Spatial simulation of co-designed land-cover change scenarios in New England: Alternative futures and their consequences for conservation priorities

To help prepare for an uncertain future, planners and scientists often engage with stakeholders to co-design alternative scenarios of land-use change. Methods to translate the resulting qualitative scenarios into quantitative simulations that characterize the future landscape condition are needed to understand consequences of the scenarios while maintaining the legitimacy of the process. We use the New England Landscape Futures (NELF) project as a case study to demonstrate a transparent method for translating participatory scenarios to simulations of Land-Use and Land-Cover (LULC) change and for understanding the major drivers of land-use change and diversity of plausible scenarios and the consequences of alternative land-use pathways for conservation priorities. The NELF project co-designed four narrative scenarios that contrast with a Recent Trends scenario that projects a continuation of observed changes across the 18-million-hectare region during the past 20 years. Here, we (1) describe the process and utility of translating qualitative scenarios into spatial simulations using a dynamic cellular land change model; (2) evaluate the outcomes of the scenarios in terms of the differences in the LULC configuration relative to the Recent Trends scenario and to each other; (3) compare the fate of forests within key areas of concern to the stakeholders; and (4) describe how a user-inspired outreach tool was developed to make the simulations and analyses accessible to diverse users. The four alternative scenarios populate a quadrant of future conditions that crosses high to low natural resource planning and innovation with local to global socio-economic connectedness. The associated simulations are strongly divergent in terms of the amount of LULC change and the spatial pattern of change. Features of the simulations can be linked back to the original storylines. Among the scenarios there is a fivefold difference in the amount of high-density development, and a twofold difference in the amount of protected land. Overall, the rate of LULC change has a greater influence on forestlands of concern to the stakeholders than does the spatial configuration. The simulated scenarios have been integrated into an online mapping tool that was designed via a user-engagement process to meet the needs of diverse stakeholders who are interested the future of the land and in using future scenarios to guide land use planning and conservation priorities.


ABSTRACT: 13
To help prepare for an uncertain future, planners and scientists often engage with stakeholders to co-14 design alternative scenarios of land-use change. Methods to translate the resulting qualitative scenarios 15 into quantitative simulations that characterize the future landscape condition are needed to understand 16 consequences of the scenarios while maintaining the legitimacy of the process. We use the New England 17 Landscape Futures (NELF) project as a case study to demonstrate a transparent method for translating 18 participatory scenarios to simulations of Land-Use and Land-Cover (LULC) change and for understanding 19 the major drivers of land-use change and diversity of plausible scenarios and the consequences of 20 alternative land-use pathways for conservation priorities. The NELF project co-designed four narrative 21 scenarios that contrast with a Recent Trends scenario that projects a continuation of observed changes 22 across the 18-million-hectare region during the past 20 years. Here, we (1) describe the process and 23 utility of translating qualitative scenarios into spatial simulations using a dynamic cellular land change 24 model; (2) evaluate the outcomes of the scenarios in terms of the differences in the LULC configuration 25 relative to the Recent Trends scenario and to each other; (3) compare the fate of forests within key areas 26 of concern to the stakeholders; and (4) describe how a user-inspired outreach tool was developed to 27 make the simulations and analyses accessible to diverse users. The four alternative scenarios populate a 28 quadrant of future conditions that crosses high to low natural resource planning and innovation with local 29 to global socio-economic connectedness. The associated simulations are strongly divergent in terms of 30 the amount of LULC change and the spatial pattern of change. Features of the simulations can be linked 31 back to the original storylines. Among the scenarios there is a fivefold difference in the amount of high-32 density development, and a twofold difference in the amount of protected land. Overall, the rate of LULC 33 change has a greater influence on forestlands of concern to the stakeholders than does the spatial 34 configuration. The simulated scenarios have been integrated into an online mapping tool that was 35 designed via a user-engagement process to meet the needs of diverse stakeholders who are interested 36 the future of the land and in using future scenarios to guide land use planning and conservation priorities. 37

INTRODUCTION: 38
Scenario planning is a rigorous way of asking "what if?" and it can be a powerful tool for natural 39 resource professionals preparing for the future of socio-ecological systems. In the context of land-use or planning describe alternative trajectories of landscape change that would logically emerge from different 44 sets of assumptions (Thompson et al. 2012). Scenarios are not forecasts or predictions; instead, they are 45 a way to explore multiple hypothetical futures in a way that recognizes the irreducible uncertainty and 46 unpredictability of complex systems (Pedde et al. 2018). 47 Scientists are increasingly co-designing scenarios with stakeholders-i.e., groups of people who The utility of qualitative, co-designed scenarios can be enhanced by linking them to quantitative 58 representations of future land-use change, as generated by a spatially explicit simulation model. 59 However, translating between narrative scenario descriptions and quantitative models presents 60 challenges and tradeoffs related to the treatment of uncertainty, the potential to accommodate 61 stakeholders in the process, the resources required, and the compatibility with different types of 62 simulation models (see reviews of these factors in: Mallampalli  Cellular LCMs are phenomenologically driven, as opposed to process-driven, and are often used to 70 project observed trends of land use and land cover (LULC) change forward in time. By projecting observed 71 trends of LULC change, they operate with the implicit assumption that the future will be a continuation of 72 the past (e.g., Thompson et al. 2017). These models quantify the rate of LULC change and the 73 relationships between the location of observed LULC change (i.e., a change detection) and a suite of 74 spatial predictor variables--e.g., patterns of existing development, proximity to city centers or roads, 75 topography, demographics etc. Simulating these patterns into the future constitutes a "recent trends" 76 scenario, which can be used as a baseline, against which alternative scenarios can be evaluated. making authority for land use; instead, the condition of future landscape will be the product of countless 110 independent landowner decisions and a conglomerate of local, regional, and state policies.  scenarios were co-designed through a structured scenario development process that engaged > 150 117 stakeholders and scientists from throughout the study region. Using the Intuitive Logics approach to 118 scenario development popularized by Royal Dutch Shell/Global Business Network (Bradfield et al. 2005), 119 the NELF project stakeholders envisioned opposing outcomes of two key drivers of land-use change that 120 they identified as highly impactful and highly uncertain: socio-economic connectedness and natural 121 resource planning and innovation. The process resulted in a matrix of four quadrants that encompassed 122 four broad scenarios. Participants then added details about each scenario storyline in qualitative terms, 123 which took the form of ~1000 word narratives (McBride et al. 2017) and are summarized in the Scenario 124 Narratives (Table 1). Next, participants were presented with key features of the Recent Trends scenario 125 and asked to describe how land use would differ in each of the alternative scenarios using semi-126 quantitative terms. We then adjusted model input parameters to reflect the characteristics of each of 127 the four divergent scenarios. Finally, through a series of subsequent interactive webinars we worked with 128 participants to refine these parameters to ensure the scenarios captured their intent. 129 130 Connected Communities -This is the story of how a shift towards living 'local' and valuing regional self-sufficiency and local resource use increases the urgency to protect local resources.
The New England population has increased slowly over the past fifty years and most communities are coping with climate change by anchoring in place rather than relocating, making local culture and the use and protection of local resources increasingly important to governments and communities. New England has been less affected by climate change than many other regions of the U.S. in this scenario. Concerns about global unrest and the environmental impacts of global trade have led New Englanders to strengthen their local ties and become more self-reliant. These factors combine with heightened community interest and public policies to strengthen local economies and fuel burgeoning markets for local food, local wood, and local recreation.

DRIVERS: High natural resource planning & innovation / Local socio-economic connectedness
Yankee Cosmopolitan -This is the story of how we embrace change through experimentation and upfront investments. While environmental changes break records and urbanization continues to pressure natural systems, society responds with greater flexibility, ingenuity, and integration.
In this scenario, New England has experienced substantial population growth spurred by climate and economic migrants who are seeking areas less vulnerable to heat waves, drought, and sea-level rise. Most migrants are international but some have relocated from more climate-affected regions in the U.S. At the same time, a strong track record in research and technology has made New England a world leader in biotech and engineering, creating a large demand for skilled labor. The region's relative resilience to climate change and growing employment opportunities has made New England a major economic and population growth center of the U.S. Abundant forests remain a central part of New England's identity, and support increases in tourism, particularly in Vermont, Maine, and New Hampshire.

DRIVERS: High natural resource planning & innovation / Global socio-economic connectedness
Growing Global -This is the story of an influx of climate change migrants seeking refuge in New England, and taking the region by surprise. New pressures on municipal services drive a trend towards privatization. Regional to national policies have promoted global trade but global agreements to address climate change have failed.
In this scenario, by 2060, a steady stream of migrants has driven up New England's population, with newcomers seeking to live in areas with few natural hazards, ample clean air and water, and low vulnerability to climate change. This influx of people has taken the region by surprise and local planning efforts have failed to keep pace with development. The region has experienced increasing privatization of municipal services as state and local governments struggle to keep up with the needs of the burgeoning population. Trade barriers were lifted in the 2020s to counter economic stagnation and the volume of global trade has multiplied over the past 40 years as a result of increasing globalization. However, all attempts at global climate change negotiations and renewable energy commitments have failed in this globally divided world.

DRIVERS: Low natural resource planning & innovation / Global socio-economic connectedness
Go It Alone -This is the story of a region challenged by shrinking economic opportunities paired with increasing costs to meet basic needs, yet innovation is stagnant and new technologies are not rising to increase efficiency or create new opportunities. With local self-reliance and survival as the primary objectives, natural resource protections are rolled-back and communities turn heavily to extractive industries.
In this scenario, population growth in the region has remained fairly low and stable over the past 50 years as the lack of economic opportunity, high energy costs, and tightened national borders have deterred immigration and the relocation of people from within the U.S. to New England. The concurrent shrinking of national budgets and lack of global economic connections have left little leeway to deal with challenges such as high unemployment, demographic change, and climate resilience. Within New England this has resulted in the rolling back of natural resource protection policies and the drying up of investments in new technologies and ecosystem protections in response to a lack of regulatory drivers. Over the last 50 years, the region has seen the significant degradation of ecosystem services as a result of poor planning, increased pollution, and heavy extractive uses of local resources using conventional technologies.

131
Here our objectives are to: 1) assess the utility and challenges of translating qualitative scenarios into 132 spatial simulations using a cellular LCM; 2) evaluate the outcomes of the scenarios in terms of the 133 differences in the LULC configuration relative to the Recent Trends scenario and to each other; 3) 134 compare the fate the landscape in terms of development and conservation within key Impact Areas (i.e., 135 areas that have been identified as being important for conservation, wetland, flood, drinking water, 136 farmland, and or wildlife management) ( Figure 2). (4) make the scenarios and simulations available to 137 New England land use stakeholders. 138  Forest, Agriculture, Water, and a composite "Other" class that consisted of landcovers such as bare rock 154 and, wetlands which made up less than 5% of the landscape at year 2010 (Appendix I, table 1). 155 To account for regional variation in the patterns and drivers of land-cover change, we delineated 156 32 subregions within New England ( Figure 1) and independently fit the LCM to the rate and spatial 157 allocation of change within each subregion. The subregions primarily follow U.S. Census Bureau defined 158 Core Base Statistical Areas (CBSA), which represent both Census Metropolitan and Micropolitan statistical 159 areas (www.census.gov; accessed 4/20/2019). CBSAs are delineated to include a core area containing a 160 substantial population nucleus, together with adjacent towns and communities that are integrated with 161 the core in terms of economic and social factors. New England includes 27 CBSAs, however not all of New 162 England is covered by a CBSA. Accordingly, we added five rural areas to fill the gaps, for a total of 32 163 unique subregions. Among subregions, the Boston-Cambridge-Newton subregion (hereafter "Boston") is, 164 by far, the most populous; it contains the city of Boston, which is the region's largest city, and in 2010 165 accounted for 31% of the region's total population. 166 The simulation framework: 167  Simulating co-designed scenarios: 183 We simulated each of the five LULC change scenarios using Dinamica (Figure 4). The first scenario, the 184 Recent Trends, projects the types, rates, and spatial allocation of land cover change and land protection 185 observed during the period spanning 1990 to 2010. Thompson  subregions. This allowed high development growth subregions like Boston (#7) to spill over into 195 neighboring subregions. The exception to this rule was the island subregions of Nantucket (#28) and 196 Martha's Vineyard (#3), which were not allowed to spill over since they had no neighboring subregions. 197  with the stakeholders via webinars and online real-time polling to assess whether they accurately 207 captured their intended deviation from the spatial patterns present in Recent Trends. For example, the 208 Connected Communities scenario narrative stated that "New settlements tend to occur in planned urban 209 centers"; in response, we suggested that the probability of development be increased as a function of 210 proximity to urban centers and, in a webinar, the stakeholders voted on one of three such modifications 211 that differed in terms of the magnitudes of the adjustment. Table 3 shows the final spatial allocation 212 plans in conjunction with their corresponding quotes from the scenario narratives. The stakeholders 213 assumed that shifts in the LULC change regime would take some time to deviate from the Recent Trends 214 rate, so in the first ten-year time step, the rates of LULC change ramp up or down to half of their final 215 target rate ( Figure 5). 216 Table 3. Spatial Allocation Plans Narrative Quotes (Stakeholders) Spatial Allocation Plan (Modeling Team) Connected Communities 1. "From the early 2020s onward, local and regional governments have used tax incentives, public policies, and market subsidies to drive a shift toward sustainability and climate resilience." 2. "This renewed focus on community planning and protection of natural resources has advanced 'smart growth' measures that balance development needs with the need to protect natural infrastructure." 3. "New settlements tend to occur in planned urban centers…" 4. "…resulting in higher density development (in-fill), and as pockets of clustered growth at the urban fringe." 5. "Strong urban planning yields developments where more people can walk to work." 6. "With the interest in localism there is a strong focus on the protection of wildlands for wildlife and ecosystem services." 7. "State and local governments have invested greater public funding in land protection for forest health, flood control, and water quality." 8. "Municipal governments are also protecting land for public parks near population centers." 1. Probability of development is reduced by -40%:1k, -30%:2k, -20%:3k, and -10%:4k away from the coast.
2. All FEMA +1 foot sea level rise, FWS wetlands, and NHD flood risk zones are ineligible for development.
Yankee Cosmopolitan 1. "New England has experienced substantial population growth spurred by climate and economic migrants who are seeking areas less vulnerable to heat waves, drought, and sea-level rise." 1. Probability of development is reduced by 20% within 500m of the coast, -19% 1000m from the coast, -18% 1500m from the coast, down to -1% 20k from the coast. All NOAH +1 foot costal flood zones have no chance of development.
2. "Proactive city planning as well as public and private investment in infrastructure have helped to meet the needs of New England's growing population through well-planned housing, transportation hubs, and municipal services near city centers." 3. "As the population influx continues through the 2030s and 2040s, the pace of development begins to exceed the planning and physical capacity of many cities and development patterns devolve into sprawl." 4. "Smart growth, high-density urban development, and carbon offset markets have facilitated a doubling in rates of land protection within high priority conservation areas throughout the 2020s and 2030s." 5. "New urban parks track with new development." 6. "Land protection priorities focus on the maintenance of ecosystem services, particularly in southern New England where cities depend on watershed lands for low-cost, clean drinking water." 7. "In northern New England a modest increase in agriculture occurs near existing farms and some small patch farming emerges near towns to feed local niche markets." 2. Probability of development is increased by 30% within 1k of city centers with populations over 10,000, 29% within 2k, 28% within 3k, ramping down to 1% within 30k. Reduced probability of development on prime agricultural soils by 10%. All FEMA and NHD flood risk zones have probability of development reduced by 20%.
3. Mean patch size for new development has been doubled. Isometry modifier increased from 1.1 to 1.2. The ratio of new vs. expansion patches has been increased by + 0.1 for all regions (a few regions max out at 100% by expansion). From 2030 onward, patterns follow recent trends.
4. Probability of conservation has been increased by 20% on all high priority conservation areas (State Wildlife Action Plans).

Probability of new public park creation is increased by 30%
within 1k of city centers with populations over 10,000, 29% within 2k, 28% within 3k, ramping down to 1% within 30k.
6. Probability of conservation has been increased by 20% in MA, CT, and RI in the top 25% Forest to Faucets defined high importance watersheds.
7. All non-prime agricultural soils are ineligible for new agriculture. Zero probability of new agriculture within Census Urban Areas, but increase by 30% within 1k, 29% within 2k, 28% within 3k, down to 1% within 30k of the urban area boundary.
Growing Global 1. "New England is characterized by sprawling cities with poor transportation infrastructure, inefficient energy use, and haphazard expansion of residential development. Walkability in most cities is low and cars remain necessary to access services in most parts of the region." 2. "New residential and commercial development around parks serve the wealthy and perforate forests around protected lands." 3. "U.S. food exports surge in response to changing global agricultural commodity markets, and drive the conversion of forestland to farmland. These new agricultural lands mostly extend out from existing farmland, and typically take the form of large-scale, intensive production farms for commodity crops by leading multinational agri-businesses." 1. Increase probability around highways by 20%-100m 15%-200m 10%-300m 5%-400 so that cities sprawl along transportation corridors.
2. Probability of new development has been increased by 10% within 90m of all conservation area boundaries.
3. All prime agricultural soil and non-prime soils within 300m of prime soil are eligible for conversion to agriculture. Mean new agricultural patch size has been increased by 1000%. The ratio of new vs. expansion has been increased by +0.25 for all regions (some regions max out at 100% by expansion).
Go It Alone 1. Spatial allocation identical to Recent Trends 1. Spatial allocation identical to Recent Trends. Only differences are in land-use quantity Figure 5. Changes in land cover within New England over time for each LULC class and scenario. Note varying Y-axes. 217

Scenario Impacts on Conservation Priorities: 218
To explore the impacts of the scenarios, we estimated the impacts of simulated LULC change on forests 219 within each scenario on the following seven key Impact Areas. We selected these areas because they 220 serve as reasonable proxies for a range of values and conditions that are important to stakeholders 221 ( farmland of unique importance, and farmland of local importance into one "Prime 254 Farmlands" classification. 255 Impact Areas were assessed based on the amount of land available for conversion to either 256 development or conservation at the start of the simulations in 2010. Areas already developed or 257 conserved in 2010 were considered unavailable and were thus not assessed. Additionally, areas within 258 delineated Impact Areas that were ineligible for a transition based on our model rules (e.g. non-forest 259 covers such as agriculture, water and other) were not considered. 260 261

Developing outreach tool: 262
We used the scenarios and simulation products to develop an online interactive mapping tool to portray 263 the interaction between land use choices and land use outcomes in New England and support efforts by 264 community groups and conservation groups to explore how they might adapt their LULC plans and 265 conservation priorities to ensure that they are robust under an uncertain future. Farmland, and Core Forests are described within the tool. The tool is static; the underlying data and 279 calculations were completed in advance via the simulation process. Therefore, the NELF Explorer is a 280 conduit for accessing pre-computed data and visualizations. 19,265 km 2 ); there was little change (< 5%) in agricultural land cover (10,409 to 10,908 km 2 ). The largest 289 LULC change was to protected land, which increased by 123% (from 35,300 to 78,500 km 2 ). 290 Throughout the fifty-year simulation, the rate of land protection in the Recent Trends scenario was more 291 than eight times greater than the rate of development. Because Impact Areas are not evenly distributed 292 throughout New England, the spatial distribution of land protection in the Recent Trends scenario was 293 most effective for securing protection in Impact Areas that are concentrated in the north, such as Core 294 Forest, where 48% was protected and only 3% developed and TNC Priority Conservation Areas where 49% 295 was protected and only 4% developed. Impact Areas that are concentrated in the south, such as with the 296 Important Watersheds for Drinking water only 28% was Protected and11% was developed. In addition, 297 the impact of LULC change on other conservation priorities was driven by local patterns observed in the 298 historical data. For example, wetlands have regulatory protection (included in our model) and thus have a 299 low probability of development. Indeed, despite being common throughout the region, 45% of forested 300 wetland areas were protected while just 0.7% were developed (note that non-forested wetlands were 301 protected from any transition). 302

Yankee Cosmopolitan 303
The Yankee Cosmopolitan scenario envisions a future New England that is a global hub of activity, with 304 commensurate changes to land use. The population is growing much faster than Recent Trends, but, at 305 the same time, natural resource planning and innovation are a priority. To accommodate population 306 growth spurred by climate and economic migrants, development occurred at a rate 40% greater than 307 Recent Trends (136 km 2 per year). Global food supply chains required minimal agriculture expansion, 308 which was maintained at 16 km 2 per year (the same as Recent Trends). The rate of new land protection 309 was reduced in the north and increased in the south, relative to Recent Trends. Overall, across the region, 310 the rate of land protection in this scenario was 736km 2 per year, 12% lower than Recent Trends. 311 Yankee Cosmopolitan includes several modifications to the spatial allocation of LULC change in Recent 312 Trends, which were intended to minimize development within areas desirable for protection. However, 313 the large (40%) increase in the rate of development often overwhelmed modifications to the spatial 314 allocation rules. For example, the spatial allocation plan for Yankee Cosmopolitan included a reduced 315 probability of new development within flood zones (Table 3); nonetheless, forest loss within flood zones 316 by year 2060 was 86% higher than in Recent Trends. Reduced development probability in flood zones was 317 only effective in rural subregions, where there was less development pressure. In urbanizing subregions, 318 where development rates were highest even low probability sites were eventually developed. Similarly, 319 the spatial allocation plan for this scenario increased the probability of land protection within wildlife 320 habitat areas; however, the increased rate of development had a greater influence. Overall, while there 321 was a small increase in protected land within wildlife habitat areas, there was also a 49% increase in 322 developed areas, as compared to Recent Trends. Other modifications to the spatial allocation were more 323 effective. For example, this scenario envisioned more urban parks thus the spatial allocation plan 324 increased the probability of new protected lands within two km of city centers, which resulted in a 75% 325 increase in protected areas within two km of city centers, compared to the Recent Trends scenario. In 326 addition, concentrating development around city centers resulted in a similar amount of core forest to 327 the Recent Trends, despite accommodating 40% more development. 328

Connected Communities 329
The proportion of new development was within 10 km of cities among all scenario (XX% more development 346 within 10km of cities than Recent Trends) . As part of this scenario's emphasis on climate change 347 adaptation, the proportion of development within 5-km of the coast (where sea-level rise is a concern) 348 was significantly less than sprawl to an area covering more than 10,000 km2, larger in size than Tokyo, Japan. On one hand, this is 388 such a drastic change that it may seem implausible to stakeholders and thereby undermine the utility of 389 the scenario. On the other hand, the simulation is faithful to the stakeholders' storyline, which envisions 390 New England as a destination for millions of migrants fleeing the growing impacts of climate change 391 elsewhere (National Climate Assessment 2018). Specifically, the stakeholders describe: "sprawling cities 392 with poor transportation infrastructure, inefficient energy use, and haphazard expansion of residential 393 development." The plausibility of this scenario is supported anecdotally by events such as Hurricane 394 Maria, which, in 2017, displaced as many as 500,000 people from the island of Puerto Rico to the 395 mainland U.S. (Pew Research Center 2018). Given that a single storm can cause such large changes to 396 settlement patterns, it will be important to consider the consequences of scenarios, such as Growing 397 Global which push our assumptions about how the past can or cannot shape the future. Overall, the 398 simulated scenarios bound a wide range of future possibilities for the New England landscape and, as 399 such, have high potential for broadening the perspectives of planners, counteracting a general tendency 400 toward 'narrow-thinking' when planning for an uncertain future (Soll et al. 2014). 401 Our simulations effectively captured the land-use dynamics and features described in the scenario 402 storylines. Each specific modification to Recent Trends is annotated within the qualitative scenario 403 descriptions so that our stakeholders can see how their vision for each scenario was incorporated into the 404 simulation. By identifying specific quotes that referenced differences in land-use patterns, then 405 translating them into explicit rules for the spatial allocation of simulated LULC change (Table 3), we were 406 able to capture the intentions of the stakeholders in ways that had substantive and readily attributable 407 impacts on the simulated landscape. For example, simulated development surrounding the area of Keene, 408 New Hampshire (subregion 24) in Go it Alone and Yankee Cosmopolitan both have the same rate of 409 development but different spatial allocation of that development ( Figure 6). The Yankee Cosmopolitan 410 narrative described: "Proactive city planning as well as public and private investment in infrastructure 411 have helped to meet the needs of New England's growing population through well-planned housing, 412 transportation hubs, and municipal services near city centers." Thus, a spatial modifier was implemented 413 in this scenario to concentrate development close to city centers while protecting farm soils and limiting 414 development in flood zones (Table 3). Overall this approach represents an effective and transparent 415 method for bridging the gap between non-technical stakeholders who developed the scenarios and the 416 technical experts who simulated them (Mallampalli et al. 2017). We are hopeful that this clear translation 417 of the scenarios to the simulations bolsters the legitimacy and salience of the participatory scenario 418 process (sensu Cash et al 2002) and results in greater use by the stakeholders and decision-makers. 419 Figure 6. Spatial Allocation Example. Distance to Keene, NH city center. Two scenarios with same amount of development but different spatial allocation. 420 These simulations reveal much about the potential impacts of future land use on conservation priorities. 421 In general, the amount of projected LULC change affected the Impact Areas more than the differences in 422 their spatial allocation. For example, the Yankee Cosmopolitan scenario has several spatial allocation rules 423 designed to mitigate the impacts to conservation goals, including: reduced probability of new 424 development within flood zones and increased probability of land protection within wildlife habitat areas. 425 In comparison, the Go It Alone scenario has no modifications to the spatial allocation rules. However, 426 Yankee Cosmopolitan has **87%** more development than Go it Alone. So despite substantial efforts to 427 mitigate the impacts of development, the Yankee Cosmopolitan scenario resulted in more development in 428 every category of Impact Area than Go it Alone. This pattern is consistent across all scenarios and Impact 429 Areas, insomuch as the rank order of development within each impact area matched the rank order of 430 the amount of development, despite strong differences in the spatial allocation patterns (Figure 7). 431 Figure 7. Impact Areas. Inset bar charts represent the percent of each conservation priority area that was developed (bar left of zero), and conserved (bar right of zero) for each scenario at year 2060.