Measures Guidebook for Flood and Storm Risk ...

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Measures Guidebook for Flood and Storm Risk Reduction Projects North America Risk Reduction and Resilience Priority March 2017

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TABLE OF CONTENTS Introduction ............................................................................................................................................................... 3 Chapter 1: Physical Exposure Metrics ....................................................................................................................... 8 Core Physical Exposure Metrics............................................................................................................................. 9 1.1 Erosion Reduction and Shoreline Stabilization Afforded by Intertidal and Shallow Nearshore Reefs ........... 9 1.2 Attenuation of Wave and Storm Induced Flooding by Coastal Ecosystems ................................................. 12 1.3 Flood Attenuation in River Floodplains ......................................................................................................... 18 Chapter 2: Environmental Metrics .......................................................................................................................... 22 Core Environmental Metrics................................................................................................................................ 23 2.1 Coastal Habitat Extent and Connectivity ....................................................................................................... 23 2.2 Abundance and Diversity of Target Species .................................................................................................. 28 Additional Environmental Metrics ...................................................................................................................... 31 2.3 Water Clarity in Coastal Systems ................................................................................................................... 31 2.4 Water Quality in Freshwater Systems ........................................................................................................... 36 2.5 Habitat Protection ......................................................................................................................................... 39 2.6 Carbon Sequestration .................................................................................................................................... 42 Chapter 3: Economic Metrics .................................................................................................................................. 44 Core Economic Metrics........................................................................................................................................ 45 3.1 Cost of Project ............................................................................................................................................... 45 3.2 Damages Avoided .......................................................................................................................................... 46 Additional Economic Metrics .............................................................................................................................. 51 3.3 Lifecycle Costs................................................................................................................................................ 51 3.4 Jobs Touched ................................................................................................................................................. 54 Chapter 4: Social Metrics......................................................................................................................................... 56 Core Social Metrics .............................................................................................................................................. 57 4.1 People Benefitted .......................................................................................................................................... 57 Additional Social and Economic Metrics ............................................................................................................. 61 4.2 Recreation ..................................................................................................................................................... 62 4.3 Economic Development ................................................................................................................................ 63 4.4 Property Values ............................................................................................................................................. 64 4.5 Public Awareness ........................................................................................................................................... 65 4.6 Policy Change................................................................................................................................................. 66 Chapter 5: Ecosystem Services ................................................................................................................................ 67 Appendix 1: References and Literature Cited ......................................................................................................... 74

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INTRODUCTION

Risk Reduction & Resiliency Using Nature to Build Resilient Communities The United States regularly suffers from nature’s unpredictable fury. In 2016, according to NOAA’s National Climatic Data Center (NCDC) and analysis by CoreLogic, the overall flood loss in the U.S. was about $17B, which is six times the flood losses in 2015. Extreme events continue to occur. In 2011 and again in 2015, we saw historic flooding on the Mississippi River and its tributaries. Over the winter of 2015 and 2016, wild storms caused major flooding along both of our coasts and much of the Midwest and South. This past year, there were five flood events that exceeded $1B in losses. Ninety-six percent of the total U.S. population lives in counties where federally declared, weather-related disasters have occurred since 2010. Meanwhile, average flood losses in the U.S have increased steadily to nearly $10 billion annually, driving the National Flood Insurance Program $24 billion into debt. At the same time, the places affected by floods and storms face other threats. Between 1998 and 2006 the nation lost over 360,000 acres of wetlands or marshes in coastal areas. Some of this loss occurred because of development, but much happened because of water pollution and sea level rise, which can kill plants not adapted to frequent or steady deluges of saltwater. Our rivers are in no better shape. Freshwater fishes are declining at a rate higher than any other species type. A primary factor is loss of habitat, which can also impact water quality. One of the biggest threats to our coasts and rivers, however, is development in flood-prone areas combined with associated efforts to protect these developments with seawalls, dikes, dams or levees to control water. These structures are often built on beaches or wetlands where they destroy valuable habitat and block natural processes like the movement of sand along coasts. These “hardened” structures can put a chokehold on rivers

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by constraining their flows. Also, they provide a false sense of security, as communities often experience greater losses when these systems fail.

Making the Case for Nature There is a better way. Communities have choices in how they prepare for and respond to floods. Often overlooked is the role that nature itself can play instead of, or alongside, seawalls or dams and levees. For instance, we are safer when rivers have more room during floods so floodwaters can disperse and slow down across their floodplains rather than rise and threaten communities. Along our coasts, natural features like sand dunes, wetlands, coral reefs and oyster reefs reduce wave heights and moderate storm surges. In addition, most investments in “grey infrastructure” solutions for disaster risk reduction focus on single purpose—levees and seawalls are meant to hold back water or prevent land erosion. Natural features or ‘nature-based infrastructure,’ such as oyster reefs, floodplains, coastal wetlands, etc. can also perform these functions yet do so in a way that provides multiple additional benefits. In addition to risk reduction, natural systems provide a host of other benefits, or ecosystem services. They offer recreation benefits, which in turn support local economies. For instance, people don’t vacation along coasts for views of concrete seawalls or hardened shorelines. Cleaner waters and healthy beaches, a side benefit from nature-based infrastructure, improve property values. Wetlands, floodplains, prairies and marshes filter water and sequester pollutants, including nutrients that would otherwise reach our coastal waters where they fuel oxygendepleted “dead” zones that negatively impact ecosystems, including the nation’s seafood industry. Natural areas also provide valuable wildlife habitat, including nursery grounds for fish. These attractive and highly valued community amenities often have broad community support, even if restoration projects that rely on the delivery of those benefits are costlier than traditional infrastructure solutions. For example, in 1995, a $115M “gray” Napa River (California) flood protection proposal from the U.S. Army Corps of Engineers was rejected amidst strong local opposition. Two years later, Napa County voters approved a local sales tax increase to fund a “living river” design, despite its higher projected cost of $163 million.

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Finally, nature-based solutions need not be an either-or approach. We can achieve significant risk reduction when these solutions are planned and implemented together with a portfolio of other approaches.

Mainstreaming the Use of Nature-Based Approaches The Nature Conservancy (TNC) is focused on mainstreaming the use of natural infrastructure to help reduce risk from floods and storms and to maintain and restore the important ecosystem services associated with our rivers and coasts. Specifically, the Conservancy is: • Using science to test and measure the value of nature in infrastructure decisions and the benefits it provides. • Working in communities across the country to demonstrate the value of nature-based solutions. • Providing tools to help communities determine which nature-based solutions are best for them. • Advancing local, state and national policies so they enable consideration of and provide funding for nature-based solutions. • Encouraging insurance and reinsurance companies to more consistently incorporate natural solutions into their catastrophe modeling and flood insurance rate maps (FIRMS) so that premiums reflect the benefits they deliver; and working with them to provide financing mechanisms that incentivize investments in conservation and restoration to help reduce flood risk. • Working with engineering and consulting firms to help them to consistently consider natural and nature-based approaches in the flood and storm projects they design for communities and businesses.

This Guidebook The purpose of this Measures Guidebook for Flood and Storm Risk Reduction Projects (hereafter, simply referred to as the “Guidebook”) is twofold. First, this Guidebook is intended to support practitioners at The Nature Conservancy evaluate the outcomes of natural infrastructure projects designed to reduce risk from floods and storms and protect or restore the health of vital ecosystems. Second, by measuring outcomes more consistently we hope to improve our understanding of how to site, build and monitor these approaches. By using a more standardized set of performance measures across projects, we hope to gain a broader perspective of the role and success of risk reduction projects at the regional, state or even at the North America level. The metrics in this Guidebook are meant to measure both risk reduction benefits and other important social, economic and environmental outcomes. By using standardized performance measures we can more easily see how our work is collectively performing and can more readily describe and monetize the suite of benefits they provide.

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The Importance of Measuring Ecosystem Services The ways in which natural systems benefit people can be described as ecosystem services. The metrics in this Guidebook provide some important measures of the benefits of our risk reduction projects. Some of these are benefits to nature—for example, the size and type of habitat created, protected or restored. Some are benefits to people—the amount of flood damages potentially avoided by the development of a new oyster reef. However, it is challenging to separate benefits to nature and benefits to people since they are both connected through ecosystem services. More specifically, ecosystem services are the goods and services provided to people by functioning ecosystems (Daily, 1997). Human well-being is at the core of this concept. In the example above, the oyster reef that absorbs wave energy can perform a flood risk reduction service only if there are people, property or landscapes that provide other services that people value that might be subject to damage if that oyster reef were not there. That same reef may support fish habitat, but provides an ecosystem service only in the form of enhanced fishing opportunities should commercial or recreational fishermen benefit from increased fish production. (See https://www.victoriaadvocate.com/news/2016/oct/25/study-shows-oyster-reef-restoration-helps-economy/). Ecosystem services are a product of both a functioning ecosystem and the people who are the beneficiaries of ecological functions. A simple framework to describe this framework is presented by this graphic:

Starting from the left, an ecosystem service analysis starts with an understanding of the ecosystem, relevant habitat features and the changes to this system. Much of the work of the Conservancy over the last 60 years has focused these types of actions and on measures such documenting acres of important ecosystems protected or restored. Next, a project needs to identify specific ecosystem services—that is, the benefit the habitat provides to people—that might be impacted by the management action. For example, to what degree is water quality protected/enhanced. This step is critical and ideally should generally involve stakeholders to help specify the ways in which the changes might impact affected people.

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Finally, in the far right box of the illustration, is the need to understand how a change in ecosystem condition affects the services it provides. There is also the step of assessing how much this change specifically benefits people—that is, what is the value of this change to people? Did the water quality improve enough to reduce water treatment costs? Did it improve property values? How many more people have access to freshwater? What are the effects on public health? The Guidebook highlights the need to work in interdisciplinary teams that include a range of experts (e.g. ecologists, economists and other social scientists, hydrologists, engineers, etc.) to consider how such metrics can be used to inform ecosystem service analysis. Measuring ecosystem services requires understanding which services are likely to be relevant and useful early in the project design, and it requires the gathering of information on project performance. A more detailed discussion of ecosystem services and the types of analyses that can quantify the magnitude of the benefits to people is included in chapter 5.

Acknowledgements The establishment of standardized metrics related to nature-based risk reduction restoration projects has been a priority of TNC North America’s Risk Reduction and Resiliency Initiative since 2014. We would like to thank the many contributors to this Guidebook, including Emily Hayba, Tim Boucher, Kris Johnson, Greg Guannel, Laura Geselbracht, Elizabeth Schuster, Chris Shepard, Brian Boutin, Bob Kelly, Mark P. Smith, Sarah Murdock, Todd Strole, and Ryan Luster.

Using this Guidebook This Guidebook was created to provide guidance for practitioners inside the Conservancy who are planning or implementing natural infrastructure projects that demonstrate a reduced risk, increased environmental outcomes, or both. While this guide was developed with Conservancy practitioners in mind, the Guidebook is also intended to be useful to those outside the Conservancy implementing similar projects. The Guidebook provides a suite of possible metrics to be selected based on project characteristics and goals. In many sections, additional resources are provided for more information on specific metrics or methodologies. Metrics are organized into two tiers: (1) Core Metrics are those that should be considered for every project such that we can more effectively report outcomes, and (2) Additional Metrics are more site specific, and are included as applicable. The Guidebook contains five chapters on measures: two environmental, two social and one that provides a summary on the valuation of ecosystem services.

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CHAPTER 1:

Physical Exposure Metrics Core Metrics 1.1 Erosion Reduction and Shoreline Stabilization 1.2 Storm Surge/Tsunami Attenuation for Coastal Ecosystems 1.3 Flood Attenuation in River Floodplains

Additional Metrics none

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Core Physical Exposure Metrics 1.1 EROSION REDUCTION AND SHORELINE STABILIZATION AFFORDED BY INTERTIDAL AND SHALLOW NEARSHORE REEFS Adapted from Baggett, L.P., S.P. Powers, R. Brumbaugh, L.D. Coen, B. DeAngelis, J. Greene, B. Hancock, and S. Morlock, 2014. Oyster habitat restoration monitoring and assessment handbook. The Nature Conservancy, Arlington, VA, USA., 96pp. Section authors: Christine Shepard, Laura Geselbracht Metrics: Shoreline Loss/Gain, Shoreline Slope, Length affected Methodology: Permanent transects Sampling Frequency: Preand post-construction, then annually and post storm event. Performance Criteria: statistically significant change in shoreline positions, lower shoreline slope or increased mean shoreline elevation

The purpose of this metric is to measure the erosion reduction or accretion of materials to stabilize and expand shorelines. Natural infrastructure, whether existing, restored or added to a coastline, can help stabilize shoreline position and reduce erosion, making the shoreline less vulnerable to natural hazards. The type of natural infrastructure improvements most beneficial for any particular shoreline area will depend on many factors, such as exposure, ecoregion and surrounding systems, whether natural or manmade. This section describes the metrics that can be used to assess changes in shoreline position and elevation with the installation of intertidal or shallow nearshore reefs. The following is a general methodology for deploying the permanent transects, with more detailed metric-specific methods presented in the subsection. Measurements should be performed on the shoreline adjacent to the natural infrastructure project and at a control site with similar current and wave conditions.

Metric: Shoreline Loss/Gain (change in shoreline position) Units: shoreline loss/gain (m/year), and length of affected shoreline (meters)

Methodology: Establish permanent transects along the length of the project area, with the ‘base stake’ starting at least 10 m inland of the shoreline edge (farther inland if project site is in an area subject to high erosion rates), and continuing to the constructed reef. Base stake locations should be marked with a dGPS (or a mapping/survey grade GPS with post-processing for sufficient accuracy, or RTK GPS). Transects should extend from the permanent base stakes along an established compass. Permanent transects should also be established along an equal linear distance of shoreline edge at the control or natural reference site.

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Due to the high degree of variability of shoreline characteristics, both within and between restoration sites, the number of permanent transects that should be established will depend on the characteristics of a particular restoration site. If the shoreline adjacent to the restoration site has a high degree of sinuosity and irregularity, then more permanent transects are needed to adequately document changes in shoreline. With any permanent base stakes deployed in a coastal environment, there is a possibility of one or more stakes becoming dislodged, and, as such, practitioners should reinforce the permanent base stakes appropriately. Permanent base stakes should be constructed of materials that will withstand harsh environmental conditions and should be driven as far into the substrate as possible (in some environments this may be several meters), leaving 1 m of the stake exposed. Practitioners should periodically check the permanent base stakes and reset or replace them as necessary, being sure to record the locations of any new base stakes with a dGPS. The following methodologies represent low- and high-tech options for measuring shoreline loss or gain adjacent to a project. Data should be entered into mapping software and mapped over a geo-referenced basemap. Using a dGPS Map the shoreline edge adjacent to the constructed reef, taking continuous readings with a dGPS. It is preferred that the entire shoreline edge adjacent to the restored reef be measured and the length documented, but if the project is very large or this is otherwise not possible, a minimum of 100 m of shoreline edge at each end and in the middle of the project site should be measured. Repeat this process for an equal lateral distance of shoreline edge at the control or reference site. Using a Tape Measure Using a tape measure, measure the linear distance from the permanent base stakes to the shoreline edge along the established transects. Using Surveying Instrumentation If a practitioner is familiar with basic surveying techniques and is proficient with advanced surveying instrumentation (e.g., a Total Station or other instruments used to find horizontal and vertical angles and distances), then the practitioner may perform a topographic survey along each of the transects using these instruments. If using surveying instrumentation, data for the shoreline loss/gain metric and the shoreline profile/elevation change metric (below) can be obtained simultaneously by performing a topographic survey. Take elevation/location measurements at regular intervals from the permanent base stakes to the shoreline edge (or continuing all the way to the constructed feature if also collecting information for the profile/elevation change metric) along each transect. Using Aerial Photography When using aerial imagery, including very high resolution satellite imagery (1m or under), or drone imagery (5cm)—which can be flown repeatedly, be sure that you use appropriate geo-referencing tools (permanent base

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stakes with markers that are visible from the air, and the presence of a permanent feature) for measuring shoreline position and for scaling purposes. If possible, ortho-rectified aerial photographs (geometrically corrected to have a uniform scale) should be used. Using the aerial images, measure the linear distance from the permanent base stakes to the shoreline edge along the transects.

Metric: Shoreline Profile/Elevation Change Units: shoreline profile/elevation change (meters/year), Shoreline elevation change (i.e., rise/run) (unitless), and length of affected shoreline (meters) Methodology: For the methodologies listed below, it is suggested that a dGPS be used to mark the locations of the measurements taken. For all methodologies, measurements should be taken at the project site and at a control site. Using Surveying Instrumentation If a practitioner is familiar with basic surveying techniques, then traditional surveying equipment, such as a surveyor’s level or laser level and graduated rod, can be used to create profiles and measure elevation change for each transect. Take elevation measurements at 1 m intervals, moving seaward from the permanent base stake to the reef, being sure to note location and elevation of the shoreline edge. Repeat this process for an equal linear distance of shoreline edge at the control site. The practitioner may perform a topographic survey along each of the transects using these advanced surveying instruments (see above) by taking elevation measurements at regular intervals (determined by the total transect length) along each transect from the permanent base stake to the reef, being sure to note location and elevation of the shoreline edge. Repeat this process for an equal linear distance at the control site. Low-Tech Method See: http://fcit.usf.edu/florida/teacher/science/mod2/resources/emery.board.pdf http://data.naturalcapitalproject.org/nightly-build/invest-users-guide/html/coastal_protection.html#beachsurvey-with-emery-boards Calculation The mean elevation change can be calculated by taking the mean of the shoreline slopes of all transects. The shoreline profile (elevation change data per measured point) for each transect should be graphed as a line graph, and an overall shoreline profile for the site can be obtained by calculating the mean elevation change of all transects for each measured point.

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1.2 ATTENUATION OF WAVE AND STORM INDUCED FLOODING BY COASTAL ECOSYSTEMS Section authors: Laura Geselbracht, Greg Guannel Metric: Areal Extent of Inundation

The purpose of this metric is to help quantify the change (ideally reduced) area of inundation attributed to natural features or nature-based solutions.

Methodology: modeling, often verified with information from coastal community assessment and field measurements

Flooding from coastal storms is generally a result of three factors: storm surge, waves and wave runup.

Sampling Frequency: models can be done pre- or post-construction. Inundation data is gathered post storm event. Performance Criteria: statistically significant reduction is inundation area.

Storm surge is the rise of water generated by a storm, over and above the predicted astronomical tide. Wave runup refers to the height above the stillwater elevation (tide and surge) reached by the swash. Together, these forces can be highly destructive to structures and to natural features. The potential extent and severity of impact from storms is dependent on a number of variables, including local geomorphological characteristics storm intensity and duration. The extent to which a coastal ecosystem can reduce both storm surge, wave height and wave runup varies greatly by type of ecosystem and the characteristics of the specific coastal ecosystem. This section addresses the ability of a protected, created or restored coastal ecosystem to change the extent of inundation of areas caused by coastal storms.

Even though empirical data of inundation extent pre- and post-storm are helpful to estimate the protective benefits of natural systems, they are not always practical because of the random nature of storm occurrence and path, the difficulty of comparing the impacts of storms in nearly identical settings with and without natural systems, and the cost of data collection before and after storms. An alternative to on-the-ground measurement is modeling, using data from field observations for calibration. Below we provide methodologies for measuring extent inundation after a storm and some general modeling approaches. We also provide a chart that provides an overview of the roles of natural systems in a resilience project and their ability to moderate inundation area, erosion or wave energy.

Metric: Areal Extent of Inundation Unit: Acres or hectares

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Methodology: While there are multiple techniques to measure flooding extent and depth to create a volumetric measurement of flood attenuation in the inundated area, the most common techniques are: • 1, 2 & 3 dimensional models • Aerial imagery • Real time satellite imagery • Pre- and post-storm on-the-ground photo comparisons • Mapping inundation area pre- and post-storm The most typical methodology for determining coastal flood inundation area is through 1-, 2-, and 3-D modeling with 2-D modeling being the most common model used. Models inputs are digital elevation models (DEM) that include bathymetry, land cover types and associated roughness values (Manning’s coefficients), Bathymetry, vegetation density, height, diameter, footprint and drag coefficient, and reef dimensions and friction coefficient, or transmission coefficient. The most accurate elevation models are derived from LiDAR. If LiDAR is not available, then USGS produces digital elevation models at 10m and 30m resolutions for the United States (except Alaska). Storm surge is generally estimated using 2-D models, where the role of natural systems is incorporated via friction or Manning coefficients (Wamsley et al., 2009). A more complicated, but potentially more accurate approach, includes the use of 3-D models that resolve the footprint and characteristics (i.e., vegetation density, height, diameter, footprint; reef dimensions and footprint) of the natural systems (Sheng and Lapetina, 2012). The modeling of wave height in the presence of vegetation is usually achieved through the use of 2D models. There are also 1D models that provide first order estimates of the role of vegetation. Estimation of wave runup is more complex, and usually done through the use of specialized wave models (e.g., Xbeach), or approximations. References: http://89.31.100.18/~iahrpapers/87250.pdf, https://www.researchgate.net/publication/289424715_Modeling_of_wave_attenuation_by_vegetation_with_X Beach The most typical method for on-the-ground determination the extent of coastal flooding is the comparison of pre- and post- aerial photos of affected areas. This information is often coupled with on-the-ground survey of high water line on building, vegetation, etc., to estimate the height of the storm surge and its inland extent. Comparison between relatively identical areas fronted or not fronted by vegetation provides estimates of the ability of nearby natural systems to reduce flooding. In addition, pre- and post-LiDAR data or photos are used to estimate shoreline change caused by the storm. Analysis of these data provides an indication of the ability of nearby natural systems to either reduce the impact of the storm on the shoreline, or, in the case of sand dunes, to protect landward properties. https://coastal.er.usgs.gov/hurricanes/ (see Data Section tab).

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Below we provide specific information on the extent to which each coastal ecosystem may be able to reduce storm impacts and the important metrics for the following coastal ecosystems: coral reef, mangrove forest, coastal marsh, beach dune and barrier islands. Specific measurement techniques are not provided, as these are left to the coastal practitioners (see references listed).

Background Info on Performance by Habitat Type Different coastal ecosystems have different effects on storm surge, waves and wave runup. Table 1 provides an overview of the typical responses by habitat type. We also offer some discussion and some associated references for several habitat types. Coral Reefs Coral reefs are most effectives at reducing wave impacts and wave runup on coastlines; more research is still needed to determine their ability to reduce storm surge. Coral reefs, because they are a bathymetric perturbation, reduce the wave energy that would otherwise impact the shoreline by an average of 97% (Ferrario et al. 2014). The reef crest is the most important portion of the reef for reducing wave energy and has been estimated to reduce wave energy by 86%. Height of the reef crest is the most important variable, followed by the shallowest depth of the reef, and bottom friction/roughness, a function of species composition. Studies of post-storm impacts using satellite imagery found that wave penetration inland was correlated with the width of fringing coral reefs (Gunasekera, 2014), and wave intensity is magnified in areas where coral poaching had occurred (Fernando et al., 2008). Loss of corals on reefs results in an intensification of wave impacts and runup on coastal areas. Other references: Leiper et al. (2014); Rugosity: Knudby and LeDrew (2007), Dustan et al. (2013); Sheppard et al. (2005) ; http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0158094; http://www.sciencedirect.com/science/article/pii/S0272771405000545

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Oyster Reefs Oyster reefs act as nearshore breakwaters that protect coastlines against the impacts of waves. They also promote shoreline accretion during non-storm periods, which, in turn, increase the ability of the coastal area to absorb the impacts of storms. It is an open question as whether reefs are effective at moderating storm surge. Mangroves Mangrove forests have been shown to be effective at reducing storm surge and the impacts of waves on coastlines (McIvor et al., 2012). Most of their protective value comes from the fact that they are dense, wide, tall and relatively inflexible plants that dissipate incoming storm energy. For example, studies on hurricanes that affected the southwest portion of the Florida peninsula in 2004 and 2005 found peak water level height reduced by 4.2 to 9.4 cm/km over intact mangroves with few gaps (Kraus et al., 2009). Impacts associated with Wilma in 2005 (category 3, maximum storm surge 5 m) studied by Zhang et al. (2012) using field observations and numerical simulations found that surge amplitude decreased at a rate of 40-50 cm/ km over a solid mangrove forest and at a rate of 20 cm/km over a mixed mangrove island/open water area. Suzuki et al. (2012) and McIvor et al. (2012) also provide various examples of wave attenuation by mangroves. Other references: Putz and Chan (1986), Betts (2006). Coastal Marsh (saltwater, brackish and freshwater) Coastal marsh has the ability of reducing storm surge, especially if marsh plants are tall, dense and thick. For example, Wamsley et al. (2009), found that coastal marsh can attenuate storm surge by 4 cm to 25 cm per km of marsh width. However, marsh plants are also flexible, and wetlands are not uniformly covered with marsh, which reduces their ability to reduce storm surge. As a consequence, storm surge reduction by marshes is a complex process not fully explained by marsh width.

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Table 1 – Habitats and Coastal Risk Reduction What makes it protect

Habitat

Performance factor

“Uncontrollable” performance variable

(From Greg Guannel, 12/2016, In prep.)

How does it protect

“Controllable” Failure variable performance during storm variable

Reduce nearshore wave energy

Reduce nearshore currents

Reduce surge height

Reduce inundation level

Reduce risk of erosion of private property Chronic

Beaches

Height and width

Sediment size, beach slope.

Sand Dunes

Height and width

Sediment size

Consecutive Sediment supply, storms prevent vegetation replenishment Fails if erodes too much; Beach height and consecutive width, vegetation storms prevent replenishment

Salt marshes

Physical characteristics; Climate and species width

Sediment and water supply, water quality

Flattens; breaks

Mangroves

Physical characteristics; Climate and species width

Sediment and water supply, water quality

Breaks

Seagrasses

Oyster Reef

Coral Reef

* Yes Yes Yes Fisheries habitat Fisheries habitat

Storm water storage

Keeps up with SLR

Co-benefits

Acute

Yes – forms sandbars

No

No

Yes – height of berm

Yes – width

No

No - Erodes

Recreation;habitat for critters

No

No

No

Yes – barrier (until fails)

Yes – height and width

No

No - Erodes

Recreation;habitat for critters

Yes – drag Yes* – drag force force

Yes – drag force

Yes

Yes

Yes

Yes

Yes – drag Yes* – drag Yes – drag force force force

Yes

Yes

Yes

Yes

Physical characteristics, Nearshore water Yes – drag water depth Climate and species Flattens; uproots quality force and distance to shore Height, width, Yes – percent cover, relative Nearshore water water depth, Ocean water quality Destroyed quality depth and distance to roughness shore Water depth, Yes – distance to Nearshore water relative shore, percent Ocean water quality Coral destroyed quality depth and cover roughness (roughness) Legend:

Long-Term Viability

Protection Service

Yes - build up or landward Fisheries habitat; migration water filtration; carbon Yes - build sequestration up or landward migration

Yes* – drag force

No

No

Yes*

Yes*

No

Yes - moves Fisheries habitat; carbon in newly sequestration created bed

Yes*

No*

No*

Yes*

No*

No

Fisheries habitat; Yes - builds water filtration; up carbon sequestration

Yes*

Yes*

Yes*

Yes*

Yes*

No

Yes - builds Fisheries habitat; Recreation up

More research is needed; not fully proven Strong measureable impact Moderate measurable impact Low measurable impact Strong co-benefit Weak co-benefit

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Ultimately, the ability of coastal marsh to attenuate storm surge can be misleading, because this process is greatly influenced by the surrounding landscape and storm attributes, such as forward speed, track and intensity (Wamsley et al., 2010; Masters, 2013). A recent study by the USACE (2013) recommends not assuming that marshes reduce storm surge because of the wide uncertainty (http://www.corpsclimate.us/docs/USACE_Coastal_Risk_Reduction_final_CWTS_2013-3.pdf). Nevertheless, coastal marsh can reduce wave impacts, including those during hurricanes, and their effects can be modeled using the same models are for mangroves. Other references: Neckles and Dionne (2000), Niedowski (2000), Neckles et al. (2013). Beach dune Sand dunes act as a physical barrier that reduces inundation during tropical storms (Houser et al. 2008; USACE 2013). They tend to fail to protect when storm surge is higher than the crest of the dunes, or when waves erode enough of the dunes that it collapses, and an overwash regime is created. A study of storm impacts following Hurricane Ivan in 2004 along Santa Rosa Island (Florida Panhandle) demonstrated that areas with higher, more morphologically complex dunes experienced less overwash penetration (Houser et al., 2008). Thieler and Young (1991) found that dunes of 30 m in width at the base were able to protect developed areas behind the dunes from Hurricane Hugo in 1989 (Category 5). See also work that USGS did to evaluate vulnerability of sand dunes along the U.S. coast (https://marine.usgs.gov/coastalchangehazardsportal/) and information on basic protection and failure mechanisms at https://coastal.er.usgs.gov/hurricanes/coastal-change/. Coastal vegetation on sand dunes helps the dune system grow and has the potential to reduce erosion and overwash during storms. Other references: Levin et al. (2004), http://ascelibrary.org/doi/abs/10.1061/%28ASCE%290733-950X%282003%29129%3A6%28270%29, https://coastal.er.usgs.gov/hurricanes/assessments/background.php, https://www.researchgate.net/publication/270822597. Barrier islands The morphology and orientation of barrier islands can affect the extent to which storm surges impact the area behind the barrier island. Suhayda (1997) modeled the impact of a Hurricane Andrew type storm under several different morphological configurations to better understand the magnitude and type of changes. Wamsley et al. (2009) conducted storm surge simulations using the ADCIRC storm surge model and found that barrier islands reduce storm surge height and can reduce wave energy in the area behind the barrier islands. Other references: Kindinger et al. (2013).

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1.3 FLOOD ATTENUATION IN RIVER FLOODPLAINS Section author: Ryan Luster Metrics: Peak Stage and/or Areal Extent of Inundation Methodology: low and high tech options Sampling Frequency: preproject construction and post flood event.

The purpose of this metric is to quantify the benefit of intact and connected floodplains to measure the reduction of both peak flows and often the extent of flooded areas in developed or agricultural areas likely to be damaged by flood events. The areas that have a flood risk reduction benefit from a connected floodplain are often upstream or downstream of the “functional” floodplain that is storing and conveying water as a natural function of the river.

Protection of intact floodplains, the reconnection of floodplains through levee setbacks or berm removals, or restoring floodplains by removing non-flood compatible uses can reduce risk of flooding—both at the site and upstream and downstream. Flooding occurs when the river channel’s capacity (bankfull) is exceeded and the excess water spills onto adjacent land (the floodplain) as overbank flow, and, in some extreme cases, backflow events. Flood delineations take into account many factors including, but not limited to, elevation of the floodplain above the river bank, the presence of levees, the stage, depth and velocity of the water in various parts of the floodplain, flood return intervals (1,000, 500, 200, 100, 50, 20, 10, 4, 2, 1 year), infrastructure (buildings, bridges), and human activities (agriculture, urbanized areas). The ability of a floodplain to reduce the extent upstream and downstream from the floodplain site is related to the size and volumetric capacity of the inundation area and the dynamics of the water within the site and river channel during the various stages of the flood. Vegetation and other roughness factors within floodplains and along rivers also affect water movement and are often considered in modeling of floods (http://www.nys-soilandwater.org/crep/forms/FactSheet2.pdf). Performance Criteria: lowered stage to discharge relationship (rating curve), reduced damage assessment

Also, if the project involves the building, rebuilding or setting back of a levee, the areas benefiting from the project also include those areas protected by the levee in addition to the areas upstream and downstream that may benefit from the connected or reconnected floodplain. The extent of upstream and downstream benefits of such activities would need to be measured through modeling.

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Metrics: Peak Stage and/or Areal Extent of Inundation Units: acre foot; velocity (feet/second); flood stage (feet/inches); water surface elevation (feet/inches); cubic feet per second (cfs); cubic meters per second (cms); rating curve; discharge/flow (cfs or cms) Definitions: • Acre foot: The volume of one acre of surface area to a depth of one foot. This metric measures the total volume of water in a specified area of inundation. • Velocity: Feet per second. This metric measures the flow rate across an obstruction[s] (e.g., within channel, across a floodplain, against a levee, through vegetation, against a building or infrastructure). • Flood stage: Feet/inches as measured above the NOAA flood stage elevation. Although not a volumetric unit, this metric is typically used as a surrogate for a floodplain’s ability to convey and hold stormwater. The National Weather Service defines flood stage as the river level that begins to impact life and/or property. • Water surface elevation (WSE): Feet/inches as measured above a given baseline. • Cubic feet per second (cfs): One cubic foot per second equals 448.8 gallons per minute, 1.98 acre-feet per day, and is equal to 0.0283 cubic meters per second (cms). • Rating table or curve: The relationship between stage and discharge typically plotted as stage (in feet) over discharge (in cfs). More information can be found at: http://www.nws.noaa.gov/os/hod/SHManual/SHMan040_rating.htm • Discharge (also referred to as flow): The volume of water that passes through a given cross section per unit time. Discharge is commonly measured in cubic feet per second (cfs) or cubic meters per second (cms). Additional terms related to calculating and understanding flood attenuation can be found at http://www.dnr.state.mn.us/water/hydroterms.html. Methodology: While there are multiple techniques to measure flooding extent and depth of any particular flood, some sort of model or long-term measurement is needed to understand the impact of floodplain protection or restoration to flooding extents upstream and downstream. These more technical approaches are typically undertaken by experienced hydraulic modelers and/or contracted out to specialized hydraulic engineering firms. Low tech: • Monitor river flow and depth as measured by U.S. Geological Society (USGS) or state operated river gauges • Manually establish observed high‐water marks to calibrate LiDAR and 1-, 2-, and 3-D modeling outputs

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High tech: • Mapping inundation area pre- and post-floodplain change through a GIS to determine water surface elevation differential • LiDAR based inundation maps • Digital Elevation Models (DEM) • 1-, 2-, and 3-D hydraulic and hydrologic modeling • Pre- and post-aerial imagery • Time sequences of pre- and post-project satellite imagery For real-time monitoring and measurements, river gages are the most common technology used to measure the stage and volume of water for the area where the gage is located. NOAA (http://water.weather.gov/ahps/forecasts.php) has a comprehensive river monitoring network that allows for real-time river stage monitoring. For planning purposes, the most typical methodology for determining a floodplain’s flood attenuation capacity and the resulting decrease in stage and flooding extent upstream and downstream is through 1-, 2-, and 3-D modeling, with 2-D modeling being the most common model used. Digital elevation profiles of the floodplain areas are key input for these models. The most accurate elevation models are derived from LiDAR. If LiDAR is not available, then USGS produces digital elevation models at 10m and 30m resolutions for the continental United States. Roughness values (Manning’s coefficient) are then assigned to the land uses within the floodplain. When information is added from flood rating curves, historical gage data and bathymetry, the model then can calculate outputs such as water surface elevations (WSE) and flow velocity and direction. For further details regarding the type of information that is used in flood modeling, visit: http://onlinemanuals.txdot.gov/txdotmanuals/hyd/hydraulic_principles.htm. Sampling Frequency: Here, sampling frequency refers to the frequency of running and updating 1-, 2-, and 3-D models used to determine the flood attenuation capacity of an area. It is critical to establish a baseline prior to a flood or a proposed change to features or land uses on the floodplain. Re-evaluating the inputs going into the 1-, 2-, and 3D models will be necessary after a flood event or anthropogenic changes to the floodplain because: • • •

channel that changes require new bathymetric surveys, the floodplain’s planform is reworked resulting from erosion and deposition changes during a flood event, and flood rating curves are updated after each flood to incorporate new data on measured flood stage elevations by river gages.

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1-, 2-, and 3-D models rely on the accuracy of these inputs to provide a clear evaluation of an area’s flood attenuation capacity. Performance Criteria: The primary performance criteria for flood attenuation projects is the stage to discharge rating curve. This can be determined by calculating the pre- and post-project rating curve for flood events at a fixed river stage gages. If the stage to discharge (rating curve) is lowered post-project, as compared to pre-project, this would indicate the project increased flood attenuation for the area targeted for flood attenuation. Additional performance criteria, from an economic perspective, is to conduct an avoided cost analysis to determine if an increase in flood attenuation led to a decrease in damages to infrastructure and/or homes. A more complete analysis could be done to determine the number of homes or structures that benefited (i.e., those not flooded or those that flooded less) because of the increase in flood attenuation the project produced.

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CHAPTER 2:

Environmental Metrics Core Metrics 2.1 Coastal Habitat Extent and Connectivity 2.2 Abundance and Diversity of Target Species

Additional Metrics 2.3 2.4 2.5 2.6

Water Clarity in Coastal Systems Water Quality in Freshwater Systems Habitat Quality Habitat Protection

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Core Environmental Metrics 2.1 COASTAL HABITAT EXTENT AND CONNECTIVITY Section author: Timothy Boucher The purpose of this metric is to provide a measure of the environmental benefit of nature-based approaches to flood and storm risk reduction. The extent of any habitat is critical not only to its survival, but also the ecosystem Methodology: GIS services it provides—in this case coastal resilience and protection. This includes the amount of habitat that exists (patch size and configuration), the Sampling Frequency: varies, condition and viability, and how connected the habitat patches are to one see below another. Connectivity need not be direct (i.e. a joining strip of habitat), but as Performance Criteria: in the case of corals or mangroves, can connect via ocean currents as well. For varies, see below habitat extent, while size and shape are important, other factors need to be included, such as the condition of the habitat in question, and how protected it is (especially for providing future ecosystem services). For connectivity, not only must the type and extent of connection be examined, but also the condition of the connection (i.e. is it strong—allowing for the free flow of species and high performance of a service) and how secure the connection is (i.e. is it well protected or under threat). The combination of extent and connectivity has direct implications for how well an ecosystem performs the desired ecosystem service. For instance, if patches of habitat are closer together they might perform better than if spaced far apart. Metrics: Habitat Extent, Connectivity

Metric: Habitat Extent - spatial dimensions of habitat area (which can also be referred to as patch size and shape). Units: ft2, m2, acres, hectares Methodology: Almost all the extent measurements should be done in a Geographic Information System (GIS), allowing for spatial analysis of fragmentation and connectivity. This will allow ecologists and managers to more accurately assess and strategically plan for the protection and enhancement of the ecosystems and, in turn, reach the desired service they provide. While some connections lend themselves easily to a GIS (i.e. strips of habitat), others are more temporary and ephemeral in nature (such as ocean currents), and are harder to analyze. This can be determined using existing data or created using remotely sensed data (drone, satellite, etc.). Field data, including the use of an appropriate GPS system to gather spatial location, will be needed to verify habitat data.

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The natural variation of patch size and shape should also be determined (or modelled), so that the patch being studied can be assessed for viability. Initial study of extent should be done before protection or restoration plans are put in place. Broadly speaking, detailed habitat type and condition should be determined by field surveys, which would feed into a remotely sensed analysis that will inform area, dimension and connectivity with other habitats being considered in the study. Field methods and habitat description needs will vary by habitat, but there are certain universal characteristics that need to be measured. Once these are established, individual metrics for each ecosystem should be measured. It should also be noted, however, that many of these ecosystems occur together or in near proximity (such as corals, seagrasses and mangroves), and affect one another, so it is often advantageous to gather information about all of them during field surveys and consequent analyses. For an introduction on remote sensing of coastal habitats, see the publication from NOAA—A Coastal Resource Manager’s Guide (http://coast.noaa.gov/digitalcoast/publications/coastal-remote-sensing). Sampling Frequency: To evaluate habitat extent and its variation once the initial study has been conducted, the expected change needs to be evaluated and frequency of sampling designed accordingly. For instance, if winter storms are a driver of change, then habitat extent should be measured after each season. Most often habitat extent will be measured on a yearly basis (or longer), depending on the growth of the habitat. Performance Criteria: Requirements for success will depend on each project and habitat in question. If protection is what is needed, then stable habitat extent may be required. If restoration is an objective, then increased habitat extent may be required. The amount of increase (if desired) would depend on each habitat and placement of each habitat area.

Metric: Connectivity – distribution of habitat patches. Units: Using FRAGSTATS, the CONNECT function should be analyzed. CONNECT is a connectance index and is a percentage of the number of number of joins between patches divided by the total number of potential joins. Zero being no connection, 100 being total connection of all patches. Distance between patches should also be measured (in feet or meters). Methodology: These data inform the critical understanding of the ecosystem and surrounding ecosystems. The understanding of patch distribution is often vital to the success of the ecosystem in coastal and floodplain resilience. This metric might also be considered a type of connectivity metric. A GIS is needed to create the needed spatial data for FRAGSTATS to run and to evaluate the distances between patches.

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Sampling Frequency: As with Habitat Extent, consideration of the type of habitat, the disturbances, and an evaluation of natural connectivity is required. Once this is established, sampling frequency is determined by the change (or lack of change) that you want to evaluate. Most often this will be yearly or longer. Performance Criteria: Performance criteria are given for an array of habitat types as follows: Coral Reefs Coral reefs form natural coastal barriers and have the ability to reduce flooding, erosion and storm damage. Coral reefs can reduce wave energy, velocity and height, and hence, in terms of ecosystem services, can reduce rates of beach/shoreline erosion, coastal inundation and be important for sediment retention. The amount of ecosystem services provided by coral reefs (in the form of coastal resilience) is directly related to the depth, orientation and size of the coral reef[s]. For a more technical discussion of the remote sensing of coral reefs, see Mumbya et al. (2004) and Xu and Zhao (2014). Additional recommended metrics for coral reefs include: reef type, dimensions, orientation, continuity, health, reef bathymetry including reef crest height and depth of the shallowest portion of the reef, rugosity including species composition, and reef morphology including width of the reef and gaps (porosity). Oyster Reefs Connectivity and extent are dealt with extensively in the Oyster Habitat Restoration Monitoring and Assessment Handbook. Oyster reefs provide numerous ecosystem benefits that are similar to coral reefs in that they can function as critical coastal barriers and are important for wave attenuation and/or dissipation, and sediment retention. Additional recommended metrics for oyster reefs include: in addition to four universal oyster reef metrics (reef areal dimension, reef height, live oyster density, and oyster size-frequency distribution), two further metrics are proposed for measuring connectivity—nearby reef density and size frequency, and nearby-reef large oyster abundance.

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Mangroves Mangroves provide a number of ecosystem benefits linked to coastal risk reduction. Amongst others are storm surge reduction, wave energy and coastal erosion reduction. Mangroves also serve a vital role in providing fish nursery habitat and can store large amounts of carbon (but are limited in size compared to other forests). Globally, mangroves are found in 123 tropical and subtropical countries, with 73 species recognized as “true” mangroves. In the last 25 years, 20% of mangroves have disappeared, mostly due to coastal development and conversion for shrimp farming. This rate is 3-4 times faster than other terrestrial forests. Mangroves also have high economic value in terms of ecosystem benefits, especially to coastal people. Mangroves have been studied and mapped in great detail using high resolution satellite imagery (World Atlas of Mangroves, 2010). For more detailed discussion of mapping and remote sensing of mangroves, Kuenzer et al. (2011) and Green et al. (1998) are good places to start. Additional recommended metrics for mangroves include: forest length, forest width, forest density, structural complexity (prop roots, branches, stems, foliage), tree height, trunk and root diameter, species composition, canopy closure/forest morphology. Coastal Marshes and Wetlands Coastal Marshes provide important ecosystem benefits similar to corals and oyster reefs (wave attenuation) and additionally help with sediment stabilization and raw material provisioning. Since coastal marshes are above water (mostly at low tide), they are easier than belowwater habitats to measure and delineate; they can be easily measured using remotely sensed satellite imagery. For a more detailed account of mapping and remote sensing of coastal wetlands, see Hardisky et al. 1986 and Belluco et al. (2006). Additional recommended metrics for marshes and wetlands include: marsh elevation and continuity, vegetation type, density and height, marsh width, and local bathymetry and topography. Beach Dunes Beaches dunes provide several ecosystem benefits—mostly wave attenuation, supporting a sediment cycle, storing and filtering of water (through the sand). Mapping beach dunes is fairly easy using satellite imagery, although care must be taken to delineate the flatter beach area (if present) from the beach dune area. In terms

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of remote sensing and mapping, beach dunes and other beach areas are not dealt with separately as other habitats, but are map-able using general remote sensing techniques. Additional recommended metrics for beach dunes include: dune field width, berm width, height of the foredune, alongshore extent of the dune system, distance from shore, morphology of foredune and backbarrier dunes, width of dune at base, presence of dune vegetation and thickness of dune vegetation, beach slope, sediment grain size and supply. Seagrasses Seagrass beds provide many ecosystem services that are directly linked to coastal resilience; they provide vertical structure that helps slow currents down, attenuate waves, and increase deposition of and reduce resuspension of sediments. While mostly underwater, the seagrass beds are shallow enough to be identified using satellite imagery and so are not difficult to map to help identify seagrass bed dimensions and connectivity. Remote sensing of seagrasses is covered in detail in the following publication (Chapter 15 from the book Seagrasses: Biology, Ecology and Conservation by Larkum, Orth and Duarte) by Dekker et al (2006). Additional recommended metrics for seagrass include: area of seagrass, species composition, mean shoot density, mean shoot height, distance of bed from shore, bathymetry, slope of area surrounding seagrass bed, topography of land behind seagrass bed.

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2.2 ABUNDANCE AND DIVERSITY OF TARGET SPECIES Drawn from: Baggett, L.P., S.P. Powers, R. Brumbaugh, L.D. Coen, B. DeAngelis, J. Greene, B. Hancock, and S. Morlock, 2014. Oyster habitat restoration monitoring and assessment handbook. The Nature Conservancy, Arlington, VA, USA., 96pp. Section author: Brian Boutin The purpose of this metric is to provide a measure of the environmental benefit of nature-based approach to flood and storm risk reduction. Trends in the abundance and diversity of target species or species complexes (both flora and fauna) can be valuable data points to assess the overall ecological Methodology: varies, see impact of a habitat restoration project. Understanding how ecologically, below. economically or Sampling Frequency: during culturally valuable periods of maximal species species respond postrestoration is essential abundance to both adaptively Performance Criteria: manage the restoration increasing species abundance approach and to garner additional financial and community support. Selection of species for quantification is based upon individual restoration goals, and may be inclusive of all species present (e.g. biodiversity) or a single species for which the restoration project aims to enhance. These targets may vary depending on the specific location at which the restoration is occurring and take into consideration both ecological and social (i.e. community) goals of restoration. Metrics: Species Abundance, Species Diversity

Metric: Species Abundance (ST) Units: density of each focal species or species groups (individuals/unit area of measurement) Methodology: Methods to sample abundance vary widely depending on the species of interest and include active sampling such as quadrats, point counts and netting, as well as passive sampling like traps, soundscape recordings and point/intercept sampling. Techniques that provide an estimate of density are preferable, as they provide a basis for comparison. For example, in terrestrial locations vegetation is often surveyed using the plot, quadrat and Measures Guidebook for Flood and Storm Risk Reduction Projects |

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transect method where a standard number of quadrats and transects are embedded in fixed plots. When surveying waterbirds, numbers of individuals within a 100 m radius of fixed observation points can be sampled at one-hour intervals. Multiple methodologies may be necessary to adequately sample the target species or species complexes. Practitioners should consult best practices manuals (e.g. Baggett et al. 2014) to help guide the selection of the most appropriate technique[s] for their geography and species they hope to impact with their restoration project. Regardless of technique, a sufficient number of monitoring stations should be established or samples taken to provide the necessary spatial coverage for the determination of restoration benefits. Sampling points or stations can either be randomized or standardized, and both restored and control and/or natural reference sites should be surveyed. As utilization of habitats may vary for species between day and night, sampling should be conducted during the time of day in which the focal species or species complexes are generally present. Sampling Frequency: Sampling should be focused at a minimum during periods of maximal species abundance. Samples should be taken at an interval that allows for statistical comparisons of abundance to be made on a year-to-year basis. Performance Criteria: Target species or species complexes should exhibit an overall increasing trend with the ultimate goal of having a statistically greater abundance in the restored condition than that prior to restoration, or an abundance that is equal to or greater than that of the natural reference site.

Metric: Species Diversity (Shannon-Wiener Index) Units: unitless measurement (H’) Methodology: Species diversity is a mathematical expression that incorporates both the number of species (species richness) and some measure of their relative abundance within an assemblage. As with species abundance, methods to measure species diversity vary widely depending on the ecosystem context in which sampling is occurring but generally take the same form of active and passive sampling techniques (see above). Multiple methodologies may again be necessary to adequately sample the focal species complexes. Once measurements are completed, practitioners can calculate the Shannon-Weiner Index using the following formula: 𝑛𝑛𝑛𝑛 𝑛𝑛𝑛𝑛 𝐻𝐻′ = − �[ � � × ln( )] 𝑁𝑁 𝑁𝑁

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Where ni = number of individuals of each given species and N = the total number of organisms observed. Sampling Frequency: Sampling should be focused at a minimum during periods of maximal species abundance. Samples should be taken at an interval that allows for statistical comparisons of diversity to be made on a year-to-year basis. Performance Criteria: Species diversity should exhibit an overall increasing trend, with the ultimate goal of having a statistically greater diversity in the restored condition than that prior to restoration, or a diversity that is equal to or greater than that of the natural reference site.

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Additional Environmental Metrics 2.3 WATER CLARITY IN COASTAL SYSTEMS Adapted from Baggett, L.P., S.P. Powers, R. Brumbaugh, L.D. Coen, B. DeAngelis, J. Greene, B. Hancock, and S. Morlock, 2014. Oyster habitat restoration monitoring and assessment handbook. The Nature Conservancy, Arlington, VA, USA., 96pp. Section author: Christine Shepard Metrics: Seston and/or Chlorophyll-a Concentrations & Light Penetration Methodology: varies, see below Sampling Frequency: at least quarterly Performance Criteria: decrease in particulates and increase in depth of light penetration

The purpose of this metric is to provide a measure of the environmental benefit of nature-based approach to flood and storm risk reduction. Clear water is critical for healthy flora and fauna in marine systems. For example, seagrasses area keystone species in marine systems, and are thus an important species to maintain, as they improve the health of coastal ecosystems. Seagrasses flourish in regions with clear water, which enables light to reach these underwater plants. Fish also depend on clear water to avoid predation and to be able to see their prey.

To assess the performance of a restoration project in improving water clarity, practitioners may choose to measure one or more of the following aspects of water clarity: (1) seston concentration; (2) chlorophyll-a concentration; or (3) light penetration. Methodologies for these metrics are provided below. If the project has a bioremediation component, then practitioners may choose to sample additional parameters (e.g., toxins, heavy metals, bacteria) of interest.

Metric: Seston and/or Chlorophyll-a Concentrations Units: total particulates (mg/l); organic content (%); Chlorophyll a (µg/l) Methodology: Seston concentration (includes total particulates and organic content) and chlorophyll are commonly measured

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metrics in water quality studies. Sampling for seston and/or chlorophyll-a concentrations usually involves the collection of water samples at various places around the project, as well as immediately up-current and downcurrent of the project; however, newer methodologies that involve the use of in situ fluorometry have been successfully performed in the field (Grizzle et al. 2006, 2008). Further information on sampling methodologies and analytical techniques used for water quality studies can be found at Judge et al. (1993), Welschmeyer (1994), Cressman et al. (2003), Nelson et al. (2004), Grizzle et al. (2006), Grizzle et al. (2008), Booth and Heck (2009), and Plutchak et al. (2010), to name a few. Practitioners can contact any water quality lab (often affiliated with a state agency, an academic institution or a local cooperative extension) to process water samples. Sampling of seston and/or chlorophyll-a concentrations should be performed pre- and post-construction at the project site as well as at a control site or natural reference reef. Each sample set should be accompanied by a measurement of the water depth at the mid-point of the reef and by flow measurements. Flow rates may be determined by measuring the amount of time it takes for an orange, a drifter or drogue to cover a known distance and should be reported on a cm sec-1 basis (see Grizzle et al. 2006, 2008 for further information on measuring water flow in intertidal and shallow subtidal habitats). Flow rates may also be determined using an instrument such as an electromagnetic flow meter or an acoustic Doppler current velocimeter. For Seston Concentration (Total Particulates and Organic Content) For particulates, collect triplicate (n = 3) 1L water samples at three locations (midpoint of reef, 0.5 m up-current of reef, and 0.5 m down-current of reef) at 5-10 minute intervals following both slack ebb tide and slack flood tide. Ten sets of triplicate samples should be taken overall. Note the distances between the sample locations in m, as well as the water depth at the midpoint of the project. When sampling, water samples should be taken mid-depth between the water surface and the reef surface, and sampling bottles should be opened and closed under the water at the desired depth to avoid surface contamination. Each water sample should be filtered through a pre-weighed 1 µm GF/F or GF/C glass fiber filter, dried to a constant weight at 40°C, and weighed to determine total particulates (subtract filter weight from this value to determine total particulate weight). Total particulates should be reported in mg/l. To determine organic content, combust filters at 450°C for four hours, then cool and weigh (Nelson et al. 2004; Grizzle et al. 2006; and also Judge et al. 1993). Organic content is calculated by subtracting the post-combustion weight from the precombustion weight. Values should be reported as percent organic content (calculated by dividing the total particulate value by the organic content value). Chlorophyll-a For chlorophyll-a, collect triplicate 50 ml water samples at three locations (midpoint of reef, 0.5m up-current of reef, and 0.5m down-current of reef) at 5-10 minute intervals as early in both ebb tide and flood tide as possible. When sampling, water samples should be taken mid-depth between the water surface and the reef surface and sampling bottles should be opened and closed under the water at the desired depth to avoid surface

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contamination. Six sets of samples should be taken overall. Determine chlorophyll a content using the fluormetric technique of Welschmeyer (1994) (Nelson et al. 2004), and report values in µg/l. Sampling Frequency: To obtain appropriate baseline data, sampling of seston and/or chlorophyll-a concentrations should be conducted quarterly to discern seasonal differences in the year prior to reef construction. Post-construction sampling of seston and/or chlorophyll-a should also be conducted quarterly to discern seasonal differences. Performance Criteria: As monitoring progresses, there should be a trend of decreasing total particulates, organic content and/or chlorophyll values, with an ultimate goal of having statistically lower values than pre-construction conditions and at the control site, or roughly equal to that of the natural reference site. In addition, throughout the monitoring period, seston and/or chlorophyll-a concentrations should be statistically lower on-reef and immediately down-current of the reef than concentrations found immediately up-current of the reef and at offreef or control locations.

Metric: Light Penetration Units: Vary depending on instrumentation used. See methodologies for units. Some habitat restoration projects, such as oyster reefs, remove seston from the water column through their filtration activities, increasing water clarity, which in turn allows ambient light to penetrate more deeply into the water column. This increased light penetration can, in turn, have beneficial effects on submerged aquatic vegetation (SAV) populations in areas where light had previously been limiting. While light penetration can be measured using low-tech methods such as Secchi discs and transparency tubes, handheld and in situ instrumentation that measures light intensity may also be used. It is important to note that each of these instruments measures a different aspect of light penetration (i.e., a Secchi disc measures the depth to which light penetrates, whereas light sensors measure the light penetration at depth), and, as such, practitioners should be consistent with the instrumentation used to measure light penetration and should report all data in the appropriate units. Methodology: Using in situ light sensors (Units = lux) Deploy an array of 5 light intensity sensors at roughly the center of the reef (or center of the project footprint if the reef consists of patch reefs), 50 m up-current of the reef, and 50 m down-current of the reef. In each array, the height of the sensors should be as follows:

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• • •

1 sensor (the ambient light sensor) should be located so that it will not be submerged during high tide and data gained from it should be used to normalize the light field relative to ambient conditions. 2 sensors (“k” sensors) should be deployed 30.5 cm (12”) above the reef condition sensors and data gained from these sensors should be used to calculate the k-coefficients across the reef. 2 sensors (reef condition sensors) should be deployed 10 cm above the reef surface.

All light sensors should be mounted so that the sensor is facing up (unless the instructions for that particular sensor state differently). Sensors should take continuous measurements every five seconds for one hour just after slack high tide (measurements should commence at the beginning of ebb tide). Measurements should be reported in lux, and a grand mean should be calculated for each location. Please note that this methodology is meant to provide information on the relative differences in light penetration (in lux) between the restored site and pre-construction conditions or conditions at control or reference sites, and not the amount of photosynthetically active radiation (PAR) present. Using Handheld Instrumentation (Units = will vary by instrument, but may be lux or µEs-1m-2) The methods for measuring light penetration using handheld instrumentation will vary by the instrument used. Reference readings of ambient air irradiance should be taken in conjunction with irradiance readings taken at depth. Practitioners may either measure irradiance at regular depth intervals until the reef surface is reached in order to construct a light extinction curve, or only take irradiance readings just above the reef surface. Triplicate readings should be taken immediately up-current and down-current of the reef, as well as at three points on the reef (the mid-point and midway between the midpoint and both ends of the reef). Time of day and tidal stage during which measurements were taken should be noted. Using a Secchi Disk Units = Depth of disappearance (cm) Secchi discs should be 20 to 30 cm in diameter and have alternating black and white quadrants, and be attached to a weighted line that is marked in 1 cm increments. To reduce water surface glare, readings should be taken from the shady side of the boat, or if in shallow waters, with the practitioner’s back toward the sun. To take the readings, slowly lower the Secchi disc into the water until it disappears. Then slowly raise and lower the disc slightly to determine the exact depth of disappearance and record this depth. Triplicate readings should be taken immediately up-current and down-current of the reef, as well as at three points on the reef (the midpoint and midway between the mid-point and both ends of the reef). Time of day and tidal stage during which measurements were taken should be noted. Further information on measuring turbidity using a Secchi disk can be found in the EPA Voluntary Estuary Monitoring Manual (Ohrel and Register 2006, http://water.epa.gov/type/oceb/nep/monitor_index.cfm). Using a Transparency Tube A transparency tube is a clear plastic tube with marked units (preferably millimeters or centimeters), similar to a graduated cylinder, and with a black and white pattern on the bottom similar to that found on a secchi disk. To measure water clarity, collect a water sample using a bucket from mid-depth between the water surface and the top of the reef. Gently swirl the water in the bucket to homogenize the sample, and, while looking down into the Measures Guidebook for Flood and Storm Risk Reduction Projects |

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tube, carefully pour the water into the transparency tube, avoiding bubbles, until the black-and-white pattern at the bottom of the tube is no longer visible. Record the depth at which the pattern disappears. Triplicate readings should be taken immediately up-current and down-current of the reef, as well as at three points on the reef (the mid-point and midway between the mid-point and both ends of the reef). Time of day and tidal stage during which measurements were taken should be noted. Further information on measuring turbidity using a transparency tube can be found in the EPA Voluntary Estuary Monitoring Manual (Ohrel and Register 2006, http://water.epa.gov/type/oceb/nep/monitor_index.cfm). Sampling Frequency: To obtain appropriate baseline data, sampling for light penetration should be conducted quarterly in the year prior to reef construction. Post-construction sampling of light penetration should, at a minimum, be conducted quarterly to discern seasonal differences. Performance Criteria: As monitoring progresses, there should be a trend of increasing light penetration, with an ultimate goal of having statistically greater values than pre-construction conditions and at the control site, or roughly equal to that of the natural reference site. Throughout the monitoring period, light penetration should be greater on-reef and immediately down-current of the reef than found immediately up-current of the reef and at off-reef or control locations.

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2.4 WATER QUALITY IN FRESHWATER SYSTEMS Adapted from: A Primer for Monitoring Water Funds: Global Freshwater Program. TNC 2013. Section author: Ryan Luster The purpose of this metric is to provide a measure of the environmental and human use benefit of Methodology: continuous nature-based approach devices or cross-sectional to flood and storm risk sampling reduction. Freshwater ecosystems both Sampling Frequency: require clean water and continuous or produce clean water intermittently as needed when functioning properly. Unfortunately, freshwater systems are among the most degraded Performance Criteria: ecosystems in the world, placing large segments of the world’s human reduced nutrient and population in jeopardy of not having adequate access to safe drinking water sediment loads and imperiling the survival of numerous freshwater-dependent plant and animal species. Water quality sustains ecological processes that support native fish populations, vegetation, wetlands and terrestrial and bird species. Likewise, many human needs depend on water quality that is suitable for agriculture, drinking, fishing and recreation. Metrics: Nutrient Loading and Concentrations, Sediment Loads and Concentrations

When considering water quality parameters, it is necessary to distinguish between loadings and concentrations. Loadings are the amount of pollutants entering the system, while concentrations are the amounts of pollutants within a given volume of water. Models often estimate changes in loadings, while monitoring typically focuses on concentrations.

Metric: Nutrient Loading and Concentrations Units: soluble reactive phosphorus (SRP) (µg/L); soluble unreactive or soluble organic phosphorous (SUP) (µg/L); particulate phosphorus (PP) (mg/L); total suspended solids (TSS) (mg/L) Runoff from agricultural lands and livestock pastures often carries nutrients, such as nitrogen and phosphorous, into nearby streams. Nitrogen and phosphorous occur in several forms in water as a result of ongoing chemical

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transformation. Nitrogen is found as ammonia, nitrate and nitrite; total nitrogen is the sum of these. Total phosphorous is the sum of soluble reactive phosphorus (SRP), soluble unreactive or soluble organic phosphorus (SUP), and particulate phosphorus (PP). Orthophosphate is generally the major component of soluble reactive phosphorous, and is found in abundance in fertilizer and municipal and livestock waste. It is taken up readily by plants, including algae. Monitor total nitrogen and total phosphorous or orthophosphate (or SRP) concentrations in order to evaluate changes due to activities working to reduce agricultural or livestock waste runoff, or to prevent cattle from accessing streams. Monitoring external factors, such as changes in fertilizer use, cattle densities and municipal waste discharges, may be necessary to adequately explain results. Methodology: Monitoring can be conducted using continuous sampling devices that are permanently installed and regularly checked and serviced, with periodic data downloads performed. As an alternative to continuous monitoring, samples can be taken at pre-determined intervals and (ideally) during rain events, while using a hand-held flow meter. Together with cross-section measurements (discussed in the above discussion on monitoring flow), these flow meter readings can be used to calculate flow volume and rate. Chemical sampling and analysis should be conducted by a certified technicians and laboratories. Contamination can easily occur during sampling, handling and analysis. Appropriate detection limits, precision and accuracy need to be defined based on the degree of change that must be detected. Sampling and analysis should include appropriate field and laboratory blanks and duplicates. Sampling Frequency: Because nutrient runoff is strongly influenced by precipitation events, and concentrations are determined by water volume, time-matched water flow and volume data are necessary for accurate analysis of water chemistry data. Sampling should be continuous or take place across several seasons with different flow patterns and generally include storm events.

Metric: Sediment Loads and Concentrations Units: total suspended solids (TSS) (mg/L) or turbidity (nephelometric (NTU) or Jackson turbidity units (JTU)); flow volume (cfs) Sediment enters streams from surface runoff and bank erosion. While a certain level of background sedimentation in waterways is normal and expected even where natural land cover is intact, land disturbance and certain land use activities can substantially increase the amount of sediment that reaches streams and rivers, along with whatever contaminants these sediments may carry. Suspended fine sediments are generally the major sources of turbidity in streams, are transported the farthest and must be removed from municipal water supplies. Heavier components of sediment, which are suspended and transported primarily during high Measures Guidebook for Flood and Storm Risk Reduction Projects |

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flow events, are of concern for municipal water supply and agriculture intakes, since gravel, sand and heavy silts need to be removed on a regular basis. These components are also of concern for hydropower and water suppliers dependent on reservoirs, since reservoir capacity is reduced over time due to filling from sediments. Methodology: The majority of sediment inputs to waterways and transport of sediment through the watershed occurs during storm events. Monitoring source and transport of all sediment components can be challenging. However, monitoring for expected results need not include all fractions of sediment. For example, total suspended solids (TSS) measurements assess those fractions of sediment in the water column, but not sediments moving along the bottom of a stream or river (bed load sediments, mostly composed of coarse particles of higher density). Accurate monitoring of suspended sediment load requires monitoring of both flow volume and suspended sediments or turbidity. If turbidity (water clarity) is measured along with flow volume and suspended sediments, it can be correlated with suspended sediment concentrations and used as a surrogate. This relationship allows the use of continuous turbidity meters in conjunction with flow volume meters to estimate sediment concentrations in lieu of directly measuring TSS. This approach requires calibration. Sediment deposition and nutrient accumulation can also be measured through a network of feldspar clay marker horizons. Sediment cores from the material deposited over the feldspar clay pads can be dried, weighed and analyzed for its total carbon (C), nitrogen (N), and phosphorus (P) content. See https://pubs.er.usgs.gov/publication/70029583 for more information. Sampling Frequency: This monitoring design is used to evaluate in-stream changes in nutrients and sediments due to changes in runoff resulting from activities at a given site. If monitoring is conducted only after the implementation of an activity, this is a control/impact design and has inherent weaknesses. If monitoring includes before activity implementation data, this approach provides a before/after/control/impact (BACI) design at the site-level when implemented appropriately, supporting strong inference. Performance Criteria: Success is represented by a reduction in nutrients and sediment compared to baseline conditions. More information on site monitoring placement for various types of watersheds can be found in pages 47-95 in A Primer for Monitoring Water Funds: Global Freshwater Program (TNC 2013).

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2.5 HABITAT PROTECTION Section author: Todd Strole Metrics: Sites or Acres and Their Protection Status Methodology: standardize evaluation Sampling Frequency: as changes occur or new land acquired Performance Criteria: increasing area of protected land

The purpose of this metric is to provide a measure of the environmental benefit of nature-based approach to flood and storm risk reduction. The level of protection afforded to lands owned or managed by TNC is an important attribute that is useful in our internal reports as we roll up information across various geographies. This is also useful for planning or analysis efforts by partner organization and agencies designed to guide conservation in a practical and logical manner to secure land resources and landscape processes. There are several good resources available to describe levels of protection or security generally referred to as GAP Status. Generally speaking, there are 4 levels used in TNC and describe as:

Metrics: Sites or Acres in Each Category of Protection Status: Status 1. Permanent Protection for Biodiversity

Status 2. Permanent Protection to Maintain a Primarily Natural State Status 3. Permanently Secured for Multiple Uses and in natural cover Status 4. Unsecured—temporary easements lands and/or municipal lands that are already developed (e.g. with schools, golf course, soccer fields, ball fields, etc.) Science staff within each division should be consulted when assigning GAP status for TNC purposes as some employ minor modifications to these Units: level of protection, acres Methodology: A more detailed description is provided below to aid in assigning the appropriate GAP Status. Definitions of GAP status (Crist et al. 1998): Status 1: An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a natural state within which disturbance events (of natural type, frequency, intensity, and legacy) are allowed to proceed without interference or are mimicked through management.

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Status 2: An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a primarily natural state, but which may receive uses or management practices that degrade the quality of existing natural communities, including suppression of natural disturbance. Status 3: An area having permanent protection from conversion of natural land cover for the majority of the area, but subject to extractive uses of either a broad, low-intensity type (e.g., logging) or localized intense type (e.g., mining). It also confers protection to federally listed endangered and threatened species throughout the area. Status 4: There are no known public or private institutional mandates or legally recognized easements or deed restrictions held by the managing entity to prevent conversion of natural habitat types to anthropogenic habitat types. The area generally allows conversion to unnatural land cover throughout. Further guidance for gap code assignment can come from the following resources: • The USGS has a website dedicated to GAP analysis and provide useful information. http://gapanalysis.usgs.gov • If there is no practical way to contact each manager of every protected area to determine management practices, the National GAP Program (Scott et al. 1993) defines criteria for assigning GAP protection levels categorically by parcel designations. • Further distinctions by Crist (2000) were used in the “Conservation Status of Fish, Wildlife, and Natural Habitats” document include duration and intent measures. • In addition, the World Conservation Union (IUCN) has devised protection categories. https://www.iucn.org/about/work/programmes/gpap_home/gpap_capacity2/gpap_bpg/?376/Identific ation-and-gap-analysis-of-key-biodiversity-areas-targets-for-comprehensive-protected-area-systems A dichotomous key (Crist et al., 1993), such as the following, can be useful in assigning GAP Status.

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2.6 CARBON SEQUESTRATION Section author: Todd Strole The purpose of this metric is to provide a measure of the carbon capture benefits of nature-based approach to flood and storm risk reduction. Many of Methodology: approved our projects are restoring permanent vegetation and therefore would act as a methods by approved carbon sink through carbon sequestration (e.g., registries http://www.vcsprojectdatabase.org/#/project_details/919). While it is possible for projects to register and market carbon credits, simply knowing the Sampling Frequency: amount of carbon the project is capturing is valuable regardless of whether or annual not it is sold as a credit. As such, the methodologies used for carbon registries or for internal informational purposes are the same. This decision should be Performance Criteria: made in consultation with TNC’s Carbon Project Review Committee, which increasing levels of CO2 governs the process for developing and receiving internal approval for a sequestered carbon project, including working within relevant SOPs, providing the carbon project checklist, and managing the carbon project assessment and other resources. There are three voluntary registries that TNC has approved for our projects. All of them have detailed methods for various carbon streams. They each have methods for different set of activities. For instance, Climate Action Reserve and American Carbon Registry don’t have protocols at this time for wetlands, but Verified Carbon Standard does. Metrics: Mt CO2

Key Resources: The following are approved voluntary carbon registries through which TNC projects may be registered and verified, including forest protocols for improved forest management, avoided conversion and afforestation and reforestation: • Verified Carbon Standard • Climate Action Reserve • American Carbon Registry CAR and ACR are the two protocols approved for transitioning early action projects into California regulatory compliance projects. California Air Resources Board (CA ARB)—Provides details on projects considering submission to California’s compliance offset program through their forest offset protocols. Projects must be located in the continental United States. TNC staff with interest in revenuegenerating carbon projects (selling carbon credits) should investigate registering with ARB since the domestic Measures Guidebook for Flood and Storm Risk Reduction Projects |

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offset market is being driven largely by companies that must comply with CA’s cap-and-trade regulation, which means higher demand and potentially higher prices for offsets. The Regional Greenhouse Gas Initiative (RGGI) is another source of information. RGGI is a cooperative effort among the states of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island and Vermont to cap and reduce CO2 emissions from the power sector. RGGI regulated programs—RGGI uses the CA ARB protocols for its program. TNC’s Carbon Project Review Committee—Website on Connect describing standard processes for TNC and carbon markets.

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CHAPTER 3:

Economic Metrics Core Metrics 3.1 Cost of Project 3.2 Damages Avoided

Additional Metrics 3.3 Lifecycle Costs 3.4 Jos Touched

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Core Economic Metrics 3.1 COST OF PROJECT Section author: Ryan Luster

Methodology: estimated pre-project or recorded during project life

The purpose of this metric is to calculate the project costs associated with nature-based solutions to help inform future efforts in other locations. Project costs are an important metric for reasons that range from fundraising to conservation reports. Consistency enables efficient roll-up across multiple projects or a defined geography. This metric includes the up-front planning and design, development and capital costs to construct the project.

Sampling Frequency: as needed or at project close

Metric: Total Project Cost over its Expected Lifetime

Metric: Total Project Cost over its Expected Lifetime

Performance Criteria: total dollars (as compared to alternatives)

Units: dollars (in a stated year)

Methodology: Project costs are often estimated in the early stages of project development for fund raising needs, but the need here is better met by actual costs incurred. This information is useful in rolling up project costs by project type over a defined geography, often covering several business units. Costs should be reported in a constant dollar format. Planning phase • Design • Permitting • Real estate interests acquisition (fee title or easement) Implementation phase • Capital costs for project construction • Staff • Monitoring for biological outcomes • Project retirement expenses (if applicable)

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Funding Sources • The major funding sources for the project (broken out by type: private/individual, foundation, corporate and public—federal, state, local) Sampling Frequency: Ideally these costs are reported annually until the project is constructed. Operation and maintenance costs can be reported annually after construction and is address in more detail in the section 3.4. Performance Criteria: The performance criteria for this metric is total costs, and how does the chosen project alternative compare to the other alternative solutions, both natural infrastructure and traditional grey infrastructure alternatives. In certain cases, when doing nothing would lead to additional costs that are fairly well understood, it may be useful to also compare what would have happened if the project were not implemented.

3.2 DAMAGES AVOIDED Section authors: Chris Shepard, Greg Guannel, Elizabeth Schuster Metric: Avoided Damages in Dollars Methodology: Computer model or empirical Sampling Frequency: varies, see below Performance Criteria: decrease in damages to property (in Dollars) before and after a natural infrastructure project is implemented.

The purpose of this metric is to provide a measure of economic benefits (in this case avoided costs) associated with naturebased solutions to flood and storm risk management. Storms, heavy rain, large waves as well as hydrodynamic currents, threaten lives, crops and livestock. They also often damage and sometimes destroy private and public properties. Natural habitats can reduce the impacts of these hazards on people and property. Here we present methods to quantify damages to property avoided during these events.

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Metric: Avoided Damages in Dollars Damages can occur because properties are flooded during a particular event, or because some of the property eroded away during a particular event. Damages can be quantified for a wide variety of structures, including homes, public infrastructure (including critical infrastructure) and businesses. Flooding is caused by an increase in water level in rivers, at the coastline or lakes, estuaries or oceans. Erosion is caused by the action of river or coastal currents. So, the amount of avoided damages represents the amount of cost savings in properties repair or replacement due to the presence of natural infrastructures that reduced the impacts of floods and/or currents. It also represents the dollar value of natural infrastructures. While there are differences when working in coastal versus freshwater systems (e.g. one needs to consider tides when working in tidally influenced areas), the final metric of avoided damages in dollars is the same regardless of the type of system. Units: For discrete events, avoided damages 𝐷𝐷𝐴𝐴 are defined herein as the reduction in damages to the same individual properties or group of properties due to the presence of natural systems, ecologically designed structures, or natural infrastructure: 𝐷𝐷𝐴𝐴 = 𝐷𝐷𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 − 𝐷𝐷𝐻𝐻𝐻𝐻𝐻𝐻

(1)

where 𝐷𝐷𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 represents damages incurred by properties in the absence of natural infrastructure, and 𝐷𝐷𝐻𝐻𝐻𝐻𝐻𝐻 represents damages incurred by properties in the presence of natural infrastructure. For a series of events expected to occur over a given time horizon, we can compute the expected value of the natural infrastructure, or the projected total value of avoided damages, 𝐷𝐷𝐴𝐴𝑇𝑇 by taking a probabilistic approach: 𝐷𝐷𝐴𝐴𝑇𝑇

𝜏𝜏

=� 𝑡𝑡=1

𝑝𝑝𝐷𝐷𝐴𝐴 (1 + 𝑖𝑖)𝑡𝑡

(2)

where 𝑡𝑡 represents the number of years, 𝜏𝜏 represents a given time horizon, 𝑝𝑝 represents the annual probability of occurrence of the storms taken into consideration, and 𝑖𝑖 is a discount rate over the time horizon 𝜏𝜏.

For a singular or a series of storms, avoided damages can be computed using two different methods. The first method computes avoided damages using outputs of computer simulations outputs of damages calculated in the presence or absence of natural infrastructures. The second method uses actual values of damages computed at the properties affected during similar events pre- and post-construction of the green infrastructure. In the remainder of this section, we will refer to the first method as the Modeling Approach, and the second as the Empirical Approach.

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Methodology:

Modeling Approach This approach estimates avoided damages by simulating changes in flood levels or erosion using computer simulations. This approach can be completed in three steps: 1- Create a spatial inventory of the value of properties present in the area of interest, overlaid over a topographic map of the area of interest. 2- Calculate flood levels or the amount of land eroded by current during a particular storm, or a series of storms, in the presence and absence of natural infrastructure. 3- Compute avoided damages due to the presence of natural infrastructure using equations (3) and (4). A spatial property value inventory in the area of interest can be obtained by contacting local tax offices or realestate companies. These databases often contain mapped delineations of properties that include those of structures and sometimes include assessed property values. The footprints could be used to determine the square footage of a building and then be multiplied by a square footage price to derive a value estimate. In case these data cannot be accessed, it might be possible to use a combination of statistical sampling technique and census block information that include values and number of structures to develop the spatial property inventory. The program HAZUS (Natural Hazards Loss Estimation Methods) developed by FEMA contains such census block data. It is important to note that, using the modeling approach, any inventory completed long before or long after the creation of the natural infrastructure will not accurately represent the actual value of the damages avoided or prevented for three reasons. First, the value of the individual properties might have changed. Second, more development is likely to have taken place in the area of interest since construction was completed. Third, capital equipment costs per acre for agricultural lands have increased over the past 50-60 years, while per acre labor requirements have decreased. This equipment is vulnerable in the case of a flood event and would add to the tally of property at risk. Once the spatial property inventory is completed, the next step is to compute flood levels or erosion values in the area of interest. Flood levels are calculated using hydrodynamic computer simulations of the storm[s]. Different models exist, and they are different based on their level of complexity (i.e., number of processes modeled or approximated) and on whether they simulate fluvial and floodplain processes or coastal processes. For fluvial processes, flooding is computed by simulating different river stages based on the amount of rain or flow coming in the area of interest. For coastal processes, flooding is computed by estimating storm surge, waves and sometimes swash processes. Regardless of the computer model used, flood levels must be simulated in the presence or absence of natural infrastructure, and the outputs of the model simulations must show the spatial extent of the flood in the area of interest. More sophisticated approaches use a wetting/drying process to simulate the flow of water on the land. Other models only indicate flood elevation at the river banks or at the coast, in which case flood elevation over the area of interest is estimated using a bathtub approach. Measures Guidebook for Flood and Storm Risk Reduction Projects |

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From flood elevation outputs, damages are computed using empirical damage curves that estimate damage to individual structures as a function of flood elevation. Total damages in the area of interest are thus the sum of damages to all individual structures inundated for given flood levels. More information on the use of damage curves can be obtained through HAZUS and the HAZUS website. From erosion distance outputs, damages can be computed in different ways. One method is to multiply the square footage value of the various land parcels affected by the modeled event[s] by the square footage of land eroded. Another method is to compute the amount of sand or soil required to replace the eroded land (replacement cost approach). A more complex method is to determine the economic impact to the parcel[s] of land by calculating what the reduced value of the parcel will be with continued erosion (hedonic valuation approach). If a structure is affected by the erosion, it can be assumed that the entire structure needs to be evacuated or removed, and the value of this property is lost. Empirical Approach This approach estimates avoided damages by using actual observations of damages to properties and/or flood elevation or erosion distances before and after the construction of the green infrastructure. It yields more accurate estimates than the Modeling Approach, but requires a longer time, and potentially more resources and investment. Similar to the previous approach, the first step is to complete a spatial inventory of properties in the area of interest. In cases where flood reduction benefits are due to proximity to wetlands, refer to Metric 4.2 in this Guidebook to identify which structures are most likely to benefit from the natural infrastructure project. Also, note that instead of property values, it is preferable to compile data on actual damages. The next steps are a function of the data that is available or can be obtained. Ideally, there exist actual damages estimates for similar storms that occurred before and after the construction of the infrastructure. The most common source of flood damage data is from FEMA’s National Flood Insurance Program (NFIP) and the USGS. Aggregate NFIP claim data is easier to obtain (e.g. data aggregated to the municipal scale), and this claim data can often be obtained directly from municipal officials. Finer scale data (e.g. parcel-level data) may be more challenging to obtain due to privacy laws, and a Freedom of Information Act (FOIA) request can be submitted directly to your state-level FEMA contact. Allow for sufficient time, as it may take several months for the FOIA request to be processed. Data from past events may also be obtained through interviews with municipal officials or homeowners. For instance, a municipal public works department may maintain information on past damage to certain roads or other public infrastructure. Building relationships with municipalities, communities and other relevant stakeholders may increase the likelihood that these individuals are willing to share existing data with you. In any case, it is most important that damage data are obtained before and after the construction of the natural infrastructure, and those damages were incurred by similar storms.

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In cases where damage data are not available, it is necessary to obtain observed flood levels caused by similar storms, before and after the occurrence of similar storms. From observed flood levels near different structures, an estimate of damages can be computed using the flood-damage curves discussed in the previous section. If erosion caused damages, avoided damages can be estimated by using measurements of erosion before and after the construction of the infrastructure, and following the method outline in the previous section. Sampling Frequency: The sampling frequency will vary depending on the goals of the analysis and the type of flooding of interest. The two methods presented above, linking natural infrastructure to damages avoided or using the empirical approach, are relatively new areas of research, meaning that there is not an established sampling frequency. If the analysis is looking at damages avoided during storms that cause extensive damages, then one storm may be sufficient if a good control site exists. However, including a minimum of three storms would be an improvement, as it would allow one to start to see the trends, but also account for changes in storm intensity or in storm track. If one is focused on nuisance flooding caused by smaller systems that do not cause extensive damages, one may need to include a larger number of flooding events to be able to discern a difference in the level of damage before and after a natural infrastructure project is implemented. Performance Criteria: Decrease in damages to property before and after a natural infrastructure project is implemented. Note that in certain cases, the analysis may be conducted on proximity to open space (e.g. a salt marsh or a floodplain) and if damages are reduced with respect to distance to the open space area of interest, instead of before and after a natural infrastructure project.

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Additional Economic Metrics 3.3 LIFECYCLE COSTS Section author: Ryan Luster The purpose of this metric is to help quantify the long-term value of a community or project sponsor—often used to demonstrate the benefit of projects that may have higher initial costs but lower costs over time. A life cycle cost analysis (LCCA) provides a detailed account of the total costs of a Methodology: Life Cycle project over its expected life 1,2. An LCCA includes the up-front planning and Cost Analysis design, development and capital costs to construct the project, operating and maintenance costs to be incurred over the life of the project, and any costs, if Sampling Frequency: during necessary, to retire the project. Conducting an LCCA is a critical step in project alternative choosing a project alternative, as it allows project proponents to include the development full potential costs of a project in their decision-making process. An LCCA is commonly used by Performance Criteria: government agencies for planned versus realized cost choosing alternatives related to infrastructure (e.g., roads, bridges, levees), but the principles of an LCCA are easily translated to risk reduction projects for comparing nature-based risk reduction projects to hardened or engineered solutions and/or choosing alternative risk reduction projects, such as artificial reefs, levee setbacks, wetland restoration, living shorelines and other types of natural infrastructure that reduces risk. An LCCA may not be applicable to all projects, but when it is applicable and appropriate, it allows for a benefit to costs comparison, which may be required by some funding sources. Metric: cost over its expected lifetime

Metric: total project cost over its expected lifetime Units: total project cost in dollars

1

https://www.asce.org/uploadedFiles/Issues_and_Advocacy/Our_Initiatives/Infrastructure/Content_Pieces/asce-eno-lifecycle-report.pdf 2 https://lbre.stanford.edu/sites/all/lbre-shared/files/docs_public/LCCA121405.pdf

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Methodology: It is most common to do an LCCA at the beginning of a project to allow for project alternatives to be evaluated when choosing the final preferred alternative to be implemented. However, an LCCA could conceivably be conducted at the end of a project to see if the nature-based solution ended up being higher or lower costing than the traditional hardened option. The following are the lifecycle components of a project to be included in an LCCA. Planning phase • Design • Permitting • Secure funding Implementation phase • Real estate interests acquisition (fee title or easement) • Capital costs for project construction (materials) • Labor • Operate and maintain (O&M) • Repairs or replacement • Preventative maintenance • Monitor for biological outcomes • Project retirement, or expected lifespan of the project, if the project has a specified lifespan indicated to achieve project goals The project proponent can obtain cost estimates for the components of the LCCA listed above from quotes given by contractors bidding on the work to be performed. If similar projects have already been implemented, and the costs of those projects have been monitored, then a comparison can also be made between contractor estimates for the proposed project and the costs incurred from previously implemented projects. Project proponents will follow five general steps for creating an LCCA: 1. Define project goals and objectives 2. Develop an LCCA for each project alternative 3. Analyze each alternative 4. Document cost analyses conducted for each alternative 5. Review and finalize LCCA projections for each alternative 6. Choose project alternative based on project goals, objectives, and cost (best value which accounts for life cycle costs is preferred over low bid on construction)

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Sampling Frequency: An LCCA is conducted during the alternatives development phase of a project. Actual incurred costs can be compared to projected costs at any point during the implementation and O&M phases of a project. This analysis will provide critical insights into assumptions made during the planning phase of the project and provide feedback beneficial for future project planning purposes. Performance Criteria: The performance criteria for this metric is, in terms of total costs, how does the chosen project alternative compare to the other alternative solutions that were not chosen, both natural infrastructure and traditional grey infrastructure alternatives.

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3.4 JOBS TOUCHED Section authors: Bob Carey, Emily Hayba The purpose of this metric is to calculate one aspect of the broader economic benefit provided by a Methodology: computer model nature-based solution to or empirical flood and storm risk management. Jobs touched Sampling Frequency: planning phase and end of project can be defined as the number of different Performance Criteria: number employees or contractors of jobs created as a result of involved in implementing implementing a natural the project. This number infrastructure project can help to underscore the impact on the local economy that a project has in a certain area. This information can be used as an important data point in documents describing project benefits and has been of particular interest to state legislators and other elected officials focused on job creation. There are two suggested approaches to gather this information. Specific information can be gathered directly from project sponsors or a partnership can be developed with the state’s budget office to have an estimated number generated. There are benefits associated with both approaches, described below. Metric: Number of Jobs Touched

Metric: Number of Jobs Created by Implementing a Natural Infrastructure Project Units: number of jobs (unitless) Methodology: Gather information directly from project sponsors The most accurate way to determine jobs touched is to simply ask project sponsors to report on how many jobs were supported—i.e. how many employees (of the sponsor and any contractors) were involved in the project’s implementation. The advantage of this methodology is that it can be more accurate—based on those that actually working on a project—with the information coming from those directly involved in the project. It has the drawbacks; relying on multiple parties to report can be time consuming, and it can be susceptible to significant variation in the methods as well as accuracy of reporting.

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Working with state agencies Another approach to determining jobs touched is to work with the state financial management office or other relevant agency. Since job creation has been a focus of state governments, these entities often have existing methodologies for estimated jobs touched. Relying on preexisting data and methodologies can be a very simple and efficient way to determine this number and is especially helpful when trying to develop an estimate across multiple projects or project sponsors. Using a methodology that a state government uses can bring with it a certain amount of credibility and also allows the project to avoid the process of developing (and needing to explain) its own methodologies. TNC Washington developed this approach simply by reaching out to the state Office of Financial Management (OFM) and asking for assistance. First, work with OFM or other state agency to determine how to break out budget information (e.g. planning, acquisition, construction—the categories they use that are relevant to the project work anticipated) and then also have the project proponents break out their budget information using the same categories. This budget information can be sent to OFM to be plugged it into their preexisting formula. Alternatively, if the state OFM is willing to share its formula, the Conservancy could plug the budget numbers it receives from project sponsors into that formula. The information returned is the jobs touched data. This is a fast and efficient way to run the numbers and turn-around time can be as quick as the same day. Using computer software When working at larger scales (e.g. an entire bay, or the entire coastline of your state) in areas where, for instance, numerous restoration projects are being implemented over a multi-year time frame, computer software such as IMPLAN may be an option. The IMPLAN (IMpact analysis for PLANning) input-output modeling software is used to assess the “ripple effects” or multiplier effects of an increase or decrease in spending based upon some change in conditions. By modeling the interactions between every industry in an economy and tracking the flow of goods and services, one is able to estimate the total economic impact (number of jobs, income, sales) for the region in question. You will likely have to contract out an analysis to an economics department in a university or to a consulting group. IMPLAN does not come with a preprogramed “restoration sector,” so ask before contracting out this analysis if the researcher has experience working with restoration projects. Sampling Frequency: Estimating jobs touched by a project can be done at the planning phase to predict how many jobs will be created. This estimate can then be verified during project implementation and updated accordingly. Ideally, at the end of the project, a retrospective analysis is completed to determine the exact number of jobs created as a result of the project Performance Criteria: The total number of jobs estimated to be created by implementing the project compared to how many were actually created. Measures Guidebook for Flood and Storm Risk Reduction Projects |

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CHAPTER 4:

Social Metrics Core Metrics 4.1 People Benefitted

Additional Metrics 4.2 Recreation 4.3 Economic Development 4.4 Property Values 4.5 Public Awareness 4.6 Policy Change

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Core Social Metrics 4.1 PEOPLE BENEFITTED Section author: Elizabeth Schuster Metrics: People Benefitted; Demographics of People Benefitted Methodology: hydrodynamic modeling, GIS mapping, or social science methods –surveys, focus groups, etc. Sampling Frequency: preand post-construction, then post event.

The purpose of this metric is to measure the number of people benefitting from the resilience aspects of a project, most often the flood reduction benefits. The following section looks at other types of beneficiaries, such as those involved in recreation around the project. The ideal way to define the area of project influence is to use hydrodynamic modeling to model flooding and inundation with and without the project to identify people and infrastructure that are benefiting from the project. In many circumstances, this type of modeling is not available or prohibitively expensive, so less sophisticated GIS analyses may be used to estimate the zone of the project influence. These approaches can include applying a simple distance buffer around the project or calculating the people and infrastructure in mapped flood zones adjacent to the project. Though these proxies may be useful for estimating the number of beneficiaries of the project, they do not provide information about the magnitude of the benefit in the same way the hydrodynamic modeling does.

Performance Criteria: based on methods – statistical The second approach for determining the number of beneficiaries is through change in number of the application of social science methods to collect data. In many cases, the beneficiaries or anecdotal people benefitting from the project do not live in the physical area but may id f h h commute down a road each day, and thus, for evaluating many of the additional community resilience benefits, social science methods will be necessary. One can use interviews, focus groups, surveys or also rely upon existing sources of data to better understand who is most likely to benefit from a RRR project.

Metric: People Benefitted Units: numbers of people, numbers of structures, change in protection level (if determined during hydrologic modeling) • The number of beneficiaries (total population and or infrastructure) who benefit from a decrease in flood risk, which can be assessed using physical characteristics or social science methods. • The change in the level of protection for the beneficiaries. • A decrease in number of days that x number of businesses are closed after a storm or flood event, which can be evaluated using interviews, focus groups or surveys.

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• •

Increase in the speed of recovery time from a flooding event for a community, which can be evaluated using interviews, focus groups or surveys. Time saved with the reduction in roads flooding (number of people benefitting times total time saved to get an aggregate value for social well-being), which can be evaluated using an avoided costs method, and may include data from surveys or existing sources such as from a county or state department of transportation

Methodology: To the extent possible, the boundary of the zone of influence of a project should be established as accurately as possible through the use of topographic maps, FEMA flood zone maps or hydrodynamic models as noted above. Additional data sources for the zone of influence may include, but are not limited to, the following: • Census data. • Information or data from a municipal or county public works department. • Traffic counts or other types of data from a county or state department of transportation. • Insurance claims related to storm damage over time. • Crop production statistics from the U.S. Department of Agriculture (which may be relevant in cases where flooding or other types of storm damage affects farmers and/or agribusinesses). Social science methods may be necessary to supplement an analysis that involves counting the number of people or structures benefiting based upon maps or modeling. As mentioned above, in certain cases (such as where beneficiaries travel down a road), maps or modeling may not be sufficient, and interviews or surveys can help determine who is a project beneficiary. Additionally, there may be societal benefits that are not captured in these objective measures. Social science methods that allow the researcher to obtain stories on beneficiaries can supplement a metric that only quantifies number of beneficiaries. While anecdotal stories will never have the rigor to demonstrate conclusively the project impact on people, the stories can help the researcher begin to build the case of the project impact, especially when combined with quantitative data. As one increases the level of rigor of methods, the confidence in the results also increases. On the opposite end of the spectrum from anecdotal stories, one can apply a Before-After Control Impact (BACI) study design. A BACI design involves a control and treatment site as well as pre- and post-project assessment of social benefits to demonstrate a causal link between the RRR project and the social benefit. However, in practice, it may be challenging and prohibitively expense to apply a BACI design to measure the social benefits from a project. When the goal of research is to gather qualitative information (i.e. stories on individuals’ experiences surrounding a RRR project), there is no widely agreed upon minimum number of interviews needed. Guest, Bunce and Johnson (2006) recommend a minimum of 12 interviews, in a relatively homogeneous population. The number should increase with highly diverse population to the point at which the researcher has captured all of the common experiences, perceptions and understandings and no longer is getting new information during the interview process (DeLauer, personal communication, 9/4/2014).

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Interviews are one-on-one interactions between an individual and a researcher and can be conducted in person or over the phone and rely on a set list of questions. Focus groups involve approximately 6-12 individuals and allow for researchers the efficiency of interviewing a larger group of individuals at the same time. Surveys are a systematic approach to collecting data (either qualitative or quantitative) on individuals in the target population. Surveys can be conducted via mail, email (with a link to a site such as Survey Monkey), or in person. The wording of questions matters. Understanding local culture helps you understand which language to use or avoid and which issues may be more controversial and thus require greater sensitivity. To measure the efficacy of the questions and results obtained, it is important to do a “pre-test” of the interview or survey questions on a subset of the intended population. Relationships matter when collecting data and conducting interviews. Following the Conservancy’s Human Subjects Research Standard Operating Procedure is one way to help prepare. For instance, demonstrating a commitment to maintaining anonymity for your subjects is important 3. Sampling Frequency: As needed to determine the total number of project beneficiaries. Performance Criteria: Based on methods—statistical change in number of beneficiaries or anecdotal evidence of that change.

Metric: Demographics of People Benefitted Units: Basic demographic breakdown of the beneficiaries; the number of beneficiaries who benefit from a decrease in flood risk among socially- vulnerable populations in a community Methodology: It is worth elaborating briefly on census data and how that can be used to evaluate social vulnerability of beneficiaries. Data on social vulnerability of beneficiaries may be available through existing data sources as well. Census data from governmental websites may already be available on your project beneficiaries. It may be helpful in building project support to include demographic information on the project beneficiaries who are considered socially vulnerable. Census based demographic information is readily available online, and there are multiple publications outlining commonly used indicators of social vulnerability (refs). Various social vulnerability indices have already been calculated across the coastal U.S. and area readily available online through mapping portals including CoastalResilience.org and NOAA’s SLR Viewer. It is recommended that you use a local or regional social vulnerability index if one is available; they can frequently be found using a simple google or google scholar search for “social vulnerability” and “your geography”.

3

https://connect.tnc.org/Departments/CentralScience/Pages/Human-Subjects-Research.aspx

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Sampling Frequency: As needed to determine the total number of project beneficiaries. Performance Criteria: Based on methods—statistical change in number of beneficiaries or anecdotal evidence of that change; after that total number is determined, relevant demographics can be assessed for that group.

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Additional Social and Economic Metrics One of the advantages of natural infrastructure is that in addition to the flood and storm resilience benefits, it offers many co-benefits—beyond the primary stated benefit of the project. Co-benefits fall under a variety of categories including recreation, water quality, economic development and cultural values. Quantifying cobenefits can be a useful tool for advancing risk reduction and resilience strategies by demonstrating to stakeholders the multiple benefits that these projects provide. However, studies that quantify the value of cobenefits can be costly in terms of resources and time. Thus, careful consideration should go into determining which co-benefits are relevant to target audiences, which are likely to increase as a result of the project that should be quantified, and the appropriate level of rigor for the study. Benefits can be quantified as monetary values or as non-monetary indicators (also known as benefit relevant indicators). Monetary values may be important for certain target audiences, particularly when a cost-benefit analysis is required. Non-monetary indicators may be sufficient for other audiences, such as voters, if all that is needed is to know that a benefit will be provided by a project. For certain valuation methods (e.g. hedonic valuation, described below), contracting the analysis out to an environmental economist may be necessary. For certain metrics or non-monetary indicators where less technical expertise is needed, it may be feasible to gather data for a given metric internally, without contracting a specialist. The following are sample metrics and common methods for co-benefits that may be relevant for RRR projects. All metrics are intended to reflect a change in that metric due to the project. To increase rigor of analysis, measuring these metrics before and after the RRR project is completed and at a similar site in a comparable area (as a control site) can help increase the confidence in the final results. The desired level of rigor will be dependent upon a variety of user considerations, including budget and resources available, technical expertise, and the target audience for the final metric. The National Ecosystem Services Partnership provides a generally accepted framework for assessments and key references for many of these social measures. https://nespGuidebook.com/

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4.2 RECREATION Section author: Elizabeth Schuster Metric: number of visitors Methodology: multiple Sampling Frequency: annual Performance Criteria: trends in visitation rates

The purpose this metric is to measure benefits to people from nature-based solutions to flood and storm risk management. Many projects will provide recreational benefits to residents and visitors, particularly if accompanied with a public access component (e.g. a parking lot, boat launch, trails or signage). Benefits to recreation may result from an increase in fish, birds, water quality, aesthetics or other attribute that appeals to people.

Metric: Number of visitors to the site. Note that certain stakeholder groups will prefer metrics on visitors to the site to be separated into two groups, residents and visitors from outside of the area. Methodology: Visitors to the site can be quantified via a car counter, surveys or using social media (Haab and McConnell, 2002; Wood et al., 2013). Value that visitors place on the recreational experience, which can be valued using a stated preference method such as contingent valuation or a choice experiment.

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4.3 ECONOMIC DEVELOPMENT Section author: Elizabeth Schuster The purpose of this metric is to measure or estimate the broader economic benefit from a nature-based solution to flood and storm risk management. Methodology: varied Economic development is a broad category that includes direct benefits to businesses, impacts on income, an increase in the number of jobs or Sampling Frequency: annual employment rate, or an increase in sales for a particular industry. In some cases, a RRR project or demonstration site might be the primary driver behind Performance Criteria: varied the economic impact. However, in many cases, a RRR project will not be the sole cause of an economic impact. Thus, one would need to build the case that the RRR project contributed to the change in economic outcome. Lines of inquiry may be: Metric: dollars

• •



Increase in spending by visitors, which can be measured using surveys and economic impact assessment. Increase in revenues for commercial fisherman, which can be valued using interviews or surveys and a partial budget analysis. Refer to Kroeger and Guannel (2014) for examples related to an oyster reef restoration project. Economic impact on a specific sector, which typically is measured using input-output modeling software such as IMPLAN (IMpact analysis for PLANning). This type of study is typically done at a larger scale (e.g. county-scale), as opposed to the project scale. An example is a recent report showing the economic value of national wildlife refuge visitation (Carver and Caudill, 2013).

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4.4 PROPERTY VALUES Section author: Elizabeth Schuster The purpose of this metric is to measure economic benefit of nature-based solutions to flood and storm risk management by measuring changes in property values near the project. Many studies have been conducted to Methodology: Hedonic demonstrate that housing values may increase based upon a change in valuation or use of GIS environmental amenities. The value of a home will be affected by numerous software factors, such as square footage, number of rooms, lot size, school district, and other neighborhood attributes and demographic factors. Taking those factors Sampling Frequency: n/a into consideration, one can conduct a hedonic valuation study to isolate the typically one time effect of the environmental attribute, all other factors being equal. Performance Criteria: Information describing the basics of this hedonic valuation can be found at increase in value due to http://www.ecosystemvaluation.org/hedonic_pricing.htm. Environmental change in natural space attributes that may affect property values include a reduction in pollution for homes near a body of water (or conversely, an increase in water clarity), an increase in natural space or proximity to an urban park, or a reduction in flood risk. Metrics: varies, see below

Metrics: • • • •

Number of homes within walking distance that would benefit from open space, which could be assessed using GIS software. Change in property values due to an increase in natural space, analyzed through a hedonic valuation study. Change in property values due to a perceived decrease in flood risk, analyzed through a hedonic valuation study. Change in property values due to an improvement in water clarity, analyzed through a hedonic valuation study.

Methodology: See Gopalakrishnan et al. (2011), Bin et al. (2007), Michael et al. (2000), and Walsh and Milon (2015).

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4.5 PUBLIC AWARENESS Section author: Elizabeth Schuster Metrics: Varied – typically number of people reached Methodology: Varied – often available through media

The purpose of this metric is to estimate the number of people reached with key messages related to nature-based solutions to flood and storm risk management. The metric helps measure the success of communications, public relations and media outreach, including—but not limited to—the following:

• Number of earned media stories—print and online. PR firms often use circulation, online exposure, word count and placement in the publication to Sampling Frequency: n/a – determine an “ad equivalency,” which is a measure used to gauge success. per event • TV and radio news stories. This is more difficult to track. In addition to Performance Criteria: total the number of stations that ran the story, total viewer/listener reach can be annual exposure included. Important note: Oftentimes, TV stations will include news stories on their website, but not in their newscasts. In these cases, metrics above (earned media) are more applicable. • Number of web page views or visitors. If the campaign seeks to “drive traffic” to a particular web page or pages, report on the number of page views or unique online visitors during a specific time range. • E-newsletters. If the news is included in an e-newsletter, determine how many people receive the email, how many people opened it, and how many people “click thru” to related Web content if applicable. • Twitter impressions and/or “reposts." Determining the number of impressions on Twitter is much easier to track when there is a “hash tag” (#) associated with the PR campaign. This information is easy to track on Twitter, as is the number of reposts. • Facebook likes and shares. If there is a Facebook post or page associated with the campaign or outreach, these numbers are easy to track. • Internal promotions within TNC (or within partner organizations) should not be overlooked. Such instances should be considered when gauging the success of outreach efforts. • Anecdotal information, such as that received from a partnering federal or state agency or references to a project included in—for instance—a new Congressional bill to provide funding for nature-based projects can, at times, provide very valuable metrics. (See related info in the next section, 4.6, on Policy Change.)

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4.6 POLICY CHANGE Section author: Todd Strole Metrics: Varied (anecdotal – measured impacts from policy change) Methodology: Summary of policy change(s) Sampling Frequency: n/a Performance Criteria: Varied (assessment of impacts from policy change if possible)

The purpose of this metric is to collect and share the policy changes our projects helped to achieve related to mainstreaming the use of nature-based solutions for flood and storm risk management. Policy changes within government at any level indicate broad acceptance of general public or a strong recognition by leaders that change is needed. There is no standard metric for policy change, but a summary of the impact of the policy change is very desirable. If possible, the inclusion of information that measures the impact of the policy change such as: number of people impacted; the geographical extent of the policy; and, the amount of funding impacted or allocated, etc.

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CHAPTER 5:

Ecosystem Services Section author: Kris Johnson The metrics in this Guidebook provide some important measures of the benefits of our risk reduction projects. Collectively, all of the ways in which these projects benefit people as a result of improved ecological conditions are considered ecosystem services. Ecosystem services are the goods and services provided to people by functioning ecosystems (Daily, 1997). Human well-being is at the core of this concept. For example, in the context of this Guidebook, a coastal marsh that absorbs wave energy can perform a flood risk reduction service, but only if there are people and property that would otherwise be subject to damage if that marsh was lost. That same marsh may support fish habitat, but only provides an ecosystem service in the form of enhanced fishing opportunities if commercial or recreational fishermen benefit from increased fish production. Ecosystem services are a product of both a functioning ecosystem and the people who are the beneficiaries of ecological functions. While some of the metrics described in previous chapters are measures of ecosystem services—such as losses reduced or avoided—this chapter provides a brief overview of ecosystem services and a list of example socio-economic measures that might be useful. An important resource on ecosystem services is the guidebook developed by the National Ecosystem Services Partnership to inform federal agencies’ efforts to integrate ecosystem services into planning and decisionmaking processes (https://nespGuidebook.com). Another is the recent TNC publication from Elizabeth Schuster—A Guide for Incorporating Ecosystem Service Valuation into Coastal Restoration Projects. The NESP Guidebook provides a thorough synthesis of key ecosystem services concepts and describes a simple framework to enhance the rigor and applicability of ecosystem services analyses. The components and steps of the NESP framework are presented in this graphic:

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The left box focuses on the ecosystem and habitat features and changes to this system. Much of the work of the Conservancy over the last 60 years has focused in this box and on measures such as documenting acres of important ecosystems protected or restored. The middle box highlights that a project needs to identify specific ecosystem services that might be impacted by the management action. This step is critical and ideally should generally involve stakeholders to help specify the ways in the changes might impact affected people. The third box explains that in addition to understanding how a change in ecosystem condition affects the services it provides (e.g. a change in water quality) there still remains the step in assessing how much this change specifically benefits people—that is, what is the value of this change to people? Did the water quality improve enough to reduce water treatment costs? Did it improve property values?

EXAMPLE OF ECOSYSTEM SERVICES FRAMEWORK

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Quantifying Benefits Benefits to people can be valued in dollars or in other, non-monetary units. Monetization particularly makes sense when the benefits have recognized financial values, like reduced treatment costs or changes in property values. Monetizing benefits can also be important if they can be included in the benefit costs analysis used by many state and federal agencies to inform decisions. In addition to direct economic or financial values, benefits can be monetized through other technique such as contingent valuation methods. The coastal restoration guide mentioned above explains these concepts in more detail. Other times, monetization of benefits is not necessary. For instance, there is growing use of “benefit relevant indicators” (BRI’s) that may be as useful in many circumstances. These metrics link ecological change with context-specific impacts on benefits to people. For example, the number of visitors to a coastal site or the estimated number of avoided days of road closure due to the storm protection provided by a project. BRIs represent what is valued based upon number of people affected and magnitude of change, but do not measure changes in social welfare or economic values. Refer to the Federal Resources Management and Ecosystem Services Guidebook (FRMES, https://nespguidebook.com/). It is imperative to understand the audience and needs of stakeholders when determining if monetization is needed or if some other form of estimating the value of affected ecosystem services and trade-offs is adequate. As a guide to how one can quantify socio-economic benefits and thereby quantify the ecosystem services provided by a project, we have reprinted next Table 3 from A Guide for Incorporating Ecosystem Service Valuation into Coastal Restoration Projects. This table provides a good overview of methods for both data collection and valuation methods for a wide range of metrics and is generally applicable to river systems as well as coastal systems.

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SAMPLE GOAL-BASED SOCIOECONOMIC METRICS FOR COASTAL RESTORATION PROJECTS

CLASS OF METRICS Community resilience — erosion

Community resilience — flooding

FINAL METRIC (UNIT OF MEASUREMENT)

DATA COLLECTION METHODS

VALUATION METHODS OR TYPE OF ANALYSIS

USER CONSIDERATIONS

Difference in cost between hardened structure and a living shoreline

• Project budgets • Existing data sources

• Substitute cost method

Substitute cost method compares the construction and maintenance costs between two or more options (e.g., living shoreline versus a e.g., bulkhead), with the assumption that the equivalent level of functionality is provided by both options.

Cost-effectiveness of structure for shoreline stabilization (rate of erosion reduction per unit cost)

• Project budgets

• Costeffectiveness analysis

A cost-effectiveness analysis for erosion reduction will include a combination of biophysical goal-based metrics and project costs. In addition to looking at rate of erosion reduction per cost, one could also look at cost-effectiveness for a wider range of goals achieved per unit cost, in which case a wider range of goal-based metrics would be needed.

Number of homes or structures benefitting

• Visual assessment • GIS Analysis

• NA

Identifying number of homes or structures benefiting from a restoration project is a non-monetary metric that that may be useful in the site selection phase of the project or in qualitatively describing how a project affects people. It could be accompanied by interviews with homeowners or focus group meetings or by information on the social vulnerability of households benefiting from the risk reduction or resilience project.

Change in damage costs to surrounding homes

• FEMA NFIP claim data when available • Surveys • Existing data sources

• Avoided cost method • HAZUS modeling

Obtaining Federal Emergency Management Agency (FEMA) National Flood Insurance Program (NFIP) claim data can be challenging. Municipal-level data is easier to obtain than parcellevel data. In some cases, researchers have been successful at submitting a Freedom of Information Act (FOIA) request to FEMA and receiving parcel-level data. If going this route, keep in mind it will take many months to obtain the data. Damage costs avoided can also be modeled using free software such as HAZUS, FEMA’s Methodology for Estimating Potential Losses from Disasters.

Change in damages to surrounding struc- tures, roads or other public infrastructure

• Surveys or interviews • Data from municipality or county

• Avoided cost method • HAZUS modeling

Most likely, data on damage to public infrastructure will have to be obtained directly from the municipality (e.g., the public works department). Damage costs avoided can also be modeled using software such as HAZUS.

Value of time saved by individuals driving on a road where flooding is reduced

• Surveys

• Avoided cost method

Surveys or focus group meetings may need to be accompanied with hydrological modeling to ascertain where flood reduction benefits are most likely to occur and by how much.

Changes in the number of days per month that road is flooded

• Surveys or focus group meetings

• NA

Surveys or focus group meetings may need to be accompanied with hydrological modeling to ascertain where flood reduction benefits are most likely to occur and by how much. Survey or focus group meetings can support the argument qualitatively that individuals are benefitting from the decrease in days per month that the road is flooded.

A decrease in number of days that businesses are closed after a storm or flood event

• Interviews

• NA

For this metric, one likely will want to target businesses in a particular sector or in a particular location, instead of including all businesses in the region.

• GIS Analysis

• NA

Identifying number of homes or structures benefiting from a restoration project is a non-monetary metric that that may be useful in the site selection phase of the project or in qualitatively describing how a project affects people. It could be accompanied by interviews with homeowners or focus group meetings or by information on the social vulnerability of households benefiting from the risk reduction or resilience project.

Number of homes or structures benefitting

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SAMPLE GOAL-BASED SOCIOECONOMIC METRICS FOR COASTAL RESTORATION PROJECTS

CLASS OF METRICS Community resilience flooding

FINAL METRIC (UNIT OF MEASUREMENT) —

Cultural values

Economic development — general

VALUATION METHODS OR TYPE OF ANALYSIS

USER CONSIDERATIONS

Number of beneficiaries who benefit from a decrease in flood risk among socially vulnerable populations in a community

• Existing data sources • Use of online mapping portals

• NA

This metric involves two steps: 1) first identifying beneficiaries, and 2) doing an assessment of social vulnerability. Census-based demographic information can be obtained online for the vulner- ability analysis. Mapping portals like Coastalresilience.org and NOAA’s Sea Level Rise Viewer also provide vulnerability infor- mation. For a more comprehensive risk assessment incorporating future sea level rise, refer to Shepard et al. (2012).

Social value that individuals place on the resource

• Surveys • Existing data sources

• Contingent valuation or choice experiment • Benefit transfer

The social value individuals place on the resource (or habitat type) can come from a range of factors related to well-being, such as the cultural, historic or aesthetic value—or the value that individuals place on the continued existence of a resource for future generations.

Number of students benefiting from environmental education/ research

• Surveys • NA • Focus group meetings • Tracking with a log F • Focus groups • Mixed methods analysis combining sense of place with cultural ecosystem service indicator approaches

It may be possible to coordinate with elementary schools, high schools, and/or universities to create a simple log to track number of students directly benefiting from the site through research or nature walks.

Change in revenues for commercial fisherman

• Surveys • Interviews • Existing data sources

• Partial budget analysis

A partial budget analysis looks only at the portion of the budget that will be changed by the change in resources—in this case, the increase in revenues from the increase in fish caught, while subtracting out the associated variable costs from the increase in fish harvested.

Change in number of commercial fish harvested

• Surveys • Existing data sources

• NA

Fisheries data available through the National Oceanic and Atmospheric Administration’s (NOAA) National Marine Fisheries Service website.

Change in shellfisheries’ closing days

• Existing data sources

• NA

Determine local agency responsible for tracking information on shellfisheries’ closing days, such as a university, governmental agency or shellfisheries group for the industry.

Regional economic impact of an industry or sector

• Surveys • Existing data sources

• IMPLAN or other regional economic modeling, such as input-output models

The IMPLAN (IMpact analysis for PLANning) input-output modeling software is used to assess the “ripple effects” or multi- plier effects of an increase or decrease in spending. By modeling the interactions between every industry in an economy and tracking the flow of goods and services, one is able to estimate the total economic impact (jobs, income, sales) for the region in question.

Perceived quality of shellfish harvested (as an indicator of sense of place) (scale ranking 1 to 5)

Economic development — commercial fishing

DATA COLLECTION METHODS

Specific cultural values that are relevant are likely to vary by community—for instance, communities may value recreation or aesthetic attribute of the scenery. The focus groups allow the researcher to determine which cultural values are most important. Note that “quality” in this metric includes both size and abundance attributes as perceived by residents. For salt marsh and oyster reef restoration, the type of shellfish may be blue crabs, depending upon how the community ranks its cultural connection to shellfish harvesting. See Donatuto et al. (2014) for additional information on the methodology.

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SAMPLE GOAL-BASED SOCIOECONOMIC METRICS FOR COASTAL RESTORATION PROJECTS

CLASS OF METRICS

FINAL METRIC (UNIT OF MEASUREMENT)

DATA COLLECTION METHODS

VALUATION METHODS OR TYPE OF ANALYSIS

Economic development — general

Number of new jobs created directly in the restoration activity

• Surveys • Interviews

Economic development — tourism

Economic impact of ecotourism

• IMPLAN or • Surveys • Existing data other regional economic sources modeling, such as inputoutput models

Change in spending by birders

• Surveys • Existing data sources

• Economic impact assessment

Quantifying change of spending is a two-part process, where first the number of visitors before and after the restoration must be quantified, and then the average spending per visitor must be quantified. One should differentiate between spending by locals and spending by visitors from outside of the region; in order to consider the spending an economic impact, it must be from visitors from outside of the region.

Change in spending by anglers

• Surveys • Existing data sources

• Economic impact assessment

Quantifying change of spending is a two-part process, where first the number of visitors before and after the restoration must be quantified, and then the average spending per visitor must be quantified. One should differentiate between spending by locals and spending by visitors from outside of the region; in order to consider the spending an economic impact, it must be from visitors from outside of the region.

Number of new jobs created in tourismrelated industries

• Surveys • Interviews

• NA

The number of new jobs created will be relative to the size of the economy in that region. In densely populated areas, the number of new jobs created might have more weight if it is a large number, but keep in mind that for some rural areas, even a small number of new jobs created is considered important.

Number of new businesses

• Interviews

• NA

One would want to demonstrate that the restoration, at least in part, can be attributed to the opening of a new business (e.g., a restaurant or outfitter). While this metric should be considered qualitative, this type of metric can still be useful in building the case that a restoration project had a role in supporting local businesses.

Market value of carbon credits (i.e., blue carbon)

• Existing data sources

• Market price

Blue carbon credits are not currently sold in the United States, though the potential exists for this market to develop in the future.

Market value of water quality credits

• Existing data sources

• Market price

Water quality credits for oysters are not currently sold in New Jersey, though they are allowed in certain parts of the Chesapeake Bay.

Change in property value because of aesthetic improvements to view

• Existing data sources

• Hedonic valuation

There might be a lag time, if the restoration loses aesthetic appeal in the first two years post-restoration. This metric will only be relevant to certain projects and is more likely to be relevant in urbanized regions where open space is less abundant.

Market value (e.g., payments for ecosystem services)

Property values

• NA

USER CONSIDERATIONS The number of new jobs created will be relative to the size of the economy in that region. In densely populated areas, the number of new jobs created might have more weight if it is a large number, but keep in mind that for some rural areas, even a small number of new jobs created is considered important. The IMPLAN (IMpact analysis for PLANning) input-output modeling software is used to assess the “ripple effects” or multiplier effects of an increase or decrease in spending. By modeling the interactions between every industry in an economy and tracking the flow of goods and services, one is able to estimate the total economic impact (jobs, income, sales) for the region in question.

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SAMPLE GOAL-BASED SOCIOECONOMIC METRICS FOR COASTAL RESTORATION PROJECTS DATA COLLECTION METHODS

VALUATION METHODS OR TYPE OF ANALYSIS

CLASS OF METRICS

FINAL METRIC (UNIT OF MEASUREMENT)

Property values

Change in property value because of reduction in rate of erosion

• Existing data sources

• Hedonic valuation

For an example, see Gopalakrishnan et al. (2011). Although the focus was on beach erosion and dunes, the method will still be similar for erosion related to salt marshes.

Change in property value because of decrease in flood risk

• Existing data sources

• Hedonic valuation

For an example, see Bin, Dumas, Poulter and Whitehead (2007). Although linked generally to sea level rise and not to a specific restoration project, the methods will still be similar.

Change in municipal property taxes because of the change in property value

• Existing data sources

• Hedonic valuation

This metric requires two steps: 1) hedonic valuation, and 2) linking the changes in property values to changes in municipal property taxes collected.

Change in public awareness of living shorelines

• Surveys • Focus group meetings

• NA

Survey should include questions that seek to understand if residents (unprompted) list living shorelines when asked “Could you list the different types of shoreline stabilization projects (or techniques) that you know about?” This metric could also apply to public awareness of other restoration techniques.

Change in political will or public support to living shorelines

• Surveys • Interviews

Public Perception

Recreation and public access (e.g., birding, fishing, swimming, etc.)

Value visitors to the site place on their experience

Value boaters place on their experience

Number of visitors to the restoration site

Number of fish caught per angler trip

• Surveys • Existing data sources

• Surveys • Existing data sources

While the previous metric of “awareness” is solely based upon knowledge of living shorelines, this metric gets at a willingness to change behaviors and increase support for living shorelines. It is important to recognize that there are likely to be multiple groups advocating a change in political will toward living shorelines. This metric could also apply to other restoration techniques. • Contingent valuation or choice experiment • Benefit transfer

Note that value placed on the individual experience represents the social value of the visitor experience, or the value beyond the actual amount spent. This method of valuing public preferences is common when comparing policy alternatives to understand which policies have the largest benefit for the most people.

• Contingent valuation or choice experiment • Benefit transfer

Note that value placed on the individual experience represents the social value of the visitor experience, or the value beyond the actual amount spent. This method of valuing public preferences is common when comparing policy alternatives to understand which policies have the largest benefit for the most people.

• Car counter • NA • Surveys • Geospatially referenced social media methodology • Surveys • Existing data sources

USER CONSIDERATIONS

• NA

Benefit transfer is a lower-cost option than contingent valuation. However, benefit transfer should only be used if the conditions and demographics of the initial study site are similar to the current restoration site. When possible, benefit function transfer and meta-analysis are more accurate than simple benefit transfer.

Benefit transfer is a lower-cost option than contingent valuation. However, benefit transfer should only be used if the conditions and demographics of the initial study site are similar to the current restoration site. When possible, benefit function transfer and meta-analysis are more accurate than simple benefit transfer. This is a common non-monetary metric that can be applied at a relatively low cost to any restoration project with a public access component. See Wood, Guerry, Silver and Lacayo (2013) for their methodology of using of geospatially referenced photos on Flickr to estimate visitation rates. Existing data may also be available from other sources, such as through the following link from NOAA’s National Marine Fisheries Service website.

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SAMPLE GOAL-BASED SOCIOECONOMIC METRICS FOR COASTAL RESTORATION PROJECTS DATA COLLECTION METHODS

VALUATION METHODS OR TYPE OF ANALYSIS

CLASS OF METRICS

FINAL METRIC (UNIT OF MEASUREMENT)

Recreation and public access (e.g., birding, fishing, swimming, etc.)

Number of anglers

• Surveys • Existing data sources

• NA

Existing data may be available from state agencies who issue fishing permits.

Change in number of beach closing days

• Surveys • Existing data sources

• NA

Most likely, salt marsh or oyster reef restoration projects will only have a quantifiable impact on improving water quality and reducing the number of beach closings because of water quality when a sufficiently large number of acres are restored. This metric is not likely to be relevant to small-scale projects.

Value visitors place on the improved water quality (boaters, anglers, beach visitors, etc.)

• Surveys • Existing data sources

• Contingent valuation or choice experiment • Benefit transfer

Note that value placed on the individual experience represents the social value of the visitor experience, or the value beyond the actual amount spent. This method of valuing public preferences is common when comparing policy alternatives to understand which policies have the largest benefit for the most people.

Water quality

USER CONSIDERATIONS

Benefit transfer is a lower-cost option than contingent valuation. However, benefit transfer should only be used if the conditions and demographics of the initial study site are similar to the current restoration site. When possible, benefit function transfer and meta-analysis are more accurate than simple benefit transfer.

Market value of water quality credits in a water quality market

• Existing data sources

• Market price

Water quality credits for oyster restoration are not currently sold in most Mid-Atlantic states, though they are allowed in certain parts of the Chesapeake.

Change in property value because of water clarity improvements

• Existing data sources

• Hedonic valuation

Literature shows that proximity to polluted water can lead to lower property values, all else being equal. Water clarity tends to be the preferred water quality parameter, since it is observable by the prospective home buyer.

Willingness to pay for improved water quality on a water utility bill

• Surveys

• Contingent valuation or choice experiment

By framing the survey in terms of a potential referendum that would result in a fee on a water utility bill, the respondent to the survey is more likely to state an accurate value of what they would be willing to pay, removing the hypothetical bias. Thus, willingness to pay questions should be framed in such a way that the respondent believes that his/her survey answers are likely to impact policy.

Change in number of visitors because of reduction in number of beach closings

• Surveys • Existing data sources

• NA

Most likely, salt marsh or oyster reef restoration projects will only have a quantifiable impact on improving water quality and reducing the number of beach closings because of water quality when done at the landscape scale. This metric is not likely to be relevant to small-scale projects.

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APPENDIX 1: REFERENCES AND LITERATURE CITED Baggett, L.P., S.P. Powers, R. Brumbaugh, L.D. Coen, B. DeAngelis, J. Greene, B. Hancock, and S. Morlock. 2014. Oyster habitat restoration monitoring and assessment handbook. The Nature Conservancy, Arlington, VA, USA., 96pp. Belluco, E., M. Camuffo, S. Ferrari, L. Modenese, S. Silvestri, A. Marani, M. Marani. 2006. Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing. Remote Sensing of Environment, 105: 54–67 Betts T. 2006. An Assessment of Mangrove Cover and Forest Structure in Las Perlas, Panama. Master’s Thesis, Heriot Watt University, Edinburgh, Scotland Bin, O., Dumas, C., Pouter, B., Whitehead, J. 2007. Measuring the impacts of climate change on North Carolina coastal resources. Report prepared for National Commission on Energy Policy, Washington, DC, USA. Booth, D.M., and K.L. Heck. 2009. Effects of the American oyster Crassostrea virginica on growth rates of the seagrass Halodule wrightii. Marine Ecology Progress Series, 389: 117-126. Carver, E., Caudill, J. (2013). Banking on Nature: The Economic Benefits to Local Communities of National Wildlife Refuge Visitation. Washington, D.C. Division of Economics, U.S. Fish and Wildlife Service. Cressman, K.A., M.H. Posey, M.A. Mallin, L.A. Loenard, and T.D. Alphin. 2003. Effects of oyster reefs on water quality in a tidal creek estuary. Journal of Shellfish Research, 22: 753-762 Crist, P.J. 2000. Animal-Distribution Modeling in Gap Analysis: an Evolving Science. Conservation Biology, 14(5): 1224. Crist, Patrick J., et al. 1993. "Mapping and categorizing land stewardship." A Handbook for Gap Analysis. Version 2.0 (2000). Crist, P.J., B. Thompson, T. C. Edwards, C. G. Homer, S. D. Bassett. 1998. Mapping and Categorizing Land Stewardship. A Handbook for Conducting Gap Analysis http://www.gap.uidaho.edu/handbook/Stewardship/default.htm Daily, G. 1997. Nature’s Services: Societal dependence of natural ecosystems. Island Press. A. Dekker, V. Brando, J. Anstee, S. T. Malthus and E. Karpouzli. 2006. Remote Sensing of Seagrass Ecosystems: Use of Spaceborne and Airborne Sensors IN Seagrasses: Biology, Ecology and Conservation, edited by A. Larkum, R.J. Orth, C. Duarte. Springer. Donatuto, Jamie, Melissa Poe, Larry Campbell, Terre Satterfield, Aleta Poste, and Robin Gregory. “Evaluating Human Well-being in Relation to Shellfish as a Place-Based Cultural Ecosystem Service of Puget Sound.” A Community on Ecosystem Services (ACES) Conference, Washington, D.C. December 9, 2014. Presentation. Dustan P, Doherty O, Pardede S. 2013. Digital Reef Rugosity Estimates Coral Reef Habitat Complexity. PLoS ONE 8(2). Fernando HJS, SP Samarawickrama, S Balasubramanian, SSL Hettiarachchi, S Voropayev. 2008. Effects of porous barriers such as coral reefs on coastal wave propagation. Journal of Hydro-environment Research, 1(3–4): 187194.

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APPENDIX 1: REFERENCES AND LITERATURE CITED Ferrario, F., M. W. Beck, C. D. Storlazzi, F. Micheli, C. C. Shepard, and L. Airoldi. 2014, The effectiveness of coral reefs for coastal hazard risk reduction and adaptation., Natural Communities, 5: 3794. Gopalakrishnan, S., Smith, M. D., Slott, J. M., & Murray, A. B. 2011. The Value of Disappearing Beaches: A Hedonic Pricing Model with Endogenous Beach Width. Journal of Environmental Economics and Management, 60(3): 297–310. E. P. Green, C. D. Clark, P. J. Mumby, A. J. Edwards, and A. C. Ellis. 1998. Remote sensing techniques for mangrove mapping. International Journal of Remote Sensing Vol. 19, Iss. 5. Grizzle, R.E., J.K. Greene, M.W. Luckenbach, and L.D. Coen. 2006. A new in situ method for measuring seston uptake by suspension-feeding bivalve mollusks. Journal of Shellfish Research 25:643-649. Grizzle, R.E., J.K. Greene, and L.D. Coen. 2008. Seston removal by natural and constructed intertidal eastern oyster (Crassostrea virginica) reefs: a comparison with previous laboratory studies. Estuaries and Coasts, 31: 1208-1220. Guest, G., A. Bunce, and L. Johnson. 2006. How many interviews are enough? An experiment with data saturation and variability. Field Methods (18): 59-82. Gunasekera K. 2014. Variation of Impact along the East Coast of Eastern Samar Due to Typhoon Haiyan in the Philippines. Jstage, Vol. 70 (2) 241-244. Haab, T., McConnell, K. (2002). Valuing Environmental and Natural Resources: The Econometrics of Non-Market Valuation. New Horizons in Environmental Economics, Northampton, Massachusetts. M. A. Hardisky, M. F. Gross and V. Klemas. 1986 Remote Sensing of Coastal Wetlands. BioScience, Vol. 36, No. 7, Ecology from Space (Jul. - Aug., 1986), pp. 453-460 Houser C, C Hapke, S Hamilton. 2008. Controls on coastal dune morphology, shoreline erosion and barrier island response to extreme storms. Geomorphology, 100 (3-4): 223 – 240. Judge, M.L., L.D. Coen, and K.L. Heck. 1993. Does Mercenaria mercenaria encounter elevated food levels in seagrass beds? Results from a novel technique to collect suspended food resources. Marine Ecology Progress Series, 92: 141-150. Keeler, Bonnie L., Stephen Polasky, Kate A. Brauman, Kris A. Johnson, Jacques C. Finlay, Ann O’Neil, Kent Kovacs, and Brent Dalzell. 2012. Linking water quality and well-being for improved assessment and valuation of ecosystem services. PNAS 109(45): 18619–18624. C. Kuenzer, A. Bluemel, S. Gebhardt, T. Vo Quoc, S. Dech. 2011. Remote Sensing of Mangrove Ecosystems: A Review. Remote Sensing, 3(5):878-928. Knudby A and E LeDrew. 2007. Measuring Structural Complexity on Coral Reefs. In: Pollock NW, Godfrey JM, eds. Diving for Science 2007. Proceedings of the American Academy of Underwater Sciences 26th Symposium. Dauphin Island, AL: AAUS. Krauss, K.W., Doyle, T.W., Doyle, T.J., Swarzenski, C.M., From, A.S., Day, R.H. and Conner, W.H. 2009. Water level observations in mangrove swamps during two hurricanes in Florida. Wetlands, 29(1): 142-149.

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APPENDIX 1: REFERENCES AND LITERATURE CITED Kroeger, T., & Guannel, G. 2014. Fishery enhancement and coastal protection services provided by two restored Gulf of Mexico oyster reefs. In K. Ninan (Ed.), Valuing ecosystem services — methodological issues and case studies. Cheltenham, MA: Edward Elgar. Leiper IA, SR Phinn, CM Roelfsema , KE Joyce, AG Dekker. 2014. Mapping Coral Reef Benthos, Substrates, and Bathymetry, Using Compact Airborne Spectrographic Imager (CASI) Data. Remote Sens, 6: 6423-6445. Levin N, E Ben-Dor, A Karnieli. 2004. Topographic information of sand dunes as extracted from shading effects using Landsat images. Remote Sensing of Environment. Masters J. 2013. Storm Surge Reduction by Wetlands. Weather Underground. Available at: http://www.wunderground.com/hurricane/surge_wetlands.asp. McIvor, A.L., Spencer, T., Möller, I. and Spalding. M. 2012. Storm surge reduction by mangroves. Natural Coastal Protection Series: Report 2. Cambridge Coastal Research Unit Working Paper 41. Published by The Nature Conservancy and Wetlands International. Michael, H., Boyle, K., Bouchard, R. 2000. Does the Measurement of Environmental Quality Affect Implicit Prices Estimated from Hedonic Models? Land Economics, 76(2): 283-298 P.J. Mumbya, W.Skirvingb, A. E. Strongb, J.T. Hardyc, E.F. LeDrewd, E.J. Hochberge, R.P. Stumpff, L.T. Davidg. 2004. Marine Pollution Bulletin,48(3–4): 219–228. Neckles, H.A. and M.Dionne, Editors. 2000. Regional standards to identify and evaluate tidal wetland restoration in the Gulf of Maine. Wells National Estuarine Research Reserve Technical Report, Wells, ME. Neckles, H. A., G. R. Guntenspergen, W. G. Shriver, N. P. Danz, W. A. Wiest, J. L. Nagel, and J. H. Olker. 2013. Identification of Metrics to Monitor Salt Marsh Integrity on National Wildlife Refuges In Relation to Conservation and Management Objectives. Final Report to U.S. Fish and Wildlife Service, Northeast Region. USGS Patuxent Wildlife Research Center, Laurel, MD. Nelson, K.A., L.A. Leonard, M.H. Posey, T.D. Alphin, and M.A. Mallin. 2004. Using transplanted oyster (Crassostrea virginica) beds to improve water quality in small tidal creeks: a pilot study. Journal of Experimental Marine Biology and Ecology, 298: 347-368. Niedowski NL. 2000. New York State Salt Marsh Restoration and Monitoring Guidelines. New York State Department of Environmental Conservation. Ohrel, R.L. Jr., and K.M. Register. 2006. Volunteer Estuary Monitoring: A Methods Manual, 2nd Edition. U.S. Environmental Protection Agency, Washington D.C. and The Ocean Conservancy, Washington D.C. Plutchak. R., K. Major, J. Cebrian, C.D. Foster, M.E.C. Miller, A. Anton, K.L. Sheehan, K.L. Heck, Jr. and S.P. Powers. 2010. Impacts of oyster reef restoration on primary productivity and nutrient dynamics in tidal creeks of the north central Gulf of Mexico. Estuaries and Coasts, 33: 1355–1364. Putz, F. E. and Chan, H. T. 1986. Tree growth, dynamics and productivity in a mature mangrove forest in Malaysia. Forest Ecology and Management, 17: 211-230

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APPENDIX 1: REFERENCES AND LITERATURE CITED Scott, J. Michael, et al. "Gap analysis: a geographic approach to protection of biological diversity." Wildlife monographs (1993): 3-41. Sheng YP, Lapetina A, Ma G. 2012. The reduction of storm surge by vegetation canopies: Three-dimensional simulations. Geophys. Res. Lett., 39, L20601. Shepard CC, Crain CM, Beck MW. 2011. The Protective Role of Coastal Marshes: A Systematic Review and Metaanalysis. PLoS ONE 6(11). Sheppard, C., D. J. Dixon, M. Gourlay, A. Sheppard, and R. Payet. 2005. Coral mortality increases wave energy reaching shores protected by reef flats: Examples from the Seychelles, Estuar. Coast. Shelf Sci., 64(2–3): 223– 234. Suhayda, J.N. 1997. Modeling impacts of Louisiana barrier islands on wetland hydrology. Journal of Coastal Research, 13: 686-693. Suzuki, T., M. Zijlema, B. Burger, M. C. Meijer, and S. Narayan. 2012. Wave dissipation by vegetation with layer schematization in SWAN, Coastal Engineering, 59(1): 64–71. Thieler ER and Young RS. 1991. Quantitative Evaluation of Coastal Geomorphological Changes in South Carolina After Hurricane Hugo, Journal of Coastal Research, SPECIAL ISSUE NO. 8. Impacts of Hurricane Hugo: September 10-22, 1989, pp. 187-200 TNC. 2013. A Primer for Monitoring Water Funds: Global Freshwater Program. Walsh, P., Milon, J. 2015. Nutrient Standards, Water Quality Indicators, and Economic Benefits. From Water Quality Regulations. Environmental and Resource Economics: 1-19. Wamsley TV, Cialone MA, Smith JM, Ebersole BA, Grzegorzewski AS. 2009. Influence of landscape restoration and degradation on storm surge and waves in southern Louisiana. Natural Hazards, 51: 207–224. Wamsley TV, Cialone MA, Smith JM, Atkinson JH, Rosati JD. 2010. The potential of wetlands in reducing storm surge. Ocean Engineering 37: 59–68. Welschmeyer, N.A. 1994. Flourometric analysis of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnology and Oceanography, 39:1985-1992. Wood, Spencer A., Anne D. Guerry, Jessica M. Silver, and Martin Lacayo. 2013. Using social media to quantify nature-based tourism and recreation. Scientific Reports, 3: 2976. Xu, J. and D. Zhao. 2014. Review of coral reef ecosystem remote sensing. Acta Ecologica Sinica, 34: 19–25 Zhang, K.Q., Liu, H., Li, Y., Hongzhou, X., Jian, S., Rhome, J. and Smith III, T.J. 2012. The role of mangroves in attenuating storm surges. Estuarine, Coastal and Shelf Science, 102: 11-23.

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