Mineral Resource Assessment of Marine Sand Resources 

in Cape- and Ridge-Associated Marine Sand Deposits in 

Three Tracts, New York and New Jersey, United States 

Atlantic Continental Shelf 

Chapter N of 

Contributions to Industrial-Minerals Research 

Bulletin 2209–N
 

U.S. Department of the Interior 

U.S. Geological Survey 

 

Mineral Resource Assessment of Marine Sand Resources 

in Cape- and Ridge-Associated Marine Sand Deposits in 

Three Tracts, New York and New Jersey, United States 

Atlantic Continental Shelf 

By James D. Bliss, S. Jeffress Williams, and Matthew A. Arsenault 

Chapter N of 

Contributions to Industrial-Minerals Research 

James D. Bliss, Phillip R. Moyle, and Keith R. Long, Editors 

Bulletin 2209–N
 

U.S. Department of the Interior 

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

KEN SALAZAR, Secretary 

U.S. Geological Survey 

Suzette M. Kimball, Acting Director 

U.S. Geological Survey, Reston, Virginia: 2009 

This report and any updates to it are available online at: 

http://pubs.usgs.gov/bul/b2209-n/ 

For product and ordering information: 

World Wide Web: http://www.usgs.gov/pubprod 

Telephone: 1–888–ASK–USGS 

For more information on the USGS—the Federal source for science about the Earth, its natural 

and living resources, natural hazards, and the environment: 

World Wide Web: http://www.usgs.gov 

Telephone: 1–888–ASK–USGS 

Suggested citation: 

Bliss, J.D., Williams, S.J., and Arsenault, M.A., 2009, Mineral resource assessment of marine sand resources in capeand ridge-associated deposits in three tracts, New York and New Jersey, United States Atlantic continental shelf, chap. 

N of Bliss, J.D., Moyle, P.R., and Long, K.R., eds., Contributions to industrial-minerals research: U.S. Geological Survey 

Bulletin 2209–N, 6 p. [http://pubs.usgs.gov/bul/b2209-n] 

Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not 

imply endorsement by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual copyright 

owners to reproduce any copyrighted materials contained within this report. 

Cataloging-in-Publication data are on file with the Library of Congress (URL http://www.loc.gov/). 

Produced in the Western Region, Menlo Park, California 

Manuscript approved for publication, February 2, 2009 

Text edited by Theresa Iki 

Layout and design by Stephen L. Scott 
 

 

 

 

 

 

 

 

 

 

 

III

Contents
 Abstract -------------------------------------------------------------------------------------------------------1 

Introduction---------------------------------------------------------------------------------------------------1 

Acknowledgments -------------------------------------------------------------------------------------------2 

Monte Carlo Simulation -------------------------------------------------------------------------------------2 

Mineral Resource Assessment ----------------------------------------------------------------------------2 

Introduction---------------------------------------------------------------------------------------------2 

Tracts ---------------------------------------------------------------------------------------------------3 

Summary of Results------------------------------------------------------------------------------------------5 

References Cited---------------------------------------------------------------------------------------------5 

Figures

1.	 Location of three tracts assessed (A-2, B-2, and C-2) for cape- and ridge-associated 

marine sand deposits in the New York and New Jersey, USA-------------------------------------3

 2. Cumulative distribution of marine sand predicted in undiscovered cape- and 

ridge-associated marine sand deposits in Tract A-2, Cape May, south 

New Jersey shelf area--------------------------------------------------------------------------------4

 3. Cumulative distribution of marine sand predicted in undiscovered cape- and 

ridge-associated marine sand deposits in Tract B-2, central New Jersey 

shelf area------------------------------------------------------------------------------------------------4

 4. Cumulative distribution of marine sand predicted in undiscovered cape- and 

ridge-associated marine sand deposits in Tract C-2, Long Island Shelf area------------------5 

Tables

1.	 Estimated number of undiscovered cape- and ridge-associated marine sand 

deposits in Tract A-2, Cape May, south New Jersey shelf area; Tract B-2, 

central New Jersey shelf area; and Tract C-2, Long Island shelf area -------------------------4 

2. 	 Estimated sand resources in cape- and ridge-associated marine sand 

deposits in three tracts in the New York and New Jersey offshore region, USA--------------5 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Mineral Resource Assessment of Marine Sand Resources 

in Cape- and Ridge-Associated Marine Sand Deposits in 

Three Tracts, New York and New Jersey, United States 

Atlantic Continental Shelf 

By James D. Bliss, S. Jeffress Williams, and Matthew A. Arsenault 

Abstract 

Demand is growing in the United States and worldwide 

for information about the geology of offshore continental 

shelf regions, the character of the seafloor, and sediments 

comprising the seafloor and subbottom. Interest in locating 

sand bodies or high quality deposits that have potential as 

sources for beach nourishment and ecosystem restoration is 

especially great in some regions of the country. The Atlantic 

coast, particularly New York and New Jersey, has been the 

focus of these studies for the past 40 years with widely varying 

results. This study is the first attempt at applying probability 

statistics to modeling Holocene-age cape- and ridge-associated 

sand deposits and thus focuses on distinct sand body morphology. This modeling technique may have application for 

other continental shelf regions that have similar geologic 

character and late Quaternary sea-level transgression history. 

An estimated volume of 3.9 billion m3 of marine sand 

resources is predicted in the cape- and ridge-associated marine 

sand deposits in three representative regions or tracts on the 

continental shelf offshore of New York and New Jersey. These 

estimates are taken from probabilistic distributions of sand 

resources and are produced using deposit models and Monte 

Carlo Simulation (MCS) techniques. The estimated sand 

resources presented here are for only three tracts as described 

below and for Holocene age sand resources contained in 

cape- and ridge-associated marine sand deposit types within 

this area. Other areas may qualify as tracts for this deposit 

type and other deposit types and geologic ages (for example, 

paleo-stream channels, blanket and outwash deposits, ebb-tide 

shoals, and lower sea level-stand deltas), which are present 

on the New Jersey and New York continental shelf area but 

are not delineated and modeled in this initial evaluation. 

Admittedly, only a portion of these probable sand resources 

will ultimately be available and suitable for production, dependent largely on geographic, economic, preemptive use, environmental, geologic and political factors. In addition, offshore sand 

resources should only be considered if the area is seaward of the 

active zone of significant nearshore sediment transport, about 

10 to 12 m in depth, and in sufficiently shallow water so that 

sand can be extracted within U.S. dredging equipment limits, 

currently about 40 m in depth. If the material is to be used for 

beach nourishment, material must be of an appropriate sediment texture and character (grain size, sorting, shape, and color) 

to match the native beach and have mineralogical properties 

important to its use. Extraction of sand can disturb or alter the 

benthic habitat and seafloor ecology, so these factors and other 

site-specific effects will need to be evaluated for any intended 

use. These and other factors are not considered in this report 

but can be expected to reduce the total net volume of sand 

resources available for production. The purpose of this report 

is to describe and present results from a probabilistic mineral 

modeling technique previously applied to onshore mineral 

resources. This modeling and assessment procedure is being 

used for the first time to assess and estimate offshore aggregate resources; this study is part of the U.S. Geological Survey 

(USGS) Marine Aggregates Resources and Processes Project 

(http://woodshole.er.usgs.gov/project-pages/aggregates/). 

Introduction 

Federal, state, and local coastal managers and planners 

have been and continue to be concerned about the availability of high quality marine sand and gravel (primarily sand) 

suitable to mitigate erosion and protect coastal development 

and infrastructure, nourish beaches, and maintain recreation 

areas. Colony (1932) and Stetson (1938) were among the first 

marine scientists who expressed an interest in the character 

and distribution of sediments off the continental shelves of 

Long Island and New Jersey. Hall (1952) expanded upon 

this with an early awareness of the possibility that offshore 

sand may be used to nourish eroded beaches and possibly 

construct new beaches. A number of surveys to map seafloor 

geology to locate and quantify the volume of sand located 

offshore have been completed since the 1960s. One of the 

earliest studies using geophysical instruments and sediment 

cores was made along the northern New Jersey to the western 

Long Island coast in an area of about 400 km2 in the inner 

New York Bight just seaward of Lower New York Harbor 

(Williams and Duane, 1974). This was followed by a study 

Mineral resource assessment of marine sand resources in cape- and ridge-associated marine sand deposits in three tracts 1 
 

 

 

 

 

 

 

 

off the Long Island south shore inner continental shelf in an 

area of slightly less than 1,300 km2

 (Williams, 1976). Many 

other studies focusing on locating and quantifying marine 

sand deposits have been made by the U.S. Army Corps of 

Engineers (Meisburger and Williams, 1980; 1982) and USGS 

(Schlee, 1968; Foster and others, 1999; Schwab and others, 

2000; Williams and others, 2006), as well as by states and 

universities (Uptegrove and others, 1999). State studies were 

funded, in part, by the U.S. Minerals Management Service 

to meet their sand leasing mission (Byrnes and others, 2001, 

2004). Williams and others (2003) report details on publications about U.S. marine sand and gravel resources, and 

Williams and others (2006) most recently present maps and 

descriptions of surficial sediments for the New York Bight 

region based on the new usSEABED sediment database 

(see Reid and others, 2005 for the Atlantic shelf region). 

Overall, federally sponsored beach nourishment operations in the U.S. have used about 920 million m3

 of sand in 

the past 80 years (http://psds.wcu.edu/1038.asp) Increased 

and often competing demands for marine sand raise concerns about long-term potential supply and emphasize the 

need for quantitative assessment of sand resources. Managers need to know the volume of sand resources likely present 

and what limitations may exist in both near term and longer 

term. With prospects for higher sea level and increased storm 

activity in the near future due to climate change, managers 

have a pressing need for credible and reliable information 

about the costs and sustainability of adaptation methods, 

such as beach nourishment, which is dependent on large 

quantities of high quality sand within economic transport 

distances to beaches being considered for nourishment. 

The following mineral resource assessment of cape- and 

ridge-associated marine sand deposits is conducted using 

deposit models, quantitative assessment techniques, and a 

Monte Carlo Simulation (MCS) program described in Bliss 

and others (2009). Cape- and ridge-associated marine sand 

deposits, two classes of seafloor bedforms, develop on stormdominated, relatively sand-rich continental shelves. These 

bedforms are particularly notable along a segment of the 

mid-Atlantic U.S. continental shelf that extends south from 

the eastern end of Long Island, New York and east from Cape 

May, at the southern end of New Jersey (fig. l). This type 

of marine sand deposit typically contains high quality sand 

suitable to meet the requirements for nourishment of eroded 

beaches along the Long Island and New Jersey coasts. 

Acknowledgments 

We thank Dave S. Foster for providing a helpful review 

and suggestions from a marine-geologic perspective, and 

Keith R. Long from a mineral-resource-assessment and 

modeling perspective. Mark R. Byrnes with Applied Coastal 

Research and Engineering, Mashpee, Massachusetts, and Jeffrey Waters with the U.S. Army Corps of Engineers also provided valuable suggestions on paper organization and content. 

Monte Carlo Simulation 

The use of Monte Carlo Simulation (MCS) techniques 

allows a representation of the uncertainty in a natural system 

based on a user-defined conditional distribution of undiscovered deposits, and models previously identified. The MCS 

program used in this assessment is written in SYSTAT Basic® 

that produces a distribution that allows a probabilistic estimate 

of how much marine sand is present in undiscovered cape- and 

sand-ridge associated marine sand deposits in three tracts (fig. 

1) in the New York and New Jersey continental shelf area. The 

conditional distribution (number of deposits) estimated for the 

assessment are used in the simulation using a protocol outlined 

by Root and others (1992) and are given in this assessment 

for each tract following the subjective estimate. The estimates of undiscovered deposits are based on three criteria: 

1) Expert judgment from a fundamental understanding of mid-Atlantic continental shelf geology, 

2) Results of numerous other assessments, most based 

on analysis of geophysical data and sediment cores from 

field surveys, such as in Meisburger and Williams (1980, 

1982), Williams (1976), and Byrnes and others (2004), and, 

3) The character and distribution of sand bodies 

on other shelf regions having similar morphology and late Quaternary geologic history. 

In addition, Singer and Menzie (2005) developed an 

algorithm that calculates the mean, standard deviation and 

coefficient of variation of the distribution of estimated numbers of undiscovered deposits in each tract given below. 

For this assessment, MCS was executed for 4,999 iterations, using two distribution models for cape- and ridgeassociated marine sand deposits: 1) a sand-volume model, 

and 2) a percent-of-sand content model. Both models are 

described in Bliss and others (2009). On the basis of the 

two distribution models, together with an estimate of the 

number of undiscovered deposits (table 1), we made probabilistic estimates of marine sand resources in cape- and 

ridge-associated marine sand deposits; the assessment results 

are presented and described below. However, the estimates 

provided and the actual amount of undiscovered marine sand 

suitable for extraction is likely considerably less because 

of the environmental and economic factors as discussed in 

the introduction and reported by Bliss and others (2009). 

Mineral Resource Assessment 

Introduction 

The tract boundaries in this study are defined generally by seafloor features and landforms that are consistent with the presence of cape- and sand-ridge associated 

marine sand deposits. Some considerations for resource 

boundaries are made for minimum and maximum water 

depth criteria set forth for a generalized depth of closure, 

a time-dependent estimated depth of significant crossshore sediment transport commonly used in coastal engi2 Contributions to Industrial-Minerals Research 
 

 

 

 

 

 

 

 

 

 

 

neering modeling, and the current general U.S. offshore 

water depth dredging limits, respectively. The depth of 

closure for the Long Island region has been reported to 

range from 7.3 m to 12 m in depth (Hapke and others, in 

press). As such, resources being considered for dredging 

offshore Long Island and New Jersey should be seaward 

of a minimum of approximately 10 m water depth and 

landward of a maximum of 40 m water depth (the approximate current U.S. dredge equipment water depth limit). 

These inshore and offshore water depth limits have been 

broadly considered in setting the tract boundaries (fig. 1). 

Tracts 

Deposits in Tract A-1, B-1, and C-1 are not included 

in this assessment, but rather are described by Meisburger 

and Williams (1980), Meisburger and Williams (1982), 

and Williams (1976) using non-probabilistic assessment 

methods. Tract A-1 has an area of 1,200 km2 on the Cape 

May platform and estimated sand resource volumes of 

slightly more than 1,000 million m3. Tract B-1 has an area 

of 1,800 km2 of the central New Jersey shelf and estimated 

sand resource volumes of 170 million m3. Tract C-1 has 

an area of 2,100 km2 of the Long Island Atlantic shelf and 

estimated sand resource volumes of 8 billion m3. Noteworthy for all these studies, however, is that the sand volume 

estimates include a wide range of deposit types and geologic ages (i.e., Holocene and Pleistocene deposits). 

Table 1 includes the estimated number of undiscovered 

marine cape- and ridge-associated marine sand deposits 

(column B) at three percentage levels of certainty (column 

A) for Tract A-2, B-2, and C-2 (fig. 1). The estimates of 

undiscovered deposits in all tracts were guided by the mineral deposit density (MDD) as described in Bliss and others 

(2008, table 3) and tract area. Table 1 also includes the 

actual number of deposits given in MCS (column C) and 

the probability that number of deposits was selected and 

defined as the allocated probability (column D) for all three 

tracts. Because the last two estimates in Tract A-2 are both 

32 deposits (50 percent chance and 10 percent chance as 

given in table 1, column A) only one allocated probability 

value (column D) is given for 32 undiscovered deposits. 

Using the algorithm developed by Singer and Menzie 

(2005), the mean of the number of undiscovered deposits in Tract A-2 is 28 deposits with a standard deviation 

of 3.4 and a coefficient of variation of 12 percent for the 

estimated numbers of undiscovered deposits (table 1). The 

mean of the number of undiscovered deposits in Tract B-2 

is 12 deposits with a standard deviation of 2.1 and a coefficient of variation of 18 percent for the estimated numbers 

of undiscovered deposits (table 1.) The mean of the number 

Figure 1. Location of three tracts assessed (A-2, B-2, and C-2) for cape- and ridge-associated marine sand 

deposits in the New York and New Jersey region, USA. Nearshore tracts (A-1, B-1, C-1), separated by the 

red lines from the offshore tracts assessed, are described in earlier publications (Meisburger and Williams, 

1980; 1982; Williams, 1976), and are only briefly summarized in this assessment. 

Mineral resource assessment of marine sand resources in cape- and ridge-associated marine sand deposits in three tracts 3 
A-2 

Table 1. Estimated numbers at three probability levels of undiscov- 1.00 n=4,999 ered cape- and ridge-associated marine sand deposits in Tracts A-2, 

0.90 B-2, and C-2. 

A B C D 0.80 

Tract Level of Estimated Number of deposits Allocated 0.70 Number Uncertainty number of for Monte Carlo probability of

deposits Simulation (MCS) deposit(s) for MCS 0.60 Not an None made 0-24 0.00385 ea 

estimated 

Probability 0.50 

0.40 

1,200 interval 

90% chance 25 25 0.0324 

of at least 

Not an None made 26-31 0.0571 ea 

estimated 

interval 

50% chance 32 32 0.528 

of at least 

10% chance 32 See Table footnote. 

of at least 

B-2 Not an None made. 0-10 0.0087 ea 

estimated

interval 

90% chance 11 11 0.204 

of at least 

50% chance 12 12 0.267 

of at least 

Not an None made 0.133 ea 

estimated 13-14 

interval 

10% chance 15 15 0.167 

of at least 

C-2 Not an None made. 0-47 0.00206 

estimated 

interval 

90% chance 48 48 0.0296 

of at least 

Not an None made. 49-54 0.0571 ea 

estimated

interval 

50% chance 55 55 0.0571 

of at least 

Not an None made. 56-61 0.0571 ea 

estimated 

interval 

10% chance 62 62 0.1286 

of at least 

No additional deposits are needed in MCS as the 50 percent and 10 percent 

chance of estimated number of deposits are the same (32) and the maximum 

number of undiscovered deposits is 32. 

of undiscovered deposits in Tract C-2 is 52 deposits with 

a standard deviation of 7.1 and a coefficient of variation 

of 14 percent for the estimated numbers of undiscovered 

deposits (table 1). The low coefficient of variation sug0.30 

0.20 

0.10 

700 1,200 1,700 0.00 

0	 2000 

Volume, in million cubic meters 

Figure 2. Cumulative distribution of marine sand predicted in 

undiscovered cape- and ridge-associated marine sand deposits 

in Tract A-2. Values of 700, 1,200 and 1,700 million m3

 for the 

generated distribution are given for the 90th, 50th, and 10th percentiles. 

The mean of the distribution (1,200 million m3

) is given at the blue 

point. N=4,999 is the number of MCS iterations used for figure 

preparation. 

The MCS distribution of the sand predicted in undiscovered 

cape- and ridge-associated marine sand deposits in Tract C-2 

are reported as a cumulative probability distribution (fig. 4). 

There is a 90 percent chance that Tract C-2 contains 1,400 million m3

 or more of marine sand, a 50 percent chance of 2,200 

n=4,999 1.00 

0.90 

0.80 

0.70 

Probability 

gests low uncertainty and no clustering of undiscovered 

deposits within assessment Tracts A-2, B-2, and C-2.
	

The MCS distribution of the sand predicted in undiscovered cape- and ridge-associated marine sand deposits in 

0.60 

0.50 

0.40 500

0.30 Tract A-2 are reported as a cumulative probability distribution 

(fig. 2). There is a 90 percent chance that Tract A-2 contains 

700 million m3 or more of marine sand, a 50 percent chance 

that the tract contains 1,200 million m3 or more of marine 

sand, and a 10 percent chance of 1,700 million m3 or more. 

The mean value of the distribution is 1,200 million m3. 

The MCS distribution of the sand predicted in undiscovered cape- and ridge-associated marine sand deposits in Tract 

B-2 are reported as a cumulative probability distribution (fig. 

3). There is a 90 percent chance that Tract B-2 contains 230 

million m3

 or more of marine sand, a 50 percent chance of 440 

million m3 or more, and 10 percent of 870 million m3 or more. 

The mean value of the MCS distribution is 500 million m3. 

0.20 

0.10 

230 440 870 0.00 

0 1000 

Volume, in million cubic meters 

Figure 3. Cumulative distribution of marine sand predicted in 

undiscovered cape- and ridge-associated marine sand deposits 

in Tract B-2. Values of 230, 440 and 870 million m3

 for the generated 

distribution are given for the 90th, 50th, and 10th percentiles. The mean 

of the distribution (500 million m3

) is given at the blue point. N=4,999 is 

the number of MCS iterations used for figure preparation. 

4 Contributions to Industrial-Minerals Research 

2000 
500 

1.00 n=4,999

0.90

0.80

0.70

0.60

ty

0.50

abili

2,200

Prob

0.40

0.30

0.20

0.10

1,400 2,200 2,900

0.00

0 1000 2000 3000 4000 5000

Vol ume, in mil lion cubic meters 

Figure 4. Cumulative distribution of marine sand predicted in 

undiscovered cape- and ridge-associated marine sand deposits 

in Tract C-2. Values of 1,400, 2,200 and 2,900 million m3

 for 

the generated distribution are given for the 90th, 50th, and 10th

percentiles. The mean of the distribution (2,200 million m3

) is given 

at the blue point. N=4,999 is the number of MCS iterations used for 

figure preparation. 

million m3 or more, and 10 percent of 2,900 million m3 or 

more. The mean value of the distribution is 2,200 million m3. 

Summary of Results 

The results of the MCS modeling for cape- and ridge-associated marine sand deposits types in the three tracts are summarized in table 2. The mean value of the estimated volume for 

the distribution of undiscovered sand in Tracts A-2, B-2, and 

C-2 is 3,900 million m3 or 3.9 billion m3. The actual amount 

of undiscovered marine sand suitable for extraction is likely 

considerably less for reasons discussed in the introduction and 

discussed in Bliss and others (2009). 

Mineral resource assessments are a time-dependent 

picture of expected mineral endowments. An assessment 

expresses the level of understanding about mineral deposit 

types and geological situations under evaluation, the quality 

and quantity of data available, and the accuracy and reliability of the deposit models. While this may be the first 

assessment of marine sand resources that gives probabilistic 

estimates of amounts of marine sand in cape- and ridgeassociated marine sand deposits in three tracts in the New 

York and New Jersey continental shelf area, the assessment 

shows promise of yielding useful results and can be used in 

other regions. New and improved mineral resources assessments will be possible given additional new data, new and 

improved models and new and improved assessment methodologies combined with credible scientific evaluation. Assessment models for other sand body deposit types are being 

developed. Perhaps most importantly, modification of the 

assessment methodology will be required as our understanding of geologic controls and processes of marine sand deposiTable 2. Estimated sand (in million m3

) in undiscovered cape- and 

ridge-associated marine sand deposits in three tracts (Tract A-2, B-2, 

C-2) in the New York and New Jersey offshore region, USA. 

Marine Sand Resources, in million m3

Tract 90th percentile 50th percentile 10th percentile Mean 

A-2 700 1,200 1,700 1,200 

B-2 230 440 870 

C-2 1,400 2,200 2,900 2,200 

Total Not applicable Not applicable Not applicable 3,900 

tion improves with continued data collection and research. 

There will be a continued demand for such marine mineral 

assessments to provide timely information to federal, state, 

and local policy makers and marine resources managers. 

References Cited 

Bliss, J.D., Williams, S.J., and Bolm, K.S., 2009, Modeling 

cape and ridge-associated marine sand deposits: a focus on 

the U.S. Atlantic Shelf , chapter M in Bliss, J.D., Moyle, P.R., 

and Long, K.R., eds., Contributions to industrial-minerals 

research: U.S. Geological Survey Bulletin 2209-M, 22 p. 

Byrnes, M.R., Hammer, R.M., Vittor, B.A., Ramsey, J.S., 

Snyder, D.B., Wood, J.D., Bosma, K.F., Thibaut, T.D., and 

Philips, N.W., 2001, Environmental survey of potential sand 

resource sites: offshore New Jersey. Volume I: Main Text, 

Volume II: Appendices: U.S. Department of the Interior, 

Minerals Management Service, International Activities and 

Marine Minerals Division (INTERMAR), OCS Report 

MMS 2000-052, 664 p. 

Byrnes, M.R., Hammer R.M., Kelley, S.W., Baker, J.L., 

Snyder, D.B., Thibaut, T.D., Zichichi, S.A., Lagera, L.M., 

Viada, S.T., Vittor, B.A., Ramsey, J.S., and Germano, J.D., 

2004, Environmental surveys of potential borrow areas 

offshore northern New Jersey and southern New York and 

the environmental implications of sand removal for coastal 

and beach restoration: U.S. Department of the Interior, 

Minerals Management Service OCS Report MMS 2004-044, 

v. I, 264 p., and v. II: Appendices 194 p. 

Colony, R.J., 1932, Source of the sands on the south shore 

of Long Island and the coast of New Jersey: Journal of 

Sedimentary Petrology, v. 2, no. 3, p. 150-159. 

Foster, D.S., Swift, B.A., and Schwab, W.C., 1999, 

Stratigraphic framework maps of the nearshore area of 

southern Long Island from Fire Island to Montauk Point, 

New York: U.S. Geological Survey Open-File Report 

99-559. Online at http://pubs.usgs.gov/of/of99-559/ 

Hall, J.V., 1952, Artificially nourished and constructed beaches: 

U.S. Army Corps of Engineers, Beach Erosion Board, 

Washington, D.C., TM-29.
	

Hapke, C.J., Lentz, E.E., Gayes, P.T., McCoy, C.A., Hehre, 

R., Schwab, W.C., and Williams, S.J., in press, A review of 

sediment budget imbalances along Fire Island, New York: 

can nearshore geologic framework and patterns of shoreline 

change explain the deficit?: Journal of Coastal Research. 

Mineral resource assessment of marine sand resources in cape- and ridge-associated marine sand deposits in three tracts 5 
Meisburger, E.P., and Williams, S.J., 1980, Sand resources on 

the inner continental shelf of the Cape May region, New 

Jersey: U.S. Army Corps of Engineers Coastal Engineering 

Research Center Miscellaneous Report MR 80-4, 40 p. 

Meisburger, E.P., and Williams, S.J., 1982, Sand resources 

on the inner continental shelf off the central New Jersey 

coast: U.S. Army Corps of Engineers Coastal Engineering 

Research Center Miscellaneous Report MR 82-10, 48 p. 

Reid, J.M., Reid, J.A., Jenkins, C.J., Hastings, M.E., Williams, 

S.J., and Poppe, L.J., 2005, usSEABED: Atlantic coast 

offshore surficial sediment data release: U.S. Geological 

Survey Data Series 118, version 1.0. Online at http://pubs. 

usgs.gov/ds/2005/118/. 

Root, D.H., Menzie, W.D., and Scott, W.A., 1992, Computer 

Monte Carlo simulation in quantitative resource estimation: 

Natural Resources Research, v. 1, no. 2, p. 125-138. 

Schlee, J., 1968, Sand and gravel on the continental shelf off 

the northeastern United States: U.S. Geological Survey 

Circular 602, 9 p. 

Schwab, W.C., Denny, J.F., Butman, B., Danforth, W.W., 

Foster, D.S., Swift, B.A., Lotto, L.L., Allison, M.A. and 

Thieler, E.R., 2000, Sea-floor characterization offshore of 

the New York-New Jersey metropolitan area using sidescan 

sonar: U.S. Geological Survey Open-File Report 00-295. 

Online at http://pubs.usgs.gov/of/of00-295/ 

Singer, D.A., and Menzie, W.D., 2005, Statistical guides to 

estimating the number of undiscovered mineral deposits: 

an example with porphyry copper deposits, in Cheng, 

Qiuming, and Bonham-Carter, Graeme, eds., Proceedings 

of IAMG-The annual conference of the International 

Association for Mathematical Geology: Geomatics 

Research Laboratory, York University, Toronto, Canada, p. 

1028-1033. 

Stetson, H.C., 1938, The sediments of the continental shelf 

off the eastern coast of the United States: Massachusetts 

Institute of Technology and Woods Hole Oceanographic 

Institution, Papers in Physical Oceanography and 

Meteorology, v. 5, no. 4, 48 p. 

Uptegrove, J., Hall, D.W., Waldner, J.S., Sheridan, R.E., 

Lubchansky, B.J., and Ashley, G.M., 1999, Geologic 

framework of the New Jersey inner shelf: results from 

resource-based seismic and vibracore studies, in Puffer, 

J.H., ed., New Jersey beaches and coastal processes from 

a geologic and environmental perspectives: Newark, N.J., 

Geological Association of New Jersey, p. 45-64. 

Williams, S.J., 1976, Geomorphology, shallow subbottom 

structure, and sediments of the Atlantic Inner Continental 

Shelf off Long Island: U.S. Army Corps of Engineers, 

Coastal Engineering Research Center, Technical Paper TP 

76-2, 123 p. 

Williams, S.J., and Duane, D.B., 1974, Geomorphology 

and sediments of the inner New York Bight continental 

shelf: U.S. Army Corps of Engineers, Coastal Engineering 

Research Center, Technical Paper TM-45, 81 p. 

Williams, S.J., Arsenault, M.A., Poppe, L.J., Reid, J.A., Reid, 

J.M. and Jenkins, C.J., 2006, Surficial sediment character 

of the New York-New Jersey offshore continental shelf 

region; a GIS compilation: U.S. Geological Survey OpenFile Report 2006-1046. Online at http://pubs.usgs.gov/ 

of/2006/1046 

Williams, S.J., Reid, J.R., and Manheim, F.T., 2003, A 

bibliography of selected references to U.S. marine sand and 

gravel mineral resources: U.S. Geological Survey Open-File 

Report 03-300, CD-ROM. 

6 Contributions to Industrial-Minerals Research