­ HCM Scenario ­ 50 year

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Map 9: Fire ID ­ LCM Scenario ­ 50 year

Map 10: Fire ID ­ HCM Scenario ­ 50 year

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Appendix C: GraphsGraphsGraph 13: Burned Area, Oak Restoration, Budget and Fire Risk ­ LCM Results

Graph 14: Burned Area, Oak Restoration, Budget and Fire Risk ­ HCM Results

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Appendix D: ChartsCharts

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Appendix E: Policy XMLLCM Policy Code<description> Low Climate Impact, Compact Development, Mixed Fuels Treatment </description> <policies><policy id='1010' name='FT0a. Initial Pasture Management Assignment ­ Rural Resident' inUse='1' /> <policy id='1011' name='FT0a. Initial Pasture Management Assignment ­ MicroFarmer' inUse='1' /> <policy id='1012' name='FT0a. Initial Pasture Management Assignment ­ Farmer' inUse='1' /> <policy id='1013' name='FT0a. Initial Pasture Management Assignment ­ Forester' inUse='1' /> <policy id='1014' name='FT0a. Initial Pasture Management Assignment ­ Rural Estate' inUse='1' /> <policy id='1001' name='FT1a. Defensible space maintenance and dwelling protection ­ All burnable vegclasses' inUse='1'/> <policy id='1002' name='FT1b. Defensible space maintenance and dwelling protection ­ grassland addition' inUse='1' /> <policy id='1003' name='FT1c. Defensible space maintenance in manage 10, 11, 15, 16 (oak savana and prairie)' inUse='1'/> <policy id='1004' name='FT1d. Defensible space maintenance in manage 12, 13, 17, 18 (oak woodlands)' inUse='1' /> <policy id='1005' name='FT1e. Defensible space maintenance in manage 14 (fuels reduction)' inUse='1' /> <policy id='2' name='FT2. Fuels reduction treatments on rural IDUs with residences or other structures' inUse='1' /> <policy id='25' name='FT2.5. Fuels reduction treatment blocks without incentives (Manage=14)' inUse='1' /> <policy id='3' name='FT3(if). Fuels reduction treatment blocks within the WUI' inUse='1' /> <policy id='4' name='FT4(if). Fuels reduction treatment blocks outside the WUI' inUse='0' /> <policy id='5' name='FT5(if). Firebreaks along transportation corridors' inUse='1' /> <policy id='60' name='FT6aCON. Savanna restoration on historic oak and upland prairie habitats (Manage=10,Conventional)' inUse='0' />

<policy id='601' name='FT6aMIX. Savanna restoration on historic oak and upland prairie habitats(Manage=10, Mixed)' inUse='1' /> <policy id='61' name='FT6bCON. Savanna restoration on historic oak and upland prairie habitats (Manage=11,Conventional)' inUse='0' />

<policy id='611' name='FT6bMIX. Savanna restoration on historic oak and upland prairie habitats(Manage=11, Mixed)' inUse='1' /> <policy id='70' name='FT7aCON. Oak woodland restoration on historic oak and upland prairie habitats (Manage=12,Conventional)' inUse='0' /> <policy id='701' name='FT7aMIX. Oak woodland restoration on historic oak and upland prairie habitats (Manage=12,Mixed)' inUse='1' />

<policy id='71' name='FT7bCON. Oak woodland restoration on historic oak and upland prairie habitats(Manage=13, Conventional)' inUse='0' />

<policy id='711' name='FT7bMIX. Oak woodland restoration on historic oak and upland prairie habitats(Manage=13, Mixed)' inUse='1' /> <policy id='8' name='FT8. Oak savanna and woodland restoration in climate­stressed habitats' inUse='1' /> <policy id='90' name='FT9a(ir). Upland prairie restoration within conservation zones (Manage=15)' inUse='1' /> <policy id='91' name='FT9b(ir). Wetland prairie restoration within conservation zones (Manage=16)' inUse='1' /> <policy id='100' name='FT10a(ir). Oak savanna restoration within conservation zones (Manage=10)' inUse='1' /> <policy id='101' name='FT10b(ir). Oak savanna restoration within conservation zones (Manage=11)' inUse='1' /> <policy id='110' name='FT11a(ir). Oak woodland restoration within conservation zones (Manage=12)' inUse='1' /> <policy id='111' name='FT11b(ir). Oak woodland restoration within conservation zones (Manage=13)' inUse='1' /> <policy id='13' name='FT13(if). Extreme makeover (oak restoration in conifer forest)' inUse='1' /> <policy id='140' name='FT14a(ir). Oak woodland restoration within fire hazard zones (Manage=12)' inUse='0' /> <policy id='141' name='FT14b(if). Oak woodland restoration within fire hazard zones (Manage=13)' inUse='1' /> <policy id='142' name='FT14c(if). Oak woodland restoration for fire hazard outside key fire hazard zones (Manage=12)'inUse='1' /> <policy id='143' name='FT14d(if). Extreme Makeover inside WUI (Oak woodland restoration in conifer forest (Manage=13)'inUse='1' />

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<policy id='144' name='FT14e(if). Extreme Makeover outside WUI (Oak woodland restoration in conifer forest(Manage=12)' inUse='0' /> <policy id='15' name='FT15. Post­fire Douglas­fir plantation establishment' inUse='0' /> <policy id='16' name='FT16. Post­fire oak woodland establishment' inUse='1' /> <policy id='17' name='FT17a(ir). Upland prairie conservation reserve program' inUse='1' /> <policy id='171' name='FT17b(ir). Wetland prairie conservation reserve program' inUse='0' /> <policy id='18' name='FT18. Abandoned agricultural land' inUse='1' /> <policy id='30' name='LM1.1. Conventional timber harvest by foresters' inUse='1' /> <policy id='31' name='LM1.2. Conventional timber harvest by farmers and rural estate owners' inUse='1' /> <policy id='32' name='LM1.3. Conventional timber harvest by rural residents and rural ranchette owners' inUse='0' /> <policy id='33' name='LM2. Convert mixed broadleaf­conifer forest to conifer forest (large trees)' inUse='1' /> <policy id='34' name='LM3. Convert mixed broadleaf­conifer forest to conifer forest (medium­size trees)' inUse='1' /> <policy id='301' name='LM4. Rural resident agent changes agricultural land Use' inUse='1' /> <policy id='302' name='LM5. Rural resident agent pasture management' inUse='1' /> <policy id='35' name='RR1D. Conversion of AGRICULTURAL lands to rural residential (Dispersed)' inUse='0' /> <policy id='36' name='RR2D. Conversion of FOREST lands to rural residential (Dispersed)' inUse='0' /> <policy id='37' name='RR1C. Conversion of AGRICULTURAL lands to rural residential (Compact)' inUse='1' /> <policy id='38' name='RR2C. Conversion of FOREST lands to rural residential (Compact)' inUse='1' /> <policy id='39' name='RR7­AG­Cl AGRICULTURAL lands to CLUSTERED rural residential' inUse='0' /> <policy id='40' name='RR8­FOR­Cl FOREST lands to CLUSTERED rural residential' inUse='0' /> <policy id='50' name='A1. Abandon Management of Structural Oak Savanna Restoration Treatments' inUse='1' /> <policy id='51' name='A2. Abandon Management of High Quality Oak Savanna Restoration Treatments' inUse='1' /> <policy id='52' name='A3. Abandon Management of Structural Oak Woodland Restoration Treatments' inUse='1' /> <policy id='53' name='A4. Abandon Management of High Quality Oak Woodland Restoration Treatments' inUse='1' /> <policy id='54' name='A5. Abandon Management of Fire Hazard Reduction Treatments' inUse='1' /> </policies>

HCM Policy Code<description> HCM ­ High Impact of Climate Change on Vegetation and Fire, Compact Development, Mixed Fuel Treatment Approach The HCM Scenario anticipates a high degree of compact development within the context of higher climate change impacts.Precipitation and temperatures are altered significantly from current levels, impacting vegetation succession, fuels and fireweather, thereby intensifying potential wildfire behavior. As populations in the study areas increase significantly between 2000and 2050 (from 11,942 to 82,000 in the Eugene/Springfield study area), Oregon's land use policies are relaxed and allow moreresidential development in rural areas. Wildfire risk reduction relies on mixed techniques. </description> <policies> <policy id='1010' name='FT0a. Initial Pasture Management Assignment ­ Rural Resident' inUse='1' /> <policy id='1011' name='FT0a. Initial Pasture Management Assignment ­ MicroFarmer' inUse='1' /> <policy id='1012' name='FT0a. Initial Pasture Management Assignment ­ Farmer' inUse='1' /> <policy id='1013' name='FT0a. Initial Pasture Management Assignment ­ Forester' inUse='1' /> <policy id='1014' name='FT0a. Initial Pasture Management Assignment ­ Rural Estate' inUse='1' /> <policy id='1001' name='FT1a. Defensible space maintenance and dwelling protection ­ All burnable vegclasses' inUse='1'/> <policy id='1002' name='FT1b. Defensible space maintenance and dwelling protection ­ grassland addition' inUse='1' /> <policy id='1003' name='FT1c. Defensible space maintenance in manage 10, 11, 15, 16 (oak savana and prairie)' inUse='1'/> <policy id='1004' name='FT1d. Defensible space maintenance in manage 12, 13, 17, 18 (oak woodlands)' inUse='1' /> <policy id='1005' name='FT1e. Defensible space maintenance in manage 14 (fuels reduction)' inUse='1' /> <policy id='2' name='FT2. Fuels reduction treatments on rural IDUs with residences or other structures' inUse='1' /> <policy id='25' name='FT2.5. Fuels reduction treatment blocks without incentives (Manage=14)' inUse='1' /> <policy id='3' name='FT3(if). Fuels reduction treatment blocks within the WUI' inUse='1' /> <policy id='4' name='FT4(if). Fuels reduction treatment blocks outside the WUI' inUse='0' />

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<policy id='5' name='FT5(if). Firebreaks along transportation corridors' inUse='1' /> <policy id='60' name='FT6aCON. Savanna restoration on historic oak and upland prairie habitats (Manage=10,Conventional)' inUse='0' />

<policy id='601' name='FT6aMIX. Savanna restoration on historic oak and upland prairie habitats(Manage=10, Mixed)' inUse='1' /> <policy id='61' name='FT6bCON. Savanna restoration on historic oak and upland prairie habitats (Manage=11,Conventional)' inUse='0' />

<policy id='611' name='FT6bMIX. Savanna restoration on historic oak and upland prairie habitats(Manage=11, Mixed)' inUse='1' /> <policy id='70' name='FT7aCON. Oak woodland restoration on historic oak and upland prairie habitats (Manage=12,Conventional)' inUse='0' /> <policy id='701' name='FT7aMIX. Oak woodland restoration on historic oak and upland prairie habitats (Manage=12,Mixed)' inUse='1' />

<policy id='71' name='FT7bCON. Oak woodland restoration on historic oak and upland prairie habitats(Manage=13, Conventional)' inUse='0' />

<policy id='711' name='FT7bMIX. Oak woodland restoration on historic oak and upland prairie habitats(Manage=13, Mixed)' inUse='1' /> <policy id='8' name='FT8. Oak savanna and woodland restoration in climate­stressed habitats' inUse='1' /> <policy id='90' name='FT9a(ir). Upland prairie restoration within conservation zones (Manage=15)' inUse='1' /> <policy id='91' name='FT9b(ir). Wetland prairie restoration within conservation zones (Manage=16)' inUse='1' /> <policy id='100' name='FT10a(ir). Oak savanna restoration within conservation zones (Manage=10)' inUse='1' /> <policy id='101' name='FT10b(ir). Oak savanna restoration within conservation zones (Manage=11)' inUse='1' /> <policy id='110' name='FT11a(ir). Oak woodland restoration within conservation zones (Manage=12)' inUse='1' /> <policy id='111' name='FT11b(ir). Oak woodland restoration within conservation zones (Manage=13)' inUse='1' /> <policy id='13' name='FT13(ir). Extreme makeover (oak restoration in conifer forest)' inUse='1' /> <policy id='140' name='FT14a(if). Oak woodland restoration within fire hazard zones (Manage=12)' inUse='0' /> <policy id='141' name='FT14b(if). Oak woodland restoration within fire hazard zones (Manage=13)' inUse='1' /> <policy id='142' name='FT14c(if). Oak woodland restoration for fire hazard outside key fire hazard zones (Manage=12)'inUse='1' /> <policy id='143' name='FT14d(if). Extreme Makeover inside WUI (Oak woodland restoration in conifer forest (Manage=13)'inUse='1' /> <policy id='144' name='FT14e(if). Extreme Makeover outside WUI (Oak woodland restoration in conifer forest(Manage=12)' inUse='0' /> <policy id='15' name='FT15. Post­fire Douglas­fir plantation establishment' inUse='0' /> <policy id='16' name='FT16. Post­fire oak woodland establishment' inUse='1' /> <policy id='17' name='FT17a(ir). Upland prairie conservation reserve program' inUse='1' /> <policy id='171' name='FT17b(ir). Wetland prairie conservation reserve program' inUse='0' /> <policy id='18' name='FT18. Abandoned agricultural land' inUse='1' /> <policy id='30' name='LM1.1. Conventional timber harvest by foresters' inUse='1' /> <policy id='31' name='LM1.2. Conventional timber harvest by farmers and rural estate owners' inUse='1' /> <policy id='32' name='LM1.3. Conventional timber harvest by rural residents and rural ranchette owners' inUse='0' /> <policy id='33' name='LM2. Convert mixed broadleaf­conifer forest to conifer forest (large trees)' inUse='1' /> <policy id='34' name='LM3. Convert mixed broadleaf­conifer forest to conifer forest (medium­size trees)' inUse='1' /> <policy id='301' name='LM4. Rural resident agent changes agricultural land Use' inUse='1' /> <policy id='302' name='LM5. Rural resident agent pasture management' inUse='1' />

<policy id='35' name='RR1D. Conversion of AGRICULTURAL lands to rural residential (Dispersed)'inUse='0' /> <policy id='36' name='RR2D. Conversion of FOREST lands to rural residential (Dispersed)' inUse='0' /> <policy id='37' name='RR1C. Conversion of AGRICULTURAL lands to rural residential (Compact)' inUse='1' /> <policy id='38' name='RR2C. Conversion of FOREST lands to rural residential (Compact)' inUse='1' /> <policy id='39' name='RR7­AG­Cl AGRICULTURAL lands to CLUSTERED rural residential' inUse='1' /> <policy id='40' name='RR8­FOR­Cl FOREST lands to CLUSTERED rural residential' inUse='1' /> <policy id='50' name='A1. Abandon Management of Structural Oak Savanna Restoration Treatments' inUse='1' /> <policy id='51' name='A2. Abandon Management of High Quality Oak Savanna Restoration Treatments' inUse='1' />

26

<policy id='52' name='A3. Abandon Management of Structural Oak Woodland Restoration Treatments' inUse='1' /> <policy id='53' name='A4. Abandon Management of High Quality Oak Woodland Restoration Treatments' inUse='1' /> <policy id='54' name='A5. Abandon Management of Fire Hazard Reduction Treatments' inUse='1' /> </policies>

Appendix F: Attributes XML

<siteAttr>(NEAREST_UG = 8 Eugene/Springfield or NEAREST_UG = 10 Creswell or NEAREST_UG = 11

Lowellor NEAREST_UG = 9 Veneta)and D_UGB<3000 and (ZONE=3 or ZONE=4) and SLOPEAV< 10 and D_ROADS < 600and FLD100 = 0 Outside Floodplainand SOILACCC != "1X" 1X = Class 1 soils and N_DU >0 </siteAttr>

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Works Cited

1. Bart Johnson, available envision policies and options

2. Cohen, J. 2008. The wildland­urban interface fire problem: A consequence of the fire exclusionparadigm. Forest History Today. Fall: 20­26

3. Dodson, Mark, and Jane Lubchenco. "Oregon Strategy for Greenhouse Gas Reduction."(2004): 8­13.

4. Nielsen­Pincus, Max. "Agent Based Actors in Envision." 22 Feb. 2013. Lecture.

5. Nielsen­Pincus, M., R. G. Ribe, and B. R. Johnson. 2011. The sociology of landowner interestin restoring fire­adapted, biodiverse habitats in the wildland­urban interface of Oregon'sWillamette Valley Ecoregion. Pages 58­66 in Proceedings of the second conference on theHuman Dimensions of Wildland Fire. U.S. Department of Agriculture, Forest Service, NorthernResearch Station.

6. PNW Research Station Science Update. January 2004. Western Forests, Fire Risk, andClimate Change.

7. Summary for Policymakers: A Report of Working Group I of the Intergovernmental Panel onClimate Change.

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