Results Population Characteristics of Highlands Region s Municipalities

Transcription

1 2-3. Potential Changes and Resources at Risk Population Growth Introduction Since human land use is one of the major factor shaping the Highlands region, a better understanding of trends in human population and projected growth is critical. U.S. Census data for the years of 1990 and 2000 were analyzed to better understand the population and sociodemographic picture of the Highlands. Methods The population and socio-demographic analyses were performed using 1990 and 2000 data from the U.S. Census Bureau. These data were, and can be, downloaded from Two separate analyses were undertaken: 1) population trends of Highlands municipalities; and 2) socio-demographic trends in Highlands counties. The population trend data were compiled using municipal level data available from the U.S. Census Bureau. The socio-demographic data were compiled at a county scale due to the limited availability of the 2000 Census data at finer levels of resolution at the time of the study. It, therefore, includes data about the population of entire Highlands counties (not just Highlands municipalities). The counties include Dutchess, Orange, Putnam, Rockland and Westchester in New York and Bergen, Hunterdon, Morris, Passaic, Somerset, Sussex and Warren in New Jersey. Basic trends in the gender, age, racial make-up, and housing characteristics of the Highlands population were examined. Results Population Characteristics of Highlands Region s Municipalities The 2000 U.S. Census revealed that the New York and New Jersey portion of the Highlands has approximately 1,372,423 residents (Table 2-19). Fifty-four percent of those live in New Jersey and 46 percent in New York. The region experienced an 11.5 percent increase in population by comparison to the 1990 population estimate of 1,230,324. Population density for the entire region is estimated at slightly less than one person per acre (Figure 2-29). The region averaged 2.76 persons per household in The New York portion experienced a slightly higher average of 2.9 persons per household compared with New Jersey's average of 2.6 persons per household. The vast majority of Highlands municipalities increased in population between 1990 and 2000 (Figure 2-30). Greenwich Township was both the fastest growing municipality in the New York New Jersey Highlands from , and the fastest growing in New Jersey during the same period. Greenwich was the only municipality in the region to double in size, showing a 130 percent population increase between 1990 and The next fastest growing municipalities were Independence Township, NJ (42 percent), Monroe Town, NY (36 percent), Chester Borough, NJ (35 percent), Mahwah Township, NJ (34 percent), and Montville Township, NJ (34 percent). A total of 21 (of 108) municipalities experienced more than 20 percent population growth during this time. 120

2 New Jersey is also home to the only two municipalities to experience population losses greater than 10 percent during the 10-year period: Netcong Borough (22 percent), and Harding Township (13 percent). A total of 13 (of 108) municipalities in the Highlands study region experienced population loss. The 2000 population average for the 108 study-area municipalities was 12,708 while the median population was 7,471. The most populous municipality was Ramapo, NY with 108,905 residents. Only three municipalities had more than 50,000 residents. The smallest municipalities were Far Hills, NJ and Bloomsbury, NJ, both with less than 1,000 residents. Tables 2-20, 2-21, and 2-22 list the smallest, largest, and most densely populated municipalities in the New York New Jersey Highlands. 121

3 Table Highlands population change: 1990 to Source: U.S. Census data. Region Population 1990 Population 2000 Change New Jersey 665, , New York 565, , Total 1,230,324 1,372, Table Smallest municipalities in the New York New Jersey Highlands. Name 2000 Population Far Hills borough 859 Bloomsbury borough 886 Califon borough 1,055 Lebanon borough 1,065 Milford borough 1,195 Table Largest municipalities in the New York New Jersey Highlands. Name 2000 Population Warwick town 30,764 Monroe town 31,407 Carmel town 33,006 Haverstraw town 33,811 Yorktown town 36,318 Cortlandt town 38,467 Parsippany-Troy Hills township 50,649 Clarkstown town 82,082 Ramapo town 108,905 Table Most densely populated municipalities in the New York New Jersey Highlands. Name Persons per acre Pompton Lakes borough 5.27 Washington borough 5.36 Boonton town 5.38 Butler borough 5.54 Peekskill city 6.41 Phillipsburg town 7.10 Morristown town 9.65 Dover town Victory Gardens borough

4 Figure population density by municipality. 123

5 Figure change of population from 1990 to 2000 (by municipality). 124

6 Socio-demographic Characteristics of the Highlands Region s Counties In many respects, the population of the Highlands region is representative of the overall populations of New York and New Jersey. The gender ratio of males to females in the Highlands (48.7 percent male, 51.3 percent female) is similar to the overall New York and New Jersey State totals of 48.2 percent male to 51.8 percent female and 48.5 percent male to 51.5 percent female, respectively (Table 2-23). This gender ratio does not represent a significant change since the 1990 Census when the Highlands experienced a 48.6 percent male to 51.2 percent female ratio. Similarly, the percentage of the 2000 Highlands population under 15 years of age is 21.5 percent, and is similar to the overall New York and New Jersey State figures of 20.7 percent and 20.9 percent, respectively (Table 2-24). Likewise, the percentage of the 2000 Highlands population over the age of 65 is 12.7 percent. This figure is similar to the overall New York and New Jersey State figures of 12.9 percent and 13.2 percent, respectively. The 1990 percentage of the population over the age of 65 is 12.6 percent, which represents no significant change over the 10-year period. The 2000 median ages of population vary significantly across the Highlands counties, ranging from 34.7 to 39.1 years. Despite the variations, these are not radically different from the median ages for New York and New Jersey, 35.9 and 36.7 years of age, respectively (Table 2-23). The Highlands region has a less racially diverse population than that of the states of New York and New Jersey. In the year 2000, the Highlands counties showed a white to nonwhite ratio of 78.5 percent white and 21.5 percent nonwhite, while the states of New York and New Jersey showed white to nonwhite ratios of 67.9 percent to 32.1 percent and 72.6 percent to 27.4 percent, respectively (Table 2-24). The Highlands, like the larger New York New Jersey bi-state region, have become more racially diverse over the past decade, showing a white to nonwhite ratio of 85.3 percent white to 15.4 percent nonwhite in 1990 (as compared to 78.9 percent white 21.1 percent nonwhite in 2000). There is, however, great variability in racial diversity across the Highlands region. Counties that house major urban centers with large minority and recent immigrant populations, such as Passaic County in New Jersey (62.3 percent white to 37.7 percent nonwhite ratio), have more racially diverse populations than many of the more rural counties that are greater than 90 percent white. The percentage of occupied housing, at 96.1 percent, is slightly higher in Highlands counties than in the larger New York and New Jersey regions (91.9 percent and 92.6 percent, respectively) (Table 2-24). There has been a slight increase in the percentage of occupied housing over the past decade from 94.3 percent in 1990 to 96.1 percent in The percentage of housing that is owner occupied is 67.9 percent versus 32.1 percent renter occupied. The New York Highlands counties have a somewhat lower percentage of owner occupied housing than New Jersey, with 65.2 percent and 69.9 percent, respectively. Over the past decade from 1990 to 2000, the more urban counties in New Jersey (e.g., Bergen and Passaic counties) showed a slight decrease in owner occupied housing, while the more rural counties such as Hunterdon and Warren counties showed an increase. The various counties in New York showed no significant pattern over the decadal time period. 125

7 Table Highlands demographic trends, : population, gender, age, and racial characteristics. Source: U.S. Census. Note: the thresholds for the younger age category changed from Under 18 in 1990 to Under 15 in Name Total Pop 2000 Total Pop 1990 Total Pop Change Males 2000 Males 1990 Males Change Under Under % Over % Over Over 65 Change Median Age 2000 Median Age 1990 White 2000 White 1990 White Change NEW JERSEY Bergen county 884, , N/A Hunterdon county 121, , N/A Morris county 470, , N/A Passaic county 489, , N/A Somerset county 297, , N/A Sussex County 144, , N/A Warren county 102,437 91, N/A NJ county total 2,509,461 2,270, N/A N/A NEW YORK Dutchess county 280, , N/A Orange county 341, , N/A Putnam county 95,745 83, N/A Rockland county 286, , N/A Westchester county 923, , N/A NY county total 1,927,474 1,791, N/A N/A Highlands county total 4,436,935 4,061, N/A N/A New Jersey 8,414,350 7,730, N/A New York 18,976,457 17,990, N/A

8 Table Highlands housing trends, : occupied and owner-occupied housing. Source: U.S. Census. Name Housing Units 2000 Housing Units 1990 Housing Units Change Housing Units Occupied 2000 Housing Units Occupied 1990 Housing Units Occupied Change Housing Units Owner Occupied 2000 Housing Units Owner Occupied 1990 Housing Units Owner Occupied Change NEW JERSEY Bergen county 339, , Hunterdon county 45,032 39, Morris county 174, , Passaic county 170, , Somerset county 112,023 92, Sussex County 56,528 51, Warren county 41,157 36, NJ county total 938, , NEW YORK Dutchess county 106,103 97, Orange county 122, , Putnam county 35,030 31, Rockland county 94,973 88, Westchester county 349, , NY county total 708, , Highlands county total 1,647,292 1,529, NJ State total 3,310,275 3,075, NY State total 7,679,307 7,226,

9 Future Change Scenarios Build-Out Analysis and Econometric Modeling Build-Out Analysis Introduction A simple way to consider future change would be to simply answer the question, "How much could be built TODAY under existing zoning and environmental constraints?" Basically, that is the question the build-out analysis seeks to answer. The analysis can also be expanded to include a few different future policy scenarios to demonstrate a variety of future population distributions. For an area being analyzed, the process begins by removing from consideration places that would simply not be realistic for future development. These areas might include lands that are rendered unbuildable due to natural features, areas in which an existing policy prohibits development, urban areas already developed to their fullest legal extent, and permanently preserved properties (including public lands). The remaining areas are analyzed to find out how many houses could be built on them under the current zoning restrictions, with some recognition of additional infrastructure needs. Methods How was the build-out analysis applied? The first step of the build-out analysis for the Highlands was to map vacant land, i.e. privately owned land that was presently not developed. This was accomplished by removing from consideration places where future development and population change would not be expected. All publicly and privately owned conservation lands, military lands and lands with mapped conservation easements (see Section 2-2) were excluded. Areas mapped as already developed, based on the land use and land cover analysis (see Section 2-3, Changes in Land Use and Land Cover), and areas that were already built as densely as allowed by current zoning were excluded. In addition, small tracts of undeveloped lands within a matrix of existing development that were less than 1 acre in size were further excluded. As the focus was on residential development and future population growth, commercially and industrially-zoned areas were also removed from consideration. The second step was to further exclude land based on various regulatory constraints. In order to provide multiple outcomes, two different scenarios were constructed to show potential patterns of varying impacts: Low-constraint scenario map of areas that would presumably develop if current policies (including zoning) were continued unchanged indefinitely, and High-constraint scenario map of areas that would presumably develop if a few current policies (excluding zoning) were changed to increase the constraints on future development. After removing these constrained areas, the remaining area was then considered available for residential development. 128

10 The build-out analysis relied on existing land use zoning data to map out possible future land use patterns. Digital zoning mapped data for the New Jersey Highlands municipalities was acquired from the Environmental Defense Fund (in New York City). These digital maps were edge matched and quality checked and the zoning designation updated as appropriate. Zoning maps and data for the New York municipalities were acquired from a variety of local and county sources. Digital data was acquired for Orange, Rockland and Westchester counties from the county planning departments. Zoning maps were digitized for Dutchess and Putnam Counties. These digital maps were edge-matched and quality checked. The zoning ordinances from more than 100 different municipalities had to be generalized to create a standard zoning density map across the entire study area (Figure 2-31). The map of available land was cross-tabulated with land use zoning maps to estimate the density of future development and calculate the number of additional housing units that might potentially be built. In available land areas where new development was calculated, 20 percent of the area was removed from consideration to account for future infrastructure necessary to support the new development. Based on the 2000 Census average of number of people per household for that locality, the additional population was then estimated. The final numbers were then summarized to describe the population that could inhabit the area under the previously described set of assumptions. As one means of assessing the validity of the overall build-out modeling approach, the build-out model was applied to the present (i.e. year 2000) development patterns. Using the low-constraint scenario rules (i.e. existing regulations), the number of housing units allowable under existing zoning was estimated. The model estimates of housing units and population were then compared with the 2000 Census data on a study area-wide basis. What are the limitations of build-out analysis? The build-out analysis of the Highlands describes a future scenario that is based on an assumption that existing zoning policies continue unchanged into the foreseeable future. While one may argue that this is unrealistic, as zoning and associated policies will certainly change in the future, the build-out analysis provides a meaningful measure of the capacity of an area under an assumed set of constraints. To understand the results of the analysis, it is important to recognize some of the limitations including problems related to: The temporal nature of the data assumptions of the analysis; Generalized zoning data; and The scale of analysis. One of the basic problems with this type of analysis is that it relies heavily on current zoning data. Each of the more than 100 municipalities in the Highlands has the opportunity to change zoning for individual properties each month. Almost as quickly as a zoning map can be compiled for the Highlands, it begins to fade in its ability to reflect the zoning of the region. While some of the zoning adjustments are insignificant, a municipality could adopt a new plan for a new town center or apartment complexes that will lead to dramatic increases in population. This change would not be reflected in the build-out analysis and would result in an underestimate of future population numbers. Additional properties will inevitably also be bought or preserved 129

11 as open space, reducing the final built area and population numbers as compared to the build-out analysis. More dramatic policies and projects such as new highways, environmental regulations, and land acquisition will all work quickly to change the future of the Highlands in ways that we cannot presently predict. The build-out analysis is based on a series of assumptions that are fairly limiting. Aside from the temporal assumption described previously, a build-out analysis assumes that all buildable properties will be built to their fullest capacity and that the houses built will hold the area's average number of people per household. These assumptions may reflect large regional trends, but can be problematic in areas with unusual patterns of change, such as a sudden shift to "empty nesters" (i.e. couples whose children have left home for college and life, but who often continue to maintain a larger home). In order to analyze the entire region, the zoning ordinances from more than 100 different municipalities had to be generalized to make them comparable. Local variations and distinctions in the zoning ordinances get lost in this sort of analysis. The build-out analysis for the Highlands was conducted with an awareness of these issues in an attempt to minimize their impact, but many subtleties and complex mechanisms suffer from this necessary generalization. Finally, it is important to understand that a build-out analysis is conducted at a large regional scale, making it impossible to include some of the careful intertwining of development and constrained areas. A simple example of this problem is that a 100-acre parcel with 50 acres of wetlands and wetlands buffer might sometimes be carefully subdivided into 5-acre lots in a spatial arrangement that still achieves the maximum 20 houses, without infringing upon the wetlands. The build-out analysis would only calculate the area as having room for ten 5-acre lots. What are the criteria for the low-constraint map? The intent of the low-constraint scenario was to map those areas that would presumably develop if a few current policies were changed to increase the constraints on future development (Figure 2-32). These constraints were: Known public lands and preserved lands (this includes State parks, local parks, Federal properties, and known conservation easements), Open water with 50-foot buffers, Wetlands with 50-foot buffers, Slopes over 33 percent, Areas zoned for non-residential use, and Residential areas already built to their zoning capacity. The wetlands for the low-constraint map were delineated based on the existing maps from the New York State Department of Environmental Conservation (NYS DEC) and the New Jersey Department of Environmental Protection (NJ DEP) delineation of regulated fresh water wetlands. The known public lands included only those water supply lands that were known to the assessment team to be permanently preserved lands. For example, portions of the Newark 130

12 water supply areas that are not protected by Green Acres are considered eligible for development under the low-constraint scenario. These constraints are based on a series of assumptions designed to reflect realistic patterns of future development. The 33 percent limitation on slope does not reflect existing zoning limitations in most places, but is meant to approximate a significant reduction of housing density on particularly steep slopes. The buffers do not generally reflect existing polices, but recognizes that a limited amount of housing would be built directly on stream banks and the edges of many wetland areas. What are the criteria for the high-constraint map? The intent of the high-constraint scenario was to map those areas that would presumably develop if current policies and conditions were modified to provide additional environmental protections (Figure 2-33). These constraints were: Known public lands and preserved lands (this includes State parks, local parks, Federal properties, known conservation easements, and all water supply lands), Open water with 200-foot buffers, Wetlands with 150-foot buffers, Slopes over 15 percent, Areas zoned for non-residential use, and Residential areas already built to their zoning capacity. The wetlands for the high-constraint map were different for each State. For New Jersey, the NJ DEP delineation of wetlands was combined with the National Wetlands Inventory (NWI). For New York, NYS DEC data were combined with the NWI. The known public lands included all known water supply lands as permanently preserved lands. Potential future constraints are difficult to determine, but the existing constraints were expanded based on patterns in other areas. The 15 percent limitation on slope reflects some of the more recent zoning ordinances in the greater New York New Jersey region. In addition to the previously described justifications, the wider buffers reflect some of the more restrictive buffers used in forestry and planning regulations or practice and are also meant as a consideration of ongoing discussions about increased protection around water and wetland areas. However, the overall restrictiveness of these constraints also helps compensate for other future constraints that are not plausible to include (like private deed-restricted properties, sewer-related limitations, future zoning changes, etc.). Results The comparison of the housing unit and population numbers for the build-out model estimate with the 2000 Census estimate shows that there is a close correspondence (Table 2-25A). The model slightly underestimated the number of housing units, on the order of 4.7 percent, and population, on the order of 1.6 percent. Based on these results and the caveats outlined above, we are reasonably confident on the overall validity of the build-out model approach. Approximately 585,000 acres were classified vacant, representing approximately 40 percent of the Highlands study area. The high and low-constraint models illustrate two potential directions that development might take in the future. Under the low-constraint scenario, 126,911 acres 131

13 would be excluded, leaving 458,431 acres of land available for development (Figure 2-34, Table 2-25B). Under the high-constraint scenario, 332,922 acres would be excluded, leaving 252,420 acres of land available for development (Figure 2-35, Table 2-25B). The lowconstraint scenario, perhaps a more realistic reflection of the current regulatory limitations, estimated 231,580 additional housing units and a population increase of 47.6 percent (Table 2-25B). Under the more restrictive high-constraint model, approximately 100,000 fewer housing units would be added for a total of 127,253 additional housing units and a population increase of only 26.3 percent (Table 2-25B). The high-constraint scenario estimates lower future development potential and population growth without any significant change in current zoning. Under both scenarios, the two states would experience relatively similar rates of growth. It should be noted that these above results are different from those initially developed and presented to the Highlands study work group in January The initial build-out scenario modeling efforts completed in January 2001 utilized a different methodology that allowed additional infill development in partially developed areas until the zoned capacity was reached. However, based on feedback from the study work group, an alternative methodology was adopted that explicitly removed existing developed areas based on the year 2000 land use and land cover mapping. Thus future growth was allowed only on those lands considered vacant. Both methodologies provide a defensible estimate of future potential population growth; with the initial methodology allowing for substantial infill and thereby providing a high-end estimate, while the second method was more restrictive, providing a low-end estimate. As expected, the initial build-out modeling methodology (i.e., infill allowed) produced higher estimates of future population growth. An additional population of 653,888 and 361,261 was estimated for the low and high-constraint scenarios, respectively. This would represent an increase in population of 71.2 percent and 50.4 percent over the year 2000 census estimate for the Highlands study region (as compared to the alternative estimates of 47.6 percent and 26.3 percent as presented in Table 2-24b). These initial high-end population estimates provided a worst case scenario and were used by the U.S. Geological Survey in their water budget modeling of future conditions. Due to time constraints, the alternative low-end estimate was not further evaluated by the U.S. Geological Survey in their water budget modeling efforts. 132

14 Table Results of build-out analysis. A. Comparison of 2000 Census and build-out model estimates of housing units and population. Census observed Model estimation Difference Housing units 496, , percent Population 1,372,413 1,350, percent B. Estimated future housing units and population change under the low and high-constraint scenarios. Lowconstraint Highconstraint Low high difference Available land (acres) Additional housing units Additional population Total population 1 Population change 458, , ,888 2,026, percent 252, , ,261 1,733, percent 236, , , , Figures 2-34 and 2-35 show the estimated population density of the various municipalities under the low and high-constraint scenarios, respectively. Figures 2-36 and 2-37 show the estimated percent change in population, at the municipal level, under the low and high-constraint scenarios respectively. These figures highlight those municipalities that will most likely experience high levels of future growth, as well as those municipalities that are near or already built-out. Under the low-constraint scenario, six different Highlands municipalities are zoned in a manner that would allow more than a tripling of the population. These municipalities are: Patterson Town (Putnam, NY), White Township (Warren, NJ), Greenwich Township (Warren, NJ), Harmony Township (Warren, NJ), Hardystown Township (Sussex, NJ), and Franklin Township (Warren, NJ) Thirteen municipalities appeared to already be at or near build-out, with less than a 1 percent population increase under the low-constraint scenario. While this may mean that these municipalities have limited growth potential, it might instead reflect local zoning practices. While the build-out analysis is meant as a temporal measure of potential change (i.e., the analysis provides no technical expectation of when build-out would occur), it can offer a glimpse at the 1 Total population equals estimated additional and Census 2000 population. 133

15 temporal problem that exists. Under the assumptions of the build-out scenarios and assuming that the Highlands population continues to grow at the same rate as it did between 1990 and 2000 (an average annual rate of about 1.1 percent), build-out will be reached in the not so distant future. Of course, these assumptions do not reflect the more complex growth patterns that would surely occur (like preserved land that reverts to private ownership and development, or privately owned lands which simply never get built). The high-constraint build-out would be reached in 2021, and the low-constraint build-out would be reached in Even within this uncertainty, the numbers suggest that the bulk of presently vacant available lands will be developed within only a few decades. 134

16 Figure Map of zoning density. 135

17 Figure Map of constrained and available lands under the low-constraint scenario. 136

18 Figure Map of constrained and available lands under the high-constraint scenario. 137

19 Figure Map of population density by municipality at build-out under the low-constraint scenario. 138

20 Figure Map of population density by municipality at build-out under the high-constraint scenario. 139

21 Figure Map of percent population change necessary to reach build-out under the lowconstraint scenario. 140

22 Figure Map of percent population change necessary to reach build-out under the highconstraint scenario. 141