United States Department of Agriculture

New Jersey Forests 

2013

Forest Service Northern 

Research Station

Resource Bulletin

NRS-109

Publication Date 

January 2017
Abstract

The second full annual inventory of New Jersey’s forests reports more than 2.0 million acres of forest 

land and 77 tree species. Forest land is dominated by oak/hickory forest types in the north and pitch 

pine forest types in the south. The volume of growing stock on timberland has been rising since 1956 

and currently totals 3.3 billion cubic feet. Average annual net growth of growing stock from 2008 to 

2013 was about 65.7 million cubic feet per year. This report includes additional information on forest 

attributes, land-use change, carbon, timber products, and forest health. The following information is 

available online at https://doi.org/10.2737/NRS-RB-109: 1) detailed information on forest inventory 

statistics, methods, and quality assurance of data collection, 2) a glossary of terms, 3) tables that 

summarize quality assurance, 4) a core set of tabular estimates for a variety of forest resources, and 

5) a Microsoft® Access database that represents an archive of data used in this report, with tools that 

allow users to produce customized estimates. 

Acknowledgments

The authors would like to thank the many individuals who contributed to both the inventory and the 

analysis of New Jersey’s forest resources. Primary field crew and quality assurance staff over the 

2009-2013 inventory cycle were Thomas Albright, Joseph Kernan, William Moir, Stephen Potter, 

Richard Starr, Jr., Michael Whitehill, and Thomas Willard. Data management personnel were Charles 

Barnett, James Blehm, Mark Hatfield, Bob Ilgenfritz, Dan Kaisershot, Richard McCullough, Kevin 

Nimerfro, Barbara O’Connell, Jay Solomakos, and Paul Sowers. Thanks also to Courtney Compton, 

Bernard Isaacson, Richard Widmann, and Michael Zsoldos for reviewing the manuscript and 

providing insightful, constructive comments.

Cover: Fall color in southern New Jersey. Photo by New Jersey State Forestry Services, used with permission.

Published by:

U.S. FOREST SERVICE

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Manuscript received for publication February 2016.

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Printed on recycled paper
New Jersey Forests 2013

Susan J. Crocker, Charles J. Barnett, Brett J. Butler, Mark A. Hatfield, Cassandra M. Kurtz, 

Tonya W. Lister, Dacia M. Meneguzzo, Patrick D. Miles, Randall S. Morin, Mark D. Nelson, 

Ronald J. Piva, Rachel Riemann, James E. Smith, Christopher W. Woodall, William Zipse

Contact Author: 

Susan J. Crocker 

scrocker@fs.fed.us 

651-649-5136

About the Authors

Susan J. Crocker, Dacia M. Meneguzzo, Patrick 

D. Miles, Mark D. Nelson, and Christopher W.

Woodall are research foresters with the Forest

Inventory and Analysis (FIA) program, Northern

Research Station, St. Paul, MN.

Charles J. Barnett is a biological scientist with 

the FIA program, Northern Research Station, 

Newtown Square, PA.

Brett J. Butler is a research forester with the 

FIA program, Northern Research Station, 

Amherst, MA.

Mark A. Hatfield is a forester with the 

FIA program, Northern Research Station, 

Durham, NH.

Cassandra M. Kurtz is a natural resources 

specialist with the FIA program, Northern 

Research Station, St. Paul, MN.

Tonya W. Lister and Randall S. Morin are 

research foresters with the FIA program, 

Northern Research Station, Newtown 

Square, PA.

Ronald J. Piva is a forester with the FIA 

program, Northern Research Station, 

St. Paul, MN.

Rachel Riemann is a research forester/

geographer with the FIA program, Northern 

Research Station, Troy, NY.

James E. Smith is a research plant physiologist 

with the FIA program, Northern Research 

Station, Durham, NH. 

William Zipse is a regional forester with the 

New Jersey State Forestry Services, New 

Jersey Department of Environmental Protection, 

Trenton, NJ.
Foreword

It is with great satisfaction that we present to you New Jersey’s statewide forest 

inventory report. This report is a cooperative effort led by the Forest Inventory and 

Analysis program of the Forest Service, U.S. Department of Agriculture, and the New 

Jersey State Forestry Services, New Jersey Department of Environmental Protection 

summarizing conditions and trends in New Jersey’s forest resources. 

Maintaining open space is a value supported by the majority of New Jersey residents. 

Despite New Jersey’s dense population and small size, the State is 40 percent forested. 

As New Jersey’s population has risen, the amount of forest land in the State has 

remained fairly constant since the 1970s. The reversion of farmland to forest plays 

a role in maintaining forest land. In addition, the State’s dedication to conservation 

efforts has expanded public land holdings and promoted the stewardship of private 

lands. 

The continued conservation of forested land in our State is not without its challenges, 

however. New Jersey’s forests are aging and increasing in volume, and regeneration of 

younger trees has been in decline, leaving our forests vulnerable to rapid, widespread 

changes due to succession. These changes could have impacts on water quality, 

wildlife habitat, recreation opportunities, and overall quality of life in the State. 

Threats from insects and diseases, parcelization, invasive species, wildfire, urban 

sprawl, and associated land conversion present additional challenges.

Moving forward, New Jersey land managers must be flexible and adapt to changing 

land use and conditions. With nearly half of our State’s forested lands in private 

ownership, government and private entities will have to meet these challenges 

together. It is our hope that New Jersey Forests, 2013 will provide valuable 

information to land managers. We invite the readers of this report to reach out to 

other interested stakeholders in order to engage in thought-provoking discussion 

about our forest resources.

John Sacco

State Forester

New Jersey State Forestry Services

Department of Environmental Protection
Contents

Highlights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Forest Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Forest Health Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Forest Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Future Forests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

Data Sources and Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Appendix 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Appendix 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Statistics, Methods, and Quality Assurance . . . . . . . . . . . . . . . . . . . . . . . . . . 

Online at https://doi.org/10.2737/NRS-RB-109

Summary Tables for Statistics, Methods, and Quality Assurance . . . . . . . . 

Online at https://doi.org/10.2737/NRS-RB-109

Additional Resources .............................................

Online at https://doi.org/10.2737/NRS-RB-109

 | 1

Highlights

On the Plus Side

• Despite a growing population, statewide estimates of forest area have remained 

relatively consistent since 1971 and currently account for 40 percent of total land 

area.

• New Jersey forests are highly diverse and support a wealth of tree species.

• Maturing forests have contributed to a rise in carbon stocks across the State.

• More than half of New Jersey’s forested resources are held in public ownership, 

which ensures that the land will remain in forest for years to come.

• Forest growth continues to increase and exceeds volume losses from harvest, landuse change, and mortality.

• The quality and quantity of sawtimber resources on timberland have been steadily 

increasing across New Jersey.

• Wildlife habitat provided by standing dead trees (snags) is relatively high; most of 

these snags are Atlantic white-cedar.

• The small amount of forest loss that occurred over the last 5 years was offset by 

gains in forest land. 

Areas of Concern

• Mortality is on the rise, particularly within large diameter stands and among 

hemlock, ash, and cottonwood and aspen species groups.

• Rising housing density within the wildland-urban interface contributes to 

fragmentation of contiguous forest parcels, which is likely to lead to permanent loss 

of wildlife habitat. 

• Largely attributable to hemlock woolly adelgid, mortality of hemlock has reached 

its highest rate since 1987.

• Invasive plant species, including multiflora rose, Japanese honeysuckle, and 

Japanese barberry, are widely distributed across New Jersey.

Photo at left: Shortleaf pine, Silas Little Experimental Forest. Photo by Rich Widmann, U.S. Forest Service.
2 | 

• Emerald ash borer, an exotic tree-killing bark beetle, has been detected in New 

Jersey and threatens the statewide ash resource. Ash mortality was relatively stable 

from 1987 to 1999, but has since doubled.

• The abundance of high density pine stands in southern New Jersey increases 

potential damage from southern pine beetle.

Issues to Watch

• Nearly half of forest land in New Jersey is privately owned; it is important to 

understand landowner needs and desires in order to help protect forests for future 

generations. 

• Though growing-stock volume continues to rise, most forest stands are maturing 

and will eventually undergo density- and age-related issues.

• Increasing demands for bioenergy and carbon will make monitoring forest biomass 

more critical. As the bulk of New Jersey biomass is found in tree boles, forest 

management is closely tied to carbon storage dynamics and future wood availability.

• Under a variety of potential economic and climate scenarios, New Jersey forest land 

is projected to decrease in area over the next 50 years. Nevertheless, knowledge of 

potential future trends will help land managers to manage for desired conditions.
 | 3

Background

Aerial view of wetlands near Cape May Villas. Photo by Anthony Bley, U.S. Army Corps of Engineers.

 | 3
4 | BACKGROUND

An Overview of Forest Inventory

What is a tree?

The U.S. Forest Service’s Forest Inventory and Analysis (FIA) program defines a tree as 

any perennial woody plant species with central stems and distinct crowns that can attain a 

height of 15 feet at maturity. A complete list of the tree species measured in this inventory 

can be found in Appendix 1. An electronic record of every tree measured in this inventory, 

as well as a glossary of additional terms, is available online at https://doi.org/10.2737/NRSRB-109.

What is a forest?

The FIA program defines forest land as land that has at least 10 percent canopy cover of 

live tree species of any size or has had at least 10 percent canopy cover of live species in 

the past, based on the presence of stumps, snags, or other evidence, and not currently 

developed for nonforest use(s) that prevent normal tree regeneration and succession. 

The area with trees must be at least 1 acre in size; and roadside, streamside, and 

shelterbelt strips of trees must be at least 120 feet wide to qualify as forest land. Trees in 

narrow windbreaks, urban boulevards, orchards, and other “nonforest” situations are 

very valuable too, but they are not described in this report.

What is the difference between timberland, reserved forest land, 

and other forest land?

From an FIA perspective, there are three types of forest land: timberland, reserved forest 

land, and other forest land. In New Jersey, about 87 percent of forest land is timberland, 

13 percent is reserved forest land, and less than 1 percent is other forest land.

• Reserved forest land is land withdrawn from timber utilization through legislation or 

administrative regulation. 

• Timberland is unreserved forest land that meets the minimum productivity 

requirement of 20 cubic feet per acre per year at its peak. 

• Other forest land is commonly found on low-lying sites with poor soils where the 

forest is incapable of producing 20 cubic feet per acre per year at its peak. 

In New Jersey’s periodic inventories (1999 and prior), only trees occurring on timberland 

plots were measured. Therefore, volume of trees on forest land cannot be reported for 

those inventories. Since the implementation of the annual inventory system, which in 

New Jersey began with the 2004-2008 inventory, FIA has been able to report volume 

on all forest land. With the first remeasurement of annual plots completed, comparison 
 | 5

of growth, mortality, and removals on forest land is now possible. Because periodic 

inventories reported only on timberland, trend reporting in this publication is primarily 

focused on timberland.

Where are New Jersey’s forests and how many trees are in 

New Jersey?

Where trees grow, how they grow, and the types of forests they form are influenced 

by an array of ecological characteristics, such as terrain, soil type, geology, climate, 

and hydrology, which vary across the landscape. These characteristics help define the 

five physiographic regions of New Jersey: Ridge and Valley, Highlands, Piedmont, 

Inner Coastal Plain, and Outer Coastal Plain (Collins and Anderson 1994) (Fig. 1). 

The unique features of each region influence where forests are found and their 

composition and structure. Exposed bedrock and thin, rocky soils characterize the 

Ridge and Valley section, where oak/hickory and oak/pine forest types are prominent 

on the landscape (Collins and Anderson 1994). Mesic soils, which characterize the 

broad ridges of the Highlands and rolling hills of the Piedmont, then give way to 

white oak/red oak/hickory and maple/beech/birch forests. Soils of the Inner Coastal 

Plain have higher clay content and are thus more fertile than the dry, sandy, acidic 

soils of the Outer Coastal Plain. Therefore, white oak, chestnut oak, scarlet oak, and 

American holly are dominant species within the Inner Coastal Plain; pitch pine, red 

maple, and scrub oaks thrive in the Outer Coastal Plain (Collins and Anderson 1994).

Data Source: NJ Dept. of Environmental 

Protection and the National Atlas of the

United States.

Physiographic Region

County Group

Southern New Jersey

Ridge and Valley

Highlands

Piedmont

Inner Coastal Plain

Outer Coastal Plain

Northern New Jersey

Figure 1.—Physiographic regions and county groups, New Jersey.

Physiographic Region

Ridge and Valley

Highlands

Piedmont

Inner Coastal Plain

Outer Coastal Plain

County Group

Northern New Jersey

Southern New Jersey

Data sources: New Jersey 

Department of Environmental 

Protection and the National 

Atlas of the United States.
6 | BACKGROUND

Forest land area is concentrated in the southeastern and northwestern portions of 

the State (Fig. 2). Forest types in these two regions vary greatly. Northern New Jersey 

is dominated by forest types within the oak/hickory forest-type group and southern 

New Jersey is largely made up of the pitch pine forest type. New Jersey forest land 

contains about 917.4 million trees that are at least 1 inch in diameter at breast height 

(d.b.h., 4.5 feet above the ground). We do not know the exact number of trees because 

the estimate is based on a sample of the total population. Trees were measured 

on 364 forested plots. Full details of sample design and estimation procedures are 

available in Bechtold and Patterson (2005) and a summary explanation is included 

in the Statistics, Methods, and Quality Assurance section available at https://doi.

org/10.2737/NRS-RB-109. 

Processing note: This map was produced by 

linking plot data to MODIS satellite pixels (250 m) 

using gradient nearest neighbor techniques.

Distribution of forest land

Nonforest

Forest

Figure 2.—Distribution of forest land, New Jersey, 2009.

Distribution of 

Forest Land

Forest

Nonforest

Processing note: This map was 

produced by linking plot data to MODIS 

satellite pixels (250 m) using gradient 

nearest neighbor techniques.
 | 7

How do we estimate a tree's volume?

Statistical models are used to predict volumes within a species group or for a specific 

species. Individual tree volumes are based upon species, diameter, and merchantable 

height from trees within the region. Tree volumes are reported in cubic feet or board 

feet based on the International 1⁄4-inch log scale rule.

How much does a tree weigh? 

Specific gravity values for each tree species or group of species were developed at the 

U.S. Forest Service’s Forest Products Laboratory (Miles and Smith 2009) and were 

applied to FIA tree volume estimates to determine merchantable tree biomass (weight 

of tree bole). Total aboveground live-tree biomass is calculated by adding the biomass 

for stumps, limbs, and tops (Woodall et al. 2011). Live biomass for foliage is currently 

not reported. FIA inventories report biomass weights as oven-dry short tons. Ovendry weight of a tree is the green weight minus the moisture content. Generally, 1 ton 

of oven-dry biomass is equal to 1.9 tons of green biomass.

How do we estimate all the forest carbon pools?

FIA does not directly measure the carbon in standing trees; it estimates forest carbon 

pools by assuming that half the biomass in standing live/dead trees consists of carbon. 

Additional carbon pools (e.g., soil, understory vegetation, belowground biomass) are 

modeled based on stand/site characteristics (e.g., stand age and forest type). 

How do we compare data from different inventories?

Data from new inventories are often compared with data from earlier inventories to 

determine trends in forest resources. A pitfall occurs when the comparison involves 

data collected under different schemes or processed using different algorithms. 

Recently, significant changes were made to the methods for estimating tree-level 

volume and biomass (dry weight) for northeastern states, and the calculation of 

change components (net growth, removals, and mortality) was modified for national 

consistency. These changes focus on improving the ability to report consistent 

estimates across time and space—a primary objective for FIA. Regression models 

were developed for tree height and percent cull to reduce random variability across 

datasets. 

Volume and biomass were originally estimated using separate sets of equations; 

recently the component ratio method (CRM) has been implemented (Heath et al. 

2009). With the CRM, determining the biomass of individual trees and forests has 
8 | BACKGROUND

become an extension of FIA volume estimates, allowing biomass estimates for tree 

growth, mortality, and removals to be obtained not only for live trees, but also for 

belowground coarse roots, standing dead wood, and down woody debris.

Another new method, termed the “midpoint method,” has introduced some differences 

in methodology for determining growth, removals, and mortality for a specified 

sample of trees (Westfall et al. 2009). The new approach involves calculating tree size 

attributes at the midpoint of the inventory cycle (2.5 years for a 5-year cycle) to obtain 

a better estimate for ingrowth, mortality, and removals. Although the overall net 

change component is equivalent under the previous and new evaluations, estimates 

for individual components will be different. For ingrowth, the midpoint method can 

produce a smaller estimate because the volumes are calculated at the 5.0-inch threshold 

instead of the actual diameter at the time of measurement. The actual diameter could be 

larger than the 5.0-inch threshold. The estimate for accretion is higher because growth 

from ingrowth, mortality, and removal trees is included. As such, the removals and 

mortality estimates will be higher than before (Bechtold and Patterson 2005).

Reserved status—improved implementation

FIA defines reserved forest land as forest land withdrawn by law(s) prohibiting the 

management of land for the production of wood products (not merely controlling 

or prohibiting wood-harvesting methods). All private forest lands, regardless of 

conservation easements that may restrict harvesting, are considered not reserved. Such 

lands are declared timberland if they meet minimum productivity requirements and 

“other forest” if they do not. Timberland does not include reserved forest land.

In an effort to increase consistency among states and across inventory years, a refined 

set of procedures for determining reserved status have been implemented with version 

6.0 of the FIA field manual, which took effect with the 2013 inventory year (which 

began in October 2012). Furthermore, all previously collected annual inventory data 

(2004 to present) have been updated using the new standardized interpretation. 

Starting with this report, timberland estimates generated for earlier annual 

inventories will differ from previously published estimates. The 2012 inventory was 

the last inventory in which all data were available under the previous and improved 

implementations. Small changes are associated with timberland acreage, number of 

trees, volume, and biomass. The changes associated with the remaining timberland 

estimates are minor given the inherent variability in the associated estimates. The 

improved implementation of the reserved status definition increases the spatial and 

temporal precision of timberland estimates allowing for higher quality trend analyses 

and potentially better forest management decisions.
 | 9

A word of caution on suitability and availability

FIA does not attempt to identify which lands are suitable or available for timber 

harvesting. Land classified by FIA as “timberland” is not necessarily suitable or 

available for timber production. Suitability and availability are subject to changing 

laws, economic and market constraints, physical conditions, adjacency to human 

populations, and ownership objectives. Forest inventory data alone are inadequate 

for determining the area of forest land available for timber production. Additional 

factors, like those provided above, need to be considered when estimating the timber 

base, and these factors may change with time.

How do we produce maps?

A geographic information system (GIS) and various geospatial datasets were used to 

produce the maps in this report. Maps were constructed using (1) categorical coloring 

of New Jersey counties according to forest attributes (such as forest land area), (2) 

a variation of the k-nearest-neighbor (KNN) technique to apply information from 

forest inventory plots to remotely sensed MODIS imagery (250-m pixel size) based 

on the spectral characterization of pixels and additional geospatial information (see 

Wilson et al. 2012 for more information on this technique), or (3) colored dots to 

represent plot attributes at approximate plot location.

Unless otherwise indicated, forest resource data are from FIA; base map layers, such 

as state and county boundaries, were obtained from the National Atlas of the United 

StatesTM (U.S. Geological Survey 2011). Depicted FIA plot locations are approximate. 

Additional FIA data are available at http://fia.fs.fed.us/tools-data/. Sources of other 

geospatial datasets are cited within individual figures. All New Jersey maps are 

portrayed in the State Plane Coordinate System, North American Datum of 1983. 
10 | BACKGROUND
 | 11

Forest Features

Hemlock Pond, Delaware Water Gap National Recreation Area. Photo by Noel Schneeberger, U.S. Forest Service.

 | 11
12 | FOREST FEATURES

Forest Area

Background

Forest ecosystems play an important role in providing wildlife habitat, wood 

products, and clean air and water; therefore, information on the current status 

and trends is essential for assessing the quality and quantity of these resources. As 

fluctuations in estimates of forest land area may indicate changing land use or forest 

health conditions, monitoring these changes provides information necessary for 

management and decisionmaking.

What we found 

Forest land area in New Jersey is an estimated 2.0 million acres, or 40 percent of the 

State’s land base (Fig. 3). Although forest land area has remained stable over the past 5 

years, it has significantly decreased from the 2.2 million acres (46 percent of total land 

area) estimated in 1956. Forest land is found throughout most of the State, though it is 

predominantly found in northwestern and southeastern New Jersey (Fig. 4). 

Since 1987, gains and losses in forest land have varied by county. Sussex, Passaic, 

Burlington, and Atlantic Counties have remained the most heavily forested counties—

each with more than 50 percent forest land—over the past two and a half decades 

(Fig. 4). Forests continue to grow and age. Sawtimber stands predominate, making 

up 68 percent of forest area (Fig. 5). Poletimber stands compose nearly 26 percent of 

forest land. Five percent of forest land contains seedling-sapling stands and 1 percent 

is nonstocked. Across the State, the age of forest stands continues to increase: 68 

percent of forest land is more than 60 years old (Fig. 6). 

1,500

1,750

2,000

2,250

2,500

1955 1965 1975 1985 1995 2005 2015

Forest Land Area (thousand acres)

Year

Figure 3.—Area of forest land by inventory year, New Jersey. 

Error bars represent a 68 percent confidence interval.
 | 13

1

5

9

14

4

15

19

20

3

13

2

18

17

11

10

21

6

12

16

8 7

Figure 4.—Area of forest land as a percentage of county land area by 

inventory year, New Jersey.

1987

2008

1999

2013

Area of Forest Land 

(percentage of 

county land area)

50-70

40-49

30-39

20-29

6-19

0

County List 

1 Sussex

2 Passaic

3 Bergen

4 Warren

5 Morris

6 Essex

7 Hudson

8 Union

9 Hunterdon

10 Somerset

11 Middlesex

12 Mercer

13 Monmouth

14 Burlington

15 Ocean

16 Camden

17 Gloucester

18 Salem

19 Atlantic

20 Cumberland

21 Cape May

0

 200 

 400 

 600 

 800 

 1,000 

 1,200 

 1,400 

 1,600 

Small diameter Medium diameter Large diameter

Forest Land Area (thousand acres)

Stand-size Class

1987

1999

2008

2013

1986 

1998 

2003 

Figure 5.—Area of forest land by stand-size class and inventory year, 

New Jersey. Error bars represent a 68 percent confidence interval.
14 | FOREST FEATURES

0

5

10

15

20

25

30

35

40

45

0-20 21-40 41-60 61-80 81-100 100+

Forest Land Area (percent)

Stand Age (years)

1987

1999

2008

2013

Figure 6.—Proportion of forest land by stand-age class and 

inventory year, New Jersey.

What this means

Although one of the Nation’s smallest and most densely populated states, New Jersey has 

a high concentration of forest land that is widely distributed across the State. Reversion 

of farmland to forest and successful preservation efforts have helped to maintain a 

consistent forest land base since the 1970s concurrent with human population growth. 

As these forests continue to mature, maintaining a diverse range of size and age classes 

will become increasingly important in terms of overall forest health and sustainability.

Forest Biomass

Background

Measurements of total biomass and its allocation among tree components, including 

saplings, tree boles, and tree limbs, help to further our understanding of the distribution 

of forest resources and their availability for different uses (e.g., carbon sequestration, 

wildlife habitat, or biofuels).

What we found

New Jersey forest land supports an estimated 117 million dry tons of aboveground 

live-tree biomass, held almost equally by public and private owners (49 and 51 percent, 

respectively). However, the distribution of biomass across the landscape is uneven, with 

the highest concentrations in the northern half of the State, primarily in the Highlands 

region (Fig. 7). Two-thirds of statewide biomass is contained in the boles of growingstock trees; 19 percent is in growing-stock stumps, tops, and limbs; 6 percent is in 

saplings; and 8 percent is in nongrowing-stock trees (Fig. 8).
 | 15

ocessing note: This map was 

oduced by linking plot data to 

ODIS satellite pixels (250 m) 

ing gradient nearest neighbor 

chniques.

ve-tree and Sapling

iomass on Forest Land

ons/acre)

> 60

40 - 59

20 - 39

< 20

Nonforest

Figure 7.—Distribution of aboveground live-tree biomass on forest land, New Jersey, 2009.

Processing note: This map was produced 

by linking plot data to MODIS satellite 

pixels (250 m) using gradient nearest 

neighbor techniques.

Aboveground Biomass of 

Live Trees on Forest Land 

(tons per acre)

≥60

40-59

20-39

<20

Nonforest
16 | FOREST FEATURES

67%

6%

Growing-stock boles

Growing-stock stumps,

tops, and limbs

19%

 

Nongrowing-stock boles

6%

Nongrowing-stock stumps,

tops, and limbs

2%

Saplings

Figure 8.—Forest biomass on forest land by tree component, 

New Jersey, 2013.

What this means 

Public and private forest landowners play an important role in sustaining forest biomass, 

which is a valuable resource with environmental and economic importance. In light of 

potential opportunities to expand woody biomass for energy production and carbon 

sequestration, it is important to continue to monitor the status and trends of this resource. 

Additionally, because most forest biomass is found in the boles of growing-stock trees, the 

management of forests is closely tied to the dynamics of carbon storage and future wood 

availability. Given the increasing demand to manage biomass components for bioenergy 

and carbon, monitoring forest biomass will become more critical.

Species Composition

Background

Forest composition is constantly evolving. Influenced by the presence or absence of 

disturbances such as timber management, recreation, wildfire, prescribed burning, 

extreme weather, and invasive species, the current state of species composition is 

a reflection of historical and environmental trends within a forest. As a result, the 

composition of species in a forest is an indicator of forest health, growth, succession, 

and the need for stand improvement, i.e., management. Knowledge of the distribution 

of species within a stand allows for the measurement and prediction of change.

What we found 

New Jersey forest land contains 917.4 million trees (1-inch d.b.h. or greater) representing 

77 different tree species (common and scientific names of trees are found in Appendix 1). 
 | 17

Pitch pine and red maple remain the most abundant species by both number and 

volume; combined, they represent 30 percent of total trees by number and 26 percent 

of total volume (Figs. 9 and 10). Oaks are also prolific throughout New Jersey. Fifteen 

species of oaks were recorded on forest land; these species account for 16 percent of all 

species by number and 28 percent of total live-tree volume. Species composition varies 

across the State (Fig. 11A, B). Red maple has decreased in number of trees per acre since 

2008, but it is still the most numerous species per acre in northern New Jersey (Fig. 11A). 

Declines in red maple and sugar maple abundance have accompanied an increase in the 

prevalence of eastern redcedar. In southern New Jersey, pitch pine, red maple, Atlantic 

white-cedar, and white oak are the most numerous species (Fig. 11B). Pitch pine showed 

the greatest reduction in trees per acre since 2008. Pines, which make up 29 percent of 

southern New Jersey’s species composition, decreased from 183 trees per acre in 2008 to 

158 trees per acre in 2013.

0 50 100 150 200 250 

Pitch pine

Red maple

Atlantic white-cedar

Black gum

White oak

Eastern redcedar

American holly

Sassafras

Black cherry

Sweet birch

Sweetgum

Sugar maple

Number of Trees (millions)

Species 2008

2013

Figure 9.—Number of live trees on forest land for the 12 most 

numerous species in 2013, New Jersey. Error bars represent a 68 

percent confidence interval.

0 200 400 600 800 

Pitch pine

Red maple

Yellow-poplar

Northern red oak

White oak

White ash

Chestnut oak

Sweetgum

Black oak

Sweet birch

Atlantic white-cedar

Scarlet oak

Live Volume (million ft3

)

Species

2008

2013

Figure 10.—Volume of live trees on forest land for the 12 most 

voluminous species in 2013, New Jersey. Error bars represent a 68 

percent confidence interval.
18 | FOREST FEATURES

0 20 40 60 80 100 

Red maple

Eastern redcedar

Sweet birch

Sugar maple

White ash

Black gum

Black cherry

Yellow-poplar

American beech

Sassafras

Northern red oak

Chestnut oak

Trees per Acre

A Species

0 50 100 150 200 

Pitch pine

Red maple

Atlantic white-cedar

White oak

American holly

Black gum

Sweetgum

Sassafras

Scarlet oak

Blackjack oak

Scrub oak

Sweetbay magnolia

Trees per Acre

B Species

2008

2013

2008

2013

Figure 11.—Trees per acre for the 12 species with the highest 

densities on forest land in (A) northern New Jersey and (B) southern 

New Jersey. Error bars represent a 68 percent confidence interval.

What this means

Thanks to a rich geologic past, the landscape of New Jersey varies over a wide 

ecological gradient that extends from the mesic soils of the northwest to the sandy, 

acidic soils of the southeast. The range of conditions is reflected in the diverse 

composition of species across the State. In southern New Jersey, there has been 

little change in species dominance, which is likely a reflection of harsher growing 

conditions, to which relatively few species are adapted. The decrease in pine density 

may be due to increased mortality from southern pine beetle activity.
 | 19

Forest Density

Background

The density of a forest indicates the current phase of stand development and has 

implications for diameter growth, tree mortality, and yield. Density is typically 

measured in terms of number of trees or basal area per unit area. Stocking, a relative 

measure of density, represents the degree of tree occupancy required to fully utilize 

the growth potential of the land.

What we found

The density of trees in New Jersey’s forests has gradually decreased since 1987 

(Fig. 12). In contrast, the average volume of live trees per acre of timberland continues 

to increase; currently, total live-tree volume is an estimated 2,088 cubic feet per acre 

(Fig. 13). The level of stocking has remained fairly constant since 1999. Currently, 

overstocked stands, which contain too many trees to support adequate tree growth 

and development, represent only 3 percent of timberland, or 60,000 acres (Fig. 14). 

Most stands are fully stocked (44 percent or 765,000 acres) or moderately stocked 

(40 percent or 700,000 acres). Poorly stocked stands, which do not contain enough 

trees to fully utilize a site, represent 11 percent of timberland, or 181,000 acres 

(Fig. 14).

400

450

500

550

600

650

1985 1990 1995 2000 2005 2010 2015

Density (trees per acre)

Year

Figure 12.—Density of live trees on timberland by inventory year, 

New Jersey. Error bars represent a 68 percent confidence interval.
20 | FOREST FEATURES

1,000

1,300

1,600

1,900

2,200

2,500

1985 1990 1995 2000 2005 2010 2015

Live-tree Volume (ft3 per acre)

Year

Figure 13.—Live-tree volume per acre on timberland by 

inventory year, New Jersey. Error bars represent a 68 percent 

confidence interval.

0

 200 

 400 

 600 

 800 

 1,000 

 1,200 

Overstocked Fully 

stocked

Moderately 

stocked

Poorly 

stocked

Nonstocked

Timberland Area (thousand acres)

Stocking Class

1999

2008

2013

Figure 14.—Area of timberland by stocking class and inventory 

year, New Jersey. Error bars represent a 68 percent confidence 

interval.

What this means 

Decreasing numbers of trees and increasing volume are indicative of a maturing forest 

resource. In the absence of natural or human disturbance, this trend can be expected 

to continue until stands reach a state of senescence. Current stocking levels indicate 

adequate growing conditions, but also show a preponderance of fully stocked stands. 

As trees grow and put on additional volume, these stands are expected to face an 

increased amount of stand stagnation issues, such as density-induced mortality.
 | 21

Carbon Stocks

Background

Among terrestrial ecosystems, forests contain the largest reserves of sequestered 

carbon. Forests sequester carbon from the atmosphere and thus help mitigate 

greenhouse gas emissions. The continuing increase in carbon stocks in New Jersey 

forests contributes to the offset of total U.S. greenhouse gas emissions that result from 

forest fires and the burning of fossil fuels. Carbon accumulates in growing trees via 

the photosynthetically driven production of structural and energy-containing organic 

(carbon) compounds that primarily accumulate in trees as wood. Over time, this 

stored carbon also accumulates in dead trees, woody debris, litter, and forest soils. For 

most forests, the understory grasses, forbs, and nonvascular plants as well as animals 

represent minor pools of carbon stocks. Procedures for the estimation of carbon are 

detailed in U.S. Environmental Protection Agency (2015). 

What we found

Total forest ecosystem carbon stocks in New Jersey are estimated to be 152 million 

tons, a 3 percent increase since 2008. Live trees and soil organic carbon are the largest 

pools and account for 87 percent of forest carbon stocks (Fig. 15). Statewide, 68 

percent of total carbon stocks are in two forest-type groups: oak/hickory and loblolly/

shortleaf pine. Average aboveground carbon per acre increased with increasing stand 

age (Fig. 16). Fifty-eight percent of total aboveground carbon stocks are represented 

by the two age classes spanning stand ages of 61 to 100 years; in contrast, the two 

youngest age classes together account for 6 percent of forest carbon stocks. The largest 

single pool is soil organic carbon within the elm/ash/cottonwood forest-type group, 

which totals 49.8 short tons of carbon per acre (Fig. 17). 

Soil organic carbon 40%

47%

Forest floor/litter 10%

Down dead wood 1% Understory 1%

Standing dead trees 1%

Live trees, saplings 3%

Live trees 5 inch d.b.h., top/branches 7%

Live trees 5 inch d.b.h., bole 28%

Live trees 5 inch d.b.h., stump 2%

Live trees 5 inch d.b.h., coarse roots 7%

Figure 15.—Estimated carbon stocks on forest land by forest ecosystem component, New Jersey, 2013.
22 | FOREST FEATURES

0

5

10

15

20

25

30

35

40

45

50

0-20 21-40 41-60 61-80 81-100 101+

Carbon Stocks (short tons per acre)

Age Class (years)

Aboveground 

live biomass 

Aboveground 

dead wood and litter

Figure 16.—Average carbon stocks per acre for aboveground 

live biomass on forest land by stand-age class, New Jersey, 

2013. Error bars represent a 68 percent confidence interval.

0 10 20 30 40 50 60 70 80 90 100

Additional hardwood types

Additional softwood types

Loblolly/shortleaf pine

Oak/pine

Maple/beech/birch

Oak/hickory

Oak/gum/cypress

Elm/ash/cottonwood

Carbon (short tons per acre)

Forest-type Group Biomass Dead wood Litter SOC

Figure 17.—Average carbon stocks per acre on forest land by 

forest-type group and carbon pool, New Jersey, 2013. SOC 

indicates soil organic carbon.

What this means

New Jersey’s forest carbon stocks continue to rise, as maturing stands accumulate 

carbon, particularly in aboveground components. Given the age-class structure and 

species composition, this trend is likely to persist. Managing forest carbon to help 

offset U.S. greenhouse gas emissions has become increasingly important. Therefore, 

an understanding of trends in carbon storage will be an essential tool for forest 

managers. 
 | 23

Forest Ownership

Background

How land is managed is primarily the owner’s decision. Therefore, landowners largely 

determine the availability and quality of forest resources, including recreational 

opportunities, timber, and wildlife habitat. By understanding their priorities, the 

forest conservation community can better help forest landowners meet their needs, 

and in so doing, help conserve New Jersey’s forests for future generations. The 

National Woodland Owner Survey (NWOS; www.fia.fs.fed.us/nwos), conducted by 

the FIA program, studies private forest landowners’ attitudes, management objectives, 

and concerns. It focuses on the diverse and dynamic group of owners that is the least 

understood—families, individuals, and other unincorporated groups, collectively 

referred to as “family forest owners.” The NWOS data reported here are based on 

the responses from 115 family forest ownerships from New Jersey that participated 

between 2011 and 2013 (Butler et al. 2016).

What we found

More than half (52 percent or 1.0 million acres) of New Jersey forest land is publicly 

owned (Fig. 18). State agencies maintain the greatest percentage (60 percent) of public 

forest land, followed by local government (28 percent) and Federal agencies (12 

percent), such as the U.S. Fish and Wildlife Service. Of the nearly 967,000 privately 

owned acres, most is held by family forest owners (584,000 acres). Corporations and 

other private owners, including conservation organizations and unincorporated clubs 

and partnerships, own an estimated 274,000 acres and 113,000 acres, respectively.

State

31% Local

14%

Federal

6%

Family

29%

Corporate

14%

Other private

6%

Figure 18.—Distribution of forest land by ownership category, 

New Jersey, 2013.
24 | FOREST FEATURES

The majority of family forest land (60 percent or 348,000 acres) is held by owners with at 

least 10 acres of forest land (Fig. 19). Eighty-three percent of family forest owners have 

between 10 and 49 acres of forest land. However, 50 percent of land owned by family 

forest owners is in holdings of 50 acres or more. The primary reasons for owning forest 

land are related to aesthetics, privacy, and nature. The most common activities on family 

forest land are cutting trees for personal use, such as firewood, and personal recreation, 

such as hunting and hiking (Fig. 20). Participation in a preferential property tax program, 

such as the State’s Farmland Assessment program, is fairly common with an estimated 

48 percent of the ownership having partaken. Additionally, 38 percent of owners have 

received forest management advice and 31 percent have a forest management plan (Fig. 

21). The average age of family forest owners in New Jersey is 60 years and 44 percent of 

family forest land is held by people who are 65 years of age or older. 

0 10 20 30 40 50 60 70 80

10-19

20-49

50-99

100-199

200-499

500+

Percentage

Size of Forest Holdings (acres)

Area

Owners

Figure 19.—Area of forest land and number of family forest 

owners by size of forest landholdings, New Jersey, 2013. Error 

bars represent a 68 percent confidence interval.

0 20 40 60 80

Controlled burning

NTFP collection

Road construction/maintenance

Grazing

Fire hazard reduction

Wildlife habitat improvement

Insect reduction

Cutting trees (sale)

Trail construction/maintenance

Invasive species reduction

Recreation

Cutting trees (personal)

Percentage

Owner Activity

Area

Owners

Figure 20.—Area of forest land and number of family forest owners by 

primary activity within the past 5 years, New Jersey, 2013. Categories 

are not exclusive. NTFP indicates nontimber forest products. Error 

bars represent a 68 percent confidence interval.
 | 25

0 20 40 60 80 100

Cost share

Certification

Easement

Management plan

Advice

Tax program

Percentage

Program

Area

Owners

Figure 21.—Area of forest land and number of family forest 

owners by participation in forest management programs, New 

Jersey, 2013. Categories are not exclusive. Error bars represent 

a 68 percent confidence interval.

What this means

The future of the forests lies primarily in the hands of those who own and manage the 

land. It is therefore critical to understand forest owners and the policies and programs 

that can help them conserve forests for current and future generations. Family forest 

owners are the least understood ownership group and the fate of their land is arguably 

the most uncertain; more than half of family forest owners do not have a management 

plan and most have not participated in traditional forest management planning or 

assistance programs, other than preferential property tax programs. Opportunities to 

help these owners increase their engagement and stewardship of their lands can be 

found in programs such as Tools for Engaging Landowners Effectively (http://www.

engaginglandowners.org). As a substantial share of New Jersey’s private forest land 

is owned by individuals aged 65 years and older, much of private forest land in New 

Jersey is at an increased likelihood of a change in ownership. Programs such as Your 

Land, Your Legacy (http://masswoods.net/monthly-update/your-land-your-legacydeciding-future-your-land) and Ties to the Land (http://tiestotheland.org) are being 

implemented to help owners meet their bequest goals. However, it is uncertain who 

future forest owners will be and what they will do with their land. As forest ownership 

in New Jersey is almost equally in public and private ownership, land stewards will 

benefit from collaborative efforts to conserve forest land for future generations. 
26 | FOREST FEATURES

Land-Use Change

Background

A period of rapid population growth in the northeastern United States during the 1990s 

raised a great deal of concern about the effects of increased urban pressures on forest 

resources. Some areas in this region experienced significant loss and fragmentation of 

forest land due to land-use change as the population and urban development increased. 

Current census data suggest that the southern and western regions of the United States 

are now experiencing relatively more population growth and urban development than the 

Northeast. Population growth in New Jersey slowed from 8.6 percent between 1990 and 

2000 to 4.5 percent between 2000 and 2010; this shift in urban pressure may have an effect 

on land-use change in the region. 

To better understand New Jersey’s forest land dynamics, it is important to explore 

land-use change occurring throughout the State. FIA characterizes the area of the State 

using several use categories, which can be generalized to the following classes: forest, 

agriculture (including pasture and cropland), developed land, rights-of-way, water, and 

other nonforest land. By comparing land use on current inventory plots with land use 

recorded at the same location during the previous inventory, we can characterize forest 

land-use change. Understanding land-use change dynamics helps land managers make 

informed policy decisions. Because analysis of land-use change is based solely on plots 

measured in 2008 and remeasured in 2013, estimates may not be directly comparable to 

estimates that include all available plots.

What we found

The majority (60 percent) of land in New Jersey is nonforest, and most nonforest land is 

in developed uses. Little change in land use occurred between 2008 and 2013. Most of the 

State remained forested (38 percent) or stayed nonforest (60 percent); only 2 percent of land 

had a forest loss or forest gain (Fig. 22). Between 2008 and 2013, forest land decreased by 

53,000 acres; however, this was offset by a gain of 57,000 acres, resulting in no appreciable 

net change in forest land area (Fig. 23). 

Analysis of forest loss and gain by land use indicates that areas that are the source of new 

forest land have a similar land-use distribution to the nonforest areas that were formerly 

forest. Gains in forest land come from developed land (48 percent) and rights-of-way (15 

percent) converting to forest (Fig. 24). Agricultural land uses account for 24 percent of 

forest gains. The majority (56 percent) of gross forest loss is from forest land converting 

to developed land, specifically commercial and residential development. Sixteen percent 

of forest loss was classified as agricultural land uses (Fig. 24). Unlike the 2008 inventory, 

where forest loss was generally occurring in the more populated areas of the State, there 

is no strong spatial pattern in the distribution of forest change plots in New Jersey in 2013 

(Crocker et al. 2011) (Fig. 25).
 | 27

38%

1%

1%

60%

Remained forest

Forest gain

Forest loss

Remained nonforest

Figure 22.—Proportion of plots that remained forest, remained 

nonforest, or showed a loss or gain in forest land, New Jersey, 

2008 to 2013.

0 25 50 75

Forest loss

Forest gain

Area (thousand acres)

Type of Change Developed Agriculture Other nonforest Water

Figure 23.—Area of forest loss and forest gain by land-use 

category, New Jersey, 2008 to 2013. Developed class includes 

rights-of-way. Error bars represent a 68 percent confidence interval.

Water

4%

Agriculture

10%

Cropland

6%

Developed

56%

Right-of-way

7%

Other nonforest

17%

Forest Loss

Water

3% Agriculture

6%

Pasture

10%

Cropland

8%

Developed

48%

Right-of-way

15%

Other nonforest

10%

Forest Gain

Figure 24.—Forest gain by previous land use and forest loss by current 

land use, New Jersey, 2008 to 2013.
28 | FOREST FEATURES

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Remained forest

! Forest gain

! Forest loss

Remained nonforest

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Figure 25.—Distribution of remeasurement plots showing forest 

gains and losses, New Jersey, 2008 to 2013. Plot locations are 

approximate.

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Land Status on Remeasured Plots

Remained forest

! Forest gain

! Forest loss

Remained nonforest

!

!

FIA Remeasured Plots

Forest gain

Forest loss

Remained nonforest

Remained forest

What this means

Since the late 1980s, forests in the northeastern United States have been under pressure 

from urban expansion and increased population growth. A great deal of concern has 

been expressed regarding the effect of this growth on the forest resource; in particular, 

people worried that conversion to urban uses could cause significant forest loss. To a 

large extent, those pressures and concerns have lessened for many states in the region. 

Population growth in New Jersey is below the national average and the area of forest land 

appears to have stabilized, perhaps aided by the large acreage of publicly owned forest 

land. The small amount of forest loss that has occurred over the last 5 years has been 

offset by gains in forest land. 

Some gains and losses in forest land may be from marginal tracts of forest land 

moving into and out of the forest land base. Movement between forest and nonforest 

classifications may be a result of land meeting or not meeting FIA’s definition of forest 

land due to small changes in understory disturbance, forest extent, or forest cover. These 

fluctuations likely contribute to the losses from and gains in developed land and rightsof-way. In contrast with the net loss of 4 percent of forest land in the 2008 inventory, 

gains in forest land equaled forest losses in the 2013 inventory (Crocker et al. 2011). The 

difference in net change between the two inventories can be attributed to a decrease in 

the amount of gross forest losses coupled with a small increase in gross forest gains. 
 | 29

Forest Growth

Background

A forest stand’s capacity for growth, that is, for trees to increase in volume, is an 

indication of the overall condition of the stand and more specifically of tree vigor, 

forest health, and successional stage. Forest growth is measured as average annual 

net growth, where net growth is equivalent to gross growth minus mortality. Average 

annual net growth represents an average for the annual change in volume between 

previous and current inventories for the individual tally trees before accounting for 

the impact of removals.

What we found 

Despite a sharp rise and fall in net growth between 1999 and 2013, the overall rate of 

growing-stock growth on timberland has steadily increased since 1971; net growth 

of growing stock currently averages 65.7 million cubic feet per year (Fig. 26). Seventy 

percent of net growth resulted from growth in hardwoods. However, pitch pine had 

the highest growth, followed by yellow-poplar, red maple, and northern red oak 

(Fig. 27). In contrast, growth of white oak has significantly decreased since 2008. 

The bulk of growth (78 percent) has occurred in the large diameter stand-size class. 

Growth-to-volume ratios decreased for most species groups in 2013, particularly 

within the other red oaks and select white oaks groups (Fig. 28). 

0

 10 

 20 

 30 

 40 

 50 

 60 

 70 

 80 

 90 

 100 

1955 1965 1975 1985 1995 2005 2015

Annual Growth (million ft3 per year)

Year

Figure 26.—Average annual net growth of growing stock on 

timberland by inventory year, New Jersey. Error bars represent 

a 68 percent confidence interval. 
30 | FOREST FEATURES

0 5 10 15 20 25

Pitch pine

Yellow-poplar

Red maple

Northern red oak

Black oak

Sweetgum

Chestnut oak

White oak

Pignut hickory

Average Annual Growth

(million ft3

 per year)

Species

2008

2013

Figure 27.—Average annual net growth of growing stock on 

timberland for the nine species with the highest growth in 2013, 

New Jersey. Error bars represent a 68 percent confidence interval.

-6 -4 -2 0 2 4 6

Black walnut

Other yellow pines

Beech

Yellow-poplar

Select red oaks

Soft maple

Other red oaks

Other eastern softwoods

Select white oaks

Ash

Eastern hemlock

Ratio of Growth to Volume (percent)

Species Group

2008

2013

Figure 28.—Average annual net growth expressed as a 

percentage of total growing-stock volume on timberland for 11 

selected species groups, New Jersey. Error bars represent a 68 

percent confidence interval.

What this means

Even though the overall rate of growth on New Jersey’s forests is generally increasing, 

the preponderance of growth is occurring within large diameter stands, which 

indicates that mature trees are continuing to add volume. Several economically 

desirable tree species, such as northern red oak and white oak, are showing reductions 

in annual growth each year, as well as low growth relative to their total volumes. For 

species like ash and eastern hemlock, low growth rates relative to volume are likely 

due to activity from emerald ash borer and hemlock woolly adelgid (see Emerald 

Ash Borer on page 46 and Hemlock Woolly Adelgid on page 52). Given the declining 

growth rates, trends should continue to be monitored in the future.
 | 31

Tree Mortality

Background

Forest health, vigor, and the rate of accretion and depletion are all influenced by tree 

mortality. Mortality can be caused by insects, disease, adverse weather, succession, 

competition, fire, old age, or human or animal activity, alone or in combination. Tree 

volume lost as a result of land clearing or harvesting is not included in mortality 

estimates. Growing-stock mortality estimates represent the average cubic-foot volume 

of sound wood in growing-stock trees that died each year as an average for the years 

between inventories.

What we found 

Following an early decline, the rate of mortality has increased since 1987 (Fig. 29). 

Average annual mortality of growing stock on timberland is currently an estimated 

38.2 million cubic feet per year, or 1.2 percent of total growing-stock volume. 

Seventy-nine percent of mortality occurred within large diameter stands. The other 

red oaks species group, which includes black oak and pin oak, had the highest 

mortality, followed by ash and other yellow pines (Fig. 30). Mortality-to-volume 

ratios generally increased between 2008 and 2013 (Fig. 31), such that only 35 percent 

of trees had mortality-to-volume ratios less than 1 percent. Eastern hemlock had the 

highest mortality-to-volume ratio at 4.6 percent. Cottonwood and aspen, eastern 

white and red pine, other eastern soft hardwoods, and other red oaks had mortality 

ratios greater than 2 percent (Fig. 31). 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1950 1960 1970 1980 1990 2000 2010 2020

Ratio of Mortality to Volume (percent)

Year

Figure 29.—Average annual mortality of growing stock as a 

percentage of total growing-stock volume on timberland by 

inventory year, New Jersey. Error bar represents a 68 percent 

confidence interval.
32 | FOREST FEATURES

0 2 4 6 8 10 

Other red oaks

Ash

Other yellow pines

Other eastern softwoods

Soft maple

Select white oaks

Select red oaks

Other eastern soft hardwoods

Average Annual Mortality 

(million ft3

 per year)

Species Group

2008

2013

Figure 30.—Average annual mortality of growing stock on 

timberland for the eight species groups with the highest 

mortality in 2013, New Jersey. Error bars represent a 68 

percent confidence interval.

0 1 2 3 4 5 6 7 8

Select red oaks

Other yellow pines

Yellow birch

Soft maple

Hard maple

Ash

Other eastern softwoods

Other red oaks

Other eastern soft hardwoods

Eastern white and red pine

Cottonwood and aspen

Eastern hemlock

Ratio of Mortality to Volume (percent)

Species Group

2008

2013

Figure 31.—Average annual mortality of growing stock as a 

percentage of total growing-stock volume on timberland for 

12 selected species groups by inventory year, New Jersey. 

Error bars represent a 68 percent confidence interval.

What this means

Mortality is a natural process in forest stands as they develop and change over time. 

Over the past few decades, the rate of tree mortality across New Jersey has risen. High 

mortality rates within the eastern hemlock and cottonwood and aspen species groups 

indicate a yearly loss greater than 3 percent of statewide volume. The increasing 

rate of mortality of hemlock likely reflects hemlock woolly adelgid activity. As tree 

mortality is a crucial component of overall forest health, continued monitoring will 

help to identify future areas of concern.
 | 33

Tree Removals

Background

One way to analyze forest sustainability is to assess change in tree volume as a result 

of removals. Removals include harvested trees and trees lost due to a change in land 

use, in other words, living trees previously on land classified as forest land now on 

land classified as nonforest land. Changes in the quantity of growing stock removed 

help to identify trends in land-use change and forest management. Because removals 

are usually recorded on a limited number of plots, the estimates for removals show 

greater variance than those for growth, mortality, or area. Like forest growth, the rate 

at which trees are removed represents the annual average of removals that occurred 

between previous and current inventories.

What we found 

Annual growing-stock removals rates relative to volume have fallen since 2008 and 

now roughly approach 1987 estimates (Fig. 32). Growing stock is currently removed 

from timberland at an average of 17.9 million cubic feet per year; of this, 37 percent 

of removals occurred as a result of a change in land use. As a percentage of total 

growing-stock volume, the statewide removals rate is 0.3 percent (Fig. 32). Total 

removals were highest in the sweetgum, other red oaks, and select red oaks species 

groups (Fig. 33). Removals-to-volume ratios decreased for many species groups, most 

notably for black walnut (Fig. 34).

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1950 1960 1970 1980 1990 2000 2010 2020

Ratio of Removals to Volume (percent)

Year

Figure 32.—Average annual removals of growing stock as a 

percentage of total growing-stock volume on timberland by 

inventory year, New Jersey. Error bar represents a 68 percent 

confidence interval.
34 | FOREST FEATURES

0 2 4 6 8 10 

Sweetgum

Other red oaks

Select red oaks

Select white oaks

Other yellow pines

Yellow-poplar

Other white oaks

Ash

Average Annual Removals

 (million ft3

 per year)

Species Group

2008

2013

Figure 33.—Average annual removals of growing stock on timberland 

for the eight species groups with the highest removals in 2013, New 

Jersey. Error bars represent a 68 percent confidence interval.

-1 0 1 2 3 4 5

Sweetgum

Other red oaks

Select red oaks

Yellow-poplar

Hard maple

Select white oaks

Other eastern soft hardwoods

Soft maple

Other yellow pines

Other white oaks

Black walnut

Ratio of Removals to Volume

(percent)

Species Group

2008

2013

Figure 34.—Average annual removals of growing stock as a 

percentage of total growing-stock volume on timberland for 11 

selected species groups by inventory year, New Jersey. Error bars 

represent a 68 percent confidence interval.

What this means

Removals rates are indicative of both harvest and land-use change. The rate of 

removals (0.3 percent) is far less than mortality (1.2 percent). On the other hand, the 

rate of growth averages 1.5 percent, exceeding both removals and mortality. From 

a statewide perspective, removals appear to be in balance with forest growth and 

mortality, such that total volumes continue to increase. However, this may not be the 

case at smaller scales (e.g., county) or for specific species. In these cases, removals 

rates should be monitored and evaluated on a case-by-case basis.
 | 35

Forest Health Indicators

Shortleaf and pitch pine stand, Silas Little Experimental Forest. Photo by Rich Widmann, U.S. Forest Service.

 | 35
36 | FOREST HEALTH INDICATORS

Down Woody Materials

Background 

Down woody materials, in the form of fallen trees and shed branches, fulfill a critical 

ecological niche in the forests of New Jersey. These materials provide valuable wildlife 

habitat, structural diversity, and a store of carbon/biomass. They also contribute to 

forest fire hazards via surface woody fuels. Down woody materials include fine woody 

debris (diameter less than 3 inches), coarse woody debris (diameter of 3 inches or 

greater), and residue piles.

What we found 

The total carbon stored in down woody materials on New Jersey forest land exceeded 

2.3 million tons (Fig. 35). Downed woody debris carbon was irregularly distributed 

by stand age class with moderately aged stands having the highest total carbon (1.1 

million tons). The downed dead wood biomass across the State was dominated by fine 

woody debris at about 2.7 million tons, representing nearly 60 percent of statewide 

totals (Fig. 36). The total volume of coarse woody debris was highest in the private 

ownership category at 132.1 million cubic feet (Fig. 37). State and local forests had the 

second largest totals of coarse woody debris volume (72.4 million cubic feet). As there 

is a relatively sparse sample intensity of downed dead wood plots across New Jersey, 

no dead wood piles were sampled and sampling uncertainty is high.

-200

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

0-20 21-40 41-60 61-80 81-100 100+

Total Carbon (thousand tons)

Stand Age (years)

Figure 35.—Total carbon in down woody materials by 

stand-age class on forest land in New Jersey, 2006 to 

2010. Error bars represent a 68 percent confidence interval.
 | 37

59%

41%

0%

Fine woody debris

Coarse woody debris

Piles

Figure 36.—Proportion of down woody biomass on forest land by dead 

wood component, New Jersey, 2006 to 2010.

0

50

100

150

200

250

National 

Forest

Other 

Federal

State and 

Local

Private

Volume (million ft3

)

Ownership Group

Figure 37.—Total volume of coarse woody debris on forest 

land by ownership group, New Jersey, 2006 to 2010. Error 

bars represent a 68 percent confidence interval.

What this means 

The fuel loadings of down woody materials can be considered a forest health hazard 

in times of drought or in isolated stands with excessive tree mortality. Although 

carbon stocks of down woody materials are small compared to those of soils and 

standing live biomass statewide, they are a critical component of the carbon cycle, 

serving as a transitional stage between live biomass and other detrital pools such as 

litter. Beyond transition of dead wood carbon to other pools, these carbon stocks may 

be reduced due to increased rates of decay if future temperature and precipitation 

patterns change (Russell et al. 2014a, 2014b). This is an important consideration 

because of the lack of coarse woody debris in New Jersey. The loss of dead wood 
38 | FOREST HEALTH INDICATORS

carbon stocks could mean the reduction of other pools in the future. Unlike in 

southeastern states, where industrial management of forests is more common, dead 

wood piles were not sampled in this first down woody materials inventory of New 

Jersey’s forests (Woodall et al. 2013). Considering that the vast majority of coarse 

woody debris volume was estimated to be in private ownership, management of New 

Jersey’s private forests may affect the future of down woody material contributions to 

statewide forest carbon stocks and wildlife habitat (i.e., stand structure). As estimated 

fuel loadings were not extremely high across the State, the fire risk associated with 

down woody materials may be outweighed by the numerous ecosystem services that 

they provide.

Tree Damage and Crown Health

Background

Tree damage is assessed for all trees with a d.b.h. of 5.0 inches or greater. Up to two 

of the following types of damage can be recorded: insect damage, cankers, decay, fire, 

animal damage, weather, and logging damage. If more than two types of damage are 

observed, decisions about which two are recorded are based on the relative abundance 

of the damaging agents (U.S. Forest Service 2010a). 

Tree crown condition is influenced by various biotic (e.g., insects, diseases, invasive 

plants, and animals) and abiotic stressors (e.g., drought, flooding, cold temperatures, 

nutrient deficiencies, soil moisture and aeration, and pollutants). Crown dieback is 

defined as recent mortality of branches with fine twigs and reflects the severity of 

recent stresses on a tree. A crown was labeled as “poor” if crown dieback was greater 

than 20. This threshold is based on findings by Steinman (2000) that associated crown 

ratings with tree mortality. Additionally, crown dieback has been shown to be the best 

crown variable to use for predicting tree survival (Morin et al. 2015).

What we found

Damage was recorded on about 14 percent of the trees in New Jersey, but there was 

considerable variation between species. The most frequent damage on all species was 

decay (11 percent), which ranged from 5 percent on Atlantic white-cedar and pitch 

pine to more than 15 percent on white ash and red maple. The occurrence of all other 

injury types was very low (Table 1).
 | 39

Table 1.—Percentage of trees with damage by damage type and species, New Jersey, 2013

Damage 

type All

Atlantic 

whitecedar

Black 

oak

Chestnut 

oak

Northern 

red oak

Pitch 

pine

Red 

maple

Sweetgum

White 

ash

White 

oak

Yellowpoplar

None 86 92 87 91 87 93 77 90 80 88 88

Animal 0 0 1 1 1 0 0 0 0 1 0

Cankers 1 0 1 0 0 0 0 0 0 0 0

Decay 11 5 12 7 10 5 21 8 18 10 9

Insect damage 1 0 0 0 0 0 0 0 0 1 0

Logging 0 0 0 0 1 0 0 1 0 1 1

Other 1 2 1 2 0 2 1 2 1 1 1

Weather 0 0 0 0 0 0 1 0 2 0 1

The incidence of poor crown condition is low across New Jersey with no discernable 

spatial pattern (Fig. 38). Black oak has the highest percentage of basal area with poor 

crowns (13 percent); all other species have less than 5 percent (Table 2). For northern 

red oak, the proportion of basal area with poor crowns decreased substantially since 

2008. Mean crown dieback ranges from less than 1 percent for pitch pine up to 5 

percent for black oak (Table 3). The proportion of the trees that died increased with 

increasing crown dieback (Fig. 39). Half of trees with crown dieback greater than 20 

percent in 2008 were dead by the 2013 inventory.

Live-tree Basal Area 

with Poor Crowns

(percent of all trees)

5 - 6

< 5

0

Nonforest

Forest

Processing note: This map was produced by 

linking plot data to MODIS satellite pixels (250 

m) using gradient nearest neighbor techniques

Processing note: This map was 

produced by linking plot data to 

MODIS satellite pixels (250 m) using 

gradient nearest neighbor techniques.

Figure 38.—Distribution of plots by percentage of live-tree basal area with 

poor crowns, New Jersey, 2013. Depicted plot locations are approximate.

Percentage of 

Live-tree Basal 

Area with Poor 

Crowns

0.0

0.1-5.0

5.1-9.0

Forest

Nonforest

Water
40 | FOREST HEALTH INDICATORS

Table 2.—Percentage of live-tree basal area with poor crowns for eight selected species by inventory year, New Jersey

Percentage of Live-tree Basal Area with Poor Crowns

Species 2008 2013

Black oak 7.3 12.7

Atlantic white-cedar 0.0 4.9

White ash 0.0 4.0

White oak 4.5 2.8

Red maple 0.0 0.7

Pitch pine 0.3 0.4

Sweetgum 0.0 0.0

Northern red oak 9.1 0.0

Table 3.—Mean crown dieback and other statistics for live trees (5-inch d.b.h. or greater) on forest land by species, 

New Jersey, 2013

Species Trees Mean SE Minimum Median Maximum

number ----------------------------- percent ----------------------------

Black oak 25 4.8 2.3 0 0 55

Red maple 60 4.2 1.7 0 0 99

White ash 9 3.9 2.7 0 0 25

White oak 54 2.4 0.6 0 0 20

Atlantic white-cedar 43 1.9 0.9 0 0 30

Northern red oak 14 1.4 0.6 0 0 5

Sweetgum 18 1.4 0.8 0 0 10

Pitch pine 186 0.6 0.3 0 0 40

0

10

20

30

40

50

60

70

80

90

100

0 1-10 11-20 >20

Frequency (percent)

Crown Dieback (percent)

Cut

Mortality

Survivor

Figure 39.—Distribution of crown dieback by tree survivorship 

for remeasured trees, New Jersey, 2008 to 2013.
 | 41

What this means

Overall, New Jersey’s trees are generally in good health. As in most eastern forests, 

decay is the most commonly observed damage across the State. This is not unusual 

given that the majority of New Jersey’s forests are large diameter stands composed of 

mature trees. Additionally, red maple is a relatively short-lived species that is likely to 

develop decay as it ages. The health of tree crowns in maple and ash species should 

be monitored closely for future impacts expected from Asian longhorned beetle and 

emerald ash borer.

Fragmentation and Urbanization of Forest Land

Background

Forest fragmentation is the process by which contiguous tracts of forest land are 

broken down into smaller, more isolated forest patches that are surrounded by 

nonforest land uses, such as urban development or agriculture (Wilcox and Murphy 

1985). This results in a reduction of continuous or core forest land and an increase in 

edge habitat. Fragmentation often has negative effects, including the loss of wildlife 

habitat and biodiversity, and the increased prevalence of invasive species (Honnay 

et al. 2005). To compare changing forest condition and the degree of fragmentation 

across the landscape, an adaptation of the spatial integrity index (SII) developed by 

Kapos et al. (2000) was used to create a single fragmentation metric that integrates 

measures of patch size, local forest density, and patch connectivity1

. SII classes range 

from core forest to unconnected forest fragments, and are applied at a 30 m scale. 

Forest parcels that did not meet the definition of core forest or unconnected forest 

fragment were scaled into low, medium, and high integrity classes. 

Urbanization is a major cause of fragmentation, particularly when housing 

development occurs in or near forest land (Radeloff et al. 2005). The zone where 

undeveloped wildland vegetation intermingles with human development (with at 

least one house per 40 acres) is called the wildland-urban interface (WUI). Not only 

does housing development that takes place in the WUI contribute to the effects of 

fragmentation, but homes and structures built within the WUI face significant risk 

from wildfire (Radeloff et al. 2005).

1

 Riemann, R. 2014. Adaptation of a spatial integrity index to 30 m and 250 m scales, and its application across 

the northeastern United States. Unpublished paper on file at U.S. Forest Service, Northern Research Station, 

Forest Inventory and Analysis Program, Troy, NY.
42 | FOREST HEALTH INDICATORS

0 20 40 60 80 100

Warren

Union

Sussex

Somerset

Salem

Passaic

Ocean

Morris

Monmouth

Middlesex

Mercer

Hunterdon

Hudson

Gloucester

Essex

Cumberland

Cape May

Camden

Burlington

Bergen

Atlantic

Forest Land Area (percent)

County

Forest 

Fragment

Low 

Integrity

Medium 

Integrity

High 

Integrity

Core 

Forest

Figure 40.—Forest land by spatial integrity class and county, 

New Jersey, 2006. 

What we found 

New Jersey is largely made up of core forest parcels, which compose 55 percent of 

forest land (Figs. 40 and 41). Core forest parcels are most abundant in Passaic and 

Sussex Counties (Fig. 40). Twenty-one percent of forest parcels have high spatial 

integrity; 14 percent are in unconnected fragments and 9 percent have medium or 

low integrity. Forest connectivity is highest in northwestern and southeastern New 

Jersey, and lowest within the New York City/Philadelphia/Delaware corridor, which 

stretches from the northeastern portion of the State to the southwestern portion (Fig. 

41). Average patch size by county ranged from 8 to 153 acres (Fig. 42). Larger patches 

tend to be found in the northwestern part of the State, and the smallest patches are 

found near developed areas. Conversion of forest land to developed land was highest 

in Hudson (8 percent), Bergen (3 percent), and Essex Counties (3 percent); in each of 

these counties, average patch size decreased by 1 acre since 2006.

The area of forested WUI is steadily growing, increasing from 42 percent in 1990 to 46 

percent in 2010 (Table 4). WUI areas are primarily clustered along forested margins, 

and within core forest parcels throughout the State, particularly in the Pine Barrens 

of southern New Jersey and in the Highlands of northern New Jersey (Fig. 43). WUI 

data and SII data should be combined for a more detailed depiction of fragmentation. 

In so doing, the proportion of core forest land decreases from 55 percent to 37 

percent statewide.
 | 43

Processing note: This map was produced 

by calculating the spatial integrity index for 

forested NLCD 2006 pixels (30 m).

Spatial Integrity Class

Core Forest

High Integrity

Medium Integrity

Low Integrity

Forest Fragment

Nonforest

Processing note: This map was produced by 

calculating the spatial integrity index for forested 

NLCD 2006 pixels (30 m).

Spatial Integrity Class

Core Forest

High Integrity

Medium Integrity

Low Integrity

Forest Fragment

Nonforest

Figure 41.—Distribution of forest land by spatial integrity class, New Jersey, 2006. 
44 | FOREST HEALTH INDICATORS

19

21

23

67

48

22

20

65

26

35

47

47

35

45

88 153

13

9

23

8

62

(acres)

> 100

Data source: Estimates of 

patch size are derived from 

the 2011 National Land 

Cover Dataset.

Average Patch Size

< 15

15 - 30

31- 60

61 - 100

Average Patch Size 

(acres)

>100

61-100

31-60

15-30

<15

Data source: Estimates of 

patch size are derived from 

the 2011 National Land 

Cover Dataset.

Figure 42.—Average forest patch size (derived from NLCD 

2011) by county, New Jersey.

Table 4.—Percentage of forest land within the wildland-urban interface by county and year, New Jersey

County 1990 2000 2010

Atlantic 48 51 53

Bergen 29 34 39

Burlington 16 16 19

Camden 45 46 42

Cape May 41 42 46

Cumberland 30 33 32

Essex 31 28 29

Gloucester 54 53 56

Hudson 0 0 0

Hunterdon 60 60 66

Mercer 46 47 55

Middlesex 44 42 43

Monmouth 42 45 47

Morris 59 60 60

Ocean 22 24 23

Passaic 33 34 43

Salem 59 59 65

Somerset 58 62 62

Sussex 43 43 46

Union 48 49 47

Warren 53 54 56

Total 42 45 46
 | 45

Figure 43.—Distribution of forest land by wildland-urban interface status, New Jersey, 2010. 

Distribution of 

Forest Land

Non-WUI

WUI

Nonforest

Data sources: WUI 2010 data are based on 

the 2010 Census, NLCD 2006, and the PAD 

v1.1; FIA 2009 data; and the National Atlas of 

the United States. Processing note: Forest/

nonforest data were produced by linking plot 

data to MODIS satellite pixels (250 m) using 

gradient nearest neighbor techniques.
46 | FOREST HEALTH INDICATORS

What this means

Fragmentation and urbanization continue to influence the function and health of New 

Jersey’s forests. Even though there is a large percentage of core forest land, the arrangement 

of these parcels is not evenly distributed across the landscape. Larger tracts of continuous 

forest land are concentrated in the northwest and southeast. The remaining forest patches 

are small, isolated, and scattered within areas of heavy residential and urban development. 

Rising housing density within the WUI has further fragmented core forest land. 

Development within the WUI increases encounters with wildlife and heightens the risks 

associated with fire suppression. The latter of these risks is greatest within the fire-adapted 

landscape of the Pine Barrens, which burn on a regular basis, thus increasing the need to 

protect human populations and structures from wildfire damage. Continued development 

will further fragment existing forest land and result in long-term or permanent loss of 

forest habitat, elevated risk of invasion by nonnative species, reductions in native species 

diversity, and loss of forest connectivity necessary for wildlife.

Forest Insects 

Emerald Ash Borer

Background

A wood-boring beetle native to Asia, emerald ash borer (Agrilus planipennis; EAB) is 

a pest of all North American ash (Fraxinus spp.). Additionally, this insect has recently 

been found to attack white fringetree (Chionanthus virginicus), an understory shrub 

native to New Jersey but not tallied by FIA (Cipollini 2015, Herms and McCullough 

2014, Natural Resources Conservation Service 2015). Although EAB shows some 

preference for stressed trees, all trees 1 inch in diameter or greater are susceptible 

regardless of vigor (Herms and McCullough 2014). Since its discovery in southeastern 

Michigan in 2002, EAB has been identified in 25 states as of October 2015. EAB was not 

found in New Jersey during the 2013 inventory period; however, it was confirmed in 

Somerset County in May 2014. 

What we found

There are an estimated 23.6 million ash trees (1-inch d.b.h. or greater), about 3 percent 

of total species composition, on New Jersey forest land. White ash is the most numerous 
 | 47

ash species in the State, making up 92 percent of total ash abundance; green ash and 

black ash make up 5 percent and 3 percent, respectively. Ash is distributed across 

much of the State, but most of it is concentrated in northern New Jersey (Fig. 44). Ash 

accounts for 251.2 million cubic feet of live-tree volume on forest land.

Processing note: This map was 

produced by linking plot data to 

MODIS satellite pixels (250 m) 

using gradient nearest neighbor 

techniques.

Ash Basal Area

(ft2

/acre)

No Ash Detected

< 5

5 - 20

> 20

EAB present

Ash Basal Area

(ft2

 per acre)

>20

5-20

<5

No ash

EAB present 

Processing note: This map was produced 

by linking plot data to MODIS satellite pixels 

(250 m) using gradient nearest neighbor 

techniques. 

Figure 44.—Ash density on forest land, New Jersey, 2009. EAB-positive counties as of October 1, 2015.
48 | FOREST HEALTH INDICATORS

Due to a small sample size, mortality estimates for ash have large sampling errors. Still, 

ash mortality has significantly increased, rising from 535,000 million cubic feet in 1987 

to 3.5 million cubic feet in 2013 (Fig. 45). Though not statistically significant, the trend 

line suggests an increase between 1999 and 2013. With the exception of Salem County, 

ash mortality primarily occurred in northern New Jersey (Fig. 46). Somerset County, 

where EAB was first detected, had the highest mortality of ash (66 percent). 

0

1

2

3

4

5

6

7

8

9

1985 1990 1995 2000 2005 2010 2015

Ash Mortality (million ft3

)

Year

Figure 45.—Mortality of ash growing stock on timberland by 

inventory year, New Jersey. Error bars represent a 68 percent 

confidence interval.

Figure 46.—Ash mortality expressed as a percentage of total 

tree mortality on forest land by county, New Jersey, 2013. 

EAB-positive counties as of October 1, 2015.

Ash Mortality (percent)

>30

20-29

10-19

<10

No ash

EAB present 
 | 49

What this means

As EAB has caused extensive ash mortality throughout the eastern United States, 

it represents a significant threat to the ash resource in New Jersey. Ash mortality is 

high in several northern New Jersey counties, but EAB has not been identified in 

all of them. Counties with high ash mortality that are not currently known to be 

infested serve as good candidates for increased EAB survey efforts. Mortality of ash is 

expected to increase as EAB spreads. The loss of ash in forested ecosystems will affect 

species composition and alter community dynamics. Continued monitoring of ash 

resources will help to identify the long-term impacts of EAB in forested settings. 

Southern Pine Beetle

Background

Outbreaks of southern pine beetle (Dendroctonus frontalis; SPB) have been 

documented in the United States as early as the 1750s (Thatcher et al. 1980). SPB 

has since proven to be one of the most destructive pests of pine in the southern 

United States (Clarke and Nowak 2009). Pitch, shortleaf, loblolly, pond, and Virginia 

pines are the preferred hosts; during outbreaks, however, SPB may attack all pine 

species. Tree death results from girdling due to gallery construction by the beetle and 

blockage of water-conducting cells by the growth of blue stain fungi, spores of which 

are carried by SPB (Clarke and Nowak 2009). Periodically, populations of SPB reach 

outbreak proportions and cause extensive tree mortality. The current SPB outbreak in 

New Jersey has been ongoing since 2001.

What we found

Of the susceptible host species, pitch pine is the most numerous, with an estimated 

145.8 million trees (1-inch d.b.h. or greater). Virginia pine (68 percent), shortleaf pine 

(29 percent), pond pine (2 percent), and loblolly pine (less than 1 percent) account for 

an additional 13.2 million trees. Pitch pine is found on the ridgetops of northwestern 

New Jersey, but preferred hosts are primarily distributed throughout southern New 

Jersey, largely within the Pine Barrens (Fig. 47). Species preferred by SPB occur on 22 

percent of forest land, or 430,000 acres (Fig. 48). Of these stands, 65 percent are high 

density stands, where the basal area of host trees is greater than 80 square feet per 

acre. Mortality of preferred hosts has risen since 2008, reaching 4.3 million cubic feet 

of volume loss in 2013 (Fig. 49).
50 | FOREST HEALTH INDICATORS

Processing note: This map was produced 

by linking plot data to MODIS satellite 

pixels (250 m) using gradient nearest 

neighbor techniques.

> 80 

30 - 79

15 - 29

< 15

No hosts

Basal Area of 

Tree Species

Preferred by SPB

(ft2/acre)

Figure 47.—Density of host trees preferred by southern pine beetle on forest land, New Jersey, 2009.

Basal Area of SPB 

Preferred Hosts 

(ft2

 per acre)

>80

30-79

15-29

<15

No hosts

Processing note: This map was produced by linking plot data to 

MODIS satellite pixels (250 m) using gradient nearest neighbor 

techniques.
 | 51

0

 20 

 40 

 60 

 80 

 100 

 120 

 140 

 160 

20-40 41-60 61-80 81-100 101-120 >120

Total Forest Land (thousand acres)

Basal Area (ft2 per acre)

Figure 48.—Area of forest land by basal area for pitch, 

loblolly, shortleaf, pond, and Virginia pine forest types, New 

Jersey, 2013. Error bars represent a 68 percent confidence 

interval.

0

 1,000 

 2,000 

 3,000 

 4,000 

 5,000 

 6,000 

1999 2008 2013

Average Annual Mortality 

(thousand ft3

)

Inventory Year

Small diameter

Medium diameter

Large diameter

Total

Figure 49.—Average annual mortality of growing stock on 

timberland for preferred hosts of southern pine beetle, by 

stand-size class and inventory year, southern New Jersey. 

Error bars represent a 68 percent confidence interval.

What this means

Stand density is considered to be a critical factor in determining risk and expansion 

rate of southern pine beetle (Clarke and Nowak 2009). High density pine stands 

increase the risk of SPB outbreak. As susceptible stands cover 22 percent of New 

Jersey forest land, SPB has the potential to affect a vast area—especially in the 

southern portion of the State—and cause extensive pine mortality. 
52 | FOREST HEALTH INDICATORS

Hemlock Woolly Adelgid

Background 

White “wool” on the branches of eastern hemlock is a tell-tale sign of a hemlock woolly 

adelgid (Adelges tsugae; HWA) infestation (U.S. Forest Service 2010b). A tiny, sapfeeding insect from Asia, HWA was first reported in Virginia in 1951. By 1978, the 

adelgid had spread to Burlington County, New Jersey (Smith-Fiola et al. 2004). In the 

northern range of hemlock, tree decline and mortality generally occur within 4 to 10 

years of infestation (U.S. Forest Service 2010b). The rate of tree mortality increases if 

infested trees also experience drought, attack by secondary insects and diseases, or other 

stresses.

What we found 

There are an estimated 3.6 million hemlock trees (1-inch d.b.h. or greater) on New 

Jersey forest land. Although hemlock is distributed across much of northern New Jersey, 

its distribution is limited to cool, moist slopes and streambanks (Fig. 50) (Harlow et al. 

1996). Average annual mortality of hemlock has risen since 1987; mortality is currently 

an estimated 581,000 cubic feet of growing-stock volume on timberland (Fig. 51) and 

1.2 million board feet of sawtimber volume on timberland. Hemlock mortality reached 

a peak rate of 4.63 percent in 2013 (Fig. 52). 
 | 53

Figure 50.—Hemlock density on forest land, New Jersey, 2009.

Processing note: This map was produced by 

linking plot data to MODIS satellite pixels (250 m) 

using gradient nearest neighbor techniques.

Hemlock Basal Area 

(ft2

 per acre)

>20

11-20

5-10

<5

No hemlock
54 | FOREST HEALTH INDICATORS

-200

0

200

400

600

800

1,000

1,200

1985 1990 1995 2000 2005 2010 2015

Average Annual Mortality 

(thousand ft3 per year)

Year

Figure 51.—Average annual mortality of hemlock growing 

stock on timberland by inventory year, New Jersey. Error bars 

represent a 68 percent confidence interval. 

0

1

2

3

4

5

6

7

8

1985 1990 1995 2000 2005 2010 2015

Mortality to Volume Ratio (percent)

Year

Figure 52.—Average annual mortality of hemlock growing stock 

per unit volume of growing stock on timberland by inventory 

year, New Jersey. Error bar represents a 68 percent confidence 

interval.

What this means 

Hemlock represents a small, but unique and important, part of New Jersey’s forests. 

Because it is found in cool, moist ravines, on low ridges, and along lakeshores (Harlow 

et al. 1996), hemlock mortality could affect soil stability and water temperature and 

quality. Hemlock occurs in both pure and mixed stands (Harlow et al. 1996). Therefore, 

hemlock mortality would impact a variety of species. Based on mortality trends, HWA 

has been especially damaging since 1999. Continued monitoring of the hemlock 

resource will help to quantify the effects of HWA in New Jersey.
 | 55

Gypsy Moth

Background 

European gypsy moth (Lymantria dispar) was first introduced to New Jersey in the early 

1900s. Since then, periodic outbreaks have defoliated large areas of forest. The largest 

outbreaks occurred in the early 1980s, when more than 800,000 acres were defoliated. To 

quantify the impacts of gypsy moth defoliation, tree species were split into preferred and 

nonpreferred suitability classes based on field and laboratory tests by Liebhold et al. 

(1995). Species in suitability class 1 were considered preferred and all others were 

considered nonpreferred. In New Jersey, preferred species largely consisted of oaks but 

also included hardwoods such as birches, sweetgum, apple, and aspens (Liebhold et al. 

1995). 

What we found 

About 38 percent of New Jersey’s live-tree volume is preferred by gypsy moth. Oaks 

and sweetgum are the most abundant preferred species in the State. The density of 

host species preferred by gypsy moth is greatest in the Highlands of north-central New 

Jersey and in the southern third of the State (Fig. 53). The largest gypsy moth defoliation 

events were concentrated in the Pine Barrens of southern New Jersey and hardwood 

forests in the northern part of the State (Fig. 54). Between 1996 and 2010, nearly 500,000 

acres of forest land were defoliated at least once. Most of the defoliation occurred in the 

oak/hickory forest-type group. The annual mortality rate of species preferred by gypsy 

moth increased fourfold in areas that were defoliated two or more times in the 10 years 

preceding remeasurement (Fig. 55). 
56 | FOREST HEALTH INDICATORS

asal Area of Tree

pecies Preferred by 

ypsy Moth

ercent)

> 75

50 - 75

25 - 50

5 - 25

0 - 5

Nonforest

essing note: This map was 

uced by linking plot data to 

DIS satellite pixels (250 m) using 

ent nearest neighbor techniques.

Figure 53.—Density of host trees preferred by gypsy moth on forest land, New Jersey, 2009.

Processing note: This map was produced 

by linking plot data to MODIS satellite pixels 

(250 m) using gradient nearest neighbor 

techniques. 

Basal Area of Tree 

Species Preferred 

by Gypsy Moth 

(percent)

≥75

50-74

25-49

5-24

<5

Nonforest

Water
 | 57

Years of Gypsy

Moth Defoliation

0

1

2 or more

Nonforest

Water

Data source: USDA Forest 

Service, State and Private 

Forestry, 2010 Gypsy Moth 

Digest - defoliation data. 

Processing note: This map was 

roduced by linking plot data to 

MODIS satellite pixels (250 m) 

sing gradient nearest neighbor 

echniques.

Figure 54.—Gypsy moth defoliation events by year, New Jersey, 1996 to 2010. Years of defoliation is based on the 

number of defoliations that occurred on a plot within the 10 years prior to measurement.

Years of Gypsy 

Moth Defoliation

0

1

≥2

Nonforest

Water

Data source: U.S. Forest Service, State and Private 

Forestry, 2010 Gypsy Moth Digest—defoliation data. 

Processing note: This map was produced by linking plot 

data to MODIS satellite pixels (250 m) using gradient 

nearest neidghbor techniques.
58 | FOREST HEALTH INDICATORS

0

1

2

3

4

5

6

0 1 2 or more

Annual Mortality Rate (percent)

Years of Defoliation

Nonpreferred

Preferred

Figure 55.—Annual mortality rate by gypsy moth host 

preference, New Jersey, 2011. Years of defoliation is based 

on the number of defoliations that occurred on a plot within 

the 10 years prior to measurement. Error bars represent a 

68 percent confidence interval.

What this means 

Gypsy moth has been impacting New Jersey’s forests for more than a century, but 

records of defoliation have only been maintained since the 1960s. During that time 

defoliation has been cyclical, with peaks every 5 to 10 years. Although defoliation 

does have an impact on the health and survival of host tree species, the New Jersey 

Department of Agriculture has a comprehensive suppression program to reduce the 

impacts of gypsy moth which includes aerial spray treatments when gypsy moth 

population cycles peak. Quantifying the extent of forest area containing species 

preferred by gypsy moth can help land managers prepare for future outbreaks.

Invasive Plants

Background 

Invasive plant species (IPS), native and nonnative species that can cause negative 

ecological effects, are becoming more prevalent in forest ecosystems. Their abundance 

in introduced environments can be attributed to high adaptability, the availability of 

disturbed habitats, or a lack of natural enemies, which allows them to outcompete 

and displace native species (Pimentel et al. 2000). IPS are a concern because they can 

form dense monocultures that alter natural plant communities and processes, threaten 

biodiversity, and contribute to a decrease in sustainability, productivity, and wildlife 

habitat quality. Inspection, management, and mitigation of IPS cost billions of dollars 

annually.
 | 59

What we found

During the 2013 inventory, a subset of 65 P2 invasive plots in New Jersey were 

monitored for the presence of 39 IPS and one undifferentiated genus (nonnative bush 

honeysuckles) as part of the regional invasive plant monitoring protocol (Appendix 

2). Nearly half (46 percent) of all plots contained invasive plants; on these plots, 16 

species were observed (Table 5). Multiflora rose was found on 37 percent of plots 

and was the most commonly observed species, followed by Japanese honeysuckle 

and Japanese barberry. Invasive plants were found across the State, with the greatest 

abundance in northern New Jersey (Fig. 56). As many as 10 invasive plant species 

were found on plots (Fig. 57). Of plots with observed IPS, 47 percent had three or 

fewer species present. 

Table 5.—Number of occurrences and percentage of invasive plant species on P2 invasive plots, New Jersey, 2013

Name Occurrences Percentage of plots

Multiflora rose 24 36.9

Japanese honeysuckle 18 27.7

Japanese barberry 16 24.6

Garlic mustard 14 21.5

Nonnative bush honeysuckles 13 20.0

Nepalese browntop 12 18.5

Oriental bittersweet 11 16.9

Autumn-olive 9 13.8

European privet 6 9.2

Norway maple 3 4.6

Black locust 3 4.6

Canada thistle 2 3.1

Common reed 2 3.1

Spotted knapweed 1 1.5

Dames rocket 1 1.5

Ailanthus 1 1.5
60 | FOREST HEALTH INDICATORS

Number of Invasive 

Plant Species

No invasive plants

1-5

6-10

Forest

Nonforest

Processing note: This map was produced by 

linking plot data to MODIS satellite pixels (250 m) 

using gradient nearest neighbor techniques.

Nonforest

Forest

Number of Invasive Plant Species

6 - 10

1 - 5

No invasive plants

Figure 56.—Distribution and abundance of invasive plant species on 

forest land, New Jersey, 2013. Depicted plot locations are approximate.

Processing note: This map was 

produced by linking plot data to MODIS 

satellite pixels (250 m) using gradient 

nearest neighbor techniques. 

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6 7 8 9 10

Number of Plots

Number of Invasive Plant Species

Figure 57.—Number of invasive plant species per P2 

invasive plot, New Jersey, 2013.
 | 61

What this means

The presence of IPS within New Jersey’s forests is troublesome, and it is important 

that these species are monitored over time to ensure that managers and the public 

are aware of their occurrence and spread. Additional investigation of the inventory 

data may help to reveal influential site and regional trends as well as how the forest 

changes in response to changes in the plant community.

Forest Age and Size

Background

Forests provide habitat for many species of birds, mammals, amphibians, and reptiles. 

Forest composition and structure affect the suitability of habitat for each species. Some 

species depend upon early successional forests or the ecotone (edge) between different 

forest stages. Yet other species require old-growth forests or interior forests. Many 

species require multiple structural stages of forests to meet different phases of their life 

history needs. Abundance and trends in these structural and successional stages serve as 

indicators of population carrying capacity for wildlife species (Hunter et al. 2001). 

What we found

The small diameter stand-size class accounts for less than 4 percent of New Jersey 

timberland, a steady decrease from 14 percent in 1987 (Fig. 58). Similarly, the 

medium diameter size class decreased from 38 percent to 28 percent of timberland 

between 1987 and 2013. The large diameter class has increased since 1987 and 

now constitutes two-thirds of timberland (Fig. 58). Since 2008, the abundance of 

timberland has changed very little in the young age class (0-20 years), has increased 

substantially in the oldest age classes (81-100 years and 100+ years), and has 

decreased moderately in forests of intermediate age classes (21-80 years) (Fig. 59). It is 

difficult to interpret the amount of change since 1987 or 1999 because a large area of 

timberland was classified as “mixed” age class in older inventories. The large diameter 

stand-size class contains forests from all six 20-year age classes (although the 0- to 

20-year class is rare) and consists predominantly of forests that are 61 to 100 years old 

(Fig. 60). The medium diameter stand-size class includes five age classes and consists 

predominantly of forests 41 to 80 years of age. More than half of the small diameter 

class is in the 0- to 20-year stand age class, and most young forest is in the small 

diameter stand-size class (Fig. 60).
62 | FOREST HEALTH INDICATORS

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

1987 1999 2008 2013

Timberland Area (thousand acres)

Inventory Year

Nonstocked

Small diameter

Medium diameter

Large diameter

Figure 58.—Area of timberland by stand-size class and 

inventory year, New Jersey.

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

1987 1999 2008 2013

Timberland Area (thousand acres)

Inventory Year

Mixed age

0-20 years

21-40 years

41-60 years

61-80 years

81-100 years

100+ years

1987

1999

2008

2013

Not meas

100+ year

81-100 ye

61-80 yea

41-60 yea

21-40 yea

0-20 years 

Figure 59.—Area of timberland by stand age and inventory year, 

New Jersey.

0

50

100

150

200

250

300

350

400

450

500

Small diameter Medium diameter Large diameter

Forest Land Area (thousand acres)

Stand-size Class

0-20 years

21-40 years

41-60 years

61-80 years

81-100 years

100+ years

Figure 60.—Area of forest land by age class and stand-size class, New 

Jersey, 2013. Error bars represent a 68 percent confidence interval.
 | 63

Both the small and medium diameter stand-size classes have had gradual declines 

in area during recent decades. In contrast, timberland in the large diameter class has 

increased over this period. Similarly, the area of forests of 81 to 100 years and 100+ 

years has increased since the previous inventory; meanwhile young and intermediate 

ages have declined in area. Historical comparisons are more problematic due to a 

change in age-class definitions.

What this means

Stand-size class and stand-age class are indicators of forest structural/successional 

stage. The smallest stand-size class and youngest age class (0-20 years) are consistent 

with one another, but stands become progressively more heterogeneous as they 

become larger and older. Such mixtures of different aged or sized trees provide a 

vertical diversity of vegetation structure that can enhance habitat conditions for 

some species. Managing forest conditions in both younger and older age classes (and 

smaller and larger structural stages) to maintain both early and late successional 

habitats for a diversity of forest-associated species may conserve habitat and viable 

populations of many forest-associated wildlife species. 

Standing Dead Trees 

Background

Specific habitat features like nesting cavities and standing dead trees (5-inch d.b.h. or 

greater) provide critical habitat components for many forest-associated wildlife species. 

Standing dead trees that are large enough to meet habitat requirements for wildlife are 

referred to as “snags.” When considered for the purpose of wildlife habitat, snags are 

generally defined as being 10 inches d.b.h. or greater with a minimum height of 6 feet 

(Helms 1998). Standing dead trees serve as important indicators not only of wildlife 

habitat, but also for past mortality events and carbon storage. Further, they serve as 

sources of down woody materials, which also provide habitat features for wildlife. The 

number and density of standing dead trees, together with decay classes, species, and 

sizes, define an important wildlife habitat feature across New Jersey’s forests. 

What we found

FIA collects data on standing dead trees of numerous species and sizes in varying 

stages of decay. Currently, 29.5 million standing dead trees are present on New Jersey 
64 | FOREST HEALTH INDICATORS

forest land. This equates to an overall density of 14.8 standing dead trees per acre of 

forest land, with slightly higher densities on public (17.0 standing dead trees per acre) 

than on private (12.4 standing dead trees per acre) ownership classes. Eight species 

groups each contributed more than 1 million standing dead trees, with the four 

largest groups each contributing more than 3 million standing dead trees (Fig. 61). 

The other eastern softwoods species group had 6.8 million standing dead trees, 6.1 

million of which are in a single species: Atlantic white-cedar. Five species groups 

exceeded 10 standing dead trees per 100 live trees (5-inch d.b.h. or greater) of the 

same species group; the other eastern softwoods species group had the highest density 

at 28 standing dead trees per 100 live trees (Fig. 62). The majority (69 percent) of 

standing dead trees are less than 9 inches d.b.h. and thus do not meet the definition 

of a snag (Fig. 63). Decay of standing dead trees is limited, with 83 percent of all 

standing dead trees having little to moderate decay (Fig. 63). Other eastern softwoods 

species group contained both the largest total number of standing dead trees and the 

largest number of standing dead trees per 100 live trees of the same species group. On 

average, 14.8 standing dead trees are present for every acre of New Jersey forest land; 

9.0 standing dead trees are present for every 100 live trees.

0 2 4 6 8 10 

Other eastern softwoods

Other yellow pines

Other red oaks

Select white oaks

Other eastern soft hardwoods

Soft maple

Other eastern hard hardwoods

Other white oaks

Sweetgum

Ash

Select red oaks

Eastern hemlock

Number of Standing Dead Trees (millions) 

Species Group

Figure 61.—Number of standing dead trees on forest land 

for 12 selected species groups, New Jersey, 2013. Error bars 

represent a 68 percent confidence interval.
 | 65

0 5 10 15 20 25 30

Other eastern softwoods

Eastern hemlock

Other eastern soft hardwoods

Other red oaks

Select white oaks

Eastern white and red pine

Sweetgum

Other white oaks

Ash

Select red oaks

Other eastern hard hardwoods

Other yellow pines

Number of Standing Dead Trees per 100 Live Trees

Species Group

Figure 62.—Number of standing dead trees per 100 live trees on 

forest land for 12 selected species groups, New Jersey, 2013.

0

1

2

3

4

5

6

Standing Dead Trees (millions)

Diameter Class (inches)

All limbs and branches present

Few limbs and no fine branches

Only limb stubs present

Few or no limb stubs remain

No evidence of branches remains

5.0-6.97.0-8.9

9.0-10.9

11.0-12.913.0-14.915.0-16.917.0-18.919.0-20.9

21.0+

Figure 63.—Number of standing dead trees on forest land 

by diameter and decay class, New Jersey, 2013. Error bars 

represent a 68 percent confidence interval.

What this means

Snags and smaller standing dead trees result from a variety of potential causes, 

including diseases, insects, weather damage, fire, flooding, drought, and competition. 

Dead trees may contain significantly more cavities per tree than live trees (Fan et al. 

2003). These cavities provide habitat features for foraging, nesting, roosting, hunting, 

and excavation for wildlife—from primary colonizers such as insects, bacteria, and 

fungi to birds, mammals, and reptiles. Most cavity nesting birds are insectivores, 

which help to control insect populations (Scott et al. 1977). Providing a variety of 
66 | FOREST HEALTH INDICATORS

forest structural stages and retaining specific features like snags on both private and 

public lands in New Jersey are ways that forest managers maintain the abundance and 

quality of habitat for forest-associated wildlife species.
Forest Economics

Pakim Pond, Brendan T. Byrne State Forest. Photo by Susan Crocker, U.S. Forest Service.

 | 67
68 | FOREST ECONOMICS

Growing-stock Volume

Background 

Growing-stock volume is the amount of sound wood in live, commercial tree species 

that are 5 inches in d.b.h. or greater and free of defect. This measure has traditionally 

been used to ascertain wood volume available for commercial use. Estimates of the 

volume of growing stock are important considerations in economic planning and 

when evaluating forest sustainability.

What we found

Growing-stock volume on timberland has risen steadily since 1956 and currently 

totals an estimated 3.3 billion cubic feet (Fig. 64). Other yellow pines, which consist 

mainly of pitch pine, are the largest source of growing-stock volume, followed by 

other red oaks and soft maple (Fig. 65). Pitch pine, which accounts for 14 percent of 

growing-stock volume, is the most voluminous species on New Jersey timberland. 

Since 1987, there have been notable increases in volume in the other yellow pines, 

yellow-poplar, and select red oaks species groups. Growing-stock volume continues 

to increase in the middle diameter classes as trees grow (Fig. 66). Correspondingly, 

median tree diameter grows larger with successive inventories. 

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

1950 1960 1970 1980 1990 2000 2010 2020

Growing-stock Volume (million ft3

)

Year

Figure 64.—Growing-stock volume on timberland by inventory 

year, New Jersey. Error bars represent a 68 percent confidence 

interval.
 | 69

0 200 400 600 800

Other yellow pines

Other red oaks

Soft maple

Yellow-poplar

Select white oaks

Select red oaks

Ash

Other white oaks

Sweetgum

Other eastern softwoods

Growing-stock Volume (million ft3

)

Species Group

1987

1999

2008

2013

Figure 65.—Growing-stock volume on timberland for the 

10 most voluminous species in 2013 by inventory year and 

species group, New Jersey. Error bars represent a 68 percent 

confidence interval.

0

100

200

300

400

500

600

Growing-stock Volume (million ft3

)

Diameter Class (inches)

1987

1999

2008

2013

5.0-6.9

7.0-8.9

9.0-10.9

11.0-12.9

13.0-14.915.0-16.917.0-18.9

19.0-20.9

21.0-22.923.0-24.9

25.0-26.9

27.0-28.9

29.0+

Figure 66.—Growing-stock volume on timberland by diameter 

class and inventory year, New Jersey. Error bars represent a 

68 percent confidence interval.

What this means

Even though growing-stock volume continues to rise, the rate of increase may be 

slowing. Although pitch pine and other red oaks still maintain significant growingstock volumes, they show reductions or smaller increases than other species such as 

the soft maples (e.g., red maple). Statewide, the increase in growing-stock volume 

can be attributed to tree growth, moderate mortality of high-volume species, and 

an aging forest. New Jersey’s growing-stock volume is increasing; as stands mature, 

sustainability issues (e.g., regeneration) should continue to be monitored.
70 | FOREST ECONOMICS

Sawtimber Volume and Quality

Background 

Sawtimber trees are live trees of commercial species that contain either one 12-

foot or two noncontiguous 8-foot logs that are free of defect. Hardwoods must 

be 11 inches d.b.h. or greater and softwoods must be 9 inches d.b.h. or greater to 

qualify as sawtimber. Sawtimber volume is defined as the net volume of the saw log 

portion of live sawtimber, measured in board feet, from a 1-foot stump to minimum 

top diameter (9 inches for hardwoods and 7 inches for softwoods). Estimates of 

sawtimber volume are used to determine the monetary value of wood volume and the 

quantity of merchantable wood available.

What we found

The volume of sawtimber on New Jersey timberland has quadrupled since 1956, 

reaching an estimated 11.8 billion board feet in 2013 (Fig. 67). Most species groups 

had large gains in sawtimber volume since 2008 (Fig. 68). Eastern white and red pine 

and yellow-poplar had the greatest increases in the amount of sawtimber volume 

(45 percent and 38 percent, respectively). Sawtimber quality is determined using 

a grading system that incorporates factors including diameter, log length, and the 

cull portion of the saw log. Tree grade is based on a scale of 1 to 4, with grade 1 

representing the highest quality and grade 4 the lowest. Over the past decade, the 

quality of New Jersey sawtimber has remained consistent, with a large portion of 

higher grade sawtimber (Fig. 69). Currently, 44 percent of New Jersey’s hardwood 

sawtimber is in grade 1.

0

 2 

 4 

 6 

 8 

 10 

 12 

 14 

1955 1965 1975 1985 1995 2005 2015

Sawtimber Volume (billion board feet) 

Year

Figure 67.—Sawtimber volume on timberland by inventory 

year, New Jersey. Error bars represent a 68 percent 

confidence interval.
 | 71

0 10 20 30 40 50

Soft maple

Other eastern softwoods

Other yellow pines

Loblolly and shortleaf pine

Select red oaks

Other white oaks

Ash

Select white oaks

Other red oaks

Black walnut

Yellow-poplar

Eastern white and red pine

Change in Sawtimber Volume from 2008 to 2013 (percent)

Species Group

Figure 68.—Percent change in sawtimber volume on 

timberland for 12 selected species groups, New Jersey.

0

10

20

30

40

50

60

70

80

90

100

1999 2008 2013

Sawtimber Volume (percent)

Year

Grade 1

Grade 2

Grade 3

Grade 4

Figure 69.—Sawtimber volume for hardwood species on 

timberland by tree grade and inventory year, New Jersey.

What this means

New Jersey’s sawtimber resource has been steadily increasing for decades. This is 

indicative of a stable and sustainable component of the forest ecosystem. If current 

trends continue, one would expect increasing sawtimber volumes into the foreseeable 

future. However, this assumption may not hold locally, or following unexpected forest 

disturbances (e.g., invasive pests, disease, or weather). 
72 | FOREST ECONOMICS

Timber Products 

Background 

The harvesting and processing of timber products produce a stream of income shared 

by timber owners, managers, loggers, marketers, truckers, and processors. Although 

the wood products and paper manufacturing industries (including primary and 

secondary processors) in New Jersey are relatively small, 9,659 people were employed 

in 2013, with an average annual payroll of $485.8 million (U.S. Census Bureau 2015). 

To better manage the State’s forests, it is important to know the species, amounts, and 

locations of timber being harvested.

Surveys of New Jersey’s wood-processing mills are conducted periodically to estimate 

the amount of wood volume that is processed into wood products. This information 

is supplemented with the most recent surveys conducted in surrounding states that 

processed wood harvested from New Jersey. Five active primary wood-processing 

mills were surveyed to determine the volume of industrial roundwood processed in 

2010, by species and by the state and county that the wood material came from. 

What we found

New Jersey mills processed more than 5.7 million board feet (941,000 cubic feet), 

nearly all of which originated from forest land within the State. About 1.1 million 

cubic feet of industrial roundwood was harvested, including roundwood that was 

harvested in New Jersey but was exported to primary wood-processing mills in other 

states. Eighty-six percent of the industrial roundwood harvested was processed by 

sawmills, with the remainder processed by pulp and composite panel mills (Fig. 70). 

All timber harvested for pulp and composite panel production was exported to mills 

in other states. Sweetgum accounted for more than 40 percent (454,000 cubic feet) of 

the total industrial roundwood harvested (Fig. 71). Other important species groups 

harvested were the red oaks, white oaks, and pines. The processing of industrial 

roundwood by the State’s primary wood-using mills generated 15,200 green tons of 

wood and bark residues. More than 95 percent of these mill residues were used for 

mulch. Mill residues were also used for pulp, residential fuelwood, animal bedding, 

and other miscellaneous uses. Less than 1 percent of the mill residues were not used 

for other products.
 | 73

Saw logs

86%

Pulp and composite products

14%

Figure 70.—Industrial roundwood production by product, 

New Jersey, 2010.

0 100 200 300 400 500

Sweetgum

Red oaks

Pines

White oaks

Yellow-poplar

Beech

Other hardwoods

Other softwoods

Industrial Roundwood Harvested

(thousand ft3

)

Species Group

Figure 71.—Industrial roundwood harvested by species group, 

New Jersey, 2010.

What this means 

An important consideration for the future of the primary wood-products industry is 

its ability to retain industrial roundwood processing facilities. The number of woodprocessing mills has been steadily declining. The loss of processing facilities makes 

it harder for landowners to find markets for the timber harvested from management 

activities on their forest land.
74 | FOREST ECONOMICS
View from Wildlife Drive at Edwin B. Forsythe National Wildlife Refuge. Photo by Chelsi Hornbaker, U.S. Fish and 

Wildlife Service. 

Future Forests

 | 75
76 | FUTURE FORESTS

Future Forest Projections

Background

Future forest change will largely be the result of normal forest growth, aging, natural 

regeneration, and species succession. External forces, such as the following examples, 

will also influence forest change:

• Population increases will cause roughly 0.5 million acres of forest land to be 

converted to urban land.

• Economic conditions will affect forest products consumption, production, and 

harvest rates.

• The spread of invasive species will affect forest composition.

• Changes in human population, the economy, energy consumption, and energy 

production will affect future climate change.

• Climate change will affect patterns of forest growth and species succession.

The Northern Forest Futures study focuses on anticipated changes to forests between 

2010 and 2060 (Shifley and Moser 2016). This study examined several alternative 

futures covering a range of different assumptions about the economy, population, 

climate, and other driving forces that will affect the future conditions of forests. The 

assumptions were incorporated into seven scenarios that consider how different 

alternative future climate conditions, demographic changes, and economic policies 

will affect forests. Additional details on methods can be found in Shifley and Moser 

(2016). 

The seven scenarios that were considered are briefly described below. Naming 

conventions relate to the more detailed scenario descriptions that originated from the 

Intergovernmental Panel on Climate Change (2000):

1) A1B-C—Moderate population growth and rapid economic growth.

2) A1B-C-BIO—Moderate population growth and rapid economic growth including 

the potential impact of increased harvest and utilization of woody biomass for 

energy.

3) A2-C—Rapid population growth and moderate economic growth.

4) A2-C-BIO—Rapid population growth and moderate economic growth including 

the potential impact of increased harvest and utilization of woody biomass for 

energy.
 | 77

5) A2-C-EAB—Rapid population growth and moderate economic growth including 

the potential impact of continued spread of emerald ash borer with associated 

mortality of all ash trees in the affected areas.

6) B2-C—A trend toward low population growth and low economic growth. 

7) B2-C-BIO—A trend toward low population growth and low economic growth 

including the potential impact of increased harvest and utilization of woody 

biomass for energy.

What we found

Over the next 50 years, forest land is predicted to decline under all scenarios, thus 

reversing the long-term trend of increasing forest area in New Jersey (Fig. 72). 

Specifically, these declines are approximated to be 31 percent under scenario A1B-C, 

35 percent under scenario A2-C, and 20 percent under scenario B2-C. The greater the 

assumed increases in population and economic activity, the greater the projected loss 

of future forest land—thus the higher predicted loss of forest land in the A1B and A2 

scenarios. Forest land, which made up 41 percent of New Jersey’s land base in 2010, is 

expected to fall to between 27 and 34 percent of total land area. 

 1,000 

 1,200 

 1,400 

 1,600 

 1,800 

 2,000 

 2,200 

 2,400 

1880 1900 1920 1940 1960 1980 2000 2020 2040 2060 2080

Forest Land (thousand acres)

Year

Historic

A1B-C

A2-C

B2-C

Figure 72.—Projected area of forest land by scenario, New 

Jersey, 2010-2060.

Although the elm/ash/cottonwood forest type is projected to decline by 24,000 acres 

between 2010 and 2060 under the A2-C-EAB scenario, it remains about 4 percent 

of total area (Fig. 73). Ash volume is predicted to fall under both the A2-C-EAB and 

A2-C scenarios; however, the greater decrease is predicted in the A2-C-EAB scenario, 

where it declines from 231 million cubic feet in 2010 to 0 cubic feet by 2030. Under 

the standard A2-C scenario, ash volume remains at 169 million cubic feet in 2060.
78 | FUTURE FORESTS

0

200

400

600

800

1,000

Other

Oak/hickory

Maple/beech/birch

Elm/ash/cottonwood

White/red/jack pine

Aspen/birch

Forest Land Area (thousand acres)

Forest-type Group

Historic in 2010

A2-C-EAB in 2060

A2-C in 2060

A1B-C in 2060

B2-C in 2060

Figure 73.—Projected area of forest land by forest-type group 

and scenario, New Jersey, 2010-2060.

Due to the projected loss of forest land, live-tree volume on forest land in 2060 is 

expected to decrease under all scenarios. All three high biomass utilization scenarios 

(A1B-C-BIO, B2-C-BIO and A2-C-BIO) result in lower levels of live-tree volume in 

2060 than do their corresponding normal biomass utilization scenarios (A1B-C, B2-

C, and A2-C). Volume per acre is anticipated to increase by the following percentages 

for six of the seven scenarios: A1B-C (6 percent), A1B-C-BIO (1 percent), A2-C 

(3 percent), A2-C-BIO (11 percent), B2-C (10 percent), and B2C-BIO (3 percent) 

as forests continue to mature. Volume per acre is expected to drop by 4 percent for 

scenario A2-C-EAB. Average annual removals of growing stock on timberland are 

expected to increase under all scenarios, but removals rates may not be sustainable for 

the high biomass utilization scenarios (Fig. 74).

0

10

20

30

40

50

60

70

80

90

100

2000 2010 2020 2030 2040 2050 2060 2070

Average Annual Removals

 (million ft3

)

Year

A1B-C

A1B-C-BIO

A1B-C-BIO

A2-C

A2-C

A2-C-BIO

A2-C-BIO

B2-C

B2-C

B2-C-BIO

B2-C-BIO

A2-C-EAB

A1B-C

Figure 74.—Average annual removals of growing stock on 

timberland by scenario, New Jersey, 2010-2060.
 | 79

What this means 

Projected trends reflect the combined effects of population and economic growth, 

which are expected to lean heavily toward continually maturing forests with 

decreasing forest area. These projections are considered to be possible trends, and 

they will be influenced by actual future climate conditions, demographic changes, 

and economic policies relative to the assumptions. Knowledge of potential trends 

in future forest conditions helps elucidate the impacts to forest land given a variety 

of circumstances. This knowledge also provides valuable information on future 

directions of and associated impacts on long-term forest health and sustainability. An 

understanding of the implications of potential changes will allow managers to make 

informed decisions and manage for desired future conditions.
80 | DATA SOURCES AND TECHNIQUES

Data Sources and Techniques

Forest Inventory

Information on the condition and status of forests in New Jersey was obtained from 

the Northern Research Station’s Forest Inventory and Analysis (NRS-FIA) program. 

Previous inventories of New Jersey’s forest resources were completed in 1956 (Webster 

and Stoltenberg 1958), 1971 (Ferguson and Mayer 1974), and 1987 and 1999 (Griffith 

and Widmann 2001). Data from New Jersey’s forest inventories can be found online at 

http://www.nrs.fs.fed.us/fia. For detailed information on inventory methods, see the 

Statistics, Methods, and Quality Assurance section online at https://doi.org/10.2737/

NRS-RB-109. 

National Woodland Owner Survey

Information about family forest owners is collected annually through the U.S. Forest 

Service’s National Woodland Owner Survey (NWOS). The NWOS was designed 

to increase our understanding of owner demographics and motivation (Butler et al. 

2016). Individuals and private groups identified as woodland owners by FIA are 

invited to participate in the NWOS. Each year, questionnaires are mailed to 20 

percent of private owners, with more detailed questionnaires sent out in years that 

end in 2 or 7 to coincide with national census, inventory, and assessment programs. 

Data presented here are based on survey responses from randomly selected families 

and individuals who own forest land in New Jersey. For additional information 

about the NWOS, visit www.fia.fs.fed.us/nwos. 

Timber Products Output Inventory 

Using a questionnaire designed to determine the size and composition of New Jersey’s 

forest products industry, its use of roundwood (round sections cut from trees), and its 

generation and disposition of wood residues, NRS-FIA personnel contacted via mail 

and telephone all primary wood-using mills in the State. Completed questionnaires 

were sent to NRS-FIA for processing. As part of data processing, all industrial 

roundwood volumes reported were converted to standard units of measure using 

regional conversion factors. 
 | 81

Literature Cited

Bechtold, W.A.; Patterson, P.L., eds. 2005. The enhanced Forest Inventory and 

Analysis program—national sampling design and estimation procedures. Gen. 

Tech. Rep. SRS-80. Asheville, NC: U.S. Department of Agriculture, Forest Service, 

Southern Research Station. 85 p.

Breiman, L. 2001. Random forests. Machine Learning. 45: 15-32.

Butler, B.J.; Hewes, J.H.; Dickinson, B.J.; Andrejczyk, K.; Butler, S.M.; MarkowskiLindsay, M. 2016. U.S. Forest Service National Woodland Owner Survey: national, 

regional, and state statistics for family forest and woodland ownerships with 10+ 

acres, 2011-2013. Resour. Bull. NRS-99. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station. 39 p.

Cipollini, D. 2015. White fringetree as a novel larval host for emerald ash borer. 

Journal of Economic Entomology. 108(1): 370-375.

Clarke, S.R.; Nowak, J.T. 2009. Southern pine beetle. Forest Insect and Disease Leaflet 

49. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Region. 8 p.

Collins, B.R.; Anderson, K.H. 1994. Plant communities of New Jersey: a study in 

landscape diversity. New Brunswick, NJ: Rutgers University Press. 287 p.

Conservation Biology Institute. 2010. Protected areas database of the United States, 

PAD-US. CBI edition. Available at https://protectedareas.databasin.org (accessed 

January 2014).

Coulston, J.W.; Moisen, G.G.; Wilson, B.T.; Finco, M.V.; Cohen, W.B.; Brewer, C.K. 

2012. Modeling percent tree canopy cover: a pilot study. Photogrammetric 

Engineering & Remote Sensing 78(7): 715-727.

Crocker, S.J.; Nelson, M.D.; Barnett, C.J.; Brand, G.J.; Butler, B.J.; Domke, G.M.; 

Hansen, M.H.; Hatfield, M.A.; Lister, T.W.; Meneguzzo, D.M.; Perry, C.H.; Piva, 

R.J.; Wilson, B.T.; Woodall, C.W.; Zipse, W. 2011. New Jersey’s forests 2008. Resour. 

Bull. NRS-59. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, 

Northern Research Station. 52 p. [DVD included].

Fan, Z.; Shifley, S.R.; Spetich, M.A.; Thompson, F.R., III; Larsen, D.R. 2003. Distribution 

of cavity trees in midwestern old-growth and second-growth forests. Canadian 

Journal of Forest Research. 33: 1481-1494. http://dx.doi.org/10.1139/x03-068.
82 | LITERATURE CITED

Ferguson, R.H.; Mayer, C.E. 1974. The timber resources of New Jersey. Res. Bull. NE34. Upper Darby, PA: U.S. Department of Agriculture, Forest Service, Northeastern 

Forest Experiment Station. 45 p.

Griffith, D.M.; Widmann, R.H. 2001. Forest statistics for New Jersey: 1987 and 1999. 

Resour. Bull. NE-152. Newtown Square, PA: U.S. Department of Agriculture, Forest 

Service, Northeastern Research Station. 33 p.

Harlow, W.M.; Harrar, E.S.; Hardin, J.W.; White, F.M. 1996. Textbook of dendrology. 

8th ed. New York: McGraw-Hill. 534 p.

Heath, L.S.; Hansen, M.H.; Smith, J.E.; Smith, W.B.; Miles, P.D. 2009. Investigation 

into calculating tree biomass and carbon in the FIADB using a biomass 

expansion factor approach. In: McWilliams, W.; Moisen, G.; Czaplewski, R., 

comps. 2008 Forest Inventory and Analysis symposium; 2008 October 21-23; Park 

City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station. [CD].

Helms, J.A., ed. 1998. The dictionary of forestry. Bethesda, MD: Society of American 

Foresters. 210 p.

Herms, D.A.; McCullough, D.G. 2014. Emerald ash borer invasion on North 

America: history, biology, ecology, impacts and management. Annual Review of 

Entomology. 59(1): 13-30. http://dx.doi.org/10.1146/annurev-ento-011613-162051. 

Homer, C.G.; Dewitz, J.A.; Yang, L.; Jin, S.; Danielson, P.; Xian, G.; Coulston, J.W; 

Herold, N.D.; Wickham, J.D.; Megown, K.A. 2015. Completion of the 2011 

National Land Cover Database for the conterminous United States—representing 

a decade of land cover change information. Photogrammetric Engineering & 

Remote Sensing. 81 (5): 345-354. http://dx.doi.org/10.14358/PERS.81.5.345.

Honnay, O.; Jacquemyn, H.; Bossuyt, B.; Hermy, M. 2005. Forest fragmentation 

effects on patch occupancy and population viability of herbaceous plant 

species. New Phytologist. 166(3): 723-736. http://dx.doi.org/10.1111/j.1469-

8137.2005.01352.x.

Hunter, W.C.; Buehler, D.A.; Canterbury, R.A.; Confer, J.L.; Hamel, P.B. 2001. 

Conservation of disturbance-dependent birds in eastern North America. Wildlife 

Society Bulletin. 29(2): 440-455.

Intergovernmental Panel on Climate Change [IPCC]. 2000. Summary for 

policymakers: emissions scenarios. Geneva, Switzerland. 21 p. https://www.ipcc.

ch/pdf/special-reports/spm/sres-en.pdf (accessed July 31, 2014).
 | 83

Kapos, V.; Lysenko, I.; Lesslie, R. 2000. Assessing forest integrity and naturalness 

in relation to biodiversity. On behalf of FAO as part of the Global Forest 

Resources Assessment 2000. Working Paper 54. Rome, Italy: Food and Agriculture 

Organization of the United Nations/UNEP-World Conservation Monitoring 

Centre. 65 p. 

Liebhold, A.M.; Gottschalk, K.W.; Muzika, R.; Montgomery, M.E.; Young, R.; O’Day, 

K.; Kelley, B. 1995. Suitability of North American tree species to the gypsy moth: 

a summary of field and laboratory tests. Gen. Tech. Rep. NE-211. Radnor, PA: U.S. 

Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 

34 p.

McRoberts, R.E. 1999. Joint annual forest inventory and monitoring system, the 

North Central perspective. Journal of Forestry. 97(12): 27-31.

McRoberts, R.E. 2005. The enhanced Forest Inventory and Analysis program. In: 

Bechtold, W.A.; Patterson, P.L., eds. The enhanced Forest Inventory and Analysis 

program—national sampling design and estimation procedures. Gen. Tech. Rep. 

SRS-80. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern 

Research Station: 1-10.

Miles, P.D.; Smith, W.B. 2009. Specific gravity and other properties of wood and bark 

for 156 tree species found in North America. Res. Pap. NRS-38. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. 35 p.

Montreal Process. 1999. Criteria and indicators for the conservation and sustainable 

management of temperate and boreal forests: the Montreal process. 2nd ed. 

Ottawa, ON: Natural Resources Canada, Canadian Forest Service. 19 p.

Morin, R.S.; Randolph, K.C.; Steinman, J. 2015. Mortality rates associated with 

crown health for eastern forest tree species. Environmental Monitoring and 

Assessment 187: 87. http://dx.doi.org/10.1007/s10661-015-4332-x.

Natural Resources Conservation Service. 2015. The PLANTS database. Greensboro, 

NC: U.S. Department of Agriculture, Natural Resources Conservation Service, 

National Plant Data Team. www.plants.usda.gov (accessed July 22, 2014). 

O’Connell, B.M.; LaPoint, E.B.; Turner, J.A.; Ridley, T.; Pugh, S.A.; Wilson, A.M.; 

Waddell, K.L.; Conkling, B.L. 2014. The Forest Inventory and Analysis database: 

database description and user guide, ver. 6.0.1 for Phase 2. Washington, DC: U.S. 

Department of Agriculture, Forest Service. 748 p. Available at http://www.fia.fs.fed.

us/library/database‐documentation/.
84 | LITERATURE CITED

O’Neill, K.P.; Amacher, M.C.; Perry, C.H. 2005. Soils as an indicator of forest health: 

a guide to the collection, analysis, and interpretation of soil indicator data in the 

Forest Inventory and Analysis program. Gen. Tech. Rep. NC-258. St. Paul, MN: U.S. 

Department of Agriculture, Forest Service, North Central Research Station. 53 p.

Pimentel, D.; Lach, L.; Zuniga, R.; Morrison, D. 2000. Environmental and economic 

costs of nonindigenous species in the United States. Bioscience. 50(1): 53-65. 

http://dx.doi.org/10.1641/0006-3568(2000)050%0053:EAECON%5D2.3.CO;2.

Radeloff, V.C.; Hammer, R.B.; Stewart, S.I.; Fried, J.S.; Holcomb, S.S.; McKeefry, J.F. 

2005. The wildland urban interface in the United States. Ecological Applications. 

15: 799-805. http://dx.doi.org/10.1890/04-1413.

Russell, M.B.; Woodall, C.W.; D’Amato, A.W.; Fraver, S.; Bradford, J.B. 2014a. Linking 

climate change and downed woody debris decomposition across forests of the 

eastern United States. Biogeosciences. 11(22): 6417-6425. http://dx.doi.org/10.5194/

bg-11-6417.2014.

Russell, M.B.; Woodall, C.W.; Fraver, S.; D’Amato, A.W.; Domke, G.M.; Skog, K.E. 

2014b. Residence time and rate of decay for downed woody debris biomass/carbon 

in eastern US forests. Ecosystems. 17: 765-777. http://dx.doi.org/10.1007/s10021-

014-9757-5.

Schomaker, M.E.; Zarnoch, S.J.; Bechtold, W.A.; Latelle, D.J.; Burkman, W.G.; Cox, 

S.M. 2007. Crown-condition classification: a guide to data collection and analysis. 

Gen. Tech. Rep. SRS-102. Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southern Research Station. 78 p.

Schulz, B.K.; Bechtold, W.A.; Zarnoch, S.J. 2009. Sampling and estimation procedures 

for the vegetation diversity and structure indicator. Gen. Tech. Rep. PNWGTR-781. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 53 p.

Scott, V.E.; Evans, K.E.; Patton, D.R.; Stone, C.P. 1977. Cavity-nesting birds of North 

American forests. Agric. Handb. 511. Washington, DC: U.S. Department of 

Agriculture, Forest Service. 112 p.

Shifley, S.R.; Moser, W.K., eds. 2016. Future forests of the Northern United States. 

Gen. Tech. Rep. NRS-151. Newtown Square, PA: U.S. Department of Agriculture, 

Forest Service, Northern Research Station. 388 p.

Smith, G.C.; Coulston, J.W.; O’Connell, B.M. 2008. Ozone bioindicators and forest 

health: a guide to the evaluation, analysis, and interpretation of the ozone injury 

data in the Forest Inventory and Analysis program. Gen. Tech. Rep. NRS-34. 

Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern 

Research Station. 100 p.
 | 85

Smith-Fiola, D.; Hamilton, G.C.; Lashomb, J. 2004. The hemlock woolly adelgid: 

life cycle, monitoring, and pest management in New Jersey. New Brunswick, NJ: 

Rutgers, The State University of New Jersey, Cooperative Research and Extension. 2 p. 

http://njaes.rutgers.edu/pubs/publication.asp?pid=FS751 (accessed April 25, 2011).

Steinman, J. 2000. Tracking the health of trees over time on forest health monitoring 

plots. In: Hansen, M.; Burk, T., eds. Integrated tools for natural resources 

inventories in the 21st century; 1998 August 16-20; Boise, ID. Gen. Tech. Rep. NC212. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central 

Research Station: 334-339.

Thatcher, R.C.; Searcy, J.L.; Coster, J.E.; Hertel, G.D., eds. 1980. The southern pine 

beetle. Tech. Bull. 1631. Pineville, LA: U.S. Department of Agriculture, Forest 

Service. 265 p.

U.S. Census Bureau. 2015. Annual survey of manufactures. Washington, DC: U.S. 

Department of Commerce, Census Bureau. Available at http://www.census.gov/

manufacturing/asm/index.html (accessed October 1, 2015).

U.S. Environmental Protection Agency. 2015. Inventory of U.S. greenhouse gas 

emissions and sinks: 1990-2013. EPA 430-R-15-004. Washington, DC: U.S. 

Environmental Protection Agency, Office of Atmospheric Programs. http://www.

epa.gov/climatechange/ghgemissions/usinventoryreport.html. 

U.S. Forest Service. 2005. Forest inventory and analysis field methods for forest 

health (Phase 3) measurements, ver. 3.0. Washington, DC: U.S. Department of 

Agriculture, Forest Service. Available at http://fia.fs.fed.us/library/field-guidesmethods-proc/docs/2006/Version-3.0.pdf (accessed October 28, 2010).

U.S. Forest Service. 2010a. Forest Inventory and Analysis national core field guide: 

field data collection procedures for Phase 2 plots, ver. 5.0. U.S. Department of 

Agriculture, Forest Service. http://www.fia.fs.fed.us/library/field-guides-methodsproc/docs/Complete FG Document/NRS FG 5.0-Oct 2010-Complete Document.

pdf (accessed April 11, 2016).

U.S. Forest Service. 2010b. Hemlock woolly adelgid. NA-PR-09-05. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, Northeastern Area State and 

Private Forestry. 2 p.

U.S. Geological Survey. 2011. 1997-2014 edition of the National Atlas of the United 

States. Reston, VA: U.S. Department of the Interior, Geological Survey. Archived 

at http://catalog.data.gov/harvest/1997-2014-edition-of-the-national-atlas-ofthe-united-states. [Note that the homepage for the new National Map is www.

nationalmap.gov/small_scale (accessed August 17, 2016)].
86 | LITERATURE CITED

 Webster, H.H.; Stoltenberg, C.H. 1958. The timber resources of New Jersey. A report on 

the Forest Survey made by the U.S. Forest Service. Upper Darby, PA: U.S. Department 

of Agriculture, Forest Service, Northeastern Forest Experiment Station. 45 p.

Westfall, J.A.; Frieswyk, T.; Griffith, D.M. 2009. Implementing the measurement interval 

midpoint method for change estimation. In: McRoberts, R.E.; Reams, G.A.; Van 

Deusen, P.C.; McWilliams, W.H. eds. Proceedings of the eighth annual Forest Inventory 

and Analysis symposium; 2006 October 16-19; Monterey, CA. Gen. Tech. Rep. WO-79. 

Washington, DC: U.S. Department of Agriculture, Forest Service: 231-236.

Wilcox, B.A.; Murphy, D.D. 1985. Conservation strategy: the effects of 

fragmentation on extinction. American Naturalist. 125(6): 879-887.

Wilson, B.T.; Lister, A.J.; Riemann, R.I. 2012. A nearest-neighbor imputation 

approach to mapping tree species over large areas using forest inventory plots 

and moderate resolution raster data. Forest Ecology and Management. 271: 182-

198. http://dx.doi.org/10.1016/j.foreco.2012.02.002.

Woodall, C.W.; Amacher, M.C.; Bechtold, W.A.; Coulston, J.W.; Jovan, S.; Perry, C.H.; 

Randolph, K.C.; Schulz, B.K.; Smith, G.C.; Tkacz, B.; Will-Wolf, S. 2011. Status 

and future of the forest health indicators program of the USA. Environmental 

Monitoring and Assessment. 177(1): 419-436. http://dx.doi.org/10.1007/s10661-

010-1644-8. 

Woodall, C.W.; Monleon, V.J. 2008. Sampling protocols, estimation, and analysis 

procedures for the down woody materials indicator of the FIA program. Gen. 

Tech. Rep. NRS-22. Newtown Square, PA: U.S. Department of Agriculture, Forest 

Service, Northern Research Station. 68 p.

Woodall, C.W.; Walters, B.F.; Oswalt, S.N.; Domke, G.M.; Toney, C.; Gray, A.N. 

2013. Biomass and carbon attributes of downed woody materials in forests of 

the United States. Forest Ecology and Management. 305: 48-59. http://dx.doi.

org/10.1016/j.foreco.2013.05.030.
 | 87

Appendixes

Appendix 1.—List of tree species, New Jersey, 2013

Common name Genus Species

boxelder Acer negundo

striped maple Acer pensylvanicum

Norway maple Acer platanoides

red maple Acer rubrum

silver maple Acer saccharinum

sugar maple Acer saccharum

ailanthus Ailanthus altissima

serviceberry spp. Amelanchier spp.

yellow birch Betula alleghaniensis

sweet birch Betula lenta

river birch Betula nigra

gray birch Betula populifolia

American hornbeam, musclewood Carpinus caroliniana

mockernut hickory Carya alba

bitternut hickory Carya cordiformis

pignut hickory Carya glabra

shagbark hickory Carya ovata

American chestnut Castanea dentata

hackberry Celtis occidentalis

Atlantic white-cedar Chamaecyparis thyoides

flowering dogwood Cornus florida

common persimmon Diospyros virginiana

Russian-olive Elaeagnus angustifolia

American beech Fagus grandifolia

white ash Fraxinus americana

black ash Fraxinus nigra

green ash Fraxinus pennsylvanica

American holly Ilex opaca

black walnut Juglans nigra

eastern redcedar Juniperus virginiana

sweetgum Liquidambar styraciflua

yellow-poplar Liriodendron tulipifera

Osage-orange Maclura pomifera

sweetbay Magnolia virginiana

apple spp. Malus spp.

red mulberry Morus rubra

blackgum Nyssa sylvatica

(Appendix continued on next page.)
88 | APPENDIXES

(Appendix continued) 

Common name Genus Species

eastern hophornbeam Ostrya virginiana

Norway spruce Picea abies

shortleaf pine Pinus echinata

red pine Pinus resinosa

pitch pine Pinus rigida

pond pine Pinus serotina

eastern white pine Pinus strobus

Scotch pine Pinus sylvestris

loblolly pine Pinus taeda

Virginia pine Pinus virginiana

American sycamore Platanus occidentalis

eastern cottonwood Populus deltoides

bigtooth aspen Populus grandidentata

cottonwood and poplar spp. Populus spp.

quaking aspen Populus tremuloides

sweet cherry, domesticated Prunus avium

black cherry Prunus serotina

white oak Quercus alba

swamp white oak Quercus bicolor

scarlet oak Quercus coccinea

southern red oak Quercus falcata

scrub oak Quercus ilicifolia

laurel oak Quercus laurifolia

blackjack oak Quercus marilandica

swamp chestnut oak Quercus michauxii

chinkapin oak Quercus muehlenbergii

pin oak Quercus palustris

willow oak Quercus phellos

chestnut oak Quercus prinus

northern red oak Quercus rubra

post oak Quercus stellata

black oak Quercus velutina

black locust Robinia pseudoacacia

black willow Salix nigra

sassafras Sassafras albidum

American basswood Tilia americana

basswood Tilia spp.

eastern hemlock Tsuga canadensis

American elm Ulmus americana

slippery elm Ulmus rubra
 | 89

Appendix 2.—List of invasive plants monitored by NRS-FIA on P2 invasive plots, 2007 to present

Tree Species Vine Species

ailanthus (Ailanthus altissima) English ivy (Hedera helix)

black locust (Robinia pseudoacacia) Japanese honeysuckle (Lonicera japonica)

chinaberry (Melia azedarach) Oriental bittersweet (Celastrus orbiculatus)

Norway maple (Acer platanoides)

paulownia, princesstree (Paulownia tomentosa) Herbaceous Species

punktree, melaleuca (Melaleuca quinquenervia) black swallow-wort (Cynanchum louiseae)

Russian-olive (Elaeagnus angustifolia) bull thistle (Cirsium vulgare)

saltcedar (Tamarix ramosissima) Canada thistle (Cirsium arvense)

Siberian elm (Ulmus pumila) creeping jenny (Lysimachia nummularia)

silktree, mimosa (Albizia julibrissin) dames rocket (Hesperis matronalis)

Chinese tallowtree (Triadica sebifera) European swallow-wort (Cynanchum rossicum)

garlic mustard (Alliaria petiolata)

Shrub Species giant knotweed (Polygonum sachalinense)

autumn-olive (Elaeagnus umbellata) Japanese knotweed (Polygonum cuspidatum)

common barberry (Berberis vulgaris) leafy spurge (Euphorbia esula)

common buckthorn (Rhamnus cathartica) Bohemian knotweed (Polygonum xbohemicum)

European cranberrybush (Viburnum opulus) purple loosestrife (Lythrum salicaria)

European privet (Ligustrum vulgare) spotted knapweed (Centaurea stoebe ssp. micranthos)

glossy buckthorn (Frangula alnus)

Japanese barberry (Berberis thunbergii) Grass Species

Japanese meadowsweet (Spiraea japonica) common reed (Phragmites australis)

multiflora rose (Rosa multiflora) Nepalese browntop (Microstegium vimineum)

nonnative bush honeysuckles (Lonicera spp.) reed canarygrass (Phalaris arundinacea)
90 | APPENDIXES

Oak/pine stand with an understory of blueberry. Photo by Rich Widmann, U.S. Forest Service.
Crocker, Susan J.; Barnett, Charles J.; Butler, Brett J.; Hatfield, Mark A.; Kurtz, Cassandra

M.; Lister, Tonya W.; Meneguzzo, Dacia M.; Miles, Patrick D.; Morin, Randall S.; Nelson,

Mark D.; Piva, Ronald J.; Riemann, Rachel; Smith, James E.; Woodall, Christopher W.; Zipse, 

William. 2017. New Jersey Forests 2013. Resour. Bull. NRS-109. Newtown Square, PA: U.S. 

Department of Agriculture, Forest Service, Northern Research Station. 90 p.

The second full annual inventory of New Jersey’s forests reports more than 2.0 million acres

of forest land and 77 tree species. Forest land is dominated by oak/hickory forest types in the

north and pitch pine forest types in the south. The volume of growing stock on timberland

has been rising since 1956 and currently totals 3.3 billion cubic feet. Average annual net

growth of growing stock from 2008 to 2013 was about 65.7 million cubic feet per year. This

report includes additional information on forest attributes, land-use change, carbon, timber

products, and forest health. The following information is available online at https://doi.

org/10.2737/NRS-RB-109: 1) detailed information on forest inventory statistics, methods,

and quality assurance of data collection, 2) a glossary of terms, 3) tables that summarize

quality assurance, 4) a core set of tabular estimates for a variety of forest resources, and 5) a

Microsoft® Access database that represents an archive of data used in this report, with tools

that allow users to produce customized estimates.

KEY WORDS: inventory, forest statistics, forest land, volume, biomass, carbon, growth,

removals, mortality, forest health, New Jersey

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