Hampton Beach Master Plan: Appendices

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Appendices

 

Appendix I: Natural Heritage Inventory

The table documents known occurrences of rare species and exemplary natural communities within the Hampton Beach Master Plan project area based on historical (pre-1980’s) as well as recent reports. Also included are non-ranked communities, indicating rare and/or good examples, that have not yet been designated a state rank.

 

Table A1. New Hampshire Natural Heritage Inventory

Name – Occurrence #

Listing Status

Conservation Rank

 

Federal

State

Global

State

Natural Community

 

 

 

 

SNE Coastal Dune Community

-

-

Rare or uncommon (G3)

Critically imperiled (S1)

Brackish marsh

  • Low graminoid brackish marshes
  • Robust forb brackish marshes

-

-

-

Critically imperiled (S1)

Coastal shoreline/strand/swale

-

-

-

Imperiled (S2)

Dry Appalachian oak-hickory forest

-

-

Secure (G5)

Critically Imperiled (S1S3)

Rare or uncommon

Low salt marsh

-

-

-

Rare or uncommon (S3)

High salt marsh

  • Triglochin (forb) panes
  • Salt marsh mosquito panes
  • Ruppia/marsh minnow deepwater

panes/ pools/ ditches

-

-

-

Rare or uncommon (S3)

Saline/brackish subtidal channel/bay bottom communities

-

-

-

Rare or uncommon (S3)

Undifferentiated saline/brackish subtidal

channel/bay bottoms

-

-

-

 

Tidal creek bottoms

-

-

-

 

Saline/brackish intertidal flat

-

-

-

Rare or uncommon (S3)

Table A1 (continued)

Name – Occurrence #

Listing Status

Conservation Rank

 

Federal

State

Global

State

Plant Species

       

Beach Grass (Ammophila breviligulata)

-

-

Secure (G5)

Rare or uncommon (S8)

Cinna-Like Reed Bent-Grass (Calamagrostis cinnoides)

-

-

Secure (G5)

Critically imperiled (S1)

Dwart Glasswort (Salicornia bigelovii)

-

Threatened

Secure (G5)

Imperiled (S2)

Gray’s Umbrella-sedge (Cyperus grayi)

-

Endangered

Secure (G5)

Critically imperiled (S1)

Hairy Hudsonia (Hudsonia tornentosa)

-

Threatened

Secure (G5)

Critically imperiled (S1)

Perennial Glasswort (Salicornia virginica)

-

Threatened

Secure (G5)

Critically imperiled (S1)

Robust knotweek (Polygonum robuslius)

-

Threatened

Apparently secure (G4)

Imperiled (S2)

Salt-Marsh Gerardia (Agalinis maritime)

-

Threatened

Secure (G5)

Imperiled (S2)

Sand Drop-Seed (Sporobokis cryplandrus)

-

Threatened

Secure (G5)

Imperiled (S2)

Sea-Beach Needlegrass (Aristida tuberculosa)

-

Endangered

Secure (G5)

Critically imperiled (S1)

Small Spike-Rush (Eleocharis parvula)

-

Threatened

Secure (G5)

Critically imperiled (S1)

Tall Wormwood (Arternisia campestris ssp caudata)

-

Threatened

Secure (T5)

Imperiled (S2)

Vertebrates Species

 

 

 

 

Arctic Tern (Stema paradisaea)

-

Threatened

Secure (G5)

No specific locations known (SZ)

Coomon Tern (Sterna hirundo)

-

Endangered

Secure (G5)

Critically imperiled (S1)

Horned Lark (Eremophila atpestris)

-

-

Secure (G5)

Rare or uncommon (S3)

Piping Plover (Charadrius melodus)

L

Endangered

Rare or uncommon(G3)

Critically imperiled (S1)

Source: Ecological Assessment of Selected Towns in New Hampshire’s Coastal Zone, Nichols 2000.

Appendix II. Consolidated Budget for Hampton Beach

This table provides a consolidated state budget for Hampton Beach. A summary on the operations and budget is discussed in Section III.F State Park System.

Table A2: State Park Budget for Hampton Beach

State Park Budget for Hampton Beach

 

Appendix III. Fiscal Impact Analysis

Introduction

Economic Research Associates (ERA) has provided two responses to the fiscal impact issues in the Town of Hampton relating to Hampton Beach. They also reflect concerns about the fiscal impacts of new housing development and other proposed changes in Hampton Beach.

  1. The first is a sensitivity model of the net fiscal impact of housing in the Town of Hampton. This model first examines the Town budget and the characteristics of residents and employees in order to understand the relationships between revenues and expenditures. It then concludes with illustrations of the net fiscal impact of different types of housing units.
  2. The second is a brief review of how the conversion of seasonal resort areas into year-round communities affects property values and tax collection.

 

Sensitivity Analysis of Fiscal Impact

The sensitivity analysis was conducted to determine the relative impact of new housing development on the budget of the Town of Hampton. Many of the inputs for this analysis originated from the Town’s 2000 Annual Report. Others are based on assumptions made by ERA based on our national experience with fiscal impact and growth issues. ERA’s overall approach to this analysis was to model the effects on the Town budget of three different types of housing: single-family, multi-family, and retirement. The key variable among these housing types is the average number of school-age children per housing unit. This issue is discussed in more detail below.

The first step in this analysis was to review the Town budget and financial statements from its Annual Report. From this review, ERA determined the total amount of revenues collected and funds expended annually by the Town of Hampton, as well as applicable property tax rates and spending per student in Town public schools. In order to provide the most accurate calculation of the impact of new development, revenues and expenditures were each split into two separate categories. For both sides of the balance sheet, a category represents a directly measurable line item, and the remainder represents revenues and expenditures that cannot be accurately measured without more detailed information.

The two categories of directly attributable factors are real property taxes (revenue side) and school expenditures (cost side). Real property taxes can be easily measured by applying the Town’s property tax rate to the input values of homes. School spending can be measured by applying the per student spending figure of $6,778.62 for Hampton (as reported by the New Hampshire Department of Education) to the number of new students generated by new housing units. In fiscal year 2000, all non-property tax revenues (including state education aid) totaled $14.3 million, and all non-school expenditures totaled $17.0 million.

For all other revenue and expenditure data, ERA used the per capita multiplier method, which establishes how much the Town receives and spends per person. In this case, "per person" not only includes the Town’s permanent residents; it also encompasses seasonal residents and those who work in Hampton, as these people also produce revenues and expenditures for the Town. As a result, it was necessary to calculate the number of "resident equivalents" in the Town of Hampton; i.e., the effective number of people who produce non-property tax revenues and generate demand for non-school public expenditures.

Calculating resident equivalent factors necessitated examining the behavior of four different types of users in order to determine what percentage of the 8,736 hours in a year each type spends as "residents" of the Town. To do this, each day during the year was divided into three eight-hour occupancy units, resulting in a total of 1,092 occupancy units per year, and a series of calculations were done to measure how many of these occupancy units are consumed by each user type. The four types of users and their occupancy characteristics are described below.

  1. Residents in Labor Force – This group lives in Hampton, and its members are therefore considered Town residents for two of three occupancy units per workday, and all three per weekend day, or 832 of the 1,092 annual occupancy units. These people may also be employed in the Town, but if they are, they are counted in the Persons Employed in Town category.
  2. Residents not in Labor Force – This group lives in Hampton and, since its members do not work, is assumed to spend all 1,092 annual occupancy units as residents of the Town.
  3. Seasonal Residents – This group’s members behave just like the Residents not in Labor Force group, but they are only part-year residents. It is assumed that, on average, these residents spend about 30 percent of the year in Hampton, or 328 of the annual occupancy units.
  4. Persons Employed in Town – Persons employed in Hampton spend one annual occupancy unit per workday in the Town, which translates to 260 for the whole year.

The resident population of the Town of Hampton was estimated in 1999 at 13,496. From the 1990 Census, it is known that about 55 percent of Hampton’s residents were in the local labor force, so applying this figure to the total population produces an estimate that 7,423 residents are in the labor force and the remaining 6,073 are not. For seasonal residents, no accurate count is available, but an estimate was made by applying the 1990 Census figure of seasonal housing units as a percent of total units to the Town’s total population. This results in an estimated seasonal population figure of 5,398. For employees, the State of New Hampshire reported a monthly average of 7,120 employees in Hampton in its most recent year-end data.

Adjusting all of these populations by the resident equivalency factors from above, the total resident equivalent population of the Town of Hampton is estimated at 19,744. This figure was then applied to the non-specific budget line item totals from above to determine the amount of non-property tax revenue and non-school expenditures generated by each resident equivalent. These totals came to $724.45 in non-property tax revenue and $861.46 in non-school expenditures per resident equivalent.

Next, a measure of resident equivalents per housing units needed to be determined, as the fiscal impact analysis approach was to assess the impact of each new unit. Dividing the resident equivalent figure of 19,744 by the Town’s total housing inventory of 9,258 units, the average number of resident equivalents per housing unit in the Town of Hampton is 2.13.

The only remaining inputs not defined are home value, which determines property tax revenue, and school-age children per housing unit, which determines school expenditures. Home value is addressed in the actual calculation of impacts; as the model is set up to show the net fiscal impact per housing units based on a range of values. School-age children are addressed by making assumptions about the average number of children per single-family, multi-family, and retirement home. ERA made the following assumptions:

  • Single-family homes: 0.75 students per housing unit
  • Multi-family homes: 0.40 students per housing unit
  • Retirement homes: 0 students

With all of the inputs set, the final step was to calculate the "breakeven" price for each type of housing unit. This signifies the home value at which the revenues produced equal the expenditures. These breakeven prices are:

  • Single-family homes: $340,950
  • Multi-family homes: $183,850
  • Retirement homes: $4,260

Clearly, whether or not a new home contains any school-age children has a tremendous influence on its net fiscal impact. Single-family homes, which are likely to have the most children, demand relatively high property values to overcome their fiscal costs. In contrast, retirement homes, which are assumed to have no schoolchildren, can produce positive impacts with relatively low property values, as new Town spending from these units is minimal.

 

Fiscal Effects of Shifting from Seasonal to Permanent Populations

The Town of Hampton expressed concern over the fiscal effects of recommended initiatives throughout the Master planning process. One of the economic initiatives suggested for Hampton Beach by ERA was to focus efforts on increasing the year-round population of the beach area. It is our understanding that this proposed strategy, while generally well received, raised concerns about the fiscal implications of such a shift.

ERA’s recognizes that these concerns are legitimate. Their analysis point out that a new house with just one school-age child would need to be worth over $450,000 to pay for itself in tax revenues. However, such an analysis only focuses on the residential development aspects of the economy. If Hampton Beach were to increase its year-round resident base, the Town of Hampton would likely experience more than just new housing—new retail and service businesses are likely to open to cater to these new residents, thus increasing commercial property values in the Town.

Beyond just the residents themselves and services created for them, making Hampton Beach more of a year-round area makes it potentially more desirable for high-tech businesses and other office users. Hampton Beach is located within a reasonable distance of major airports in Boston and Manchester (as well as Pease International Tradeport in Portsmouth), and has direct access to Interstate 95 and a wonderful natural environment. However, its perception as a seasonal beach getaway prevents it from capitalizing on many opportunities to build itself as a year-round business location.

Another aspect of increasing Hampton’s year-round appeal has to do with the types of residents it would draw. In ERA’s experience, the prime reason that seasonal resort areas evolve into year-round communities is retirement. Simply put, today’s summer beachgoer from Boston may well become tomorrow’s retiree who moves to Hampton Beach permanently. This phenomenon has begun to occur elsewhere in New England, notably on Cape Cod. Housing types also matter, as condominium or apartment developments are far more likely to draw empty nesters or retirees than families with children.

An interesting example of the above trends is Hull, Massachusetts. Hull, a historically seasonal beach town located on a narrow peninsula about 25 miles south of Boston, has experienced substantial year-round population growth over the past two decades due to suburban expansion from Boston to Hull. Transit improvements in the area, such as a commuter boat into Boston and plans for extension of a commuter rail line from Boston to neighboring Hingham, have aided Hull’s transformation.

The Town of Hull decided in the 1980s to focus its development strategies first on condominium units, and this strategy paid off, as few of the families who bought these units have school-age children. As demand continued to increase, prices of single-family housing in Hull rose dramatically, with the Town’s median sales price rising from $89,000 in 1994 to $200,000 in 2000. Hull’s profile as a destination has improved as well, and, in response, a new hotel was built in Hull for the first time in many years. Though Hull’s school system has grown substantially in recent years, the rise in property taxes has allowed the Town to build new schools and improve existing ones without raising its tax rates.

Hull provides a number of lessons that can be applied to Hampton Beach. In terms of transportation, the re-opening of the Amtrak line from Boston to Portland, while not a commuter line per se, will help improve transportation options along the New Hampshire Seacoast. Regarding housing, the type of housing developed will significantly shape the future character of beach area residents. Finally, in terms of education, the combination of rising home values and new commercial development allows school spending to increase without large tax increases.

Table A3. Net Fiscal Impact by Housing Type

Net Fiscal Impact by Housing Type

Source: Town of Hampton; New Hampshire Department of Education; Economics Research Associates.

 

 

Table A4. Town of Hampton Annual Budget and Revenues and Expenditures Per Resident Equivalent - Fiscal Year 2000

Town of Hampton Annual Budget and Revenues and Expenditures Per Resident Equivalent - Fiscal Year 2000

Source: Town of Hampton; Economics Research Associates

Table A5. Calculation of Resident Equivalents

Calculation of Resident Equivalents

1/ Estimate of labor force participation based on 1990 Census figures for Town of Hampton, which showed that about 55 percent of residents were in labor force.

2/ Estimate of seasonal population based on 1990 Census figures for Town of Hampton, which showed that about 40 percent of all housing units in the Town were vacant. Seasonal population is therefore estimated at 40 percent of total population.

Source: Town of Hampton; U.S. Bureau of the Census; Economics Research Associates.

 

Table A6. Inputs for Net Fiscal Impact by Housing Type

Inputs for Net Fiscal Impact by Housing Type

Source: Town of Hampton; New Hampshire Department of Education; Economic Research Associates.

Appendix IV. Proposed Cost Estimates for Major Hampton Beach Projects

This table provides a detailed cost estimate for major projects at Hampton Beach. An explanation and summary of costs are presented in Section V. Implementation.

Table A7. Detailed Cost Estimates for Major Project in Hampton Beach

Detailed Cost Estimates for Major Project in Hampton Beach

Table A7. (continued)

Detailed Cost Estimates for Major Project in Hampton Beach