U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2018–1180

Prepared in cooperation with the National Park Service

Optimizing Historical Preservation Under Climate Change—

An Overview of the Optimal Preservation Model and Pilot 

Testing at Cape Lookout National Seashore
Front Cover. Portsmouth Life-Saving Station (circa 1894) in Portsmouth Village (photograph credit: 

Erin Seekamp, 2015)

Back Cover. 1873 Keeper’s Quarters (circa 1873) and Cape Lookout Lighthouse (circa 1812; 1859) 

within the Light Station Complex of Cape Lookout Village, taken from the Atlantic Ocean dunes 

(photograph credit: Erin Seekamp, 2015)
Optimizing Historical Preservation Under 

Climate Change—An Overview of the 

Optimal Preservation Model and Pilot 

Testing at Cape Lookout National Seashore

By Erin Seekamp, Max Post van der Burg, Sandra Fatorić, Mitchell J. Eaton, 

Xiao Xiao, and Allie McCreary

Prepared in cooperation with the National Park Service

Open-File Report 2018–1180

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Acting Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2019

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Suggested citation:

Seekamp, E., Post van der Burg, M., Fatorić, S., Eaton, M.J., Xiao, X., and McCreary, A., 2019, Optimizing historical 

preservation under climate change—An overview of the optimal preservation model and pilot testing at Cape Lookout 

National Seashore: U.S. Geological Survey Open-File Report 2018–1180, 46 p., https://doi.org/10.3133/ofr20181180.

ISSN 2331-1258 (online)
iii

Acknowledgments

The authors would like to thank all the individuals who participated in the workshops, meetings, 

and online elicitation exercises. We are particularly appreciative of the time, creative energy, 

and support provided by specific National Park Service personnel: Pat Kenney, former Cape 

Lookout National Seashore Park Superintendent; Jeri DeYoung, former Cape Lookout National 

Seashore Chief of Resources; Curtis Rintz, former Cape Lookout National Seashore Exhibits 

Specialist; Janet Cakir, Southeast Region Climate Change, Socioeconomics, and Adaptation 

Coordinator; Cat Hoffman-Hawkins, Climate Response Program Chief; Marcy Rockman, former 

Climate Change Adaptation Coordinator for Cultural Resources; and Brian Goeken, Technical 

Preservation Services Chief. We are also particularly appreciative of the time, creative energy, 

and support provided by the North Carolina State Historic Preservation Office (Ramona Bartos, 

Deputy State Historic Preservation Officer; and John Wood, Preservation/Restoration Specialist).

This document was developed as part of the Connecting Landscape Adaptation and 

National Cultural Resource Policy to Climate Change and Cultural Resource Adaptation 

Decisions research project. The research was supported by the U.S. Geological Survey 

(https://www.usgs.gov) through the National Climate Change and Wildlife Science Center 

(https://casc.usgs.gov/) and the Department of Interior Southeast Climate Adaptation Science 

Center (https://globalchange.ncsu.edu/secsc/) through grant agreement G15AP00141. 

Additional funding for model development was provided by the National Park Service Climate 

Change Response Program through U.S. Department of Interior Inter-Agency Agreement 

P17PG00197 (project title: Optimization Model to Support NPS Cultural Resource Management). 

See also Xiao and others (2019) for more additional model outputs than those reported here.

v

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Study Area.......................................................................................................................................................2

Model Development ......................................................................................................................................3

The Optimal Preservation Model ................................................................................................................5

Model Results and Interpretations .............................................................................................................8

Scenario 1—No Action........................................................................................................................8

Scenario 2—An Uncertain Budget....................................................................................................9

Portfolio for a Budget of $50,000 ...............................................................................................9

Portfolio for a Budget of $222,000 ...........................................................................................11

Portfolio for a Budget of $500,000 ...........................................................................................14

Scenario 3—Accounting For Periodic Funding Increases..........................................................16

Portfolio For A Budget Of $70,000 With A Surge Of $225,000 Every 5 Years.....................16

Portfolio For A Budget Of $222,000 With A Surge Of $225,000 Every 5 Years...................16

Scenario 4—Ignoring Vulnerability .................................................................................................16

Portfolio For A Budget Of $222,000 Without Vulnerability...................................................16

Scenario 5—Excluding The Attributes Of “Use Potential”..........................................................16

Portfolio For A Budget Of $222,000 Without Use Potential .................................................16

Comparing Scenarios..................................................................................................................................21

Insights From The Pilot Study ....................................................................................................................21

Considerations For Advancing The Optipres Model..............................................................................24

References Cited..........................................................................................................................................25

Appendix 1. Optimal Preservation Model Objectives, Attributes, Weights, Actions, and 

Costs.................................................................................................................................................28

Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 17 Buildings 

Among Different Scenarios ..........................................................................................................37

Appendix 3. Computer Code for Optimal Preservation Model..........................................................46
vi

Figures

 1. Timeline of the structured process used in the pilot study at Cape Lookout National 

Appendix Figures

2.1–2.7. Components of resource value under annual allocation of—

 2.1. $50,000 ..........................................................................................................................................38

 2.2. $222,000 ........................................................................................................................................39

 2.3. $500,000 ........................................................................................................................................40

 2.4. $70,000 with an additional $225,000 every 5 years ................................................................41

 2.5. $222,000 with an additional $225,000 every 5 years ..............................................................42

 2.6. $222,000 assuming no vulnerability ..........................................................................................43

 2.7. $222,000 assuming no use potential ........................................................................................44

 2.8. Accumulated values and total costs of individual buildings under each scenario .........45
vii

Table

1. Details of 17 buildings selected for pilot study........................................................................4

Appendix Tables

1.1. Historical significance’s attributes, subattributes, and metrics with scores

including weights among the attributes and subattributes.................................................29

1.2. Use potential’s attributes and metrics with scores including weights among the

attributes ......................................................................................................................................30

1.3. Use potential’s attributes and metrics with scores including weights among the

attributes. Exposure’s subattributes and corresponding data sources ............................31

1.4. Sensitivity’s subattributes and corresponding data sources..............................................31

1.5. Vulnerability’s metrics and scores...........................................................................................31

1.6. Optimal Preservation Model adaptation actions and model dynamics.............................32

1.7. Adaptation actions and maintenance costs for each of the 17 historic buildings ..........36

Optimizing Historical Preservation Under Climate 

Change—An Overview of the Optimal Preservation Model 

and Pilot Testing at Cape Lookout National Seashore

By Erin Seekamp,1 Max Post van der Burg,2 Sandra Fatorić,

1

 Mitchell J. Eaton,2 Xiao Xiao,1 and Allie 

McCreary1

1

Department of Parks, Recreation and Tourism Management, College of Natural Resources, North Carolina State University.

2

U.S. Geological Survey.

Abstract

Adapting cultural resources to climate-change effects 

challenges traditional cultural resource decision making 

because some adaptation strategies can negatively affect 

the integrity of cultural resources. Yet, the inevitability of 

climate-change effects—even given the uncertain timing of 

those effects—necessitates that managers begin prioritizing resources for climate-change adaptation. Prioritization 

imposes an additional management challenge: managers must 

make difficult tradeoffs to achieve desired management outcomes related to maximizing the resource values. This report 

provides an overview of a pilot effort to integrate vulnerability (exposure and sensitivity), significance, and use potential 

metrics in a decision framework—the Optimal Preservation 

(OptiPres) Model—to inform climate adaptation planning of a 

subset of buildings in historic districts (listed on the National 

Register of Historic Places) at Cape Lookout National Seashore. The OptiPres Model uses a numerical optimization 

algorithm to assess the timing and application of a portfolio 

of adaptation actions that could most effectively preserve an 

assortment of buildings associated with different histories, 

intended uses, and construction design and materials over a 

30-year planning horizon. The outputs from the different budget scenarios, though not prescriptive, provide visualizations

of and insights to the sequence and type of optimal actions and

the changes to individual building resource values and accumulated resource values. Study findings suggest the OptiPres

Model has planning utility related to fiscal efficiency by identifying a budget threshold necessary to maintain the historical

significance and use potential of historical buildings while

reducing vulnerability (collectively, the accumulated resource

value). Specifically, findings identify that a minimum of the

industry standard ($222,000 annually for the 17 buildings) is

needed to maintain the current accumulated resource value.

Additionally, results suggest that additional appropriations

provided on regular intervals when annual appropriations are

at the industry standard are nearly as efficient as annual appropriations at twice the rate of industry standards and increase 

the amount of accumulated resource values to nearly the same 

level. However, periodic increases in funding may increase 

the risks posed to buildings from the probability of a natural 

hazard (that is, damage or loss from a hurricane). Suggestions 

for model refinements include developing standardized cost 

estimations for adaptation actions based on square footage 

and building materials, developing metrics to quantify the 

historical integrity of buildings, integrating social values data, 

including additional objectives (such as public safety) in the 

model, refining vulnerability data and transforming the data to 

include risk assessment, and incorporating stochastic events 

(that is, hurricane and wind effects) into the model.

Introduction

Cultural resources include physical and intangible aspects 

of what is significant about our heritage, having important 

historical, cultural, scientific, or technological associations 

that provide societal meanings (National Park Service [NPS], 

1995). The U.S. Department of the Interior NPS is mandated 

“to identify, protect, and share the cultural resources under 

its jurisdiction” (NPS, 1998, p. 5), and decision making is 

predicated on recognizing variations in meaning, integrity 

(that is, “retains material attributes associated with its social 

values”), and threats (NPS, 1995, p. 11). One threat that is 

of concern to the NPS is climate change because changing 

temperatures, changing precipitation patterns, and rising seas 

increase the exposure of cultural resources to typical decay 

patterns and rates, and deferred maintenance and repair make 

them more sensitive to climate change (Rockman and others, 2016). Natural hazards, such as hurricanes and nor’easter 

storms, also increase the exposure of cultural resources in the 

near term. Moreover, the uncertainties of the timing and severity of climate change-related effects complicate managers’ 
2 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

ability to enhance the resilience of physical cultural resources, 

particularly when managers must simultaneously consider an 

assortment of vulnerable resources. The purpose of this study 

was to develop and test a decision model framework, the 

Optimal Preservation (OptiPres) Model, to integrate multiple 

considerations (including budget constraints, cultural resource 

vulnerabilities to climate-change effects, cultural resource 

conditions, heritage values, and the use potential of cultural 

resources) to inform planning decisions for adapting cultural 

resources to climate change.

Adapting cultural resources to climate-change effects 

challenges traditional cultural resource decision making 

because some adaptation strategies can negatively affect 

the integrity of cultural resources, and the timing of many 

climate-change effects are uncertain. In other words, effects to 

social values and the uncertainties of climate change increase 

the complexity of adaptation because managers may need to 

apply actions that tradeoff potential or uncertain future effects 

against more near-term maintenance of cultural resources. 

Such challenges increase the complexity of long-term planning, particularly when cultural resources exist in dynamic 

landscapes like coastal systems where stochastic storms occur. 

Additionally, the lack of sufficient financial resources to 

adequately manage all cultural resources—as evidenced by the 

backlog of deferred maintenance—necessitates that decision 

makers must consider prioritizing some resources over others. 

Prioritization imposes an additional management challenge: 

managers must make difficult tradeoffs to achieve desired 

management outcomes related to maximizing the resource 

values (for example, significance, integrity, and use potential) within cultural landscapes. Yet, when approached with a 

systematic process for addressing such complex decisions, a 

management agency can enhance the transparency of values 

embedded within planning and decision making and increase 

its ability to preserve cultural resource values for present and 

future generations.

Current policy guidance (NPS, 2014) for the stewardship 

of cultural resources in relation to climate change states that 

management decisions should be directed toward resources 

that are “both significant and most at risk.” The NPS has since 

implemented a process for assessing climate change vulnerability of coastal park assets, which includes facilities, infrastructure, and cultural resources (NPS, 2016; Peek and others, 

2017). Additionally, Fatorić and Seekamp (2017a, 2018) 

developed a framework for measuring the significance and 

use potential of one specific type of cultural resource: historic 

buildings. This report provides an overview of a pilot effort to 

integrate vulnerability (exposure and sensitivity), significance, 

and use potential metrics in a decision framework to inform 

climate adaptation planning of a subset of buildings in historic 

districts (listed on the National Register of Historic Places) at 

Cape Lookout National Seashore, North Carolina.

The decision framework, the OptiPres Model, developed 

and piloted at Cape Lookout National Seashore is an innovative approach for climate adaptation planning of an assortment 

of resources, advancing single-resource planning approaches 

described in the NPS’s Cultural Resources Climate Change 

Strategy (Rockman and others, 2016) and the Interagency 

Climate-Smart Conservation (Stein and others, 2014) guidance document. More specifically, the OptiPres Model uses 

numerical optimization methods (that is, an algorithm) to 

assess the timing and application of a portfolio of adaptation 

actions that could most effectively preserve an assortment of 

buildings associated with different histories, intended uses, 

and construction design and materials over a 30-year planning 

horizon. Such optimization approaches are widely used in 

landscape planning. For example, Westphal and others (2007) 

used an optimization model to identify sites for landscape 

reconstruction to maximize the number of bird species in the 

Mount Lofty Ranges, South Australia.

The modeling effort described in this report is the culmination of the structured decision-making (SDM) process 

implemented at Cape Lookout National Seashore that began 

with Fatorić and Seekamp’s (2017b, 2018) measurement 

framework, a project funded by the U.S. Department of the 

Interior Southeast Climate Science Center. It is our intention 

that the OptiPres Model outputs can enhance NPS managers’ 

ability to make more informed and transparent climate adaptation decisions given various uncertainties and management 

constraints. Yet, it is important to note that the OptiPres Model 

is not intended to be prescriptive. Rather, it should be used as 

one of several information sources (for example, stakeholder 

studies) for guiding climate adaptation planning and management. Additional model outputs, with slight modifications to 

the algorithm, can be found in Xiao and others (2019).

It also is important to note that the cultural resources 

addressed in the decision framework are physical historic 

assets (buildings). Although intangible cultural resources (for 

example, community practices and knowledge) are important considerations for adaptation planning, they are not 

addressed in this study. Additional research is needed that 

specifically addresses how to integrate intangible resources 

into climate adaptation planning. For example, see Henderson 

and Seekamp (2018) for a community engagement study that 

provides a first step towards developing an approach for climate adaptation planning of intangible cultural resources.

Study Area

Cape Lookout National Seashore is located on a 56-mile 

long chain of barrier islands (about 29,000 acres) on the coast 

of North Carolina. The barrier islands are subject to coastal 

dynamics that change the location of sands, tidal marshes and 

flats, and inlets; historical records document the effects of 

storm-related flooding and erosion on the islands’ evolution 

and migration over the past two centuries (Riggs and Ames, 

2007). The park unit has two settlements that have been designated on the National Register of Historic Places (NRHP) as 

historic districts: (1) Portsmouth Village (designated in 1976) 

and (2) Cape Lookout Village (designated in 2000). Most 
Model Development 3

buildings in these villages experience periodic but recurring 

flooding after storms. Portsmouth Village has a traditional 

village feeling, with community buildings (church, post office 

and general store, and school) and private residences, as 

well as a former Life-Saving Service station. Although Cape 

Lookout Village also has ties to Federal maritime history (that 

is, the Cape Lookout Light Station Complex was listed on the 

NRHP in 1972, and the Cape Lookout Coast Guard Station 

Complex was listed on the NRHP in 1988), and some former 

residences are linked to this history, the 14 residential buildings (one of which is a former Life-Saving Service station) 

are not arranged as a traditional village but rather as separate 

vacation and secondary homes or seasonal fishing camps.

Although Cape Lookout National Seashore has archeological sites, cemeteries, and cultural artifacts associated with 

World War II military installments, we restricted our pilot 

study to a subset of historic buildings (n=17), predominately 

pre-World War II, to test the OptiPres Model before investing further into its development. With the guidance of park 

managers, we selected the buildings to represent a range of 

historic periods and occupational uses. During the selection 

discussions with the park superintendent and the park chief 

of resources, we sought variability in the current physical 

condition of buildings and vulnerability (that is, exposure and 

sensitivity) to climate-change effects (table 1). This initial 

assessment of exposure and sensitivity (that is, vulnerability) 

was based on park managers’ knowledge of prior flooding 

and storm-related damage. It is important to note that few 

buildings at Cape Lookout National Seashore were of low or 

moderate vulnerability, which was confirmed by the vulnerability assessment by Peek and others (2017).

Model Development

The development of the OptiPres Model represents a 

continuation of a SDM process described by Fatorić and 

Seekamp (2017b). SDM is rooted in decision analysis and 

behavioral decision theory (Gregory and others, 2011; Runge 

and others, 2013) and is considered a transparent and collaborative approach for supporting informed and defensible 

decisions (Irwin and others, 2011). The SDM process breaks 

complex decisions into six primary components that can be 

addressed individually and then reintegrated to identify a 

solution: (1) problem—defining a clear problem statement; 

(2) objectives—identifying participants’ values and translating

these into measurable objectives; (3) alternatives—specifying

a set of available actions that are viewed as possible alternatives for achieving defined objectives; (4) consequences—

predicting and quantifying the outcomes of alternative actions

in terms of stated objectives; (5) tradeoffs—when objectives

are in competition, a value-based evaluation of tradeoffs

among objectives for any given action is required; and

(6) decision—integrating the previous components allows the

decision maker to select the action that provides the highest

likelihood of achieving the specified objectives (Runge and 

others, 2013).

This structured process can facilitate transparency and, 

hence, legitimacy and buy-in for climate adaptation decisions, 

particularly in situations with high uncertainty (for example, 

financial and climate). The advantage of using such a decision 

process is the explicit valuation of decision makers’ and stakeholders’ preferences and distinguishing these from predictions 

of the outcomes of implementing a decision (that is, objective 

science; Gregory and others, 2011; Runge and others, 2013). 

To the best of our knowledge, this project represents the 

first application of an SDM process in the context of climate 

change adaptation for cultural resource preservation.

Because the purpose of this report is to present the 

OptiPres Model and describe how its outputs may inform 

climate adaptation planning efforts, we provide an overview of 

the structured process used that resulted in the OptiPres Model 

in figure 1. This process included an initial workshop at Cape 

Lookout National Seashore, followed by iterative meetings 

with Cape Lookout National Seashore managers and North 

Carolina State Historic Preservation Office managers and 

staff, online expert elicitations, and two workshops to expand 

the expert elicitation to broader audiences at (1) the 2016 

George Wright Society annual conference and (2) the National 

Conference of State Historic Preservation Officers. Additional 

details on the earlier stages of the process that resulted in the 

historical significance and use potential attributes and metrics 

were provided in Fatorić and Seekamp (2017a, 2017b, 2018).

The problem statement that was finalized at the first 

workshop at Cape Lookout National Seashore (together 

with its relevant elements shown in parentheses) stated the 

following: climate change is threating cultural resource 

preservation at coastal national park units. The NPS (decision 

maker) wants to develop a transparent and objective decision framework that will help guide their funding allocations 

(action) toward cultural resource adaptation efforts within 

Cape Lookout National Seashore that includes two historic 

districts, Portsmouth and Cape Lookout Villages, and their 

associated buildings (scope). Although the funding allocation 

decisions (within budget constraints) for cultural resource 

maintenance or additional preservation treatments are made 

annually, the NPS’ vision for managing cultural resources 

looks forward over the next 30 years (timing) and aims to 

incorporate fiscal, climate, and environmental uncertainties 

(uncertainty). Given legal requirements (constraint) and NPS’ 

mission (trigger), the decision framework would consider the 

nature and intent of the National Historic Preservation Act and 

the NPS’ stewardship responsibilities.

The objectives that were refined throughout the process 

included maintaining historical significance, maximizing the 

use of historic buildings (hereafter “maximizing use potential”), maximizing financial efficiency, and minimizing climate 

vulnerability (exposure and sensitivity to sea level rise and 

storm-related flooding effects) in adapting historic buildings. 

The first three objectives (maintaining historical significance, maximizing use potential, and maximizing financial 
4 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Table 1. Details of 17 buildings selected for pilot study.

Selection criteria

Historic district Building (circa) Building abbreviation Condition1 Vulnerability2 Use3

Iconic buildings

Cape Lookout Village Cape Lookout Lighthouse 

(1812; 1859)

Lighthouse Fair Moderate Open to public 

visitation

Portsmouth Village Methodist Church (1840; 

1915)

Church Fair High Open to public 

visitation

Early Federal maritime history

Cape Lookout Village Cape Lookout Life-Saving 

Station (1887; 1958)

Lifesaving Station CLV Poor Moderate No use

Portsmouth Village Portsmouth Life-Saving 

Station (1894)

Lifesaving Station PLV Fair High Open to public 

visitation

Mid-Federal maritime history

Cape Lookout Village 1873 Keeper's Quarters 

(1873)

Keeper's Quarters Fair High Open to public 

visitation and 

operational use

Cape Lookout Village 1907 Keeper's Quarters 

(1907; 1958)

1907 Keeper's Quarters Fair Moderate No use

Late maritime history

Cape Lookout Village Jetty Workers House I 

(1915)

Jetty Workers House 1 Fair High No use

Cape Lookout Village Jetty Workers House II 

(1920)

Jetty Workers House 2 Poor High No use

Secondary buildings within a complex of buildings

Cape Lookout Village Coast Guard Station Galley 

(1917)

Galley Fair Low No use

Portsmouth Village Portsmouth Life-Saving 

Station Summer Kitchen 

(1894)

Summer Kitchen Good High Operational use

Community buildings

Portsmouth Village Portsmouth Island 

Schoolhouse (1910)

School Fair High Open to public 

visitation

Portsmouth Village Portsmouth Island Post 

Office and General Store 

(1900)

Post Office Fair High Open to public 

visitation

Residential buildings

Cape Lookout Village Gordon Willis House 

(1950)

Gordon Willis House Fair High No use

Cape Lookout Village O'Boyle Bryant House 

(1938)

O'Boyle Bryant House Poor Moderate No use

Portsmouth Village Washington–Roberts House 

(1840)

Washington–Roberts 

House

Good High Open to public 

visitation

Portsmouth Village Frank Gaskill House (1930) Frank Gaskill House Poor High No use

Portsmouth Village Henry Pigott House (1902) Henry Pigott House Good High Open to public 

visitation

1

Condition was determined by using the List of Classified Structures (LCS) condition scores and reviewed by the park superintendent and chief of resources 

to confirm or modify current condition status.

2

Vulnerability was determined by the park superintendent and park chief of resources and confirmed by the vulnerability assessment conducted by Peek and 

others (2017).

3

Visitation and operational use were determined by the park superintendent and chief of resources.
The Optimal Preservation Model 5

efficiency) are considered fundamental objectives (the ends to 

be achieved). The fourth objective (minimizing climate vulnerability) is a means objective (the way in which the fundamental objectives can be achieved).

Other terminology used in this report include “attribute” 

(that is, an important and measurable characteristic of an 

objective that helps define its meaning and value; synonymous 

with “performance metric”), “metric” (the unit of measurement that is applied to each attribute), “score” (the numeric 

value that represents each level of a metric and the scaled 

difference between each level of a metric), and “weight” (the 

importance of each attribute relative to all other attributes).

The Optimal Preservation Model

The purpose of the OptiPres Model is to provide decision makers with guidance on how to best manage multiple 

historic buildings over time. More specifically, the model 

uses an optimization algorithm to evaluate tradeoffs among 

(1) investing in actions that maintain or preserve resources 

in situ, (2) investing in actions that preserve a structure but 

remove it from its historical context, or (3) making triage decisions to free up resources for more costly actions. The model 

selects the combination of investments that provides the most 

resource value to the decision maker over a specified period 

and budget constraint.

We have provided visual descriptions of optimal investment portfolios (sequences of actions applied to a set of buildings; hereafter “portfolio” or “portfolios”) to aid with data 

interpretation. Managers using this model should recognize 

that the model outputs (that is, visualizations) are not prescriptive (that is, do not provide a specific path for implementing 

adaptation actions) but rather are descriptive (that is, demonstrate the patterns of, or strategic approaches for, optimal 

actions given specific budget constraints) and should be used 

to inform decision making. In this report, we demonstrate the 

use of this model assuming the objective is to maximize total 

resource value (historical significance and use potential) over 

a 30-year planning horizon.

It is important to note specific limitations related to 

the use of a 30-year planning horizon. For example, climate 

change scenarios and land-cover change projections change 

as forecasting science becomes more fine-tuned, and current 

models highlight that drastic sea level rise effects may not 

be actualized in 30 years. Managers may find that inundation will occur at increased or decreased rates compared to 

the forecasting scenario used in this study (Representative 

Concentration Pathway [RCP] 8.5), which will enhance or 

Figure 1. Timeline of the 

structured process used in the 

pilot study at Cape Lookout 

National Seashore.
6 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

limit the effectiveness of some adaptation strategies in a 

30-year planning horizon.

We developed an objective function, or a numerical

expression of the statement above, which integrates weighted 

resource value attributes related to historical significance and 

use potential (for specific details, see Fatorić and Seekamp, 

2017a, 2018), and nonweighted vulnerability attributes (that 

is, exposure and sensitivity data) for flooding-related coastal 

climate change threats (for specific details, see NPS, 2016; 

Peek and others, 2017).

The historical significance attributes include the 

following:

• Association with fundamental purpose of the park unit,

• Condition of the building,

• Historic character (a weighted average of two subattributes: defining character and uniqueness to the park),

and

• National Register (a weighted average of two subattributes: spatial significance and eligibility).

The use potential attributes include the following:

• Operational use,

• Visitor use,

• Interpretive use,

• Third-party use, and

• Scientific use.

The exposure attributes include the following:

• Flooding exposure (based on Federal Emergency Management Agency flood maps),

• Storm surge estimates (mean high tide during category 3 hurricanes),

• Sea level rise projections for 2050 (under a high,

RCP 8.5 emission scenario),

• Erosion and coastal proximity, and

• Evidence of historical flooding.

The sensitivity attributes include the following:

• Flood damage potential,

• Storm resistance,

• Prior storm damage, and

• The presence of protective engineering.

The vulnerability attributes include the following:

• Exposure and

• Sensitivity.

More details for the historical significance, use potential, exposure, sensitivity, and vulnerability attributes, 

including metrics and scores, are provided in appendix 1 

(tables 1.1–1.5).

Under specific budget allocations, the model searches 

for optimal combinations of adaptation action applied to each 

building over a 30-year time horizon. Adaptation actions were 

developed based on those listed in the NPS Cultural Resource 

Climate Change Strategy (Rockman and others, 2016). The 

cost of each action is building-specific, and the total annual 

cost of these actions must stay under the annual budget cap or 

constraint. The available adaptation actions (fig. 2) include 

the following:

• Preservation (core and shell) using historic materials,

• Preservation (core and shell) using resilient materials,

• Elevate,

• Relocate,

• Relocate and elevate,

• Document and monitor, and

• Active removal.

It is important to note that “relocate and elevate” was included 

as one adaptation action for the buildings in Portsmouth 

Village. The most ideal relocation zones (mapped by project collaborators in the Program for the Study of Developed 

Shorelines at Western Carolina University who conducted the 

Vulnerability Assessment for the NPS) were in an area that 

experiences periodic standing water after storms (verified by 

Cape Lookout National Seashore staff), which made relocation 

as a stand-alone adaptation action unfeasible. Additionally, 

the relocation zone maps illustrated that there is not a suitable 

location to move the Lighthouse or the Keeper’s Quarters at 

the Light Station Complex area within Cape Lookout Village; 

the Galley at the Cape Lookout Coast Guard Complex was the 

only building with a low vulnerability score and, thus, relocation was not an applicable adaptation strategy.

All the adaptation action cost estimates include costs 

affiliated with documenting each building in its new condition (and for a historic structures report if one has yet to be 

written), as well as interpreting (minimally or extensively) the 

way the park has adapted each building to minimize climatechange effects. Additional actions that can be applied within 

the model include no action and annual maintenance. We did 

not include annual inflation rates within the cost estimates 

or within the annual budget allocations. A full description 

of the actions is provided in appendix 1, table 1.6, and the 

costs applied for each action to each building are provided in 

appendix 1, table 1.7. It is important to note that the costs estimated for each type of action being applied to each building 

are conservative (understated) given the additional burden of 

transportation and lodging needed at Cape Lookout National 
The Optimal Preservation Model 7

Seashore and that they were developed with the assumption of 

the NPS performing the work (not contracted work); however, 

the costs were consistently estimated based on building type 

and size. More research is needed to enhance the accuracy of 

these costs when the OptiPres Model is transferred to other 

park units.

The model uses a stochastic search algorithm (that is, 

simulated annealing) that randomly picks 1 year and one 

building and then randomly selects an action. It then projects 

the effect of that single change on each of the metrics, beginning with the initial conditions, over all 30 years. If the total 

resource value improves because of the change, then the 

change is retained until a better one is found. If the resource 

value does not improve, then the change is rejected and 

another one is selected. Additional model parameters are used 

to control how selective the algorithm is about how large an 

improvement is required for acceptance. If run many millions 

of times, the algorithm should converge on a near-optimal 

solution. In order to ensure this was the case, we also applied 

a local search algorithm in between runs of the simulated 

annealing algorithm. The dynamics of the projection over time 

are specific to the actions applied. As such, each action can 

affect the relative resource value of any given building (positively or negatively), as well as reduce the vulnerability of a 

specific building (fig. 3). More specific details on the model 

dynamics are provided in appendix 1, table 1.6.

We performed all our analyses in the R programming 

environment (R Core Development Team, 2017). Because 

of the large number of possible combinations of resources 

and actions, running the optimization algorithm in R would 

have taken a prohibitively long time. Instead, we wrote both 

the simulated annealing and local search algorithms in C++ 

and used the Rcpp (Eddelbuettel and Francois, 2011) and 

RcppArmadillo (Eddelbuettel and Sanderson, 2014) packages 

to embed the code in R as a function (see appendix 3 documents available for download at https://doi.org/10.3133/

ofr20181180). We then ran each of the different scenarios in R 

on the YETI High Throughput Computing System maintained 

by the U.S. Geological Survey.

We based the range of budget allocations included in this 

pilot study on realistic assumptions, including a no action scenario. We estimated the industry standard for continual preservation of buildings in these districts (inspection, corrective 

maintenance, preventative maintenance, cyclic maintenance, 

and recurring maintenance) to be $222,000 annually. We 

set the “low” range of budget allocations at $50,000 (nearly 

$20,000 less than what would be required to perform only 

Figure 2. Annual alternative actions considered in the Optimal Preservation Model. Primary categories included deferring action on a 

structure for a given year (no action), actions that are considered routine maintenance (annual maintenance), and proactive or reactive 

alternatives designed to adapt buildings to climate impacts (adaptation actions). The latter category includes seven distinct alternatives 

available to managers (middle column), each of which may share component subactions with other alternatives (right column).
8 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

annual maintenance on each of the 17 buildings within a year). 

We set the “high” range of budget allocations at $500,000 

(roughly twice the industry standard). To explore the uncertainty related to budget allocations, we ran 11 budget scenarios 

ranging from the low to the high allocations in $50,000 intervals, including one at $222,000.

Additionally, we included several other planning scenarios in the model runs. Specifically, we explored the 

outcome if annual budgets were substantially increased (for 

example, through competitive grants or donation funding) 

every 5 years. For this scenario, we set the annual allocation at $222,000 with $250,000 additional funding added 

in years 5, 10, 15, 20, 25, and 30. We ran a similar scenario 

with a reduced annual allocation of $70,000 (more realistic in 

terms of actual park budget funding received in recent years) 

and the same $250,000 increase every 5 years. In another 

scenario, we removed vulnerability from the model to explore 

how sensitive the model is to the vulnerability metrics. In a 

final scenario, we set the weight of the use potential value to 

zero so that the model only considers the buildings’ historical 

significance when calculating total resource values. We used 

this last scenario to test the importance of use potential, which 

received a lower weight than historical significance and was 

not as dynamic a variable as historical significance in terms of 

the effect of actions.

Model Results and Interpretations

We tested the behavior and summarized the output of 

the OptiPres Model under five different planning scenarios: 

(1) a baseline scenario of expected dynamics if no actions are

implemented to maintain buildings in the historic districts,

(2) an uncertain budget, (3) periodic funding increases,

(4) ignoring buildings’ vulnerability, and (5) excluding buildings’ use potential from the calculation of resource value.

Resource value (that is, weighted sum of historical significance attributes and use potential attributes) is a measurement

of overall management performance, where higher resource

values mean better performance. The accumulated resource 

value 90 serves as the reference point for all scenarios because 

it is the sum of all 17 buildings’ historical significance 

scores and use potential scores, divided by the buildings’ 

vulnerability scores, in planning year 1.

The five planning scenarios were selected because NPS 

personnel perceived these as feasible future managerial contexts, they were eventualities that the NPS personnel involved 

in the study wanted to explore during this pilot project, or 

both. Limited and uncertain budgets are status quo for many 

cultural resource managers, and periodic budget allocations 

enable special projects. Exploring the exclusion of vulnerability and use potential allows managers to better understand the 

effect of these objectives on model outcomes and enables the 

research team to evaluate the model’s performance. To assist 

in the interpretation of the results, we have included the costs 

of each action for the 17 buildings in appendix 1, table 1.7.

It is important to note that the modeling scenario results 

did not select some adaptation actions. The negative effect 

to overall resource value for two actions (that is, document 

and monitor, and active removal) seems to be driving the 

elimination of these actions for the optimal solutions, despite 

document and monitor having relatively low costs. Additionally, core and shell preservation with resilient materials did 

not appear in the modeling results. Because flooding is the 

primary climate-change effect included in the vulnerability 

attributes, a building’s vulnerability score is not substantially 

affected by this action, which includes costs more likely affiliated with preventing rain and wind damage (for example, tin 

roofs and hurricane roof clips). Therefore, it is logical that the 

model finds the core and shell preservation with historic materials more optimal because historic materials do not negatively 

affect a building’s resource value to the same extent as using 

more modern, storm-resistant materials.

Scenario 1—No Action

To illustrate the changes in resource values of buildings 

under different planning scenarios, a baseline scenario was 

Figure 3. A conceptual 

diagram of the Optimal 

Preservation Model dynamics 

and the relations between 

actions, objectives, and values.
Model Results and Interpretations 9

created. Under this scenario, no actions are applied to any 

buildings over the 30-year period. We estimated the accumulated resource values of all buildings at the beginning of the 

30-year period (“beginning values” =90) and the accumulated

values of all buildings at the end of 30-year period (“ending

values”=52; fig. 4). The accumulated resource value of the

historic buildings decreases rapidly with no adaptation actions

taken, resulting in less than 60 percent of the original value

remaining at the end of 30-year period. The substantial decline

of resource value is caused by continuous decay of the buildings’ condition and the lack of improvement in vulnerability

scores under the “no action” scenario.

We also estimate the percentage of current and future 

resource value for each building under the “no action” scenario (fig. 5). The percentages that each building contributes to 

the accumulated resource value at the beginning of 30-year 

period is displayed in the chart on the left side of figure 5; 

percentages at the end of 30-year period are displayed to the 

right. The individual resource values of buildings were nearly 

equivalent at the beginning of the period, whereas substantial 

differences in remaining value are expected by the end of the 

30-year period with no actions applied. This finding suggests

that dynamics of vulnerability and buildings’ condition are

operating asymmetrically across the study area. The Lighthouse, Galley, Lifesaving Station, and 1907 Keepers Quarters

at Cape Lookout Village account for larger percentages of

the accumulated resource value than other buildings, whereas

several buildings at Cape Lookout Village (O’Boyle Bryant,

Jetty Workers House 1, Jetty Workers House 2, and Gordon

Willis House) account for relatively small percentages of

resource values.

Scenario 2—An Uncertain Budget

We simulated the effect of an uncertain budget by running the model under a range of budget levels, from $50,000 

to $500,000 in steps of $50,000. The expected total resource 

value of the optimal portfolio of actions applied across the 

17 historic buildings for the budget levels is displayed in 

figure 6. These results suggest at least three things: (1) that 

spending any money to manage even a subset of buildings 

is better than doing nothing; (2) that spending more money 

leads to improved management performance; and (3) that for 

this range of budgets examined, the relation between budget 

and expected benefit does not result in an obvious “shoulder” in the curve, making it difficult to identify the budget 

level at which the cost-benefit ratio changes. In the following 

sections, we present the management portfolios used to generate figure 6. Because the analysis of these portfolios requires 

examining multiple parts of the model, we will only present 

results for the $50,000, $222,000, and $500,000 budget levels.

Portfolio for a Budget of $50,000

The total annual costs for maintenance of all buildings, $67,800 (appendix 1, table 1.7), was more than available under this scenario, limiting the number of buildings 

that could receive even minimal attention. The optimal set 

of actions under the $50,000 budget suggests that a focus on 

maintaining 13 of the 17 buildings leads to the best management outcome (fig. 7). The percentage of total resource value 

and relative total cost of each building is provided in figure 8. 

The resource values of two unmanaged buildings (Gordon 

Willis House and O’Boyle Bryant House at Cape Lookout Village) declined substantially and accounted for approximately 

1 percent of the accumulated resource value of all buildings. 

This budget allocation results in declining condition for all 

the buildings, declining significance for the four unmanaged 

buildings (“remaining significance” curve), stable use potential of all the buildings (“use potential” curve), and slightly 

declining resource value for each of the buildings, with most 

drastic declines for the four unmanaged buildings (“resource 

value” curve; appendix 2, fig. 2.1). Despite the relatively 

stable “use potential” curve, the declines in condition of all 

Figure 4. Accumulated resource values of all buildings at the 

beginning and end of the 30-year planning horizon under a “no 

action” scenario. Units of accumulated resource values are 

relative and on a constructed, composite scale.

Beginning values Ending values

Scenarios

Accumulated resource values

80

100

60

40

20

0
10 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore Lighthouse CLV (10%) Keeper’s Quarters CLV (7%) 1907 Keeper’s Quarters CLV (8%) Lifesaving Station CLV (8%) O’Boyle Bryant House CLV (2%) Galley (Coast Guard CLV) (11%) Jetty Workers House 1 CLV (4%) Gordon Willis House CLV (2%) Jetty Workers House 2 CLV (4%) Church PV (6%) School PV (5%) Post Office PV (5%) Lifesaving Station PV (6%) Summer Kitchen PV (7%) Washington−Roberts House PV (6%) Frank Gaskill House PV (4%) Henry Pigott House PV (5%) Original value (accumulated value: 90) Lighthouse CLV (11%) Keeper’s Quarters CLV (8%) 1907 Keeper’s Quarters CLV (8%) Lifesaving Station CLV (8%) O’Boyle Bryant House CLV (2%) Galley (Coast Guard CLV) (11%) Jetty Workers House 1 CLV (3%) Gordon Willis House CLV (1%) Jetty Workers House 2 CLV (3%) Church PV (6%) School PV (5%) Post Office PV (5%) Lifesaving Station PV (7%) Summer Kitchen PV (7%) Washington−Roberts House PV (6%) Frank Gaskill House PV (4%) Henry Pigott House PV (5%) No action (accumulated value: 52) Figure 5. Percentages of total resource value for each building under a “no action” scenario. Units of accumulated value at beginning and end of the 30-year time horizon (90 and 52, respectively) are relative and on a constructed, composite scale. [CLV, Cape Lookout Village; %, percent; PV, Portsmouth Village] Caption. Methodist Church (circa 1840; 1915) in Portsmouth Village 

(photograph credit: Erin Seekamp, 2015)

Caption. Former U.S. Coast Guard Station in Cape Lookout Village (photograph credit: Erin Seekamp, 2015)
Model Results and Interpretations 11

17 buildings suggest that an annual budget of $50,000 is 

insufficient to enable the continued use of buildings for park 

operations, for public visitation, or both.

The optimal solution seems to suggest that two of the 

buildings (Gordon Willis House and O’Boyle Bryant House at 

Cape Lookout Village) with the lowest beginning significance 

scores (the “remaining significance” curve begins near 0.2), 

which also have low use potential scores (the “use potential” curve begins near 0.0), are not high-priority buildings 

(see appendix 2, fig. 2.1). However, the two other buildings 

selected to be unmaintained during the 30-year planning 

horizon (the Keeper’s Quarters at Cape Lookout Village and 

the Church at Portsmouth Village) are likely high priorities for 

park managers, and the loss of significance could represent an 

undesired management situation because the Keeper’s Quarters functions as a visitor center and houses volunteers, and 

the Church, an iconic building in Portsmouth Village, serves 

as a meeting place for the Friends of Portsmouth Island. It is 

important to note that this finding is likely related to the fact 

that managers placed higher weight on historical significance 

than on use potential. If use potential was given more weight, 

it is possible that buildings that are used for operations or open 

for visitation would be selected when annual budget allocations are insufficient to simply maintain all buildings. Given 

the current weighting scheme, the model prioritizes buildings and management options in such a way that (1) the full 

$50,000 annual budget is expended and (2) the highest total 

resource value can be achieved. This suggested that the four 

buildings selected for “no action” minimized losses to total 

resource value and—under the current specification of objectives, attributes, and their weights—should go unmanaged for 

the entire 30-year horizon. However, the declines in condition 

for all buildings (even those receiving annual maintenance) 

indicates that none will be suitable for park operations, visitor 

access, or third-party use within 20 years; we recognize that 

this model is not fully accounting for declines in use potential 

and are working to rectify this limitation for future applications of the OptiPres Model.

Portfolio for a Budget of $222,000

The optimal strategy under this budget allocation 

suggested relocation (or elevation and relocation) of some 

buildings during the planning period and that other buildings 

should receive core and shell preservation treatments early in 

the planning window (fig. 9). Funds to perform annual 

maintenance are sufficient for each of the 17 buildings under 

this scenario. However, foregoing annual maintenance on 

some buildings provided enough savings in some years to 

enable higher-cost adaptation actions (for example, relocation, elevation, and core and shell preservation) to be applied 

to other buildings; in this scenario, the budget was only 

large enough to consider those buildings that had the lowest 

costs for this class of actions. The consequence of trading 

off management of some buildings and not managing others, 

is that the resource value of those structures not receiving 

preservation or adaptation treatments (that is, those receiving 

‘no action’ or ‘annual maintenance’) tended to decline slightly 

faster. Thus, actions that required short-term neglect of some 

buildings seemed to be pushed to the end of the planning 

horizon because that preserved the most resource value for the 

longest period.

Under this budget allocation, the Gordon Willis House 

and O’Boyle Bryant House at Cape Lookout Village are now 

candidates for relocation. This had the effect of increasing 

their condition, while simultaneously lowering their remaining historical significance (appendix 2, fig. 2.2). This same 

pattern of changes to condition and historical significance 

also occurred for the Frank Gaskill House and Summer 

Kitchen at Portsmouth Village and Jetty Worker’s House 1 at 

Cape Lookout Village. The buildings selected are associated 

with relatively low costs for relocation (most cost-effective

way to reduce vulnerability and improve accumulated

resource value).

The total resource value under this scenario increased by 

nearly 50 percent of the value under the previous scenario of 

a $50,000 annual budget. The relative proportion of accumulated value of each building under this budget differed 

from the previous scenario (fig. 10). Relative to all buildings, 

the Summer Kitchen at Portsmouth Village had the highest 

accumulated value. The Galley Lighthouse at Cape Lookout 

Village and Frank Gaskill House at Portsmouth Village also 

Annual budget, in thousands of dollars

Expected total resource value

100 200 300 400 500

40

60

80

100

120

140 Expected total resource value

Total resource value when no management

is applied during the same period

Figure 6. Expected total resource value of the optimal 

management portfolio at the end of the 30-year period, as a 

function of annual budget and compared to expected total 

resource value when no management is applied during the same 

period. Units of accumulated resource values are relative and on 

a constructed, composite scale.
12 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore Lighthouse CLV (11%)

Keeper’s Quarters CLV (5%)

1907 Keeper’s Quarters CLV (9%) Lifesaving Station CLV (9%)

O’Boyle Bryant House CLV (1%)

Galley (Coast Guard CLV) (12%)

Jetty Workers House 1 CLV (4%)

Gordon Willis House CLV (1%)

Jetty Workers House 2 CLV (4%)

Church PV (4%)

School PV (5%)

Post Office PV (6%)

Lifesaving Station PV (7%) Summer Kitchen PV (7%)

Washington−Roberts House PV (6%)

Frank Gaskill House PV (4%)

Henry Pigott House PV (5%)

Accumulated value (77)

Summer Kitchen PV (5%)

Total cost ($1,500,000)

Lifesaving Station CLV (16%)

O’Boyle Bryant House CLV (0%)

Galley (Coast Guard CLV) (7%)

Jetty Workers House 1 CLV (5%)

Gordon Willis House CLV (0%)

Jetty Workers House 2 CLV (5%)

Church PV (0%)

School PV (5%)

Post Office PV (5%)

Lifesaving Station PV (14%)

1907 Keeper’s Quarters CLV (9%)

Keeper’s Quarters CLV (0%)

Lighthouse CLV (11%)

Washington−Roberts House PV (7%)

Frank Gaskill House PV (5%)

Henry Pigott House PV (7%)

Figure 8. The proportion of each building’s accumulated value and total cost under scenario 2 and an annual budget of $50,000. Total accumulated resource value and total 

Figure 7.

scenario expenditure are provided in parentheses after the figure titles, respectively. [CLV, Cape Lookout Village; %, percent; PV, Portsmouth Village]

Optimal actions identified under scenario 2 and a $50,000 annual budget allocation. [CLV, Cape Lookout Village; PV, Portsmouth Village]

Year

13579 11 13 15 17 19 21 23 25 27 29

Lighthouse CLV

Keeper’s Quarters CLV

1907 Keeper’s Quarters CLV

Lifesaving Station CLV

Galley (Coast Guard CLV)

O’Boyle Bryant House CLV

Gordon Willis House CLV

Jetty Workers House 2 CLVJetty Workers House 1 CLV

School PV

Church PV

Post Office PV

Lifesaving Station PV

Summer Kitchen PV

Washington−Roberts House PV

Henry Pigott House PV

Frank Gaskill House PV Elevate and relocate

RelocateElevateCore and shell preservation (resilient materials)Core and shell preservation (historic materials)Active removalDocument and monitorAnnual maintenanceNo action

Historic buildings
Model Results and Interpretations 13

Accumulated value (101) Total cost ($2,941,200)

Lighthouse CLV (8%)

Keeper’s Quarters CLV (6%)

1907 Keeper’s Quarters CLV (7%)

Lifesaving Station CLV (7%) O’Boyle Bryant House CLV (3%)

Galley (Coast Guard CLV) (9%)

Jetty Workers House 1 CLV (7%)

Gordon Willis House CLV (3%)

Jetty Workers House 2 CLV (3%)

Church PV (5%)

School PV (4%)

Post Office PV (4%)

Lifesaving Station PV (5%) Summer Kitchen PV (13%)

Washington−Roberts House PV (4%)

Frank Gaskill House PV (7%)

Henry Pigott House PV (4%)

Lifesaving Station CLV (7%)

Summer Kitchen PV (8%)

O’Boyle Bryant House CLV (9%)

Galley (Coast Guard CLV) (4%)

Jetty Workers House 1 CLV (9%)

Gordon Willis House CLV (7%)

Jetty Workers House 2 CLV (2%)

Church PV (6%)

School PV (4%)

Post Office PV (4%)

Lifesaving Station PV (9%)

1907 Keeper’s Quarters CLV (5%)

Keeper’s Quarters CLV (6%)

Lighthouse CLV (16%)

Washington−Roberts House PV (4%)

Frank Gaskill House PV (9%)

Henry Pigott House PV (3%)

Figure 10. The proportion of each building’s accumulated value and total cost under scenario 2 and an annual budget of $222,000. Total accumulated resource value and total Figure 9.scenario expenditure are provided in parentheses after the figure titles, respectively. [CLV, Cape Lookout Village; %, percent; PV, Portsmouth Village]

Optimal actions identified under Scenario 2 and a $222,000 annual budget allocation. [CLV, Cape Lookout Village; PV, Portsmouth Village]

Year

13579 11 13 15 17 19 21 23 25 27 29

Elevate and relocateRelocateElevateCore and shell preservation (resilient materials)Core and shell preservation (historic materials)Active removalDocument and monitorAnnual maintenanceNo action

Lighthouse CLV

Keeper’s Quarters CLV

1907 Keeper’s Quarters CLV

Lifesaving Station CLV

Galley (Coast Guard CLV)

O’Boyle Bryant House CLV

Gordon Willis House CLV

Jetty Workers House 2 CLVJetty Workers House 1 CLV

School PV

Church PV

Post Office PV

Lifesaving Station PV

Summer Kitchen PV

Washington−Roberts House PV

Henry Pigott House PV

Frank Gaskill House PV

Historic buildings
14 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

contributed disproportionately to accumulated resource value 

under this scenario.

This scenario’s results (that is, the industry standard) 

illustrate that the available budget context affects the decision; that is, buildings regarded as not worth managing when 

budgets are low (figs. 7–8) may be worth managing when 

additional resources are available (figs. 9–10). Also, the additional funding made four structures (Lifesaving Station, Post 

Office, and School at Portsmouth Village; and Galley [Coast 

Guard] at Cape Lookout Village) eligible for core and shell 

preservation actions at the beginning of the planning period 

(fig. 9). Applying core and shell preservation actions earlier 

in the planning period seems to result in larger marginal gains 

of condition improvement for buildings than applying this 

action later.

Additionally, the timing of relocation actions seems 

to reflect the tradeoffs inherent in receiving a large boost in 

resource value from removing vulnerability and the reduction in relative value by lowering historical significance. 

The results specifically suggest that buildings that have high 

initial resource values and are more affordable to relocate 

(that is, those buildings that enable fewer tradeoffs by requiring a limited number of buildings to receive “do nothing” 

actions in the same year as relocations), should be moved 

earlier, whereas those that are more expensive to move should 

be moved later in the planning period (appendix 2, fig. 2.2). 

Buildings that have less resource value but also have more 

potential for large relative condition increases should be 

moved midway through the period for what seems to be the 

following reasons: they retain more relative resource value 

because it delays the decay rates, and they reduce long-term 

effects of not being able to maintain some buildings in the year 

during which relocation occurs.

To further explain these findings, we provide a couple 

specific examples to explain the pattern of results. The original 

significance value for the Summer Kitchen at Portsmouth 

Village was much higher than any of the other relocated 

buildings. However, relocating this building early reduced 

its significance but not by as much as the other relocated 

buildings. Therefore, more resource value could be maintained over time by relocating this building early in the 

planning period, whereas relocating the other four buildings 

earlier would have resulted in a larger penalty and lowered 

the ending accumulated resource value. In fact, in test runs 

(not presented), reducing the strength of the effect of relocation on historical significance resulted in relocation actions 

being applied earlier in the sequence. Additionally, some of 

the lower resource values were caused by the budget constraint. For example, relocating the O’Boyle Bryant House 

at Cape Lookout Village meant some other buildings could 

not be managed in the relocation year. The model seemed to 

be pushing this effect toward the end of the planning period, 

likely because the declines in historical significance were 

accumulated more slowly during the 30-year planning period.

Portfolio for a Budget of $500,000

The optimal portfolio for the largest budget we considered was very similar to the $222,000 budget outputs, 

except that the increase in potential spending meant more 

buildings could be managed (fig. 11). Relocation and annual 

maintenance actions dominated this solution, as in the 

$222,000 allocation, but “core and shell preservation (historic 

materials)” was chosen by the model for one building, the 

Galley (Coast Guard) at Cape Lookout Village. It is likely that 

this action was selected for the Galley because of the relatively 

low cost affiliated with this action for this building; the Galley 

(Coast Guard) at Cape Lookout Village and Summer Kitchen 

at Portsmouth Village have the lowest costs for core and shell 

preservation (historic materials). The Summer Kitchen at 

Portsmouth Village receives this preservation treatment as part 

of the relocate and elevate action applied in the same year. 

Therefore, this action alone seems to be a good strategy for 

improving the condition of a building, while maintaining its 

historical significance, for buildings already in low vulnerability locations (that is, the Galley [Coast Guard] at Cape 

Lookout Village).

The accumulated value of buildings under this scenario 

(fig. 12) increases by 37 percent of accumulated value under 

the scenario of annual allocation of $222,000 (fig. 10). The 

percentage contribution of resource value for each building was similar with the $222,000 scenario, except for the 

noticeable increase in relative value of a few buildings in 

Portsmouth Village, which were eligible for relocation and 

elevation under this budget scenario. Total expenditures under 

this scenario were about 70 percent higher than that spent 

under the $222,000 scenario.

The effect of this budget allocation on the aspect 

of resource value were virtually the same as those in the 

$222,000 budget scenario, with a few notable exceptions: the 

optimal timing of the relocation action for some buildings 

seems to have been moved earlier in the planning window 

(fig. 11 compared to fig. 9). For example, under a larger 

budget, moving the O’Boyle Bryant House at Cape Lookout 

Village occurs earlier in the planning period. This could be 

because the budget constraint under the previous $222,000 

allocation caused two other buildings to go unmanaged when 

the O’Boyle Bryant House was moved. These results also are 

reflected in the total accumulated resource value (fig. 12) for 

this budget allocation, which was substantially higher than for 

the previous $222,000 allocation (fig. 10). Additional details 

on each building are provided in appendix 2, figure 2.3.
Model Results and Interpretations 15

Year

1 3 11 13 15 17 19 21 23 25 27 29

Lighthouse CLV

Keeper’s Quarters CLV

1907 Keeper’s Quarters CLV

Lifesaving Station CLV

Galley (Coast Guard CLV)

O’Boyle Bryant House CLV

Gordon Willis House CLV

Jetty Workers House 2 CLVJetty Workers House 1 CLV

School PV

Church PV

Post Office PV

Lifesaving Station PV

Summer Kitchen PV

Washington−Roberts House PV

Henry Pigott House PV

Frank Gaskill House PV Elevate and relocate

RelocateElevateCore and shell preservation (resilient materials)Core and shell preservation (historic materials)Active removalDocument and monitorAnnual maintenanceNo action

Historic buildings

579

Figure 11. Optimal actions identified under scenario 2 and a $500,000 annual budget allocation. [CLV, Cape Lookout Village; PV, Portsmouth Village]

Lighthouse CLV (6%)

Keeper’s Quarters CLV (4%)

1907 Keeper’s Quarters CLV (8%)

Lifesaving Station CLV (8%) O’Boyle Bryant House CLV (2%)

Galley (Coast Guard CLV) (7%)

Jetty Workers House 1 CLV ()5%)

Gordon Willis House CLV (2%)

Jetty Workers House 2 CLV (5%)

Church PV (4%)

School PV (7%)

Post Office PV (8%)

Lifesaving Station PV (4%)

Summer Kitchen PV (10%)

Washington−Roberts House PV (8%)

Frank Gaskill House PV (5%)

Henry Pigott House PV (7%)

Accumulated value (138)

Lighthouse CLV (3%)

Keeper’s Quarters CLV (4%)

1907 Keeper’s Quarters CLV (11%)

Lifesaving Station CLV (13%)

O’Boyle Bryant House CLV (5%)

Galley (Coast Guard CLV) (2%)

Jetty Workers House 1 CLV (5%)

Gordon Willis House CLV (4%)

Jetty Workers House 2 CLV (6%)

Church PV (4%)

School PV (7%)

Post Office PV (6%)

Lifesaving Station PV (4%) Summer Kitchen PV (5%)

Washington−Roberts House PV (8%)

Frank Gaskill House PV (5%)

Henry Pigott House PV (8%)

Total cost ($5,073,700)

Figure 12. The proportion of each building’s accumulated value and total cost under Scenario 2 and an annual budget of $500,000. Total accumulated resource value and total scenario expenditure are provided in parentheses after the figure titles, respectively. [CLV, Cape Lookout Village; %, percent; PV, Portsmouth Village]
16 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Scenario 3—Accounting For Periodic Funding 

Increases

Portfolio For A Budget Of $70,000 With A Surge 

Of $225,000 Every 5 Years

The optimal portfolio for this scenario with a low budget 

allocation (but one in which annual maintenance could be 

performed on all buildings in any given year) suggested that 

some buildings could be moved when a surge in total budget 

allocated occurred every 5 years (fig. 13). Under this scenario, 

all buildings were managed but not in every year of the planning period. Unlike the $222,000 scenario (fig. 9), which 

targeted relocation and elevation actions at the beginning or 

the end of the 30-year period, the optimal strategy of this scenario ($70,000 annually with $225,000 surges every 5 years) 

dispersed the action of relocation and elevation actions more 

evenly over time (fig. 13). Similarly, lower-cost relocations 

occurred early, and higher-cost relocations were postponed 

towards the end of the planning horizon.

The outcomes of a budget allocation that included 

periodic funding increases (appendix 2, fig. 2.4) were similar 

to those of the $222,000 scenario (appendix 2, fig. 2.2), with 

the exception of the relative significance losses for several of 

the buildings. The similarities in total accumulated resource 

value between these scenarios (slightly lower values for this 

budget allocation compared to the $222,000 scenario; figs. 14 

and 10, respectively) may be caused by fact that the relocation 

and annual maintenance actions dominated the solutions for 

both scenarios.

Portfolio For A Budget Of $222,000 With A Surge 

Of $225,000 Every 5 Years

The optimal portfolio for this budget allocation (fig. 15) 

suggests that more buildings could be candidates for relocation or relocation and elevation actions than in the scenario 

of annual budget of $222,000 (fig. 9). Similar to the $70,000 

annual budget allocation with additional funding (fig. 13), 

relocation or relocation and elevation actions were selected in 

the years when the additional funding was allocated.

Interestingly, the core and shell preservation using 

historic materials action was not selected in this budget 

allocation (it was selected for one building, the Galley at 

Cape Lookout Village, under the annual budget allocation 

of $500,000; fig. 11). It is possible that the marginal gain in 

resource value for these buildings under this budget allocation (fig. 16) compared to that of the $500,000 scenario 

(fig. 12) might be greater for the relocation or relocation 

and elevation adaptation strategies than for the core and 

shell preservation treatment. Although the actual expenditures under this scenario were about 87 percent of the actual 

expenditures of $500,000 annual allocation scenario (about 

$4.48 million compared to about $5.07 million), the total 

accumulated resource value under this scenario was very 

similar (130 compared to 138, respectively) with the scenario 

of annual budget of $500,000 (figs. 16 and 12, respectively). 

Additional information for each building’s relative resource 

value is provided in appendix 2, figure 2.5.

Scenario 4—Ignoring Vulnerability

Portfolio For A Budget Of $222,000 Without 

Vulnerability

The optimal management strategy under this scenario is 

to select actions of core and shell preservation using historic 

materials and annual maintenance (fig. 17). Relocation and 

elevation actions were likely not selected under this scenario 

because these actions included the same historic preservation treatment (that is, they both increase the condition of 

the building to NPS standards) but would reduce the relative 

significance of the buildings. Because vulnerability was not 

considered, the additional costs for actions that address sea 

level rise and storm-related flooding were not justified. The 

buildings selected seem to be a function of cost (fig. 18) 

and condition (improved condition ratings; see appendix 2, 

fig. 2.6); however, it is not quite clear why the preservation 

treatments typically occurred in the middle of the planning 

horizon but it is likely related to reducing the effect of decay 

rates posttreatment.

In this scenario, the total accumulated resource value 

(fig. 18) is calculated by accumulating the annual resource 

value over the planning horizon but not penalizing the final 

score by a building’s vulnerability assessment. As a result, 

the model does not attempt to lower a building’s vulnerability 

and the resulting accumulated resource value for this scenario 

(fig. 18) is higher than in the $222,000 with vulnerability 

(fig. 10) scenario (305 compared to 101, respectively).

Scenario 5—Excluding The Attributes Of “Use 

Potential”

Portfolio For A Budget Of $222,000 Without Use 

Potential

The optimal portfolio for this scenario suggested that the 

core and shell preservation using the historic materials action 

was more likely to be chosen if the historical significance of 

buildings were given more weight (fig. 19). Four buildings 

with high historical significance (the Life-Saving Station, Post 

Office, and School at Portsmouth Village; and Galley at Cape 

Lookout Village) were candidates for historical preservation 

action at the beginning of 30-year period. Unlike the earlier 

$222,000 scenario with use potential in which relocation and 

elevation was selected for the Summer Kitchen at Portsmouth 

Village at the beginning of the planning horizon (fig. 9), this 

action was selected for the Summer Kitchen at the end of 

30-year period under this scenario (fig. 19). We infer that 
Model Results and Interpretations 17

Figure 13. Optimal actions identified under scenario 3 and a $70,000 annual budget allocation with an additional $225,000 every 5 years. [CLV, Cape Lookout Village; PV, Portsmouth Village]

Year

13579 11 13 15 17 19 21 23 25 27 29

Lighthouse CLV

Keeper’s Quarters CLV

1907 Keeper’s Quarters CLV

Lifesaving Station CLV

Galley (Coast Guard CLV)

O’Boyle Bryant House CLV

Gordon Willis House CLV 

Jetty Workers House 2 CLVJetty Workder House 1 CLV

School PV

Church PV

Post Office PV

Lifesaving Station PV

Summer Kitchen PV

Washington−Roberts House PV

Henry Pigott House PV

Frank Gaskill House PV Elevate and relocate

RelocateElevateCore and shell preservation (resilient materials)Core and shell preservation (historic materials)Active removalDocument and monitorAnnual maintenanceNo action

Historic buildings

Lighthouse CLV (8%)

Keeper’s Quarters CLV (5%)

1907 Keeper’s Quarters CLV (6&)

Lifesaving Station CLV (6%) O’Boyle Bryant House CLV (2%) Galley (Coast Guard CLV) (8%)

Jetty Workers House 1 CLV (6%)

Gordon Willis House CLV (1%)

Jetty Workers House 2 CLV (6%)

Church PV (4%)

School PV (8%)

Post Office PV (9%)

Lifesaving Station PV (5%) Summer Kitchen PV (11%)

Washington−Roberts House PV (4%)

Frank Gaskill House PV (6%)

Henry Pigott House PV (4%)

Accumulated value (110)

Lighthouse CLV (5%)

Keeper’s Quarters CLV (5%)

1907 Keeper’s Quarters CLV (4%)

Lifesaving Station CLV (7%)

O’Boyle Bryant House CLV (3%) Galley (Coast Guard CLV) (3%)

Jetty Workers House 1 CLV (8%)

Gordon Willis House CLV (2%)

Jetty Workers House 2 CLV (10%)

Church PV (5%)

School PV (10%)

Post Office PV (9%)

Lifesaving Station PV (6%)

Summer Kitchen PV (7%)

Washington−Roberts House PV (3%)

Frank Gaskill House PV (8%)

Henry Pigott House PV (3%)

Total cost ($3,246,700)

Figure 14. The proportion of each building’s accumulated value and total cost under scenario 3 and an annual budget of $70,000 with an additional $225,000 every 5 years. Total accumulated resource value and total scenario expenditure are provided in parentheses after the figure titles, respectively. [CLV, Cape Lookout Village; %, percent; PV, Portsmouth Village]
18 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore No action Elevate and relocate Relocate Elevate Core and shell preservation (resilient materials) Core and shell preservation (historic materials) Active removal Document and monitor Annual maintenance Year Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 2 CLV Jetty Workers House 1 CLV School PV Church PV Post Office PV Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Henry Pigott House PV Frank Gaskill House PV

Historic buildings

11 13 15 17 19 21 23 25 27 29 1 3 5 7 9

Figure 15. Optimal actions identified under scenario 3 and a $222,000 annual budget allocation with an additional $225,000 every 5 years. [CLV, Cape Lookout Village; PV, Portsmouth Village]

Lighthouse CLV (6%)

Keeper’s Quarters CLV (4%)

1907 Keeper’s Quarters CLV (9%)

Lifesaving Station CLV (5%) O’Boyle Bryant House CLV (2%) Galley (Coast Guard CLV) (7%)

Jetty Workers House 1 CLV (5%)

Gordon Willis House CLV (3%)

Jetty Workers House 2 CLV (5%)

Church PV (4%)

School PV (7%)

Post Office PV (7%)

Lifesaving Station PV (4%)

Summer Kitchen PV (11%)

Washington−Roberts House PV (8%)

Frank Gaskill House PV (6%)

Henry Pigott House PV (7%)

Accumulated value (130)

Lighthouse CLV (3%)

Keeper’s Quarters CLV (4%)

1907 Keeper’s Quarters CLV (13%)

Lifesaving Station CLV (5%) O’Boyle Bryant House CLV (6%) Galley (Coast Guard CLV) (2%)

Jetty Workers House 1 CLV (6%)

Gordon Willis House CLV (5%)

Jetty Workers House 2 CLV (7%)

Church PV (3%)

School PV (7%)

Post Office PV (7%)

Lifesaving Station PV (4%)

Summer Kitchen PV (5%)

Washington−Roberts House PV (9%)

Frank Gaskill House PV (6%)

Henry Pigott House PV (9%)

Total cost ($4,486,300)

Figure 16. The proportion of each building’s accumulated value and total cost under scenario 3 and an annual budget of $222,000 with an additional $225,000 every 5 years. Total accumulated resource value and total scenario expenditure are provided in parentheses after the figure titles, respectively. [CLV, Cape Lookout Village; %, percent; PV, Portsmouth Village]
Model Results and Interpretations 19

1 11 13 15 17 19 21 23 25 27 29 3 579

Elevate and relocateRelocateElevateCore and shell preservation (resilient materials)Core and shell preservation (historic materials)Active removalDocument and monitorAnnual maintenanceNo action

Lighthouse CLV

Keeper’s Quarters CLV

1907 Keeper’s Quarters CLV

Lifesaving Station CLV

Galley (Coast Guard CLV)

O’Boyle Bryant House CLV

Gordon Willis House CLV

Jetty Workers House 2 CLVJetty Workers House 1 CLV

School PV

Church PV

Post Office PV

Lifesaving Station PV

Summer Kitchen PV

Washington−Roberts House PV

Henry Pigott House PV

Frank Gaskill House PV

Historic buildings

Year

Figure 17. Optimal actions identified under scenario 4 and a $222,000 annual budget allocation without consideration of vulnerability. [CLV, Cape Lookout Village; PV, Portsmouth Village]

Lighthouse CLV (8%)

Keeper’s Quarters CLV (8%)

1907 Keeper’s Quarters CLV (7%) Lifesaving Station CLV (7%) O’Boyle Bryant House CLV (2%)

Galley (Coast Guard CLV) (6%)

Jetty Workers House 1 CLV (4%)

Gordon Willis House CLV (2%)

Jetty Workers House 2 CLV (4%)

Church PV (7%)

School PV (6%)

Post Office PV (6%)

Lifesaving Station PV (7%) Summer Kitchen PV (8%)

Washington−Roberts House PV (6%)

Frank Gaskill House PV (5%)

Henry Pigott House PV (6%)

Accumulated value (305)

Lighthouse CLV (5%)

Keeper’s Quarters CLV (10%)

1907 Keeper’s Quarters CLV (7%) Lifesaving Station CLV (12%)

O’Boyle Bryant House CLV (5%)

Galley (Coast Guard CLV) (4%)

Jetty Workers House 1 CLV (5%)

Gordon Willis House CLV (4%)

Jetty Workers House 2 CLV (7%)

Church PV (9%)

School PV (3%)

Post Office PV (3%) Lifesaving Station PV (9%)

Summer Kitchen PV (3%)

Washington−Roberts House PV (5%)

Frank Gaskill House PV (3%)

Henry Pigott House PV (5%)

Total cost ($3,142,700)

Figure 18. The proportion of each building’s accumulated value and total cost under scenario 4 and an annual budget of $222,000 without consideration of vulnerability. Total accumulated resource value and total scenario expenditure are provided in parentheses after the figure titles, respectively. [CLV, Cape Lookout Village; %, percent; PV, Portsmouth Village]
20 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore Lighthouse CLV (7%) Keeper’s Quarters CLV (5%) 1907 Keeper’s Quarters CLV (6%) Lifesaving Station CLV (6%) O’Boyle Bryant House CLV (4%) Galley (Coast Guard CLV) (10%) Jetty Workers House 1 CLV (9%) Gordon Willis House CLV (4%) Jetty Workers House 2 CLV (4%) Church PV (4%) School PV (5%) Post Office PV (5%) Lifesaving Station PV (5%) Summer Kitchen PV (11%) Washington−Roberts House PV (4%) Frank Gaskill House PV (8%) Henry Pigott House PV (4%) Accumulated value (111) Lighthouse CLV (6%) Keeper’s Quarters CLV (6%) 1907 Keeper’s Quarters CLV (5%) Lifesaving Station CLV (7%) O’Boyle Bryant House CLV (9%) Galley (Coast Guard CLV) (4%) Jetty Workers House 1 CLV (9%) Gordon Willis House CLV (7%) Jetty Workers House 2 CLV (2%) Church PV (5%) School PV (4%) Post Office PV (4%) Lifesaving Station PV (9%) Summer Kitchen PV (8%) Washington−Roberts House PV (4%) Frank Gaskill House PV (9%) Henry Pigott House PV (3%) Total cost ($2,941,300) Figure 20. The proportion of each building’s accumulated value and total cost under scenario 5 and an annual budget of $222,000 without consideration of use potential. Total accumulated resource value and total scenario expenditure are provided in parentheses after the figure titles, respectively. [CLV, Cape Lookout Village; %, percent; PV, 

Portsmouth Village]

1 11 13 15 17 19 21 23 25 27 29 3 579

Year

Elevate and relocateRelocateElevateCore and shell preservation (resilient materials)Core and shell preservation (historic materials)Active removalDocument and monitorAnnual maintenanceNo action

Lighthouse CLV

Keeper’s Quarters CLV

1907 Keeper’s Quarters CLV

Lifesaving Station CLV

Galley (Coast Guard CLV)

O’Boyle Bryant House CLV

Gordon Willis House CLV

Jetty Workers House 2 CLVJetty Workers House 1 CLV

School PV

Church PV

Post Office PV

Lifesaving Station PV

Summer Kitchen PV

Washington−Roberts House PV

Henry Pigott House PV

Frank Gaskill House PV

Historic buildings

Figure 19. Optimal actions identified under scenario 5 and a $222,000 annual budget allocation without consideration of use potential. [CLV, Cape Lookout Village; PV, Portsmouth Village]
Insights From The Pilot Study 21

relocating this building earlier in the planning horizon would 

have resulted in a larger penalty on the resource value because 

of the greater weight on historical significance in this scenario 

(appendix 2, fig. 2.7) than the scenario that included use 

potential (appendix 2, fig. 2.2).

The total accumulated resource value (fig. 20) was 

computed as in the other scenarios except that use potential 

was not included in the calculation. We accomplished this by 

allocating all the weight to historical significance. Therefore, 

the accumulated resource values displayed in figure 20 are 

not directly comparable to the other scenarios’ accumulated 

resource value because it reflects an optimal strategy assuming 

only historical significance was to be maximized; yet, comparing this solution to the others indicates how much use potential 

affected the optimal strategy.

Comparing Scenarios

To compare effects of applied actions on the resource 

values of buildings under different scenarios, we created a 

figure to show the composite, accumulated values of all buildings and total expenditures under the eight scenarios (fig. 21; 

the resource values by building for each of the scenarios can 

be viewed in appendix 2, fig. 2.8). The resource values of 

all buildings under the scenarios of “no action” and annual 

allocation of $50,000 were lower than the original value of 

all buildings. The scenarios with higher budget allocations 

(scenarios 3–8) could improve the original resource values 

of all buildings, which suggests that adaptation actions can 

help maintain and (or) enhance historical significance and use 

potential of historic buildings.

Generally, a higher budget allocation results in higher 

accumulated resource value. However, the accumulated 

resource value of the scenario of allocation of $70,000 every 

year with an additional fund of $225,000 every 5 years was 

higher than the scenario of allocation of $222,000 every year. 

This finding is caused by the fact that the allocated budgets are 

not fully spent in several scenarios; for example, the scenario 

with a periodic funding increase uses 94 percent of allocated 

budget, whereas the constant funding scenario uses only 

44 percent of the total allocated budget (fig. 22). The periodic 

allocation of additional funding makes efficient use of larger, 

more costly adaption actions for several buildings, resulting in 

slightly higher total accumulated resource value relative to the 

constant budget scenario. In addition, the high accumulated 

resource value achieved when disregarding vulnerability indicates that, based on current model specification, the quantification of resource value may be highly sensitive to vulnerability 

scores.

Insights From The Pilot Study

Building the OptiPres Model in its current state was 

completed by using the best available data and iteratively 

examining the model assumptions. The model was constructed 

based on the objective of maximizing the total resource value 

of 17 buildings. Additionally, we ran four broad scenarios, 

including two with multiple budget allocations, to test the 

model’s assumptions, dynamics, and constraints with the goal 

of providing decision-making insights for managers and other 

relevant NPS personnel.

It is important to note that, for any optimization problem, 

there is a tradeoff between computational speed and closeness 

to some global optimum. In conservation planning, finding 

one exact, optimum solution is not essential, but it is important 

to generate many good solutions in a reasonable amount of 

time using the iterative heuristics for optimization problems. 

The simulated annealing algorithm is nondeterministic; each 

run will generate a different solution. For each scenario in 

this study, we ran the algorithm 100 times, which was aligned 

with the run times in other studies about conservation planning using the simulated annealing algorithm (Westphal and 

others, 2007).

Additionally, it is important to note that, as with any 

modeling effort, we iterated through several revisions of 

model dynamics and associated metrics based on new information obtained during the project period. However, we could 

not address all considerations and limitations, but several 

key insights were gained through model exploration. These 

insights are described below.

Sufficient annual budget allocations are necessary to 

implement climate adaptation actions to historic buildings. 

Adaptation actions are costly and if park personnel are to 

maintain at least the current accumulated resource value, 

then sufficient fiscal appropriations (minimum of the industry 

standard) are necessary. Additionally, our results suggest that 

additional appropriations provided on regular intervals when 

annual appropriations are at the industry standard are nearly as 

efficient as annual appropriations at twice the rate of industry 

standards and increase the amount of accumulated resource 

value maintained to nearly the same level. However, periodic 

increases in funding may increase the risks posed to buildings from the probability of a natural hazard (that is, damage 

or loss from a hurricane). Therefore, the OptiPres Model has 

planning utility related to fiscal efficiency by identifying a 

budget threshold necessary to maintain the historical significance and use potential of historical buildings while reducing 

vulnerability. Nevertheless, it will be important for managers 

to continue seeking additional stakeholder input to ensure 

that the adaptation actions selected align with the values of 

stakeholder groups and (or) are applied to buildings that hold 

relatively high importance for stakeholder groups. For the 

latter, it will be important to update the model to weight the 

adaptation actions by acceptability to a variety of external 

stakeholders (for example, community members, partner organizations, and visitors) because certain actions may alter the 
22 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Figure 21. Accumulated value and total cost of all buildings for all budget scenarios. Units of accumulated values are on 

relative and on a constructed, composite scale.

0

2,000

4,000

6,000

0

100

200

300

Budget scenario

Total cost, in thoousands of dollars

Accumulated value

Accumulated value Total cost

X−axis represents different budget scenarios.

1: No action.

2: Allocation of $50,000 every year.

3: Allocation of $222,000 every year.

4: Allocation of $500,000 every year.

5: Allocation of $70,000 every year and an 

 addtional $225,000 every five years.

6: Allocation of $222,000 every year and an

 addtional $225,000 every five years.

7: Allocation of $222,000 every year.

 without considertation of vulnerability.

8: Allocation of $222,000 every year.

 without considertation of use potential.

Original value of all buildings

1 2 3 4 5 6 7 8
Insights From The Pilot Study 23

Figure 22. Comparison of allocated budget versus actual expenditures for all budget scenarios.

100%

44%

56%

34%

66%

94%

6%

56%

44%

47%

53%

44%

56%

0

5,000

10,000

15,000

Budget scenario

Total cost, in thousands of dollars

Remaining budget Used budget

X−axis represents different budget scenarios.

1: Annual allocation of $50,000.

2: Annual allocation of $222,000.

3: Annual allocation of $500,000 every year.

4: Annual allocation of $70,000 and an

 addtional $225,000 every five years.

5: Annual allocation of $222,000 and an

 addtional $225,000 every five years.

6: Annual allocation of $222,000 every year 

 without considertation of vulnerability.

7: Annual allocation of $222,000 every year

 without considertation of use potential.

1 2 3 4 5 6 7
24 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

intangible resource values associated with people’s connections to specific buildings.

Preferences regarding the valuation of a cultural resource 

(that is, weights applied to historical significance and use 

potential) affect the optimal adaptation strategies identified. 

Because maximizing total resource value of 17 buildings was 

the purpose behind our development of the OptiPres Model, 

the relative effect of each objective (based on weighting of 

historical significance and use potential, including associated 

attributes) must be clearly understood. We suggest that park 

managers, and perhaps cultural resource management personnel at the national NPS Headquarters and (or) personnel at 

the National State Historic Preservation Office, have focused 

discussions about their preferences regarding historical 

resources and how these values relate to each of the attributes 

and subattributes before future applications of the OptiPres 

Model. Because objective weights reflect statements of subjective values, they represent an additional source of variability 

and uncertainty in decision modeling. This uncertainty can be 

addressed in several ways, including a facilitated, consensusbased approach, surveying multiple stakeholders and calculating average weights (that is, the method applied in this pilot 

study), and (or) grouping weights into several representative 

stakeholder “types” and conducting a sensitivity analysis of 

the effect on the portfolio strategy of variation in values.

Considerations For Advancing The 

Optipres Model

The NPS’s Climate Change Response Program perceives 

utility in the OptiPres Model for enhancing national park management and supporting climate adaptation decision-making. 

After the conclusion of the second workshop at Cape Lookout 

National Seashore (see fig. 1), the Climate Change Response 

Program managers decided to provide funding to determine 

the transferability of the OptiPres Model by applying it to 

another National Park System unit. We have determined 

some additional considerations to include as improvements in 

subsequent model development. These considerations include 

the following:

• Clearly outlining how current replacement value data

can be integrated with other data from standard

Federal databases to refine the cost estimates for the 

various actions.—We found that considerable effort 

from NPS staff was needed to determine the adaptation costs for buildings because of a high degree of 

variability in reporting to the various NPS facilities management databases. To reduce the burden 

on NPS staff in future applications of the OptiPres 

Model, continual work will be needed to determine 

standard costs per square footage based on dominant 

building materials.

• Development of a metric framework for assessing the

current historic integrity of buildings to include in

the historical significance calculations.—This model 

advancement may enable us to change the structure 

of the significance calculations by replacing the attribute “building condition” with “historic integrity” 

and integrating “building condition” into the cost 

estimates for the various adaptation actions (particularly, if it is integrated with the current replacement 

value of specific buildings). This advancement may 

also help us deal with the fact that “building condition” and “use potential” are correlated but that the 

relations are not fully accounted for in this version 

of the OptiPres Model (that is, buildings in poor and 

perhaps some in fair condition would not have operational, visitor, or third-party use but may retain some 

degree of use potential depending on anticipated 

budget allocations).

• Integrating social values data as a potential model

input or lens through which to interpret model

outputs.—For example, social values data collected at 

Cape Lookout National Seashore as part of a parallel research project suggests that specific adaptation 

actions (for example, moving or elevating buildings) 

are viewed unfavorably by several stakeholder groups 

and that the managers may benefit from OptiPres 

Model scenarios that remove or discount the value 

of these adaptation actions as options. Although 

replication of these social values data will likely 

not be feasible for the second park site to test the 

model because of the timeframe of review processes 

for studies that involve members of the public, we 

will seek opportunities to explore how stakeholders’ 

values can be used to affect and (or) interpret the 

model outputs.

• Development of additional objectives.—In ongoing

discussions, we continue to sense that specifying

additional objectives could enhance the usefulness 

of the model. Examples could be objectives related 

to minimizing “public risk” (for example, removing 

buildings in poor condition) or increasing “public 

enjoyment” (for example, prioritizing a building present on the landscape in good condition).

• Refining vulnerability data.—The limited differences

observed in the vulnerability scores of the buildings

at Cape Lookout National Seashore suggest that 

refining the vulnerability analysis to a more localized 

scale could be advantageous. Specifically, the vulnerability assessment methodology bins raw scores for 

exposure and raw scores for sensitivity, adds those 

binned scores together, and then bins the total score 

to develop the final static vulnerability metric on 

a 1–4 scale; additionally, the attributes that com-
References Cited 25

pose the exposure and sensitivity metrics are added 

together without first weighting the scores based on 

different degrees of effect risk or damage. Reconfiguring how the vulnerability scores are computed 

may increase the model’s sensitivity, but using raw 

scores may not be particularly meaningful given the 

uncertainty in the data used to score the attributes and 

the stochastic nature of storm-related effects. Other 

considerations to increase model sensitivity include 

(1) changing the current vulnerability metric to a 

time-dependent persistence (risk) metric or (2) penalizing adaptation action costs (for example, moving 

or elevating buildings) to reflect the time-dependent 

likelihood for increased risk of inundation at the time 

an action is applied (costlier if already inundated or 

greatly impacted by a storm event). Additionally, 

there will be a need to periodically re-estimate the 

vulnerability metrics because climate scenarios and 

projections of land cover change evolve with time.

• Incorporating stochastic storms and wind effects.—

Coastal cultural resources—particularly those on barrier islands—are at risk from effects associated with 

natural hazards. These natural hazards are becoming 

exacerbated (in frequency, intensity, or both) by 

climate change, which highlights the importance of 

advancing the model to capture random events such 

as hurricanes and nor’easters. Integrating storms, 

with associated flooding and wind effects, as a 

random variable into the model also will allow us to 

explore nuances of climate change impacts—particularly to the condition class of a building—and adaptation actions for historic buildings because the model 

currently only accounts for chronic flooding effects. 

Moreover, incorporating stochastic events of natural 

hazards in the OptiPres Model will provide more 

information for decision makers and park managers 

about how to prioritize actions after a natural hazard. 

As more complete assessments of climate change 

effects are integrated into the model (for example, 

storm-related effects from wind and precipitation 

that penetrates buildings), specific adaptation actions 

that target nonflooding effects (for example, core and 

shell preservation treatments to improve adaptability 

that use resilient materials) may become favored 

within the model (rather than ignored).

• Enhance visualization and interpretations of model 

outputs.—Enhancing our data visualization and 

interpretation efforts may facilitate further thinking and application of the model results, which 

may ultimately improve the usability of the model. 

Visualizations of data that illustrate how significance, 

use potential, vulnerability, and adaptation costs drive 

the model and interact across the 30-year forecast 

window will allow cultural resource managers and 

NPS officials to determine optimal (that is, most 

efficient) annual budget levels. This will be particularly important as more buildings are included in 

any given modeling effort. Ultimately, the ability to 

clearly communicate data-driven support for specific 

budgets may enhance the NPS’s ability to receive the 

appropriations necessary to meet its cultural heritage 

preservation mandates.

• Incorporating dynamic outputs of vulnerability across 

the planning horizon.—Although the vulnerability 

scores for the historic buildings at Cape Lookout National Seashore only have slight changes 

between 2030 and 2050, the adaptation actions (for 

example, elevation and relocation) can dramatically 

change the vulnerability scores of historic buildings. 

Incorporating the dynamic outputs of vulnerability at each time step (that is, year) will help NPS 

officials understand the cultural resource vulnerability changes across the 30-year planning horizon. 

More importantly, combining the dynamic outputs of 

conditions, integrity, use potential, and vulnerability 

would enable the calculation of annual accumulated 

resource values. These data could then be visualized 

as a running average of annual accumulated resource 

values across the 30-year planning horizon to help 

NPS officials understand the relative increases and 

decreases in resource values across the assortment of 

historic buildings under various budget scenarios.

Additionally, the OptiPres Model also could be used in 

adaptation planning of other cultural resources (for example, 

archeological resources), other types of park assets (for 

example, facilities and roads), or efforts that consider other 

types of climate change effects (for example, fire and drought). 

However, considerable effort would be needed to first develop 

the associated measurement frameworks for other cultural 

resources and assets to determine the relative importance of 

those resources and assets.

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Hoboken, N.J., John Wiley & Sons Inc., 312 p.

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climate change: The power of intangible cultural resource 

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p. 113–122. [Also available at https://doi.org/10.1080/03632

415.2011.10389083.]

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Register criteria for evaluation: National Park Service, 

National Register Bulletin, accessed December 20, 2017, at 

https://www.nps.gov/nr/publications/bulletins/pdfs/nrb15.

pdf.

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at https://www.nps.gov/policy/PolMemos/PM-14-02.htm.

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climate change asset vulnerability protocol—Project 

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McNamee, J., and Scavo, R., 2017, Cape Lookout National 

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 27

Appendixes

Appendix 1. Optimal Preservation Model Objectives, Attributes, Weights, Actions, and Costs

Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 17 Buildings 

Among Different Scenarios

Appendix 3. Computer Code for Optimal Preservation Model

Caption. Jetty Workers House 

II (circa 1920) in Cape Lookout 

Village (photograph credit: Erin 

Seekamp, 2015)

Caption. Jetty Workers House 

I (circa 1915) with 1907 Keeper’s 

Quarters (circa 1907) in the 

background (photograph credit: 

Erin Seekamp)
28 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Appendix 1. Optimal Preservation Model Objectives, Attributes, Weights, 

Actions, and Costs

This appendix provides additional details of the multiple data sources that are used to populate the Optimal Preservation 

(OptiPres) Model. The OptiPres Model includes measures of a building’s resource value (historical significance and use potential) and vulnerability (sensitivity and exposure), and cost estimates for adaptation actions. Additionally, some adaptation actions 

affect the attributes, subattributes, or both for resource value and vulnerability. In table 1.1, the objective “historical significance” 

is presented with descriptions of attributes and subattributes, the metrics and associated scores, and the relative weights assigned 

to the attributes and subattributes. In table 1.2, the objective “use potential” is presented with descriptions of attributes and 

subattributes, the metrics and associated scores, and the relative weights assigned to the attributes and subattributes. In table 1.3, 

the attribute “exposure” is presented with descriptions of subattributes and associated data sources. In table 1.4, the attribute 

“sensitivity” is presented with descriptions of subattributes and associated data sources. In table 1.5, the objective “vulnerability” is presented to illustrate how the two attributes (exposure and sensitivity) are combined to create a final binned vulnerability 

score. In table 1.6, the actions included within the OptiPres Model are defined and the associated model dynamics (changes to a 

building’s condition, the historic integrity of a building, and the vulnerability of a building). In table 1.7, the total costs for each 

action to be performed on each building are presented.
Appendix 1. Optimal Preservation Model Objectives, Attributes, Weights, Actions, and Costs 29

Attributes and subattributes

Association to fundamental 

purpose Condition of building

Character National register

Defining character Uniqueness to park Spatial significance Eligibility

Description

This attribute uses the 

information on listed fundamental resource(s) in the park’s foundation document1 to determine 

if a historic building is considered a fundamental or nonfundamental resource.

The National Park Service 

database List of Classified Structures (LCS)2 is used 

to assess the condition of the building.

This subattribute evaluates 

if a building is the primary (historic) reason that resulted in the development (or resettlement) of the historic district or is part of the secondary development (or resettlement) of the district that occurred because of the original construction.

This subattribute considers the original (historic) 

function of the building, if its function was unique within the park, or if there are a number of buildings with the same or similar function.

The geographical scale of a 

building’s historic context listed in the National Register of Historic Places (NRHP)3 is used to 

assess the subattribute of spatial significance.

The eligibility subattribute 

assesses if the historic building is eligible for listing in the NRHP.

Metrics and scores4

Fundamental resource 

(2.2)

Nonfundamental resource 

(0.9)

Good condition 

(2.9)

Fair condition 

(1.9)

Poor condition 

(1.1)

Building as primary reason 

for the historic development of the district 

(2.3)

Building as secondary 

reason for the historic development of the district (1.1)

Being unique building to the 

region(4.2)

Being the only building of 

this type in the park 

(3.1)

Few (2–3) similar types of 

building present in the park(1.9)

Many (>3) similar types of 

building present in the park(1.0)

National significance

(3.4)

State significance

(2.1)

Local significance 

(1.1)

Eligible

(2.0)

Noneligible

(0.0)

Attribute or subattribute weight5

0.26 0.17 0.27 0.30

0.475 0.525 0.41 0.59

1Foundation documents for national parks are available at https://parkplanning.nps.gov/foundationDocuments.cfm.2The List of Classified Structures (LCS) is available at https://hscl.cr.nps.gov/insidenps/search.asp.3The National Register of Historic Places (NRHP) is available at https://npgallery.nps.gov/nrhp.4Scores were derived using an elicitation of National Park Service (NPS) and State Historic Preservation Office (SHPO) staff and reflect the mean value calculated for each metric from the elicitation.5Weights were derived using an elicitation of NPS and SHPO staff and reflect the mean value calculated for each metric from the elicitation.

Table 1.1. Historical significance’s attributes, subattributes, and metrics with scores including weights among the attributes and subattributes.
30 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore Table 1.2. Use potential’s attributes and metrics with scores including weights among the attributes. Use potential’s attributes Operational use Third party use Visitor use Interpretive use Scientific use Description This attribute evaluates if the historic building is used for park operations or has potential for it in the future. It also evalu- ates possible investment in the historic building for park opera- tions to reduce the operational use of nonhistoric (noncontrib- uting) building. This attribute assesses the current and potential future use of the building by the third party through lease agreements and concessions. This attribute explores current and future active uses of the building for public visitation in the historic district (or other specified area) of the park. The park’s Long-Range Interpre- tive Plan1 is used to assess cur- rent and future active uses of the building for communicating sto- ries and educating visitors of the park. This attribute determines whether the building’s interpre- tive plan conveys primary or secondary interpretive themes. This attribute evaluates if the building has a potential to yield new scientific information and value. Metrics and scores2 Building currently in use (4.1) Investment in historic building for operations can reduce nonhis- toric building’s use (2.8) Building has no current use but potential use in next 5 years (2.1) Building has no current use nor potential use in next 5 years (1.1) Building currently in use (1.5) Expressed potential to use building (1.0) No expressed potential to use building (0.25) Building open to public with high visitation (4.9) Building open to public with mod- erate visitation (3.9) Building open to public with low visitation (3.0) Building closed to public but like- ly to open in the next 5 years (2.1) Building closed to public and unlikely to open in the next 5 years (1.0) Primary themes interpreted cur- rently or in the next 5 years (3.2) Secondary themes interpreted cur- rently or in the next 5 years (2.1) No current nor potential link to interpretive plan in next 5 years (1.1) Building has potential to yield new scientific information (1.0) Building’s new scientific informa- tion is not determined yet (0.5) Weight3 0.17 0.12 0.17 0.26 0.28

1Long-Range Interpretive Plans are available at https://www.nps.gov/subjects/hfc/interpretive-planning.htm.2Scores were derived using an elicitation of National Park Service (NPS) and State Historic Preservation Office (SHPO) staff and reflect the mean value calculated for each metric from the elicitation.3Weights were derived using an elicitation of NPS and SHPO staff and reflect the mean value calculated for each metric from the elicitation. Historical significance’s weight is 0.79, whereas use potential’s 

weight is 0.29. This indicates that historical significance is nearly three times as important as use potential.
Appendix 1. Optimal Preservation Model Objectives, Attributes, Weights, Actions, and Costs 31

Table 1.3. Use potential’s attributes and metrics with scores including weights among the attributes. Exposure’s subattributes and corresponding data sources.

Exposure’s subattributes

Flooding Storm surge Sea level rise Erosion and coastal proximity Historical flooding

Data source1

Federal Emergency Management 

Agency Flood Maps (primary)

Light detection and ranging 

digital elevation model or other elevation model

National Park Service-specific 

Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model results (primary)

Light detection and ranging 

digital elevation model or other elevation model

National Park Service-specific sea 

level rise modeling (primary)

Light detection and ranging 

digital elevation model or other elevation model

State or U.S. Geological Survey 

erosion rate buffers (primary)

Shoreline proximity buffers

Park questionnaire (primary)Storm imagery or reconnaissance

1Methods described in Peek and others (2017).

Sensitivity’s subattributes

Flood damage potential (elevated) Storm resistance (condition) Historical damage Protective engineering

Data source1

Park questionnaire (primary)Direct measurements of threshold elevation

Park questionnaire (primary)Facility Management Software System 

database

Park questionnaire (primary)Discussion with park staf

Park questionnaire (primary)Field and aerial imagery analysisWestern Carolina University Engineering 

Inventory

1Methods described in Peek and others (2017).

Table 1.4. Sensitivity’s subattributes and corresponding data sources.Table 1.5.

Vulnerability’s metrics and scores.

Score level

(ranging from 2 to 8)

Vulnerability’s metrics

Vulnerability score1 Binned vulnerability score (ranging from 1 to 4) Binned exposure attribute score

(ranging from 1 to 4)

Binned sensitivity 

attribute score

(ranging from 1 to 4)

High 4 4 ≥7 4 

Moderate 3 3 6 3

Low 2 2 4 to 5 2Minimal 1 1 <4 1

1Vulnerability score = binned exposure score + binned sensitivity score (Peek and others, 2017).
32 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore Table 1.6. Optimal Preservation Model adaptation actions and model dynamics. Action1 Definition Model dynamics Depreciation of building condition2 Improvement in building condition3 Loss of historic integrity4 Reduced vulnerability No action This option allows managers to repurpose annual maintenance from one building to another to “capture” enough money in any given year to apply a costly adaptation action to another building. Low (8-percent annual loss)— Applied to buildings in “good” condition (List of Classified Structures [LCS] condition class score of 3). Medium (17-percent annual loss)—Applied to buildings in “fair” condition (LCS score of 2). High (25-percent annual loss)— Applied to buildings in “poor” condition (LCS score of 1). No change (apply annual depreciation rate based on current condition) 5-percent loss in integrity (reduction in overall significance score at time of action). No change. Annual maintenance Regular, annual maintenance that is supposed to keep buildings in good condition (base funded operations; inspections, corrective maintenance, and preventative maintenance). Note: values are lower corrective maintenance costs than for core and shell preservation because they reflect the bare minimum or maintenance of the status quo through application of small fixes. Low (6-percent annual loss)— Applied to buildings in “good” condition (LCS score of 3). Medium (10-percent annual loss)—Applied to buildings in “fair” condition (LCS score of 2). High (15-percent annual loss)— Applied to buildings in “poor” condition (LCS score of 1). No change (apply annual depreciation rate based on current condition). 0 percent No change.
Appendix 1. Optimal Preservation Model Objectives, Attributes, Weights, Actions, and Costs 33

Action1 Definition

Model dynamics

Depreciation of 

building condition2

Improvement in 

building condition3 Loss of historic integrity4 Reduced vulnerability

Core and shell 

preservation—historic materials

Maintenance of historic character of the 

building and its historic materials (that is, similar as possible to the materials used in the original construction), which includes annual maintenance (inspection, full corrective maintenance, and preventive maintenance) and nonannual maintenance to bring to standard (cyclic maintenance and recurring maintenance, also referred to as deferred maintenance). This action also included costs affiliated with fully (extensively) documenting the resource in its new condition (conditions report).

0 percent Building changes to “good” 

condition class.

0 percent No change.

Core and shell 

preservation—resilient materials

Maintenance using high quality, innovative, 

and functional materials (metal roofing and fiber cement siding); and additional renovations to improve the physical resiliency of the building (installing hurricane clips, stainless-steel nails, and window clips). This action also included costs affiliated with fully (extensively) documenting the resource in its new condition (conditions report), as well as minimal interpretation (for example, one panel sign that addresses adapting to climate change).

0 percent Building changes to “good” 

condition class.

31-percent loss in

integrity (reduction inoverall significancescore at time ofaction).

No change.

Elevate This action consists of (1) bringing the 

building to standard (core and shell preservation—historic materials) and (2) raising the minimum floor elevation to reduce the likelihood of structural damage from storm-related flooding, sea level rise, or both. This action also included costs affiliated with fully (extensively) documenting the resource in its new condition (historic structure report), as well as minimal interpretation (for example, one panel sign that addresses adapting to climate change).

0 percent Building changes to “good” 

condition class.

43-percent loss in

integrity (reduction inoverall significancescore at time of action,assuming historicmaterials used inpreservation).

Sensitivity changed 

to “low” (1).

Table 1.6. Optimal Preservation Model adaptation actions and model dynamics.—Continued
34 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore Table 1.6. Optimal Preservation Model adaptation actions and model dynamics.—Continued Action1 Definition Model dynamics Depreciation of building condition2 Improvement in building condition3 Loss of historic integrity4 Reduced vulnerability Relocate This action consists of (1) bringing the building to standard (core and shell preservation—historic materials) and (2) moving the building to a less vulnerable location (within the historic district) to reduce the likelihood of structural damage from storm-related flooding, sea level rise, or both. This action also included costs affiliated with fully (extensively) documenting the resource in its new location (conditions report), as well as extensive interpretation (for example, multiple panel signs that address adapting to climate change). 0 percent Building changes to “good” condition class. 30-percent loss in integrity (reduction in overall significance score at time of action, assuming historic materials used in preservation). Sensitivity changed to “low” (1). Exposure changed to “low” (1). Elevate and relocate This action consists of (1) bringing the building to standard (core and shell preservation—historic materials), (2) moving the building to a less vulnerable location (within the historic district), and (3) raising the minimum floor elevation to reduce the likelihood of structural damage from storm-related flooding, sea level rise, or both. This action also included costs affiliated with fully (extensively) documenting the resource in its new condition (conditions report), as well as extensive interpretation (for example, multiple panel signs that address adapting to climate change). 0 percent Building changes to “good” condition class. 61-percent loss in integrity (reduction in overall significance score at time of action, assuming historic materials used in preservation). Sensitivity changed to “low” (1). Exposure changed to “low” (1).
Appendix 1. Optimal Preservation Model Objectives, Attributes, Weights, Actions, and Costs 35

Action1 Definition

Model dynamics

Depreciation of 

building condition2

Improvement in 

building condition3 Loss of historic integrity4 Reduced vulnerability

Document and 

monitor

This action includes costs associated with 

fully (extensively) documenting the resource (historic structures report) and erecting a 6-foot chain-link fence around a building and monitoring the condition. The fencing reduces the potential for human injury as there is potential for the building to deteriorate by the natural elements. This action also includes costs affiliated with extensive interpretation (for example, multiple panel signs that address adapting to climate change).

Low (4-percent annual loss)—

Applied to buildings in “good” condition (LCS score of 3).

Medium (5-percent annual 

loss)—Applied to buildings in “fair” condition (LCS score of 2).

High (6-percent annual loss)—

Applied to buildings in “poor” condition (LCS score of 1).

No change (apply annual 

depreciation rate based on current condition).

5-percent loss in integrity

applied annuallyfrom year of decisionforward.

No change.

Active removal This action consists of physically removing 

the building from the historic district (debris and hazard demolition) and disposing the materials according to Federal guidelines (debris and hazard disposal). This action also included costs affiliated extensive interpretation (for example, multiple panel signs that address adapting to climate change).

N/A N/A; condition score set 

to 0.

90-percent permanent

loss in integrity(building removedfrom landscape;extensiveinterpretation to “tellthe story;” retains 10percent integrity frominterpretive panels).

Sensitivity removed 

(0).

Exposure removed 

(0).

1Any building that does not have a Historic Structure Report (HSR) also includes associated costs to develop one for all actions except “no action” and “annual maintenance.”2An estimate of how much a building’s condition would annually decay over a 30-year planning horizon. Rates determined through consultation with National Park Service (NPS) personnel. The rate is 

applied to only the “condition of the building” attribute but affects the building’s historical significance and, thus, the building’s resource value. N/A is not applicable.

3An estimate of how much a building’s condition would improve in the year an adaptation action is applied. In the year an action is applied, the model would not include the depreciation rate; however, in the 

subsequent years (if no action is applied to that building), the decay rate would be reintroduced to the model. Rates determined through consultation with NPS personnel. The rate is applied to only the “condition of the building” attribute but affects the building’s historical significance and, thus, the building’s resource value. N/A is not applicable.

4An estimate of how much historical integrity would be lost by applying specific actions, with the assumption that any action would change the historic fabric of the building and, consequently, decrease its 

integrity. Rates determined through consultation with NPS personnel, then updated to reflect values that account for percentage of integrity loss to the seven criteria of integrity. This rate is applied to each of the historical significance attributes at the time of action, except for condition of the building (because actions either improve or depreciate the condition of the building), affecting both the building’s historical 

Table 1.6.

significance score and the building’s resource value.

Optimal Preservation Model adaptation actions and model dynamics.—Continued
36 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore Table 1.7. Adaptation actions and maintenance costs for each of the 17 historic buildings. Historic building Maintenance cost1 by adaptation action Active removal Core and shell— Historic materials Core and shell— Resilient materials Relocate the building Elevate the building Document and monitor Annual maintenance Cape Lookout Village Lighthouse $10,050,000.00 $1,018,000.00 $13,126,000.00 N/A $10,626,000.00 $74,000.00 $5,400.00 Keepers Quarters $112,500.00 $125,000.00 $1,086,000.00 N/A $311,000.00 $42,500.00 $6,000.00 1907 Keepers Quarters $95,000.00 $78,000.00 $656,000.00 $435,000.00 $199,000.00 $37,000.00 $4,500.00 Live-Saving Station $122,000.00 $154,000.00 $796,000.00 $450,000.00 $264,000.00 $40,000.00 $7,800.00 Galley (Coast Guard) $70,000.00 $25,000.00 $271,000.00 N/A $81,000.00 $22,000.00 $3,500.00 O'Boyle Bryant House $105,000.00 $65,500.00 $301,000.00 $166,000.00 $127,000.00 $25,000.00 $3,400.00 Gordan Willis House $95,000.00 $53,000.00 $251,000.00 $145,000.00 $111,000.00 $25,000.00 $2,400.00 Jetty Workers House 1 $95,000.00 $91,000.00 $251,000.00 $183,000.00 $149,000.00 $25,000.00 $2,400.00 Jetty Workers House 2 $95,000.00 $158,000.00 $251,000.00 $250,000.00 $216,000.00 $25,000.00 $2,400.00 Portsmouth Village Church $234,000.00 $95,000.00 $1,111,000.00 $2,819,000.00 $306,000.00 $38,000.00 $6,000.00 School $94,500.00 $31,000.00 $397,500.00 $256,000.00 $98,500.00 $33,500.00 $2,700.00 Post Office $84,500.00 $34,000.00 $374,500.00 $228,000.00 $95,500.00 $33,500.00 $2,400.00 Lifesaving Station $320,000.00 $76,000.00 $1,611,000.00 $952,000.00 $273,000.00 $58,000.00 $7,200.00 Summer Kitchen (Live- Saving Station) $70,000.00 $23,000.00 $165,000.00 $170,000.00 $86,000.00 $24,000.00 $2,400.00 Washington-Roberts House $125,500.00 $67,000.00 $524,500.00 $302,000.00 $144,500.00 $33,500.00 $3,600.00 Frank Gaskill House $75,000.00 $36,000.00 $321,000.00 $188,000.00 $104,000.00 $27,000.00 $2,400.00 Henry Pigott House $82,500.00 $63,000.00 $366,000.00 $295,500.00 $133,000.00 $33,500.00 $3,300.00

1Maintenance costs were estimated by Cape Lookout National Seashore cultural resource management personnel. The estimated costs are likely conservative (actual costs would likely be greater due to transportation and lodging requirements); however, the costs were estimated in a consistently across building types (that is, the estimates are reliable). The individual charged with developing the cost estimates first 

grouped buildings based on type of structure, then consulted National Park Service databases (Facility Management Software System, Project Management Information System, Asset Management Reporting System, and the “Optimizer”) and used prior knowledge to estimate costs by building, type, location (that is, districts have different distances to Park Headquarters) and square footage. The cost estimation task for the 17 buildings took roughly 20 hours to complete.
Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 17 Buildings Among Different Scenarios 37

Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 

17 Buildings Among Different Scenarios

In this appendix, the relative value for each historic building is presented by year for each scenario, with the relative value 

displayed in terms of the building’s condition, remaining significance, and use potential. In the Optimal Preservation (OptiPres) 

Model, we separate the historical significance attribute “condition” in this presentation because it is directly altered by the 

application of different actions. Condition has a weight of 0.17 within the historical significance score. The remaining significance includes three other components of historical significance: association to fundamental purpose, character, and national 

register (total weight 0.83 of historical significance). Historical significance accounts for 0.71 of relative value, and use potential 

accounts for 0.21 of relative value. The model dynamics for changes in conditions, remaining significance, and use potential by 

different adaptation actions are described in appendix 1, table 1.6.
38 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Figure 2.1. Components of resource value under annual allocation of $50,000. Relative value is the weighted scores of utility for 

each building. [CLV, Cape Lookout Village; PV, Portsmouth Village]

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

Year

Relati

ve 

value

Condition Remaining significance Use potential

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30
Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 17 Buildings Among Different Scenarios 39

Year

Relati

ve 

value

Condition Remaining significance Use potential

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30

Figure 2.2. Components of resource value under annual allocation of $222,000. Relative value is the weighted scores of utility for 

each building. [CLV, Cape Lookout Village; PV, Portsmouth Village]
40 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Year

Relati

ve 

value

Condition Remaining significance Use potential

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30

Figure 2.3. Components of resource value under annual allocation of $500,000. Relative value is the weighted scores of utility for 

each building. [CLV, Cape Lookout Village; PV, Portsmouth Village]
Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 17 Buildings Among Different Scenarios 41

Year

Relati

ve 

value

Condition Remaining significance Use potential

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30

Figure 2.4. Components of resource value under annual allocation of $70,000 with an additional $225,000 every 5 years. Relative 

value is the weighted scores of utility for each building. [CLV, Cape Lookout Village; PV, Portsmouth Village]
42 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Year

Relati

ve 

value

Condition Remaining significance Use potential

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30

Figure 2.5. Components of resource value under annual allocation of $222,000 with an additional $225,000 every 5 years. Relative 

value is the weighted scores of utility for each building. [CLV, Cape Lookout Village; PV, Portsmouth Village]
Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 17 Buildings Among Different Scenarios 43

Year

Relati

ve 

value

Condition Remaining significance Use potential

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30

Figure 2.6. Components of resource value under annual allocation of $222,000 assuming no vulnerability. Relative value is the 

weighted scores of utility for each building. [CLV, Cape Lookout Village; PV, Portsmouth Village]
44 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Year

Relati

ve 

value

Condition Remaining significance

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0.0

0.2

0.4

0.6

0.8

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30

0 5 10 15 20 25 30

Figure 2.7. Components of resource value under annual allocation of $222,000 assuming no use potential. Relative value is the 

weighted scores of utility for each building. [CLV, Cape Lookout Village; PV, Portsmouth Village]
Appendix 2. Value of Condition, Remaining Significance, and Use Potential for 17 Buildings Among Different Scenarios 45

Total cost, in thousands of dollars

Accumulated value Total cost

Henry Pigott House PV

Lifesaving Station PV Summer Kitchen PV Washington−Roberts House PV Frank Gaskill House PV

Jetty Workers House 2 CLV Church PV School PV Post Office PV

Galley (Coast Guard CLV) O’Boyle Bryant House CLV Gordon Willis House CLV Jetty Workers House 1 CLV

Lighthouse CLV Keeper’s Quarters CLV 1907 Keeper’s Quarters CLV Lifesaving Station CLV

0

200

400

600

0

200

400

600

0

200

400

600

0

200

400

600

0

200

400

600

0

10

20

0

10

20

0

10

20

0

10

20

0

10

20

Accumulated 

value

1: Annual allocation of $50,000.

2: Annual allocation of $222,000.

3: Annual allocation of $500,000.

4: Annual allocation of $70,000 and an additional $225,000 every five years.

5: Annual allocation of $222,000 every year and an additional $225,000 every five

years.

6: Annual allocation of $222,000 without consideration of vulnerability.

7: Annual allocation of $222,000 every year without consideration of use potential. 

1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7

1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7

1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7

1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7

1 2 3 4 5 6 7

Figure 2.8. Accumulated values and total costs of individual buildings predicted under each scenario. X-axis identifies the scenario. 

[CLV, Cape Lookout Village; PV, Portsmouth Village]
46 Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore

Appendix 3. Computer Code for Optimal Preservation Model

Two documents of computer code for the Optimal Preservation Model are available for download at 

https://doi.org/10.3133/ofr20181180.
For more information concerning the research in this report, contact:

USGS National Climate Adaptation Science Center

12201 Sunrise Valley Drive, Mail Stop 516

Reston, VA 20192

casc@usgs.gov

For additional information, visit: https://casc.usgs.gov/

Learn more about this and other Southeast Climate Adaptation Science Center projects at:

https://casc.usgs.gov/centers/southeast

Publishing support provided by the

Reston and Rolla Publishing Service Centers
Seekamp and others—Optimizing Historical Preservation—Overview of the OptiPres Model and Pilot Test at Cape Lookout National Seashore—OFR 2018–1180

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20181180