EAI Economic Analysis, Inc.

PO Box 3462 Peace Dale, Rhode Island 02883 ( 401) 789 0050 FINAL REPORT Recreational and Resource Economic Values for the Peconic Estuary System Final Report on Phase II of the Estuarine Use and Economic Value Assessment of the Peconic Estuary System Prepared by:

James J. Opaluch, Thomas A. Grigalunas, Jerry Diamantides, Marisa Mazzotta and Robert Johnston ECONOMIC ANALYSIS, INC. P. O. Box 3462 Peace Dale, Rhode Island 02883 With a contribution by Applied Science Associates Narragansett, RI Prepared for:

Peconic Estuary Program Suffolk County Department of Health Services County Center Riverhead, NY 11901 Estuarine Use and Economic Value of the Peconic Estuary System Phase II: A Perspective on Nonmarket Values.

This is the final report of the Phase II entitled " Estuarine Use and Economic Value of the Peconic Estuary System". The goal of the study is to provide economic information to support management decisions for the Peconic estuary under the National Estuaries Program.

Phase I of the study used available data to summarize the level of key estuarine related uses and to estimate market values associated with the Peconic Estuary system. Major estuarine uses are: ( 1) commercial fishing, ( 2) sportfishing, ( 4) beach use, ( 5) non consumptive wildlife associated use, ( 6) hunting and ( 7) other uses. Market values, or " economic impacts", are measures of economic activity supported by the estuary, and include number of establishments, employment, wages and total revenues. Phase I also included a study of the potential for, and constraints on, aquaculture in the Peconic estuary.

The goal of Phase II was to collect primary data to quantify non market uses and non market values of the Peconic estuary. Phase II was comprised of ( 1) a recreational survey, ( 2) a property value study, ( 3) a wetlands productivity study, and ( 4) an amenity valuation survey. The recreation study collected data on the level participation in various recreational activities. The recreational study also estimated the economic value the public has for key activities and determined how the value of recreation activities changes with key indicators of the quality of the experience ( e. g., water quality for swimming, or changes catch rates for fishing). The property value study identifies how amenities like farmland and open space affect the value of nearby properties, providing a measure of amenity ( or disamenity) services to nearby residents. The wetlands productivity analysis estimates biological " production" of important fish and bird species by wetlands based on habitat and nursery functions. The amenity valuation survey identifies priorities and values for key amenities contained in the Peconic estuary study area, including open space, eel grass, unpolluted shellfish areas, farmland and wetlands.

The goal of Phase III is to draw together these various studies in order to prioritize specific management actions for the Peconic estuary. Phase III, scheduled for completion in Winter 1999, will link together science oriented studies, such as water quality modeling, with the economic studies described above to carry out cost benefit analysis of specific policy actions. 1 Recreational and Resource Economic Values for the Peconic Estuary System EXECUTIVE SUMMARY I. A. PURPOSE AND SCOPE The environmental and natural resources (" natural assets") of the Peconic Estuary System the bay waters, beaches, wetlands, ecosystems, habitats, and parks and watershed lands provide many services to the public. Outdoor recreation, scenic views, and the productivity of wetlands that contribute to stocks of fish, birds, and other species used for commercial and recreational purposes are but a few examples of these services.

While the quality of PES coastal amenities is widely recognized, little information exists about the uses and users of PES natural resources. Even less is known about the value that the public holds for the natural asset services of the PES that is, what they are " worth" to the public. This is because recreation, scenic views, and ecosystem productivity are not directly valued in markets. Lacking information on recreational and resources values, comparisons cannot be made of the benefits and costs of prospective actions to preserve or restore PES natural assets. This report is designed to help fill this major gap.

In this report, we present the results of four non market valuation studies carried out by Economic Analysis Inc. (" EAI") to estimate the uses and economic value that the public holds for the natural assets of the PES. We provide estimates of ( 1) outdoor recreational uses and of the non market economic values of key recreational activities, and ( 2) other resource values provided by the natural assets of the PES. The economic valuation studies described herein were done to contribute to benefit cost analyses of proposed management actions.

This document is Phase II of a series of economic studies being done by EAI for the Peconic Estuary Program. A Phase I report ( Grigalunas and Diamantides, 1996) ( 1) provided an assessment of the " economic impacts" of the PES, in terms of business revenues, employment, and wages of estuarine related sectors, and ( 2) summarized available information on recreational uses. Subsequent work by EAI will include benefit cost analyses of resource management actions and sustainable financing options for the selected, preferred actions. 2 I. B. ESTUARINE RELATED USES, RESOURCES AND ECONOMIC VALUES I. B. 1. Introduction and Overview No single method can capture the value of the variety of services provided by the natural assets of the PES. Recognizing the many uses of PES natural resources, we designed and implemented a suite of four non market valuation studies in order to provide estimates of the value of particular services:

( 1) A Property Value study examines the contribution of environmental amenities to the market price of property. Using the Town of Southold as a case study, the Property Value study was designed to measure values of amenities to residents living in the immediate vicinity.

( 2) A Travel Cost study uses original survey results to estimate outdoor recreational uses in the PES and the economic value that users have for four, key PES outdoor recreation activities: swimming, boating, fishing, and bird and wildlife viewing. This study also examines the impact that ( A) water quality has on the number of trips and the value of swimming and ( B) the effect of the catch rate on recreational fishing, important recreational uses of the estuary and activities much affected by water quality and resource abundance.

( 3) A Wetlands Productivity Value study, carried out in collaboration with Applied Science Associates, gives estimates of the economic value of eelgrass, intertidal salt marsh, and sand/ mud bottoms, based on the value of the fish, shellfish and bird species that these ecosystems help " produce". The primary focus is on the nursery and habitat services of the wetland ecosystems in the production of commercial fisheries.

( 4) The Resource Value study uses original survey results to estimate the relative preferences that residents and second homeowners have for preserving and restoring key PES natural and environmental resources: Open space, farmland, unpolluted shellfish grounds, eelgrass beds, and intertidal salt marsh. This study also provides a perspective on the economic value the public has for these resources, as indicated in their stated willingness to pay for programs to preserve and restore them.

Key results for each of these studies are outlined below. A detailed discussion of each method, its purpose, the data used, assumptions and limitations, and results is given in the chapters that follow.

A note on the style adopted for this document. We believe that the results of the economic analyses presented in this report provide a wealth of data to decision makers and to the public. To make the report accessible to a wide audience, we deliberately adopt a non technical style. For those interested, Appendixes present the technical details of the methodologies used. 3 I. C. SUMMARY OF SELECTED RESULTS I. C. 1. Property Value Study ( Chapter III).

Data for property sales in the Town of Southold were used to estimate the contribution of specific environmental attributes to the market value of nearby property. Using a property value model, we found that proximity to open space and other environmental attributes had a significant, positive impact on nearby property values.

For example, a parcel of land located next to open space has, on average, a 12.83% higher per acre value than a similar parcel located elsewhere. To illustrate the how this result might be used, we estimate that a hypothetical contribution of a parcel of approximately 10 acres of open space would increase adjoining property values by $ 410,907.

The model results also show that density of development and other attributes affect property values. For example, 2 or 4 acre zoning ( i. e., R 80 or R 120) has, on average, a 16.65% higher per acre value than a similar parcel located elsewhere ( i. e., in a 1/ 2 acre zone). Conversely, property located on a main road ( highway 25 or 48), or property adjoining a farm, has a lower value, after taking into account other property attributes.

I. C. 2. Recreational Uses and Economic Value ( Chapter IV).

A recreational survey adminstered to residents, second homeowners, and visitors allowed us to estimate ( 1) participation in outdoor recreation, and ( 2) the economic value the public has for four key PES recreational activites. We estimate that in 1995:

127,762 people took some 3.3 million swimming, boating, fishing, or shell fishing, outings 156,184 people engaged in about 5.2 million beach use, bird watching, wildlife viewing, or hunting trips Swimming and beach use were the most popular activities, followed by bird and wildlife viewing, boating, and fishing. Shell fishing and hunting had the fewest estimated number of trips. Measurement problems prevented us from including other common activities, such as hiking/ walking and bicycling.

Among the PES Bays, Great Peconic Bay is the most popular, accounting for 28% of all recreational trips to the PES. Flanders Bay is the least frequently used, with 8% of PES trips. Great Peconic Bay is the most used for swimming ( 30%), fishing ( 29%), and boating ( 25%). For shell fishing, Gardiners Bay is the most popular PES location, with 33% of all PES shell fishing trips.

Outdoor recreation in the PES is enormously valuable to users. Using a Travel Cost model, we estimate the economic value per person, per trip, for four key recreation activities: Swimming, 1Boating for the primary purpose of fishing is valued under recreational fishing.

4 boating1, fishing, and for viewing of birds and wildlife. The estimated values per trip range from $ 49.83 for viewing birds and wildlife to $ 8.59 for swimming ( in 1995 dollars). These are estimates of what participants would be willing to pay, per trip, above and beyond the amount that they actually pay to participate.

Adding across all trips, in 1995 Viewing of Birds and Wildlife ($ 49.3 million) has the highest total annual value, followed by Recreational Fishing ($ 22.4 million), Boating ($ 18.1 million), and Swimming ($ 12.1 million). The corresponding asset values of the PES ( over 25 years at 7 percent) for these key recreational activities range from $ 318 million for Bird Watching and Wildlife Viewing to $ 141 million for Swimming. The PES has an asset value of $ 276 million for Recreational Fishing and $ 210 million for Boating.

Quality is important to PES recreationists. Swimming was found to depend upon perceptions of water quality, and swimmers perceptions, in turn, were related to objective ( i. e., SCDH field sampling) measures of water quality for nitrogen, water clarity, Brown Tide, and coliform bacteria.

To illustrate how the results might be used in a Benefit Cost analysis, we simulated hypothetical, uniform improvements in water quality. For example, a 10 percent uniform improvement in water quality in each Bay increases the estimated number of annual swimming trips by 151 thousand and adds yearly benefits of $ 1.3 million. Most of the benefits ($ 754 thousand) are due to improvements in water clarity ( as measured by Secchi depth). Swimming benefits increase further with a hypothetical, 20 percent uniform water quality improvement, although the added benefits from the second 10 percent improvement is slightly less than that due to the first 10 percent improvement.

The present value of the $ 1.3 million increase in benefits due to the 10 percent hypothetical water quality improvement is $ 15.1 million, using a 7 percent discount rate and a 25 year time horizon. Thus, if the present value of the costs of the policy ( or set of policies) to improve water quality did not exceed $ 15.1 million over the same period, it would be a good investment of scarce resources.

Recreational fishing also was found to depend upon the quality of the experience in particular, the catch rate. A hypothetical 10 percent increase in catch rates raises the economic value per trip by $ 0.80, the number of trips by 11,249, and total annual fishing benefits by $ 472,359. The present value of this increase in catch rates the increase in the asset value of the PES in providing this service is $ 5.5 million, using the 7 percent rate and time horizon of 25 years used for all cases.

On another issue, to address a data gap identified in EAI's Phase I study, Phase II survey respondents were asked how much they spent at road side farmstands and at vineyards and for rental accomodations. In total, in 1995, the public spent some $ 19.4 million at East End roadside farmstands and $ 5.4 million at vineyards. Using the same assumption as in the Phase I study that 45 percent of these activities are PES related ( Grigalunas and Diamantides, 1996), the annual PESrelated expenditures for these two activities are $ 8.7 and $ 2.4 million, respectively. 5 I. C. 3. Wetlands Productivity Values ( Chapter V)

Eelgrass, saltmarsh and intertidal mud bottoms provide food web and habitat services for many species of fish, shell fish, waterfowl and birds, and thus directly or indirectly benefit people who consume, hunt, or view these species. A simple food web model was developed that used available biological data, commercial fish and shell fish prices, and viewing values for birds to provide a perspective on the economic value of the productivity of these habitat types.

The results suggest an asset value per acre for existing wetlands of approximately $ 12.4 thousand for eelgrass, $ 4.3 thousand for salt marsh, and $ 786 for mud flats, using a discount rate of 7 percent and 25 year period for the services valued. Restored wetlands are worth somewhat less since it may take several years to restore fully their natural functions as a food source or habitat.

I. C. 4. Resource Preferences and Economic Values ( Chapter VI)

Early discussions revealed that the public has a strong attachment to environmental and amenity resources of the PES, even if they do not use these resources directly. As outlined above, the Property Value study captures the value of amenities ( or disamenities) to nearby properties, the Recreation study estimates use value for key outdoor recreational activities, and the Wetlands Productivity study yields estimates of the value of wetland ecosystems in the " production" of fish, shell fish, and birds. However, none of these studies reflects the value residents and second homeowners hold for the general ambience of the PES the " sense of place" it provides, a phrase used often by participants in EAI's focus groups.

To try to capture these elusive but important non market resource values, a survey developed and administered to 968 residents and second homeowners was used to learn which amenities are most important to people in the study area, and the amount that they would pay to preserve or restore them. Our purpose was ( 1) to account for the preferences many residents have for resources, even if they do not use these resources directly, and ( 2) to measure these preferences in dollars, if possible, to compare with other study results.

Most respondents to the resource survey ( 97 percent) supported at least one hypothetical action to protect resources, and indicated they would financially support such actions. The relative priorities of respondents, in order, were for farmland, eelgrass, wetlands, shellfish, and undeveloped land.

We also estimated the monetary value that the survey responses imply for the resources concerned. The estimated per acre dollar values were about $ 13 thousand for undeveloped land, $ 30 thousand for unpolluted shellfish grounds, $ 54 thousand for saltmarsh, $ 66 thousand for eelgrass and $ 70 thousand for farmland, using a 25 year time horizon and 7 percent discount rate. However, we believe that the resource priorities or relative values of resources are more reliable than are the dollar estimates of values and recommend that relative values, rather than dollar values, be used in the process of selecting management actions. . 6 I. D. REFERENCES Freeman, A. M. III, 1993. The Measurement of Environment and Resource Values: Theory and Methods. Washington, D. C.: Resources for the Future.

Grigalunas, T. A. and J. Diamantides, 1996. The Peconic Estuary System: Perspective on Uses, Sectors, and Economic Impacts. Peace Dale, RI: Economic Analysis, Inc.

Kopp, R. and V. K. Smith, 1993. Valuing Natural Assets: The Economics of Natural Resource Damage Assessment. Washington, D. C.: Resource for the Future.

Tietenberg, Tom, 1995. Environmental and Natural Resource Economics ( 4th ed.) New York: John Wiley & Sons 7 II. BACKGROUND AND INTRODUCTION II. A. BACKGROUND Located within Suffolk County at the East End of Long Island, the PES is comprised of the Peconic Flanders Bays system, Gardiners Bay and part of Block Island Sound, and the adjoining watershed lands ( Figure II. 1). Included within the PES are five towns: East Hampton, Southampton, Riverhead, Southold, and Shelter Island, as well as a small part of a sixth town, Brookhaven. In total, the five towns comprise about 38 percent of the land area and 8 percent of the year round population of Suffolk County ( SCDHS, 1992; Long Island Business News, 1994).

Important characteristics of the PES include: ( 1) the generally high quality of its coastal estuarine environment, ( 2) its economy, which is strongly influenced by seasonal, estuarine related activities, particularly tourism and recreation, and ( 3) the population, which is highly seasonal and for yearround residents is comprised of smaller, more elderly, and lower income households than for the County or Long Island as a whole ( Long Island Business News, 1994; Grigalunas and Diamantides, 1996).

Water quality in the PES generally is very good, and the study area contains many beaches, parks, open space, and habitat for birds and other wildlife, including some endangered species. These and other environmental and natural resources of the PES can be viewed as natural assets. A significant feature of assets natural or otherwise is that they can provide a stream of valuable services (" interest") over time, if maintained.

Some of the natural assets of the PES, however, are not being maintained, and others are at risk. Localized water quality problems exist due to runoff, failing septic systems, and inadequate sewage treatment. Substantial areas of open space and farms have been lost due to development; and pollution has closed thousands of acres of shellfish grounds used for commercial and recreational purposes. Further, large areas of ecologically productive eelgrass and saltmarsh ecosystems have been lost due to development, Brown Tide, and water pollution. Fin fish and shell fish landings have declined substantially over time, in part due to these problems. The combination of all of these adverse developments threaten the quality of life of residents of, and visitors to, the PES.

Management programs being developed by the Peconic Estuary Program would preserve or restore key PES environmental or natural resources. None of these programs is free, however, and some could be very costly. Deciding whether, where, how much, and when to invest in preserving or restoring PES natural resources requires consideration of many factors. One of these is the economic benefits and cost of such actions. 8 II. B. NATURE AND IMPORTANCE OF NON MARKET RESOURCE VALUES II. B. 1. Overview of Studies and Basic Concepts Economic benefits provided by natural asset services show up in at least two ways:

( 1) As market benefits to the owners, operators and employees of over 1,000 businesses that engage in or support recreation and tourism, commercial fishing and seafood activities, and other estuarine related economic operations ( Grigalunas and Diamantides, 1996).

( 2) As non market benefits to the thousands of recreationists, visitors, property owners, renters, and others who use or otherwise enjoy the quality of the PES's natural amenities.

EAI's Phase I study summarized available information for the first of these two categories by quantifying " economic impacts" of estuarine dependent economic sectors ( Figure II. 2). Estimates were made of employment, wages, sales, and number of establishments for 29 economic sectors identified as estuarine related, in whole or in part. These sectors include commercial fishing, marinas, eating and drinking establishments, hotels/ motels, and other estuarine related activities.

The Phase I results show that estuarine related economic activity is a major component of the PES economy and an important part of the livelihood of over 10,000 residents who own, operate, or are employed in more than 1,000 marine and tourism related businesses ( Grigalunas and Diamantides, 1996).

Market data alone, however, give only a very limited view of the overall benefit or value of the services provided by PES estuary related resources. This is because much of what people enjoy in the PES for example, natural amenities, like open space, attractive views, good beaches and high levels of water quality are not bought and sold in markets. Benefits cannot be counted in economic impact studies if they are not bought and sold on markets; and many benefits that do show up on markets are indirect and hence not linked to the natural asset that provides the service ( e. g., fish or shell fish " produced" by PES wetlands and later harvested by fishermen).

This Phase II report focuses on non market benefits provided by amenities in the Peconic Estuary System (" PES"). We adopt the view that the natural resources and environmental amenities of the PES can be looked at as natural assets ( Freeman, 1993; Kopp and Smith, 1993; Tietenberg, 1995) that provide a flow of benefits over time, if maintained.

Several standard economic concepts are used throughout this report. Two of these are Consumer Surplus and Present Value. To avoid later confusion, these concepts should be explained at the outset. 2Of course if the price is more than we are willing to pay we will not buy the item because it is " too expensive" or " not worth it".

9 Consumer Surplus. People buy goods or engage in activities like recreation when the benefit they receive is at least as great as the cost to them. For example, if I can buy a discount airplane ticket for $ 200, I would do so only if it was worth at least that amount to me. If I would pay up to $ 500 for the flight, then I will buy the ticket and receive a net benefit an unpaid for benefit of $ 300. Similarly, on a summer day I might be willing to pay as much as $ 15 to use a beach, but if using it costs me only $ 5, then I receive an unpaid for benefit of $ 10 for that trip to the beach2.

In the above examples, the most that I am willing to pay is my assessment of the economic value of the airplane ticket or the day at the beach what each is worth to me. The net benefit to me in each case is the difference between the most I would pay, less what I actually pay. This " unpaid for benefit" realized in each example captures the notion of " Consumer's Surplus". Consumer Surplus the benefit people receive from a good or service above and beyond the cost to them provides the basis for the measurement of economic benefits used in this document.

Of course, the " trick" is to use sound methods to discover the Consumer Surplus the public receives for the services provided by the natural assets of the PES. Fortunately, standard methods are available to do just that. These methods, and how they were used to value the services of PES natural assets, are summarized in the next section and explained in detail in succeeding chapters.

Discounting and Present Value. A second important concept involves discounting. Many benefits or costs occur over time, and discounting is the process used to convert future benefits or costs to an equivalent, lump sum value today. This discounting process is used, for example, to convert a retirement or lottery annuity ( an equal cash amount each year) to a lump sum equivalent today. The equivalent, lump sum value today arrived at by discounting is called the " present value".

To estimate the present value of a stream of dollar flows over years 1 through " T", we discount each annual flow using the formula:

Present Value = V1/( 1+ r) 1 + ....+ VT/( 1+ r) T where V is a dollar value and r is the discount rate the interest rate used to convert future flows into a value today. For example, if the total Consumer Surplus from swimming is $ 1,000 in year 1 and $ 1,000 in year 2, and the discount rate is 10 percent, then the present value of these annual amounts is $ 1,735 (= $ 909 +$ 826) today.

The present value calculated using the above formula depends upon three factors: ( 1) the size of the annual monetary values, Vt, ( 2) when they occur, and ( 3) the discount rate, r, used. We estimate the annual monetary values, Vt for non market services in the chapters that follow, employ a time 37 % is the representative value used in this report. In later efforts, the effects of different rates will be examined.

10 horizon, T, of 25 years, and use a discount rate of 7 percent, a standard rate recommended for use in many resource management projects3.

II. C. PURPOSE AND SCOPE This report describes the four non market valuation studies comprising Phase II of a series of studies being carried out by EAI for the Peconic Estuary Program. The Phase II studies provide estimates of recreational uses and the economic values that the public holds recreation and for a variety of other services provided by key PES environmental and natural resources.

The Phase II studies reported on here are a major component of a larger program to assess the benefits and costs of proposed management actions as part of the Peconic Estuary Program ( Figure II. 3). Phase I was designed to estimate market effects provided by the PES. As discussed above, Phase I measures " economic impacts" of the PES, including employment, sales, wages, and the number of establishments associated with 29 economic sectors identified as estuarine related. Phase II provides estimates of non market benefits. Our studies were carried out for the purpose of eventually contributing to benefit cost analyses of proposed management actions by the PES Management Committee in Phase III of the project.

Phase III analyses will ( 1) provide cost analyses for specific management actions designed to protect or restore PES amenities, ( 2) combine this cost information and the benefit information from Phases I and II to provide benefit cost analyses of potential management actions, and ( 3) compare various financing options for the proposed management actions.

We designed a suite of non market valuation studies in order to be able to estimate the value of key services provided by amenities in the PES. Multiple non market valuation studies are needed because of the many different types of services provided by PES environmental and natural resources. For example, recreational participants directly use Bay waters and beaches; hence, for these activities we want to measure participants' recreational use values. In other cases, PES resources may provide amenity or aesthetic benefits to residents, which will be captured in property values, another type of use value. Additionally, some may also enjoy just knowing that PES environmental amenities, such as open space and salt marsh, are being preserved or restored, whether or not they directly use these resources. For these resources, other values, not involving direct use, may also be important and should be included. In sum, our use of a variety of methods was designed to allow us to gain a better understanding of the non market values provided by different resource services, information that will prove useful for later benefit cost studies.

The key Phase II studies are the property value study, the recreation survey, the wetlands productivity analysis, and the resource survey. The property value study was designed to estimate benefits that PES amenities provide to individuals who own adjacent properties. The recreational survey allows us to estimate recreational use and use values for a variety of outdoor activities. This 11 survey was designed fill data gaps identified in Phase I report, and to estimate recreational uses and use values to contribute to assessment of management actions in Phase III. The wetlands productivity analysis uses available data to estimate the productivity of specific habitat types, and to place a dollar measure on the ecosystem services provided. The productivity study includes only food web and habitat services and focuses on the " production" of commercial species, and to a lesser extent, on non commercial values ( viewing and hunting values). Finally, the resource survey is used to identify public priorities and values for specific environmental amenities. The resource survey used a contingent choice model to learn which amenities are most important to the public and the amount that respondents indicate that they would pay to preserve or restore them. Summary information for each study is give in Table II. 1; each study is described in detail in the chapters and appendices that follow.

II. D. REFERENCES Grigalunas, T. A. and J. Diamantides, 1996. The Peconic Estuary System: Perspective on Uses, Sectors, and Economic Impacts. Peace Dale, RI: Economic Analysis, Inc.

Long Island Business News, 1994. Long Island Almanac 1994. Ronkonkoma, NY: Long Island Business News.

Suffolk County Department of Health Services, 1992. Brown Tide Comprehensive Assessment and Management Program. 3 volumes. Suffolk County Dept. of Health Services ( November). 12 Table II. 1. Summary of EAI's Phase II Non Market Valuation Studies for PES Study Purpose Data and Method( s)

Recreational Uses and Use Values 1. Estimate Resident, Second Home Owners & Visitor Recreational Uses: ! Activities i 8 Key Activities i 8 Locations 5 PES Bays Atlantic Ocean LI & BI Sounds i 5 Towns 2. Estimate Use Value for: ! Swimming ! Boating ! Fishing ! Bird & Wildlife Viewing Convenience sampling/ Intercept Survey Self administered 1,354 completed surveys Travel Cost Method Demand for swimming and recreational fishing depends on quality Resource Values Estimate Residents' and Second Homeowners' Preferences and Economic Value for preserving and restoring PES: ! Open space ! Farmland preservation ! Unpolluted shellfish beds ! Wetlands ! Eelgrass beds Convenience sampling/ Intercept Survey Self administered 968 completed surveys Contingent Choice Method Wetlands Productivity Values Estimate the Economic Value for Nursery and Habitat Productivity functions for: ! Saltmarsh ! Eelgrass ! Intertidal mud bottom Based on Productivity approach and results in available literature.

Property Value Estimate the effect on Property Value in Town of Southhold of attributes, including: ! Site i Lot & home size i Garage i Special features ! Neighborhood i Main road ! Environmental i Wetlands i Open Space i Farmlands i Zoning Size All property sales in Town for 1996 374 sales transactions Geographical Information System Property Value (" Hedonic") Model III. ENVIRONMENTAL AMENITIES AND PROPERTY VALUES: 13 A CASE STUDY OF THE TOWN OF SOUTHOLD III. A. INTRODUCTION Property values in coastal communities depend upon many factors. These include not only the size of the property and the characteristics of the home on the property, but also on environmental amenities, such as open space and proximity to the shoreline. For example, we would expect a home located near the PES waterfront to be more valuable than another home, identical in all respects, but located a greater distance from the shore. If we could find two such homes, we could simply compare the prices at which they sell and, by that, calculate the value of being near the shore.

Of course, rarely are two homes identical in all respects except for one attribute. Instead, as anyone who has bought a home knows, the price that a property commands on real estate markets reflects a great many factors. These include: lot size, size of the home and its location, the characteristics of the surrounding neighborhood, and a wide range of other environmental factors. Nevertheless, if all of these important factors can be taken into account, it is possible to isolate the value of individual factors, much as a real estate broker or tax assessor does when appraising a property.

This Chapter exploits these simple insights. We analyze data from many residential housing transactions using a standard property value model, as we explain in detail below. The model allows us to estimate the value as captured in market prices that people attach to various environmental attributes, such as proximity to open space and farmland. If efforts to estimate the value of environmental attributes are successful, the results can be used to assess the potential benefits of possible management actions that would affect any of the factors studied. That is, we could estimate the potential benefits from a proposed management action, as measured through changes in market prices for property.

We use the Town of Southold, located on the North Fork of the PES, as a case study ( Figure III. 1). Southold is an interesting example, for several reasons. First, it has a wide range of environmental amenity levels and neighborhood conditions. For example, Southold has large areas of farmland and open space, although its population density ( 0.67 persons per acre) is highest among all five PES towns. In addition, Southold has a long and varied coastline, both on the Peconic Estuary and on Long Island Sound, and is characterized by a variety of development densities and types. About a quarter ( 26%) of the town is currently in agricultural use, compared with 30% in residential use, 12% is preserved as open space, and 18% is classified as vacant. Less than 3% is classified as commercial or industrial ( Suffolk County Department of Planning 1997a).

Southold's population increased 8.9% between 1980 and 1990, yet the number of housing units increased at nearly twice this level ( 16.6%). Thus, the growth of housing and the associated loss of undeveloped lands has far out paced population growth ( Suffolk County Department of Planning 1997b). Given the recent rapid pace of development, the protection of open space, undeveloped land, and other environmental amenities will play an important role in determining future quality of life in the Town and, perhaps, in the PES area. 14 The impacts of environmental amenities on Southold property values, and the impacts resulting from possible PES management actions, will depend upon the unique characteristics of the town ( and perhaps the quality of surrounding waters and land areas). To assess these impacts, EAI conducted a property value analysis specific to the town of Southold. We apply economic methods using the property value ( or " hedonic" method) to a database comprised of all Southold real estate transactions in 1996 and GIS parcel coverage data for the town. Briefly, the analysis estimates correlations between property values and levels of valued environmental attributes, including open space.

The policy relevance of the results lies in the assumption that established relationships between environmental amenities and property values estimated using the property value model will continue to hold in the future, as future events ( including policies) lead to changes in the level of these amenities. Through the detailed study of existing property values, we seek the best possible statistical estimate of the environmental impacts on local property values, given the available data.

III. B. RELATIONSHIP BETWEEN ENVIRONMENTAL AMENITIES AND PROPERTY VALUES Environmental amenities provide valued services to residents of local communities. For example, open space contributes, in a physical sense, to the character of local communities, while providing a wide variety of services, including scenic views, outdoor recreation, insulation from noise and other aspects of the urban landscape, and protection from erosion, flooding, and other physical hazards ( Johnston 1997a). These amenities are valued by local homeow ners, making communities with a high level of valued environmental amenities ( i. e., environmental quality) more attractive than similar communities without such amenities. As a result, home buyers are willing to pay more for land or housing with higher levels of environmental quality. The property value method ( also called the hedonic model) can be used to estimate the impact of environmental amenities on the values of local property, thereby estimating the value of these amenities to local residents, as evidenced by their actual willingness to pay higher prices for properties with higher levels of desired environmental characteristics.

A well documented example of the relationship among environmental amenities and property values involves open space. Many studies show that nearby open space increases property values, reflecting home buyers' values for the services and character offered by open space ( e. g., Freeman, 1993). In a recent, coordinated property value/ geographic information system study conducted in Middletown, Rhode Island, Johnston ( 1997) shows that positive property values impacts of open space can range from less than 1% to greater than 13%, depending on the size of nearby contiguous open space parcels, the total amount of open space in a region, and the distance of property from open space parcels. Larger property value impacts are associated with larger contiguous parcels, larger acreage of open space, and a closer proximity between valued parcels and open space ( Johnston 1997a). Similar results hold elsewhere in the New England region. A study in Worchester, MA, for example, found that houses located less than 20 feet from a community park sell for over $ 2,000 more than similar houses located more than 2000 feet from the park ( More, et 15 al., 1982). In an analysis of cluster zoning in Amherst, Massachusetts, Lacy ( 1990) estimates that cluster zoned housing with permanently protected open space appreciates at a faster rate that similar housing in conventional subdivisions. As of 1989, this difference had created an average $ 17,100 difference between the average selling price in the two types of developments.

Comparable results concerning the value of open space also have been found in other coastal areas. For example, a study of land values adjacent to Chesapeake Bay shows a positive relationship between the percentage of preserved open space in a 250 acre area surrounding a parcel of land, and the per acre selling price of that land. This study also shows that agricultural pasture land and forest land increases the per acre value of nearby land, other things being the same ( Bockstael 1996). Similar results are shown by Geoghegan et al. ( 1995). Parsons ( 1992) estimates that land use restrictions in the Chesapeake Bay watershed cause a 14 27% increase in housing prices within 1,000 feet of the bay, and a 4 11% increase up to a 3 mile distance. Garrod and Willis ( 1992) conclude that housing prices are positively related to the existence of nearby broadleaf forests. Correll et al. ( 1978) find that, on average, residential housing prices in Boulder, Colorado decrease by $ 4.20 for each additional foot of distance from a central green way, up to a distance of 3200 feet.

Of course, the impacts of environmental amenities on Southold property values depend on the unique characteristics of the town, and may be greater or less than those cited above. To assess these impacts, we conducted a property value analysis specific to the town of Southold. We apply economic methods ( hedonic methods) to a database comprised of GIS parcel coverage data and real estate sales data. In simple terms, the property value model estimates correlations between property values and levels of valued environmental attributes, including open space. The steps involved and data used are described next.

III. C. APPLICATION OF PROPERTY VALUE MODEL TO SOUTHOLD This study applies the property value model to real estate parcels sold in Southold during 1996. The analysis estimates how various site, neighborhood and environmental characteristics affect the value of individual properties. Property value analysis is a common means of estimating the effect of environmental changes on land values, as described in detail by Freeman ( 1993) and Garrod and Willis ( 1992), among many others.

III. C. 1. Explanation of The Property Value Method People buying homes in effect purchase many site, neighborhood, and environmental characteristics. For example, the characteristics of a residential property include: the size of the house, the number of baths, the square footage of the structure, the zoning classification of the land, whether the land is served by public sewers and water, the existence of wetlands on the property, and the proximity of the property to amenities such as open space, coastlines, and farms. These and other characteristics define the property, and make it more or less attractive to potential buyers. Other things being the same, home buyers are willing to pay more for properties that they find have 4 The accuracy of hedonic analysis depends on a well functioning real estate market, in which consumers have accurate information regarding all home characteristics. The technique also assumes that a large number of different housing types are available for purchase, so that consumers can choose the " package" of housing characteristics that is most to their liking, and can " mix and match" different types of characteristics. Finally, the technique assumes the availability of appropriate data, concerning all characteristics that influence property values Bias can result from the application of hedonic techniques to ill functioning real estate markets, in which few different types of housing options are available, and/ or in which consumers do not have accurate information regarding housing characteristics ( Johnston 1997a).

16 desirable characteristics, and less for properties with undesirable characteristics. These likes and dislikes across many prospective buyers and sellers are reflected in market prices. The Property Value Method attempts to estimate the portion of a property's value related to each relevant characteristic, by that providing an estimate of the ( implicit) value of each characteristic. The model works by statistically comparing values of a large number of properties with differing levels of the identified characteristics ( e. g. lot sizes, number of rooms, proximity to roads, farms, open space, etc.) ( Freeman, 1993; Johnston, 1997a).

The Property Value technique is based on the assumption that a relationship exists between the market value of a property, and the characteristics of the property. The Property Value method uses a statistical technique called " multiple regression" to assess the impact of each characteristic on the market value of the property. The technique simultaneously compares a large number of properties with different prices and different levels of each characteristic. The method establishes which characteristics are associated with higher values, which are associated with lower values, and which have no significant impact on values. The model also estimates the dollar magnitude of these impacts that is, it estimates how large an impact is likely to be caused by a specific level of a specific characteristic. Using this technique, the impact of different environmental amenities on nearby property values can be estimated. 4 The technical details of the property value model ( or hedonic technique) are presented in Appendix A.

Actual 1996 sales prices are used in the analysis of Southold property values. The data for the analysis is drawn from two sources:

( 1) Town of Southold property record cards for all properties sold during 1996; and ( 2) The computerized geographic information system ( GIS) maintained by the Suffolk County Planning Department.

Although sales data were available for 401 parcels, complete GIS coverage data exists for only 374 of these parcels. Thus, the Southold data set used in the analysis has full information on 374 parcels.

III. D. STATISTICAL ANALYSIS OF SOUTHOLD LAND VALUES 5 Wichelns and Kline ( 1996), Chicoine ( 1981), Shonkwiler and Reynolds ( 1986), and Garrod and Willis ( 1992).

17 Model variables are the characteristics that influence buyers' willingness to purchase a land parcel, or pay higher prices for that parcel. These include proximity to amenities such as open space and coastlines; the size of the parcel; the size and other characteristics of the structures on the parcel; applicable use restrictions such as zoning codes; and the existence of features such as wetlands on the parcel. These variables may be grouped into three general categories: parcel characteristics, neighborhood characteristics, and environmental characteristics. To distinguish the effects of parcel size on land values, we consider the effect of the characteristics on per acre value. This is calculated by dividing selling price by the number of acres in the parcel. Note that these per acre land values include the value of all structures built on the land. For a full description of the 23 variables included in the final analysis, see Appendix A.

The statistical analysis uses the ordinary least squares ( OLS) multiple regression approach. This approach estimates the direction, magnitude, and statistical significance of correlations between each of a set of independent variables ( the characteristics of the property), and a single dependent variable ( per acre property value).

To establish the nature of the specific functional relationship between these variables and assessed land values, the study relies on the findings of prior research. In particular, the regression analysis applies a " transcendental" or " translog functional form". 5 The transcendental form is chosen for its ability to capture realistic relationships between parcel characteristics and land values ( Chicoine 1981). Such functional forms are also preferred for their statistical properties in cases where data concerning certain relevant variables may not exist in the data set ( Garrod and Willis 1992). For a technical description of the statistical model and its properties, see Appendix B.

III. E. ANALYSIS OF SOUTHOLD LAND VALUES: RESULTS The hedonic analysis provides information on the effect of 20 characteristics on per acre land values in Southold. Final model results are illustrated in Appendix C. Overall measures of model fit indicate high levels of correlation between land characteristics and property values. An R2 value of 0.8352 indicates that over 83% of the variation in per acre value is " explained" by the model, or is correlated with model variables. An F statistic of 75.945 indicates only a .01% chance that the set of correlations reported by the model could be observed through random chance alone. The signs associated with model variables are consistent with prior expectations and with the findings of earlier hedonic studies ( e. g., Bockstael 1996; Johnston 1997a; Des Rosiers and Theriault 1992; Garrod andWillis 1992). Of those variables with demonstrated impacts on property values, seven have potential implications for environmental policy. These include the following:

° openspace: This variable identified parcels adjacent to open space land, as defined by the GIS database. A parcel of land located next to open space has, on average, 12.83% higher per acre value than a similar parcel located 18 elsewhere. Parcels adjacent to open space are defined as those with a border within 25 ft. ( 7.62 meters) of an open space parcel. As defined by the GIS for Suffolk County, open space includes: parks; nature and wildlife preserves; recreational fields; unbuildable swamps or wetlands; large tracts of land associated with schools, cemeteries, or other institutions; and selected large parcels of preserved farmland.

° farmdistance: This variable represents the distance between a specific parcel and the nearest farmland ( farmland on which agricultural crops or nursery products are grown), in meters. For every meter of additional distance between a parcel and the nearest farmland, average per acre property value increases by 0.0017% ( i. e., the magnitude of the impact is quite small).

° onfarm: This variable identifies parcels contiguous to farmland. A parcel of land located next to farmland has, on average, a 13.32% lower per acre value than a similar parcel located elsewhere.

° onroad: This variable identifies parcels within 20 meters of a major road ( defined as Rts. 25 and 48). A parcel of land located next to a major road has, on average, a 16.16% lower per acre value than a similar parcel located elsewhere.

° largezone: This variable identifies parcels located in districts zoned R 80 or R 120 ( two or three acre zoning). A parcel of land located within a district zoned R 80 or R 120 has, on average, 16.65% higher per acre value than a similar parcel located elsewhere.

° wetland: This variable indicates the percentage of a parcel classified as a freshwater wetland. For every one percentage point increase in the percent of a parcel classified as wetlands, average per acre property value increases by 0.27%. ( However, this variable is only significant at the 14% level.)

III. F. SIMPLE ILLUSTRATION OF PROPERTY VALUE IMPACTS: VALUE OF OPEN SPACE Given the definition of the open space variable, the impact of open space on neighboring property values will differ depending on the characteristics of the surrounding property. However, to illustrate the basic implications of the model results for policy, the following section simulates the predicted property value impact of the hypothetical loss of 10 acres of open space, in a highly simplified scenario. Given specific locations for the open space land under consideration, and the characteristics of the surrounding parcels, similar results could be generated for actual areas in Southold. 6In this regard, we note that recent support for an open space initiative in Suffolk County suggests that the electorate has a strong preference for open space as a public good.

19 According to the model results, properties adjacent to open space land ( or within 25 ft.) are an average of 12.83% more valuable than those not adjacent to open space. Within the Southold data sample, the average parcel sales price was $ 213,514, with an average parcel size of 2941.95 square meters ( 0.72 acre). Given this average value, a loss of 12.83% ( related to the loss of our hypothetical 10 acres of adjacent open space) implies that average property value for the adjacent parcels would decrease by $ 27,394, all else held constant.

To estimate a hypothetical total impact in a simple case, assume that the lost open space was ten acres in a square shape, surrounded by parcels of average 0.72 acre size ( the average in our sample), also square in shape. Assuming a square shape for the open space parcel, it would have a perimeter of 805.2 meters that would be bordered by other parcels. Given an average per parcel area of 2941.95 square meters ( also assumed square), the length per side of these bordering parcels would be approximately 54 meters. Given these measurements, approximately 15 parcels would fit adjacent to the 10 acre open space parcel, assuming each had a full 54 meter side bordering the open space ( 805.2 ÷ 54 = 14.9). Accordingly, for this simple example, we assume that 15 average parcels would be affected by the loss, or development, of our square ten acres of open space.

As stated previously, development of the open space parcel would result in a loss of 12.83% of average value per lot or $ 213,514, according to the calculations made above. Thus, the average parcel would lose $ 27,394 in total value. Multiplied by the 15 parcels adjacent to the newly developed parcel, the total property value loss is equal to $ 27,394 × 15=$ 410,907. This equates to an average loss of $ 41,090 in total property value per acre of open space lost. Looked at another way, the estimated benefits of preserving the ten acres of open space thus would be $ 410,907, as this is the increase in nearby property value associated with this open space parcel.

For this illustration we do not compare costs with benefits since we do not have information on the costs of acquiring specific undeveloped property for open space. However, in the illustration, if the 10 acres of undeveloped property for open space could be acquired for less than $ 410,907 or $ 41,097 per acre, then the benefits would be greater than costs. Note that even if the property to be acquired for open space costs more than $ 410,907, benefits still may exceed costs. This is because not all of the public benefits of open space are captured in our hedonic analysis. For example, our results in this section do not capture general amenity benefits enjoyed by all local residents, regardless of the location of their homes ( see Chapter VI for discussion of this issue). 6 We note that the impacts illustrated above should not be regarded as exact results expected in any single instance, and are included for illustration purposes only. A full benefit cost analysis would require much more detailed analysis of the proposed project and its impacts, including impacts on surrounding property values. However, the illustrated results do indicate the general types of benefits and costs that may be expected, on average, over the entire community. Although the results require various assumptions as noted above, they are robust with respect to the quantity of open space preserved. 20 III. G. LIMITATIONS IN PROPERTY VALUE ANALYSIS As noted, the model provides a good fit for sales data for the town, and the results of the Southold property value analysis correspond to prior expectations and with the results of similar analyses. Nevertheless several potential limitations should be noted. The most important of these limitations is that the results of the statistical analysis are sensitive to characteristics of the data set. The combined property card GIS database may exclude information on certain variables that may affect property values. Although numerous environmental variables may influence property purchase decisions, data limitations allowed us to include only a sub set of these variables in the model. For example, the data set includes water quality monitoring data for the Peconic Estuary, conducted at numerous sites. However, no parcels in the 1996 sales database are located within 100 meters of the Peconic Estuary. Thus, for those parcels in the current database, water quality is not expected to have an impact. However, were data to exist for parcels close to the estuary, one would expect that water quality might have an impact on property values. Other variables for which data was unavailable included fresh water ( including groundwater) quality; beach erosion ( likely only important for beachfront properties); and proximity to creeks, all of which would be expected to affect property values. If in fact important variables are excluded from the model, statistical results may show upward or downward bias. Omission of important variables can either increase or decrease the estimated effects of environmental amenities on property values, based on the extent to which these variables are correlated with environmental variables. ( If these omitted variables are uncorrelated with the environmental policy variables of interest, then their absence should not influence reported results.)

For all of the above reasons, the estimated Property Value model results should not be interpreted as " exact". Rather, they provide the best possible estimate, given available data, of the impacts of existing environmental attributes on current per acre land values.

A second limitation is that increased property values, related to improved environmental quality, may not be favored by all residents. For example, residents may resist open space preservation on the grounds that it tends to increase property values, thereby increasing the costs of housing for young home buyers. Others may reject increases in property taxes that accompany higher property values. Still others may object that higher property values tend to " squeeze out" low income residents. Real estate agents may oppose additional open space on the basis that fewer housing units are available, despite the act that average property values in the area affected will be higher with the additional open space. Such arguments should be acknowledged when considering environmental policy changes using the results of property value methods.

Finally, we note that many people beyond the immediate area may derive benefits from open space but their benefits are not included in numbers given in the above illustration. For example, residents of the town who live outside of the grid used in the illustration may value open space elsewhere in town ( see Chapter V).

III. H. SUMMARY 21 Environmental amenities increase property values of nearby parcels, reflecting the valuable services offered by these amenities. An analysis of Southold property values supports this contention, and corresponds with the results of prior studies. In Southold, existing open space increases the values of adjacent properties by an estimated 12.83%. In addition, average per acre property values are higher in parcels located further from farms and major roads. Finally, higher property values appear to be associated with the existence of wetlands on the property, and with large lot ( 2 and 3 acre) zoning. These results indicate that environmental policies can have significant impacts on property values, reflecting the influence of local environmental amenities on local quality of life.

III. I REFERENCES Bockstael, N. E. 1996. " Modeling Economics and Ecology: The Importance of a Spatial Perspective," American Journal of Agricultural Economics 78: 1168 1180.

Chicoine, D. L., 1981. Farmland Values at the Urban Fringe: An Analysis of Sales Prices." Land Economics 57( 3): 353 362.

Correll, M., J. Lillydahl and L. Singell, 1978. " The Effects of Greenbelts on Property Values: Some Findings on the Political Economy of Open Space." Land Economics 54: 207 217.

Des Rosiers, F. and M. Theriault. 1992. " Integrating Geographic Information Systems to Hedonic Price Modeling: An Application to the Quebec Region. Property Tax Journal 11( 1): 29 57.

Edwards, Steven and Glenn Anderson, 1984. " Land Use Conflicts in the Coastal Zone: An Approach for the Analysis of the Opportunity Costs of Protecting Coastal Resources." Journal of the Northeastern Agricultural and Resource Economics Association ( April).

Freeman, M. A., 1979. The Benefits of Environmental Improvement: Theory and Practice. Baltimore: Johns Hopkins University Press.

Freeman, M. A. 1993. The Measurement of Environmental and Natural Resource Values. Washington, DC: Resources for the Future.

Garrod, G. and K. Willis, 1992. " The Environmental Economic Impact of a Woodland: A Two Stage Hedonic Price Model of the Amenity Value of Forestry in Britain." Applied Economics 24: 715 728.

Geoghegan, J., N. Bockstael, and D. Lipton. 1996. The Economics of Land Use Change in the Patuxent Watershed. prepared for the Land Use and Management in Maryland Seminar, 1996. College Park, MD: Center for Agricultural and Natural Resource Policy. 22 Geoghegan, J., N. Bockstael, and L. Wainger. 1995. " Spatial Landscape Indices in a Hedonic Framework: An Ecological Economics Analysis Using GIS." presented at the annual meetings of the Association of Environmental and Resource Economics, Indianapolis, IN.

Hammer, T. R., R. E. Coughlin and E. T. Horn IV. 1974. Research Report: The Effect of a Large Park on Real Estate Values. Journal of the American Institute of Planners, July.

Johnston, R. J. 1997a Aquidneck Island and Open Space: An Economic Perspective: Technical Manual Narragansett, RI: The Aquidneck Island Partnership and the Coastal Resources Center, University of Rhode Island.

Johnston, R. J. 1997b. Aquidneck Island and Open Space: An Economic Perspective. Narragansett, RI: The Aquidneck Island Partnership and the Coastal Resources Center, University of Rhode Island.

Kask, S. B. and S. A. Maani, 1992. " Uncertainty, Information, and Hedonic Pricing." Land Economics 68( 2): 170 184.

Kimmel, M. M., 1985. Parks and Property Values: An Empirical Study in Dayton and Columbus, Ohio. Thesis. Oxford, OH: Miami Univ., Inst. of Environmental Sciences.

Lacy, J. 1990. An Examination of Market Appreciation for Clustered Housing with Permanently Protected Open Space. Center for Rural Massachusetts Monograph Series. Amherst, MA: University of Massachusetts.

Lardaro, L., 1993. Applied Econometrics. New York: Harper Collins College Publishers.

More, T. A., Thomas Stevens and P. Geoffrey Allen, 1992. " The Economics of Urban Parks." Parks and Recreation.

National Park Service, 1995. The Economic Impacts of Protection Rivers, Trails, and Greenway Corridors. Washington, D. C.: Rivers, Trails, and Conservation Assistance Program.

Nelson, A. C., 1985. " A Unifying View of Greenbelt Influences on Regional Land Values and Implications for Regional Planning Policy." Growth and Change 16( 2): 43 48.

Parsons, G. R., 1992. " The Effect of Coastal Land Use Restrictions on Housing Prices: A Repeat Sale Analysis." Jour. of Environmental Economics and Management 22: 25 37.

Rosen, S., 1974. Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition." Journal of Political Economy 82( 1): 34 55.

SAS Institute Inc. 1996. SAS User's Guide: Statistics. Cary: NC: SAS Institute Inc. 23 Shonkwiler, J. S. and J. E Reynolds, 1986. " A Note on the Use of Hedonic Models in the Analysis of Land Prices at the Urban Fringe." Land Economics 62( 1).

Wichelns, D. and J. Kline, 1993. " The Impact of Parcel Characteristics on the Cost of Development Rights to Farmland". Agric. and Resource Economics Review: 150 158. 24 APPENDIX A. Variables in the Hedonic Analysis All model variables were generated from one of two sources: 1] Official Southold Property Record Cards for all parcels sold during 1996; 2] GIS coverages maintained Suffolk County Planning Department, updated 1995.

Dependent Variable:

LVALACRE: The natural log of per acre sales price, in dollars. Based on Southold property record cards for properties sold during 1996.

Independent Variables:

LNACRES: the natural log of acres in each parcel. Estimated using GIS coverages.

WATFRONT: dummy variable: value of 1 assigned if property is located on the waterfront ( Long Island Sound or Peconic); value of value of 0 assigned if property is not located on a waterfront. Value assigned based on waterfront classification of property record cards.

BULKHEAD: dummy variable: value of 1 assigned if property has a bulkhead on the waterfront, value of 0 assigned if no bulkhead. Value assigned based on property record cards.

LARGEZONE: dummy variable: value of 1 assigned for parcels located in districts zoned R 80 or R 120; value of zero assigned to all other zoning classifications.

YEAR: year the house was built, based on property records, minus 1950.

YEARSQ: YEAR * YEAR ( year squared).

GARSQFT: the number of square feet in the garage, based on property records. If no garage exists, value of 0 is assigned.

PATIO: dummy variable: value of 1 assigned if the house has a patio or deck; value of 0 assigned if there is no patio or deck, based on property records.

BATHS: the number of bathrooms, based on property records.

NOHEAT: dummy variable: value of 1 assigned if the house has no heat, value of 0 assigned if house has heat, based on property records. 25 FIRE: dummy variable: value of 1 assigned if the house has a fireplace or woodburning stove; value of 0 assigned if there is no fireplace or woodburning stove, based on property records.

SQFT: square footage of the house, based on property records.

SPECIAL: dummy variable: value of 1 assigned if the house has a " special" feature ( tennis court, swimming pool, etc.); value of 0 assigned if no special features are present, based on property records.

DSOUNDT: The linear distance to Long Island Sound, truncated at 800 meters ( i. e., the maximum possible value is 800). Based on GIS coverages.

PECON100: dummy variable: value of 1 assigned if the parcel is within 100 meters of the Peconic Estuary; value of zero assigned if the parcel is further than 100 linear meters from the estuary. Based on GIS coverages.

SOUND100: dummy variable: value of 1 assigned if the parcel is within 100 meters of Long Island Sound; value of zero assigned if the parcel is further than 100 linear meters from the Sound. Based on GIS coverages.

ONROAD: dummy variable: value of 1 assigned if the parcel is within 20 meters of a main road ( Rts. 25 and 48); value of 0 assigned if the parcel is further than 20 meters from a main road. Based on GIS coverages.

FARMDISTANCE: the linear distance between the parcel and the nearest farmland ( farmland), in meters. Based on GIS coverages.

ONFARM: dummy variable: value of 1 assigned if the parcel is contiguous ( distance= 0) to farmland; value of 0 assigned if the parcel is further than 0 meters from farmland. Based on GIS coverages.

WETLAND: indicates the percentage of the property covered by freshwater wetlands.

OPENSPACE: dummy variable: value of 1 assigned if the parcel is adjacent to open space ( where adjacent is defined as a parcel whose border is within 25 feet of an open space parcel); value of 0 assigned if the parcel is further than 25 feet from open space. Based on GIS coverages.

The Southold GIS coverage classifies the following land uses as open space: fish, game, and wildlife preserves; public golf courses; private golf courses and country clubs; improved beaches; camps and camping facilities; parks; nature trails and bike paths; cemeteries; private hunting and fishing clubs; state owned forest land; reforested land and other conservation land; public 26 parks; other wild or conservation lands; and taxable state owned conservation easements.

Farms and undeveloped private property, in general, are not considered open space.

Mean values of variables included in the analysis, for the 374 observations in the database, are illustrated below.

Table B. 1 Mean Values of Model Variables Variable Mean Value LVALACRE 12.8362 LNACRE  0.7521 WATFRONT 0.2340 BULKHEAD 0.0718 PORCH 0.5266 YEAR 16.7500 GARSQFT 265.1861 PATIO 0.4734 BATHS 1.6303 NOHEAT 0.1197 FIRE 0.5372 SQFT 1270.3200 SPECIAL 0.1064 PECON100 0.0053 SOUND100 0.0848 ONROAD 0.0585 ONFARM 0.0452 DFARM 2395.1400 OPENSPACE 0.050398 WETLAND 2.4548 LARGEZONE 0.1011 27 #

#

#

#

# pond Long Island Sound 100 meter radius ROUTE 25 Agricultural Land Distance > 100 m Agricultural Land Distance < 100 m GIS Maps Used to Define Model Variables: Examples Many of the variables in the analysis were derived from GIS parcel coverages of Southold. The following GIS map illustrates the type of analysis applied. In this case, the map illustrates the process used to determine the existence of agricultural land within 100 meters of each parcel in the sales database. 28 Wetlands pond Long Island Sound RO UTE 25 The following GIS map covers the same area of Southold, yet illustrates the distribution of wetlands, used to assess the percentage of each sales parcel covered by freshwater wetlands. 29 APPENDIX B. The Statistical Model To establish the functional ( mathematical) relationship between model variables and assessed land values, the analysis on the findings of prior research. In particular, the analysis follows Wichelns and Kline ( 1996), Chicoine ( 1981), Shonkwiler and Reynolds ( 1986), and Garrod and Willis ( 1992) applying a transcendental or translog functional form to the property price   characteristics equation Vi =   0Xi1  1exp[    jXij] j= 2... n where Vi is the 1996 selling price of the ith parcel, in dollars per acre, Xi1 is parcel size in acres, and Xij are measures of the j = 2  n other characteristics that affect land value. The  ' s are parameters to be estimated, and represent the effects of each of the characteristics on per acre land price. Estimated parameters are used to calculate the effects of different open space characteristics on the value of land in Southold. The transcendental form is chosen for its ability to capture realistic relationships between parcel characteristics and land values ( Chicoine 1981). For example, the transcendental form permits a positive or negative marginal relationship between value and parcel size ( acres), requires value to be zero when parcel size is zero, can detect proportional value size relationships, and allows for increasing or decreasing returns to scale for land parcel characteristics ( Chicoine 1981; Wichelns and Kline 1993). Moreover, functional forms such as the semi log or transcendental are preferred ( to the more flexible functional forms) when there is potential omitted variable bias ( Garrod and Willis 1992).

The empirical version of the translog model is as follows:

where the variables are as defined above, and ln(.) represents the natural log. This is the form used for statistical analysis in the Southold property value study.

The estimated trans log model appears to fit the data well. Overall model statistics and individual variable significance levels indicate good model fit, and trials with alternate functional forms ( e. g., linear, semi log) indicate that these alternate forms result in lower significance levels and explanatory power. A White test for heteroskedasticity ( White 1980) fails to reject the null hypothesis of homoskedasticity at the 5% level. Although multicollinearity is ubiquitous in hedonic models, tests for multicollinearity indicate that it does not have severe impacts on model results in the present application. As the data is cross sectional and data order has been randomized, tests for autocorrelation are unnecessary. 30 APPENDIX C. OLS Model Results Dependent Variable: LVALACRE Sum of Mean Source DF Squares Square F Value Prob> F Model 20 152.03723 7.60186 89.930 Error 355 30.00860 0.08453 C Total 375 182.04583 Root MSE 0.29074 R square 0.8352 Dep Mean 12.83621 Adj R sq 0.8259 C. V. 2.26502 Parameter Estimates Parameter Standard T for H0: Variable Estimate Error Parameter= 0 Prob > | T|

INTERCEP 11.409748 0.08174613 139.575 0.0001 LNACRE  0.905956 0.02606823  34.753 0.0001 WATFRONT 0.333735 0.04497479 7.420 0.0001 BULKHEAD 0.200245 0.06780928 2.953 0.0034 YEARSQ 0.000302 0.00011945 2.528 0.0119 YEAR  0.012017 0.00484814  2.479 0.0136 GARSQFT 0.000165 0.00006797 2.428 0.0157 PATIO 0.103269 0.03166099 3.262 0.0012 BATHS 0.109587 0.02678655 4.091 0.0001 NOHEAT  0.099710 0.04189498  2.380 0.0178 FIRE 0.117428 0.03516537 3.339 0.0009 SQFT 0.000264 0.00004262 6.193 0.0001 SPECIAL 0.123980 0.05349404 2.318 0.0210 SOUND100 0.294474 0.07076478 4.161 0.0001 PECON100 0.671739 0.30810728 2.180 0.0299 ONROAD  0.176308 0.06582347  2.678 0.0077 FARMDISTANCE 0.000017320 0.00000374 4.625 0.0001 ONFARM  0.142932 0.07661228  1.866 0.0629 WETLAND 0.002729 0.00181653 1.502 0.1339 LARGEZONE 0.154045 0.06636055 2.321 0.0208 OPENSPACE 0.120691 0.07154488 1.687 0.0925 31 IV. OUTDOOR RECREATIONAL USES AND USE VALUES IN THE PES IV. A. INTRODUCTION This chapter presents results of EAI's study of outdoor recreational uses and use values for the Peconic Estuary System (" PES"). The information presented includes: ( 1) a review of participation and location choice for key recreational uses, and ( 2) estimates of the economic value of those uses. Also presented is a summary of expenditures at PES farm stands, wineries, and rental housing, data that was identified as a gap in EAI's Phase I study and is of interest to decision makers.

The main tool for providing information for this analysis is a recreational use survey carried out in August, 1995. The recreational survey was designed to:

identify key outdoor recreational activities and locations in the PES estimate the level of participation in key recreational activities identify key characteristics and preferences of users estimate the value of recreational uses of the PES fill data gaps identified in the Phase I study.

Key recreational uses and locations. More than 15 recreational uses of the PES were identified through focus groups and discussions with local citizens and officials. One key component of the recreational use survey is to assess where these recreational uses take place throughout the PES.

Participation in key recreational uses. EAI's Phase I study ( Diamantides and Grigalunas, 1996) estimated participation in only a few key recreational uses, using " off the shelf" information. Phase I also identified many data gaps concerning participation rates and values for outdoor recreation in the PES. The Phase II recreational survey is designed to fill these data gaps.

Characteristics and preferences of users. Prior to the recreational use survey, only anecdotal information existed concerning recreational users of the PES. Information, such as residency, accommodations, recreational preferences, etc., are provided by EAI's Phase II recreational survey.

Recreational use values. Data from the Phase II recreational survey is used to estimate the economic value of key recreational activities in the PES and, when possible, to estimate the change in recreational value resulting from changes in water quality.

Phase I economic impact data gaps. Key data gaps identified in the Phase I study include the economic impact of specialized sectors of the local economy. These sectors include: summer rentals, winery tours and sales, and farm stand sales. Each of these sectors was identified by local citizens and officials as playing an important, but unquantified role, in the local economy. Economic data for these sectors sales is presented in this report. 7Hunting was not included in the occasion specific questioning, due to the time of year and anticipated low participation.

32 IV. B. IDENTIFICATION OF RECREATIONAL USES AND LOCATIONS Outdoor recreation is a major activity in the PES. Based on recreational uses identified during the survey development process ( see Sec. C, Survey Development), the survey questionnaire included 16 major natural resource based recreational uses. Of these, eight key recreational activities were identified:

Fishing Boating Swimming Shell fishing Beach Use Bird Watching Wildlife Viewing Hunting Data were collected for these eight key recreational uses, including annual participation during the past year. Detailed information also was obtained on these activities for the respondent's most recent recreational outing to the East End.

Annual participation data on key recreational activities include the number of times the respondent had done each activity at specific East End locations during that year ( 1995). The survey instrument identified eight water bodies as potential locations for fishing, boating, swimming, and Shell fishing. The eight locations identified by water body are:

Flanders Bay Great Peconic Bay Little Peconic Bay Shelter Island Sound Gardiners Bay Block Island Sound Long Island Sound Atlantic Ocean.

Locations for the remaining key recreational activities ( beach use, bird watching, wildlife viewing, and hunting) were categorized by the town in which the activity took place. Five East End towns were identified by the survey instrument. The five recreation locations identified by town are:

East Hampton Riverhead Shelter Island Southampton. Southold.

Single day data on key recreational activities include information on activities the respondent participated in during their most recent recreation day at the East End. This question was followed by occasion specific, write in questions concerning the: ( 1) location of the activity, ( 2) perceived water quality, ( 3) number of people in the recreation party, ( 4) travel time, and ( 5) time on site. Other activity specific data collected included fishing catch, shellfish harvest, choice of marina or ramp, perception of beach facility quality, and number of birds or type of wildlife sighted7. 33 IV. C. SURVEY DEVELOPMENT AND IMPLEMENTATION The development and implementation of the recreational use survey parallels the development and implementation of the resource survey. Meetings, interviews, and focus groups were instrumental in the development of both surveys. Similarly, implementation of the two surveys occured at the same time and places using the same survey staff. Only significant aspects of the development of the recreational survey that differ from the resource survey will be discussed here. For a full discussion of the resource survey development and implementation including similarities with the recreational survey ( see Chapter VI, Resource Value Survey).

A major challenge in the development of the recreational use survey was the creation of a question format. A single instrument was selected to cover all the major recreational uses and locations of the PES. The single instrument format allowed collection of data for multiple current and past uses and was a much easier, and less costly, method for acquiring data, an important issue given realistic limits on budgets for this project.

Questionnaire development began with meetings with the Management Committee, the Citizen's advisory group, and " expert informants" from major stakeholder groups, such as marina operators and Baymen. Based on issues raised by the three groups, questionnaire development then proceeded with informal interviews with the public, focus groups, and pretests in order to determine the most relevant questions, wording of questions, and survey presentation.

Informal interviews with the public were a critical component of questionnaire development. From these interviews we gained insight into who the users are and their perspective on recreation in the PES. For example, during these interviews, it became apparent that many recreational users did not think in terms of the PES as an estuary system. Instead individuals more easily identified the East End or individual bays within the PES as geographic entities. The questionnaire, therefore, asks about recreational uses at locations at the East End with which individuals could easily identify.

Focus groups and pretests were used to hone the questionnaire down to an efficient presentation that would allow us to collect all the required data. For example, one issue we used focus groups to refine was the questionnaire's approach to eliciting water quality perceptions. Originally we had hoped to use the questionnaire to ask very specific water quality questions, such as clarity, smell, debris, etc., so that we might be able to estimate the contribution of these different attributes to an individual's overall perception of water quality. However, during focus groups we found that recreational users can have very complex and inconsistent ways of assessing water quality, which include numerous additional attributes such as beach condition, signs, and plant abundance. Eliciting information on all of these attributes became too cumbersome, and a more simplified approach was eventually used. The simplified approach asks the respondent to rank water quality at the site on a four point scale from " excellent" to " poor". As is described below, this approach worked satisfactorily in that we found a statistical association between respondents' subjective estimates of water quality and objective measures of water quality based on field sampling undertaken by the County. 34 A key objective in the survey development phase was to keep the questioning simple and consistent across uses. Many versions of the recreational use survey were pretested, to assess the ease with which respondents could understand and answer the questions. The survey pretests were instrumental in reducing the size of the questionnaire. One of our concerns was that if the questionnaire was too long, only the first few questions would be answered, or respondents would only answer selected questions. Another important concern was that the survey be clear and relatively brief in order to allow us to use an intercept survey, self administration approach, to economize on scarce research funds. The final version of the recreational use survey questionnaire is available from the authors.

The recreational use survey and the resource use survey were implemented simultaneously during the week of August 22 29, 1995, in pre selected, public places in each of the five East End towns. Interviewers solicited potential respondents by simply approaching them and asking if they would be willing to spend 10 15 minutes filling out a survey to be used to help develop a plan to protect and manage the bays. Survey locations included beaches, shopping areas, libraries, Post Offices, and miscellaneous public places throughout the study area.

Other natural resource based recreational activities were identified in the survey development process. These activities include: walking/ hiking, biking, sightseeing, jet skiing, jogging, windsurfing, art work, and photography. Questions on these activities were retained in the questionnaire for comprehensiveness. However, these activities are considered less significant than the key activities identified above, and data collected on these " non key" activities are limited to a single question on participation.

IV. D. DESCRIPTION OF THE RECREATIONAL USE SURVEY QUESTIONNAIRE The survey booklet cover provides a map of the East End to orient respondents. The first set of questions asks whether the respondent is an East End resident, owns a second home in the East End, or is a visitor. Visitors are also asked the mode of transportation they used to travel to the East End and the type of accommodations used, if any.

Subsequent questions address the issue of Brown Tide (" BT"). BT refers to the discoloration of the waters in and around the PES due to an algae that sporadically grows in enormous numbers. Recent incidents of BT may have contributed to a significant decline in ecologically productive eelgrass beds and caused major disruptions in the formerly valuable scallop industry. BT also was a significant concern to recreationists, as described in some detail later.

Throughout the survey development process, the issue of BT repeatedly surfaced. Questions concerning the BT were placed in the beginning of the questionnaire in part to diffuse this issue early on, allowing respondents to focus on the questions that follow. We asked respondents whether they were aware of BT and which, if any, of their recreational activities were affected by BT.

The next set of questions asked respondents to indicate their annual participation in key recreational 35 activities by filling out two brief charts. One chart identified recreation locations by water body. The other chart identified recreation locations by town. Respondents indicated the number of times that they did each activity in each location during the past year ( 1995).

The annual participation questions were followed by single day recreation activity questions. Respondents were asked to identify their most recent recreation day at the east End. They then were asked to identify all the recreational activities participated during that day. Shell fishing, swimming and beach use, boat use, fishing, bird watching, and wildlife viewing were selected as key activities. For each of these recreational pursuits, a separate page of questions asked for activity specific information. Activity specific questions included: location, travel distance, time on site, number of people in the party, catch or harvest, and water quality and site quality ratings.

After the participation questions, respondents were asked about selected expenditures made at the East End during the past twelve months. As noted, these questions were designed to fill data gaps in the Phase I study for farm stands, wineries, and housing rentals. Residents and second home owners were also asked a referendum type question about their willingness to support selected water quality initiatives ( see section on water quality initiative referendum). Finally, a. set of questions was asked in order to obtain socio demographic data, such as residency, household status, income, age, education, and employment status.

IV. E. DESCRIPTIVE RESULTS: DEMOGRAPHICS A total of 1,354 respondents provided usable survey questionnaires, although not every respondent answered all questions. Selected, major demographic results of the survey are summarized as follows:

Residents and second homeowners from all East End towns were represented in the sample A majority ( 59 %) of respondents were visitors to the East End Most visitors ( 76%) came from either Long Island or New York City Most visitors ( 60 %) stayed at the East End overnight The most common overnight accommodation was with friends or relatives ( 39%) Compared to 1990 Census data, the sample has a slightly higher share of women and people in the middle age groups; is better educated; and is wealthier than the resident population.

Residency Status. Of the 1,267 respondents who provided this information, over half of those responding ( 59%) were visitors from outside the East End ( Table IV. 1). Of the remainder, 28% indicated that their primary residence was at one of the five East End towns, and 13% owned a second home at the East End, but had a primary residence somewhere else. Some Brookhaven residents considered themselves East End residents but were not counted as such in this study.

Residents and Second Home Owners  Place of Residency. Residents and second home owners from each of the five East End towns were represented in the survey sample. Southampton ( 30%) and Southold ( 28%) had the largest percentages of resident respondents. The remainder was 36 closely distributed among Shelter Island ( 16%), East Hampton ( 14%), and Riverhead ( 12%). The relatively high proportion of Shelter Island resident respondents is not expected to have a significant effect on survey results.

Table IV. 1  Residency Status of Survey Respondents Residency Number of Respondents Percentage of all Respondents East End Residents 358 28%

Second Home Owners 159 13%

Visitors 750 59%

Total 1267 100%

For second home owners, New York City was the dominant primary place of residence ( 45 % of second home owners surveyed), followed by Nassau ( 19 %) and Suffolk counties ( 14 %). Other locations, largely distributed across Westchester and Rockland counties in New York and northeastern New Jersey, were the primary residences of the remaining 22%.

Visitors  Place of Residency. Visitors to the East End predominately came from Long Island and New York City. 40% of visitors came from Suffolk county, 20% came from New York City, and 16% from Nassau county. Only 8% came from other locations in New York State and New Jersey, and just 5% came from Connecticut and Massachusetts. Other locations, such as Florida, California, and several foreign countries accounted for the primary residences of the remaining 11%.

Visitor Classification and Accommodations. Most visitors in our sample ( 60%) were overnight visitors. Day trippers ( those who returned to a home outside the East End at the end of the day) accounted for 39% of visitors surveyed.

Of the 700 overnight visitors who provided accommodation information, the most common ( 39%) type of accommodation was with friends or relatives. Rental ( 24%) and hotel or motel ( 22%) accommodations were closely matched. Surprisingly, 15% of overnight visitors to the East End reported that they stayed at accommodations other than friends or relatives, hotels or motels, or rental properties. Presumably these other accommodations are predominately boats and camp sites.

Sample characteristics: comparison with resident census data. Gender, age, education, and income characteristics of survey respondents can be compared to the characteristics of the resident population as identified by the most recent ( 1990) census. Only comparisons to the resident population are possible, since characteristics of the second homeowner and visitor populations are unknown. 37 For all residency and visitor categories, the share of female respondents was only slightly more than in the resident population. The age distribution of the sample reflects the survey implementation practice of not including individuals less than 18 years of age.

Our survey sample is much more educated than the resident population. For example, census data indicates that 49% of the resident population had some level of post secondary education. The same level of education was achieved by 80% of the resident sample, 95% of second homeowners, 91% of overnight visitors, and 82% of day trippers.

The survey sample also has higher household incomes than the resident population. According to the census, 34% of the resident population has a household income of $ 50,000 or more. However, nearly half ( 48%) the residents in the survey sample have household incomes of $ 50,000 or more, as do 80% of second homeowners, 64% of overnight visitors, and 59% of day trippers.

Sample characteristics: comparison among resident and visitor categories. The distribution among female and male respondents slightly favored females in all categories. Day trippers have the most respondents under 24 years of age ( 10%), and overnight visitors have the most respondents in the 25 44 age group ( 60%). Second homeowners have the largest percentage of 45 74 year olds ( 62%). Second homeowners are also the most highly educated ( 95% post secondary schooling) and have the highest incomes ( 80% above $ 50,000 household income).

Sample characteristics: East End Town of Residence. Residents and second home owners from Shelter Island and Southold were over represented in the survey sample, based on comparisons to year round and seasonal population statistics. Residents were under represented in Riverhead and Southampton. Second home owners were under represented slightly in East Hampton and also in Southampton. This disproportionate distribution of the sample most likely has little, if any, effect on survey results since the type and frequency of recreational activity is not strongly related to the East End town the respondent lives in. 38 Table IV. 2  Population Demographics vs. Survey Respondent Demographics 1990 Population Resident Sample Second Homewner Sample Overnight Visitor Sample Day tripper Sample Gender Female 51.83% 53.57% 54.67% 53.63% 55.34%

Male 48.17% 46.43% 45.33% 46.37% 44.66%

Age up to 20 23.89% 3.83% 3.36% 1.49% 2.76%

21 24 4.53% 1.91% 1.34% 4.95% 7.09%

25 34 16.23% 14.48% 8.72% 25.50% 22.83%

35 44 12.84% 21.86% 19.46% 34.65% 24.02%

45 54 11.01% 18.85% 30.87% 21.29% 20.87%

55 64 11.04% 13.39% 18.79% 8.42% 12.20%

65 74 11.17% 21.31% 12.08% 2.97% 7.87%

75 84 7.25% 3.83% 4.70% 0.50% 1.97%

85 and up 2.04% 0.55% 0.67% 0.25% 0.39% 39 Table IV. 2  Population Demographics vs. Survey Respondent Demographics, cont.

1990 Population Resident Sample Second Homewner Sample Overnight Visitor Sample Day tripper Sample Education < High School 7.44% 1.27% 0.00% 0.28% 0.46%

Some HS 11.55% 2.55% 0.77% 0.84% 2.78%

HS Grad. 31.77% 16.56% 4.62% 7.58% 14.35%

Some Coll. 18.35% 21.66% 13.85% 17.42% 26.39%

Assoc. Deg. 6.66% 12.74% 4.62% 7.30% 12.04%

Bachelor's Deg. 13.51% 21.97% 23.85% 29.78% 19.44%

Advanced Deg. 10.72% 23.25% 52.31% 36.80% 24.54%

Income <$ 15,000 19.17% 9.42% 1.57% 5.16% 3.70%

$ 15,000  $ 24,999 14.60% 12.01% 3.15% 4.01% 8.80%

$ 25,000  $ 34,999 14.40% 13.31% 5.51% 10.32% 8.33%

$ 35,000  $ 49,999 17.52% 17.53% 10.24% 16.62% 20.37%

$ 50,000  $ 74,999 18.90% 23.38% 13.39% 19.48% 26.85%

$ 75,000  $ 99,999 7.04% 11.36% 14.96% 11.75% 17.59%

$ 100,000  $ 149,999 4.93% 6.82% 18.11% 17.19% 9.26%

$ 150,000 and up 3.41% 6.17% 33.07% 15.47% 5.09% 40 IV. F. DESCRIPTIVE RESULTS: KEY RECREATION ACTIVITY PROFILE Respondents were asked the number of times that they performed each of the following outdoor recreational activities at various East End locations ( Bays and towns) this year ( 1995):

Activities: Fishing, Boating, Swimming, Shell fishing Locations: Flanders Bay, Great Peconic Bay, Little Peconic Bay, Shelter Island Sound, Gardiners Bay, Block Island Sound, Long Island Sound, and Atlantic Ocean Activities: Beach Use, Bird Watching, Wildlife Viewing, and Hunting Locations: East Hampton, Riverhead, Shelter Island, Southampton, and Southold.

The water bodies of the Peconic Estuary System are identified as Flanders Bay, Great Peconic Bay, Little Peconic Bay, Shelter Island Sound, and Gardiners Bay. Substitute water bodies included in the survey were Long Island Sound, Block Island Sound, and the Atlantic Ocean.

Swimming and beach use were treated as separate activities in the questionnaire in order to identify swimming locations by body of water and identify the number of beach goers by town. Since each of the five towns has multiple water body options for swimming, it was necessary to ask for location by both water body and town.

Figures for swimming and beach use should not be summed. This is because the activities are not mutually exclusive, and it is expected that most respondents gave a positive answer to both categories even though they may be referring to a single outing.

Major characteristics of respondents' annual recreational activity during the year are:

Most ( 83%) engaged in at least one key recreational activity, half in more than one activity. Most residents ( 95 %) participated in key recreational activities Swimming was the most popular activity The PES was the most popular swimming location ( 42% of all swimming trips) Boating, fishing, and Shell fishing were predominantly done in the PES.

Sample Participation Overall. Most respondents ( 83%) engaged in at least one outdoor recreational activity at the East End and during the past year averaged 38 recreational experiences per respondent. In total, respondents engaged in more than 48,400 outdoor recreational experiences during the past year. Of this number, more than 26,000 were water based outdoor recreational experiences, and the majority of these ( 15,506) were in the PES. Land based outdoor recreational experiences the five East End towns amounted to 22,300.

Sample Participation By Activity. Among all respondents, swimming and beach use were the most popular activities. Swimming was done on more than 15,000 occasions by respondents. The most popular area for swimming was the PES, which accounted for 42% of all swimming trips. More than 12,000 beach visits at the five East End towns were reported. 41 Shell fishing was the least frequent water based activity ( 1,304 trips). More than half ( 59%) of these Shell fishing trips took place in the PES. Hunting was the least popular land based activity ( 255 occasions). Note that bird watching and wildlife viewing responses given in Table IV. 3 were adjusted to include only trips for viewing, i. e., activity less than one mile from home was not included.

Table IV. 3  Participation in Key Recreation Activities  By Residency Status Residents ( n= 358) SHO ( n= 159) Overnight ( n= 427) Day trippers ( n= 273) Total ( n= 1217)

Fishing 88 ( 25%) 41 ( 26%) 62 ( 15%) 13 ( 5%) 204 ( 17%)

Boating 132 ( 37%) 63 ( 40%) 88 ( 21%) 39 ( 14%) 322 ( 26%)

Swimming 186 ( 52%) 80 ( 50%) 153 ( 36%) 28 ( 10%) 447 ( 37%)

Shell fishing 49 ( 14%) 19 ( 12%) 14 ( 3%) 6 ( 2%) 88 ( 7%)

Beach use 282 ( 79%) 103 ( 65%) 235 ( 55%) 74 ( 27%) 694 ( 57%)

Bird watching 36 ( 10%) 13 ( 8%) 23 ( 5%) 32 ( 12%) 104 ( 9%)

Wildlife viewing 73 ( 20%) 39 ( 17%) 45 ( 11%) 40 ( 15%) 185 ( 15%)

Hunting 10 ( 3%) 3 ( 2%) 6 ( 1%) 2 ( 1%) 21 ( 2%)

Any key activity* 342 ( 96%) 132 ( 83%) 287 ( 67%) 117 ( 43%) 878 ( 72%)

Multiple key activities 262 ( 73%) 103 ( 65%) 182 ( 43%) 65 ( 24%) 612 ( 50%)

* May include bird watching and wildlife viewing trips less than one mile from home.

Participation Rate Overall By Residency Status. East End residents are more likely to participate in outdoor recreation than any other group. Fully 95% of the residents surveyed engaged in at least one, key water based activity in the PES or one key land based activity in one of the East End towns. By comparison, 83% of second homeowners and 67% of overnight visitors also participated in outdoor recreation. Day trippers have the lowest rate of participation ( 43%).

A direct comparison between the number of people engaging in land based and water based activities cannot be made. This is due to the inability to tell the difference between beach use in the PES and beach use on the Atlantic Ocean or Long Island Sound shoreline at the East End. 42 However, the majority of residents ( 73%) and second home owners ( 65%) and 50% of all survey respondents engaged in more than one key recreational activity during the past year.

Participation Rate in Key Recreational Activities By Residency Status. Proportionately more residents ( 70%) and second homeowners ( 65%) swim, boat, fish, and shellfish than overnight visitors ( 45%) and day trippers ( 22%). Among these activities, the highest participation rates across all residency status categories are for swimming ( 37%) followed by boating ( 26%) and fishing ( 17%). Shell fishing is more popular with residents ( 14%) and second home owners ( 12%) as compared with the overall sample ( only 7 %).

Residents and second homeowners are more likely to go to the beach, watch birds, view wildlife, and hunt in the East End than other groups. Proportionately more residents ( 85%) and second homeowners ( 70%) engage in these activities than overnight visitors ( 59%) and day trippers ( 37%). Among these activities, the highest participation rates across all groups are for beach use ( 57%) followed by wildlife viewing ( 21%) and bird watching ( 19%). Only 2% of survey respondents hunt.

Location of Key Recreational Activities. Respondents used the PES more times ( 15,506 occasions) for all key outdoor recreation activities swimming, boating, fishing, and Shell fishing than any other water body at the East End ( Table IV. 4).

Table IV. 4  Water Body Selection by Activity  ( n= 1267)

Fishing Shell fishing Boating Swimming Totals Block Island Sd. 320 ( 6%) 71 ( 5%) 467 ( 5%) 380 ( 2%) 1238 ( 5%)

Long Island Sd. 1422 ( 25%) 266 ( 20%) 1760 ( 20%) 2801 ( 18%) 6249 ( 24%)

Atlantic Ocean 1125 ( 20%) 201 ( 15%) 1056 ( 12%) 5685 ( 37%) 7116 ( 27%)

PES 2732 ( 49%) 766 ( 59%) 5470 ( 62%) 6538 ( 42%) 15506 ( 60%)

Totals 5599 ( 100%) 1304 ( 100%) 8753 ( 100%) 15404 ( 100%) 26060 ( 100%) * Percentages may not sum precisely due to rounding No single town is the dominant site for all categories of recreation by respondents. For example, beach use occurs most often at Southampton ( 3334 occasions) and East Hampton ( 3139). Shelter Island was the most used for bird watching ( 567) and hunting ( 92), and East Hampton had the most 43 ( 1123) wildlife viewing experiences. On the other hand, Riverhead was the least used town for beach use ( 1075), bird watching ( 68), and wildlife viewing ( 220). Southampton had the least number of hunting occasions ( 26).

Table IV. 5  Town Selection by Activity  ( n= 1267)

Beach Use Bird Watching Wildlife Viewing Hunting Total Trips East Hampton 3139 ( 26%) 300 ( 20%) 1123 ( 29%) 50 ( 20%) 4612 ( 25%)

Riverhead 1075 ( 9%) 68 ( 5%) 220 ( 6%) 56 ( 22%) 1419 ( 7%)

Shelter Island 2461 ( 20%) 567 ( 37%) 1030 ( 27%) 92 ( 36%) 4150 ( 25%)

Southampton 3334 ( 27%) 386 ( 25%) 690 ( 18%) 26 ( 10%) 4436 ( 24%)

Southold 2239 ( 18%) 215 ( 14%) 764 ( 20%) 31 ( 12%) 3249 ( 18%)

Totals 12248 ( 100%) 1536 ( 100%) 3827 ( 100%) 255 ( 100%) 17866 ( 100)

* Percentages may not sum precisely due to rounding Location of PES Water Based Activities. Great Peconic Bay is the most popular water body in the PES for recreational activity, with 28% of recreational trips in the PES, while Flanders Bay is the least frequently used, with 8%. Great Peconic Bay is also the most popular location in the PES for swimming ( 30%), fishing ( 29%), and boating ( 25%). Gardiners Bay is the most popular PES location for Shell fishing, accounting for 33% of all PES Shell fishing trips. 44 Table IV. 6  PES Key Recreational Activity Outings  ( n= 1267)

Fishing Shell fishing Boating Swimming Totals Flanders Bay 288 ( 11%) 45 ( 6%) 562 ( 10%) 366 ( 6%) 1261 ( 8%)

Gt. Peconic Bay 793 ( 29%) 199 ( 26%) 1362 ( 25%) 1991 ( 30%) 4345 ( 28%)

Ltl. Peconic Bay 486 ( 18%) 109 ( 14%) 1021 ( 19%) 1298 ( 20%) 2914 ( 19%)

Shelter Isl. Sound 511 ( 19%) 158 ( 21%) 1321 ( 24%) 1410 ( 22%) 3400 ( 22%)

Gardiners Bay 654 ( 24%) 255 ( 33%) 1204 ( 22%) 1473 ( 23%) 3586 ( 23%)

Totals 2732 ( 100%) 766 ( 100%) 5470 ( 100%) 6538 ( 100%) 15506 ( 100%) * Percentages may not sum precisely due to rounding PES Key Recreational Activities by Residency Status. Swimming is the most popular waterbased activity in the PES for all residency groups and overall accounts for 42% of all water based recreation trips ( Table IV. 7). Boating is nearly as popular ( 36% of all PES trips).

Overnight visitors fish more ( 22% of their outdoor recreation activity) than any other group. Day trippers allocate a larger percentage of their PES trips to Shell fishing ( 16%) than to fishing ( 9%), although Shell fishing overall is a modest activity ( 5% of PES all trips).

Table IV. 7  PES Key Recreational Activity Outings by Residency Status  ( n= 1217)

Residents SHO Overnight Day tripper Total Fishing 1114 ( 17%) 401 ( 11%) 947 ( 22%) 30 ( 9%) 2492 ( 17%)

Boating 2354 ( 37%) 1275 ( 36%) 1450 ( 34%) 110 ( 34%) 5189 ( 36%)

Swimming 2520 ( 39%) 1676 ( 48%) 1839 ( 43%) 132 ( 41%) 6167 ( 42%)

Shell fishing 396 ( 6%) 154 ( 4%) 92 ( 2%) 52 ( 16%) 694 ( 5%)

Totals 6384 ( 100%) 3506 ( 100%) 4328 ( 100%) 324 ( 100%) 14542 ( 100%) * Percentages may not sum precisely due to rounding 45 Locations of PES Activities  By Residency Status. For residents, Shelter Island Sound ( 27%) is the most popular location in the PES, followed closely by Great Peconic Bay ( 25%) ( Table V. 8). Gardiners Bay ( 31%) is the most frequented destination for second home owners, with Great Peconic Bay ( 30%) again nearly as popular. Over night visitors and day trippers prefer Great Peconic Bay ( 30% and 34%, respectively) over all other locations.

Flanders Bay is by far the least often visited location for residents ( 7%), second home owners ( 3%), and overnight visitors ( 10%). The least visited location by day trippers is Gardiners Bay ( 13%), presumably because it is the furthest of the bays from their homes. Flanders Bay is more popular with day trippers ( 17%) than with any other group.

Table IV. 8  PES Key Recreational Activity Locations by Residency Status ( n= 1217)

Residents SHO Overnight Day tripper Total Flanders Bay 451 ( 7%) 114 ( 3%) 446 ( 10%) 54 ( 17%) 1065 ( 7%)

Gt. Peconic Bay 1589 ( 25%) 1048 ( 30%) 1304 ( 30%) 110 ( 34%) 4051 ( 28%)

Ltl. Peconic Bay 1260 ( 20%) 740 ( 21%) 736 ( 17%) 60 ( 19%) 2796 ( 19%)

Shelter Isl. Sound 1752 ( 27%) 525 ( 15%) 1031 ( 24%) 58 ( 18%) 3366 ( 23%)

Gardiners Bay 1332 ( 21%) 1079 ( 31%) 811 ( 19%) 42 ( 13%) 3264 ( 22%)

Total 6384 ( 100%) 3506 ( 100%) 4328 ( 100%) 324 ( 100%) 14542 ( 100%) * Percentages may not sum precisely due to rounding IV. G. DESCRIPTIVE RESULTS: PARTICIPATION AND TRIP ESTIMATES Introduction The total number of trips ( or " outings") for outdoor recreation is the product of three factors: ( 1) The potential number of participants, ( 2) the proportion who actually participate, and ( 3) the number of times those who participate engage in an recreation activity. Thus, we have:

Trips = No. of Potential Participants x Percent Participating x No. of Times Participate 8Day tripper are excluded because we have no reliable way of estimating the total number in this group. This omission slightly understates total participation in PES recreation ( see text).

46 For example, assume that there are 2 million potential participants ( i. e., residents, second home owners, over night visitors, and day trippers) for swimming, that 20 % of these actually swim, and that of these participants, each swims an average of 10 times per year. In this case, the number of swimming trips or outings is 4 million:

= 2 million x 20 % x 10 = 400,000 x 10 = 4 million trips The data and assumptions used to estimate trips for each PES recreation activity is explained below.

Estimation of Total Number of Trips. The population of potential participants include all East End residents, second homeowners, overnight visitors, and day trippers. To estimate this population, we used 1990 census data from the Long Island Regional Planning Board (" LIRPB"). The LIRPB analysis provides estimates of the year round resident population; the seasonal population, including second homeowners and guests; year round resident guests; and hotel, motel, and campsite capacities. The number of participants in each recreational activity was estimated separately for each of these residency category. The resident population over age 15 is estimated by the LIRPB to be 84,871.

Data are not available for the age breakdown of the seasonal population. Lacking authoritative data, we assume that the seasonal population has the same percentage over the age of 15 ( 80%) as the resident population. This implies an estimated seasonal population over age 15 of 135,620.

The seasonal population is split into two groups, based on EAI's recreational use survey results: Second Home Owners ( 27%) and Overnight Visitors ( 73%). Our survey results indicate that the two components of the seasonal population have different participation rates and therefore should be considered separately, when possible. Note that many overnight visitors stay with second homeowners and residents as renters or guests.

Population data is not available for day trippers; therefore this group is excluded from our participation estimates. The absence of this information will slightly understate outdoor recreation participation.

Information concerning the percent of potential participants that participates in one or more recreational activity was presented earlier. The trips per participant are given in Table IV. 9.

The major results of estimated annual participation in PES outdoor recreation ( excluding day trippers8) for 1995 can be summarized as follows: 47 127,762 people participate in either swimming, boating, fishing, or Shell fishing in the PES, taking 3.3 million outings.

156,184 people participated in either beach use, bird watching, wildlife viewing, or hunting in the East End towns, engaging in 5.2 million trips.

Table IV. 9  Average Annual Outings per Participant by Activity and Residence*

Residents SHO Overnight Day trippers Fishing 12.66 9.78 15.27 2.31 Boating 17.83 20.24 16.48 2.82 Swimming 13.55 20.95 12.02 4.71 Shell fishing 8.08 8.11 6.57 8.67 Beach Use 22.50 25.85 9.20 6.11 Bird Watching 37.55 23.49 8.83 3.28 Wildlife Viewing 34.36 25.39 9.99 3.80 Hunting 13.20 16.33 7.00 5.50 * Includes activities at the five East End towns and PES water bodies only The total number of trips by each group, for each activity, is estimated by multiplying the estimated number of trips per participant ( Table IV. 9) for each group ( i. e., residents, second homeowners, etc.) by the estimated total number of participants by group. The results are shown in Table IV. 10.

Overall, there are 5.15 million beach use, bird watching, wildlife viewing, and hunting outings taken in East End towns and 3.35 million swimming fishing, boating, and Shell fishing outings taken in the PES in 1995 ( Table IV. 10). Most outdoor recreational activity is accounted for by residents, who engaged in 3.3 million land based and 1.5 million water based occasions locally. Second homeowners took 1.1 million land based trips and more than 800 thousand water based trips. Overnight visitors engaged in more than 780 thousand land based, and 1 million water based, trips.

Total trip estimates slightly understate actual recreation trips because day tripper trip estimates are not included due to the lack of population data for this group, as noted earlier. According to EAI's recreational use survey, day trippers account for 3% of land based and 2% of water based recreational trips taken by the sample. 48 Comparison with Phase I Total Outdoor Recreational Trip Estimates: Introduction. The Phase I study ( Grigalunas and Diamantides, 1996) gave estimates of total recreation trips to the area for selected activities based on available " off the shelf" data and were comprised of a variety of sources. No original data was collected during Phase I. In Phase II original data was assembled and it is important to note and to explain the major differences between the two sets of results ( Table IV. 11).

Table IV. 10  Estimated Annual Key Recreation Activity Outings*

Residents SHO Overnight Totals Fishing 268,617 93,110 226,766 588,493 Boating 559,902 296,451 342,630 1,198,983 Swimming 598,001 383,563 428,406 1,409,970 Shell fishing 96,006 35,636 19,513 151,155 Beach Use 1,508,582 615,257 500,955 2,624,794 Bird Watching 219,008 32,139 41,699 292,846 Wildlife Viewing 174,861 39,218 40,392 254,471 Hunting 33,609 11,959 6,930 52,498 Totals 3,458,586 1,507,333 1,607,291 6,573,210 * Includes activities at the five East End towns and PES water bodies only In general, we found major that the Phase I estimates of recreational activity were understated in some cases, greatly understated as compared to the Phase II results. The major reason for the large differences in estimates between the Phase I and II reports can be explained as follows. Our survey based estimates find much high participation rates and trips per participant than the Phase I report, which used a state wide average for New York. For example, in Phase II for bird watching and wildlife viewing we found a high participation rate ( 19% for bird watching and 21% for wildlife viewing) for respondents and a large number of trips per participant ( 37.55 bird watching trips and 34.36 wildlife viewing trips for residents). The Phase I survey, in contrast, was based on NFWS statewide estimates for New York. These statewide participation rates ( 9.4%) and number of trips per participant ( 8.3) are very much lower than those found in the PES survey sample.

This major difference between the Phase I and Phase II results is not surprising ( at least in retrospect). Residents and seasonal visitors to the PES are attracted to the area precisely because they are interested in estuary related outdoor recreation. We thus would expect this group to be 49 much more interested in outdoor recreation than the general population of the state. Similar large differences between the Phase I and II results were found for other activities ( see Table IV. 11 and also see Appendix for details) and the same explanation seems relevant.

Table IV. 11  Comparison of Participation Estimates Phase I Versus Phase II PES  Phase II PES  Phase I*

Beach Use 2,624,794 NA**

Non Consumptive 547,317 91,713 Hunting 52,498 77,300 Fishing 588,493 113,589 Boating 1,198,983 NA Swimming 1,409,970 714,600 * Grigalunas and Diamantides ( 1996). ** NA = Not available IV. H. DESCRIPTIVE RESULTS: SELECTED EXPENDITURE ESTIMATES Introduction. During the early survey development phase of our work, members of the Citizens Advisory Committee and officials at the Suffolk County Dept. of Health Services expressed interest in our collecting information on sectors of the PES economy for which data are difficult to find using standard economic sources. Specific sectors of the economy targeted for special consideration were Farm Stands, Wineries, and Rental Lodging.

The survey questionnaire asked respondents to estimate the amount that their household spent at Farm stands and Wineries at the East End over the past year. Visitors also were asked whether they rented a house, condo, apartment, etc., at the East End over the past twelve months. Respondents who answered " yes" to this question were asked the length of the rental agreement and the amount they spent. Responses to these questions were given in 1995 dollars, summarized in Table IV. 12 and explained briefly below.

Population of Potential Participants. Expenditure data on Farm stands, Wineries, and Rental Lodging collected in this survey are household ( not per person) expenditures. The number of East End resident households ( 44,241) and seasonal households ( 29,183) are based on 1995 Long Island Lighting Company estimates. 50 The number of overnight visitor households cannot be adequately estimated with available data. LIRPB seasonal population estimates account for occupancy of some rental lodgings, such as hotels, motels, and campsites. However, this component of the population estimate does not account for turnover, i. e., the same rental lodgings will be used by an unknown number of overnight visitors over the course of a season. Estimating the number of overnight visitor households is further complicated by the large percentage of overnight visitors ( 39%) who indicated that they stayed with friends or relatives, which implies that some amount of their expenditures may be included in resident and seasonal household estimates. For these reasons, expenditures of overnight visitors are not estimated in this analysis. Still, the average annual expenditure for rental accommodations per household from our survey $ 5,400 make it evident that seasonal rentals are a major source of income for PES rental property owners and owners of hotels, motels, and inns.

Estimated Total Participation and Expenditures. Table IV. 13: Estimated Farm Stand and Winery Expenditures presents estimates ( in 1995 dollars) of participation and expenditures in these sectors for resident and seasonal households. Table IV. 13 also presents estimates of PES related expenditures in these sectors. PES related expenditures were estimated using the same seasonal adjustment ( 45 %) used in the Phase I Report to estimate the PES related impacts of tourism and recreation sectors. Total rental lodging expenditures could not be estimated due to incomplete information on the number of participants. 51 Table IV. 12  Survey Farm Stand, Winery, and Rental Lodging Expenditures ( 1995 dollars)*

Farm stand Winery Rentals Residents Participation 316 ( 88%) 114 ( 32%)

Total Expenditures $ 86,400 $ 20,871

Average Expenditures $ 273 $ 183

Second Home Owners Participation 131 ( 82%) 67 ( 42%)

Total Expenditures $ 48,122 $ 15,350

Average Expenditures $ 367 $ 229

Overnight Visitors Participation 225 ( 53%) 114 ( 27%) 103 ( 26%)

Total Expenditures $ 41,228 $ 18,360 $ 556,000 Average Expenditures $ 183 $ 161 $ 5,398 Day Trippers Participation 153 ( 56%) 94 ( 34%)

Total Expenditures $ 12,755 $ 9,121

Average Expenditures $ 83 $ 97

Totals Participation 825 ( 68%) 389 ( 32%) 103 ( 9%)

Total Expenditures $ 188,505 $ 63,702 $ 556,000 Average Expenditures $ 228 $ 164 $ 5,398 * Figures in parentheses indicate the percent who made such expenditures 52 Table IV. 13  Estimated PES Farm Stand and Winery Expenditures Farm stand Winery Residents Estimated Participating Households 38,932 14,157 Estimated Total Expenditures $ 10,628,436 $ 2,590,731 Estimated PES Related Expenditures $ 4,782,796 $ 1,165,829 Second Home Owners Estimated Participating Households 23,929 12,256 Estimated Total Expenditures $ 8,781,943 $ 2,806,624 Estimated PES Related Expenditures $ 3,951,874 $ 1,262,981 Totals Estimated Participating Households 62,861 26,413 Estimated Total Expenditures $ 19,410,379 $ 5,397,355 Estimated PES Related Expenditures $ 8,734,671 $ 2,428810 An interesting finding is that PES related Farm stand expenditures are greater than earlier estimates for several other food related sectors presented in the Phase I Report. For example, PESrelated farm stand expenditures are greater than expenditures ( in 1995 dollars) in Meat and Fish Markets ($ 6.5 million), Fruit and Vegetable Markets ($ 3.8 million), Retail Bakeries ($ 2.9 million), and Drinking Establishments ($ 6.0 million) ( Grigalunas and Diamantides, 1996). 53 IV. I. DESCRIPTIVE RESULTS: REFERENDA AND BROWN TIDE RESULTS IV. I. 1. Hypothetical Referenda Introduction. One section of the recreational use survey posed referendum type policy questions to East End residents and second home owners. These questions were added to " test the waters" on selected policy issues and were not designed as a basis for resource valuation, which would have required considerably more effort and data than was possible for this project.

Referenda Questions. The referenda questions focus on four policy actions:

( 1) reseeding scallops following Brown Tide,

( 2) planting hard clams,

( 3) upgrading the Riverhead sewage treatment plant, and ( 4) reducing road runoff.

Respondents were presented with one of these programs and were asked whether they support the program, if they had to pay a given annual cost. Annual costs were varied for each of the proposed policy actions as described in Table IV. 14.

Referenda Results. Respondents overwhelmingly supported the policy actions and indicated a willingness to pay the annual costs. Support ranged from a high of 100% for reseeding scallops following Brown Tide at an annual cost of $ 10, to a low of 75% for upgrading the Riverhead sewage treatment plant at an annual cost of $ 100. This high level of support for PES management programs was consistent across residents and second home owners. Overall, 87% of respondents indicated they support the policy actions at the given costs ( Table IV. 14).

IV. I. 2. Descriptive Results: Effects of Brown Tide Respondents were asked whether they had heard of Brown Tide (" BT"). Those who had heard of BT were asked about their level of concern and about any activities that may have been affected by BT. Overall, most respondents ( 83%) had heard of BT, and of those, most ( 71%) were also very concerned ( Table IV. 15).

BT had the biggest effect on swimming. Fifty eight percent of those who had heard of BT indicated that it had affected their swimming. Recreational fishing ( 34 percent) and shell fishing ( 33 percent) also were affected by BT.

Residents and second home owners had the most knowledge of and the highest concern for BT. Overnight visitors had the least knowledge and indicated that their activities were affected the least. 54 Table IV. 14. Management Action Referenda Results Proposal; Annual Cost Resident s Y/ N SHO Y/ N Total s Y/ N Total % Yes Reseed Scallops Following Brown Tide; $ 5 21/ 2 6/ 0 27/ 2 93%

Reseed Scallops Following Brown Tide; $ 10 14/ 0 10/ 0 24/ 0 100%

Reseed Scallops Following Brown Tide; $ 25 17/ 2 5/ 1 22/ 3 88%

Plant Hard Clams; $ 5 21/ 4 12/ 0 33/ 4 89%

Plant Hard Clams; $ 10 18/ 3 5/ 0 23/ 3 88%

Plant Hard Clams; $ 25 14/ 2 2/ 2 16/ 4 80%

Upgrade Riverhead Sewage Treatment Plant;$ 5 16/ 2 6/ 0 22/ 2 92%

Upgrade Riverhead Sewage Treatment Plant;$ 25 18/ 3 9/ 1 27/ 4 87%

Upgrade Riverhead Sewage Treatment Plant;$ 50 15/ 4 6/ 0 21/ 4 84%

Upgrade Riverhead Sewage Treatment Plant;$ 100 73/ 28 30/ 6 103/ 34 75%

Reduce Road Run Off; $ 10 19/ 1 11/ 0 30/ 1 97%

Reduce Road Run Off; $ 25 22/ 1 15/ 1 37/ 2 95%

Reduce Road Run Off; $ 50 22/ 1 6/ 0 28/ 1 97%

Totals 290/ 53 123/ 11 413/ 64 87% 55 Table IV. 15 Awareness of Brown Tide Second Overnight Day Residents Home Owners Visitors Trippers Total Heard of Brown 370 159 279 202 1010 97.11% 91.91% 67.72% 78.29% 82.52%

Have NOT Heard of 11 14 133 56 214 Brown Tide 2.89% 8.09% 32.28% 21.71% 17.48%

Very Concerned 295 113 174 131 713 about Brown Tide* 80.16% 71.52% 62.37% 65.17% 70.87%

A Little Concerned 70 44 100 64 278 about Brown Tide* 19.02% 27.85% 35.84% 31.84% 27.63%

NOT Concerned 3 1 5 6 15 about Brown Tide* 0.82% 0.63% 1.79% 2.99% 1.49% * Includes only respondents who have heard of Brown Tide 56 Table IV. 16. Activities Affected By Brown Tide Second Resident s Home Owners Overnght Visitors Day Trippers Total Swimming 224 98 151 118 591 60.54% 61.64% 54.12% 58.42% 58.51% Fishing 148 49 82 69 348 40.00% 30.82% 29.39% 34.16% 34.46% Shell fishing 168 52 62 58 340 45.41% 32.70% 22.22% 28.71% 33.66% Boating 72 30 43 37 182 19.46% 18.87% 15.41% 18.32% 18.02% Other 32 13 20 10 75 8.65% 8.18% 7.17% 4.95% 7.43% * Includes only respondents who have heard of Brown Tide IV. J. ESTIMATES OF THE ECONOMIC VALUE OF RECREATION IV. J. 1. Introduction Our intention was to use data from the recreational survey to assess the use value for many waterbased and shore based recreational activities. The survey collected activity specific data on fishing, Shell fishing, boating, and swimming in the PES and surrounding waters. Information also was collected on beach use, birdwatching, wildlife viewing, and hunting in the five PES towns.

Unfortunately, the total number of surveys was limited to 1,354 completed responses due to budgetary reasons. The number of completed responses for each activity was the limiting factor in assessing which activities could be valued. Values were estimated for primary activities of interest: swimming, fishing, boating, and for birdwatching and wildlife viewing ( the last two of which were combined into one activity). However, the number of responses was insufficient to estimate the value of Shell fishing and hunting. Beach use was not valued separately from swimming.

Swimming is the most popular activity, and swimming and recreational fishing are the activities most directly affected by water quality and hence by management actions aimed at enhancing water 9This contrasts with policy actions to replant shellfish or to stock fish, the latter of which is often done in fresh water to enhance recreational fishing. In these cases, it may be easier to link a policy to a change in catch rate and hence to benefits.

57 quality ( e. g., Table IV. 15) For this reason, swimming is a focus of our efforts to estimates the benefits of management actions in terms of changes in swimming values. We recognize that participation in, and the economic value of, all activities depends upon the quality of the experience. For example, substantial research on recreational fishing, including the results of this study, shows the importance of the quality of the experience the catch rate on the number of trips and their economic value ( e. g., Freeman, 1995; McConnell and Strand, 1994). However, establishing the necessary cause and effect scientific links between policies to preserve or restore habitat, for example, with changes in salt water recreational catch rates appears to be beyond the state of the art9. Nevertheless, we can simulate how benefits to recreation fishing would change if the catch rate increased by, say, 10 percent.

Individual recreation trip value estimates and annual aggregate value estimates are given for three cases. First, we present the existing (" baseline") conditions for swimming, fishing, boating, and for birdwatching and wildlife viewing. For the baseline, we show consumer surplus per trip, total estimated number of trips in 1995, and total benefits for the year for the four key recreation activities studied.

Second, we show how economic value for swimming changes for illustrative, hypothetical policies affecting water quality. One such policy is assumed to increase water quality by 10 percent in each of the five PES bays. We also simulate a 20 percent uniform improvement in water quality for comparative purposes. Finally, a 10 percent improvement in the recreational fishing catch rate is simulated.

IV. J. 2. Methodology Value estimates for each activity are derived using the Travel Cost method of valuation ( see, for example, Freeman, 1993). The rationale behind this methodology is that, although there is no market price that reveals the value of a recreational activity, an implicit price can be observed through the cost of traveling to the activity's location. Included in this implicit price is the cost of transportation, such as gas, wear and tear on the automobile, etc., and the value of the individual's travel time. In theory, an individual's opportunity cost is valued as his or her next best use of their time. However, a fraction of the individual's wage is generally used, in practice, to represent income foregone in favor of recreation.

In the travel cost model, the number of trips a person takes for recreation at a specific site depends on the costs of getting to that site, the comparative costs of getting to substitute sites, and the quality of the recreational experience at the sites. In other words, the cheaper it is to get to a site, the cheaper travel to that site is relative to other sites, and the better the quality of the recreational experience at that site, the more times the individual will visit that site, all else equal. Thus, observed recreation choices reveal tradeoffs between cost of participation, as measured by travel 10We note that a water quality model developed by Tetra Tech of Fairfax, VA for the PES Program will estimate water quality changes in each of the bays due to proposed program policies.

58 cost, and participation rates. In addition, participants might reveal values for site quality by participating more at sites of higher quality, and less at sites of lower quality, all else being the same.