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Relationships Between Major Ownerships, Forest Aboveground Biomass Distributions, and Landscape Dynamics in the New England Region of USA


Abstract and Figures

This study utilizes remote sensing derived forest aboveground biomass (AGB) estimates and ownership information obtained from the Protected Areas Database (PAD), combining landscape analyses and GIS techniques to demonstrate how different ownerships (public, regulated private, and other private) relate to the spatial distribution of AGB in New England states of the USA. "Regulated private" lands were dominated by lands in Maine covered by a Land Use Regulatory Commission. The AGB means between all pairs of the identified ownership categories were significantly different (P < 0.05). Mean AGB observed in public lands (156 Mg/ha) was 43% higher than that in regulated private lands (109 Mg/ha), or 30% higher than that of private lands as a whole. Seventy-seven percent of the regional forests (or about 9,300 km(2)) with AGB >200 Mg/ha were located outside the area designated in the PAD and concentrated in western MA, southern VT, southwestern NH, and northwestern CT. While relatively unfragmented and high-AGB forests (>200 Mg/ha) accounted for about 8% of total forested land, they were unevenly proportioned among the three major ownership groups across the region: 19.6% of the public land, 0.8% of the regulated private land, and 11.0% of the other private land. Mean disturbance rates (in absolute value) between 1992 and 2001 were 16, 66, and 19 percent, respectively, on public, regulated private, and other private land. This indicates that management practices from different ownerships have a strong impact on dynamic changes of landscape structures and AGB distributions. Our results may provide insight information for policy makers on issues regarding forest carbon management, conservation biology, and biodiversity studies at regional level.
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Relationships Between Major Ownerships, Forest Aboveground
Biomass Distributions, and Landscape Dynamics in the New
England Region of USA
Daolan Zheng Linda S. Heath Mark J. Ducey
Brett Butler
Received: 16 November 2008 / Accepted: 15 November 2009 / Published online: 5 December 2009
ÓSpringer Science+Business Media, LLC 2009
Abstract This study utilizes remote sensing derived
forest aboveground biomass (AGB) estimates and owner-
ship information obtained from the Protected Areas Data-
base (PAD), combining landscape analyses and GIS
techniques to demonstrate how different ownerships
(public, regulated private, and other private) relate to the
spatial distribution of AGB in New England states of the
USA. ‘‘Regulated private’’ lands were dominated by lands
in Maine covered by a Land Use Regulatory Commission.
The AGB means between all pairs of the identified own-
ership categories were significantly different (P\0.05).
Mean AGB observed in public lands (156 Mg/ha) was 43%
higher than that in regulated private lands (109 Mg/ha), or
30% higher than that of private lands as a whole. Seventy-
seven percent of the regional forests (or about 9,300 km
with AGB [200 Mg/ha were located outside the area
designated in the PAD and concentrated in western MA,
southern VT, southwestern NH, and northwestern CT.
While relatively unfragmented and high-AGB forests
([200 Mg/ha) accounted for about 8% of total forested
land, they were unevenly proportioned among the three
major ownership groups across the region: 19.6% of the
public land, 0.8% of the regulated private land, and 11.0%
of the other private land. Mean disturbance rates (in
absolute value) between 1992 and 2001 were 16, 66, and
19 percent, respectively, on public, regulated private, and
other private land. This indicates that management prac-
tices from different ownerships have a strong impact on
dynamic changes of landscape structures and AGB distri-
butions. Our results may provide insight information for
policy makers on issues regarding forest carbon manage-
ment, conservation biology, and biodiversity studies at
regional level.
Keywords Biomass accumulation
Forest carbon storage Forest management
Land conservation Ownership behaviors
Forest aboveground biomass (AGB) is an important eco-
system property related to carbon cycles, fuel loading, and
biodiversity of flora and fauna (Cleary and others 2005;
Houghton 2005; Ryu and others 2006; Smith and Heath
2007; Zheng and others 2008a). Remote sensing techniques
have become prevalent in estimating AGB in recent years
at various scales (Nelson and others 1988; Franklin and
Hiernaux 1991; Lefsky and others 2002; Zheng and others
2004;Lu2005; Muukkonen and Heiskanen 2007; Zheng
and others 2007). Continuous AGB maps derived from RS
observations include all forest conditions, and are needed
to identify spatial distribution and variation of regional
forest AGB to provide information to support biodiversity
conservation. For example, late-developmental forests are
relatively rare in the Northern Forest region because of
land-use history and have high conservation value, but they
are sparsely represented, especially in sample-based,
D. Zheng (&)M. J. Ducey
Department of Natural Resources and the Environment,
University of New Hampshire, Durham, NH 03824, USA
L. S. Heath
USDA Forest Service, Northern Research Station, Mast Rd,
Durham, NH, USA
B. Butler
USDA Forest Service, Forest Inventory and Analysis, Family
Forest Research Center, Amherst, MA 01003, USA
Environmental Management (2010) 45:377–386
DOI 10.1007/s00267-009-9408-3
broad-scale inventories such as that of the USDA Forest
Service, Forest Inventory and Analysis (FIA) program.
Thus, spatially identifying these late-developmental forests
associated with their ownerships could provide necessary
information for ecological and biodiversity studies at
regional levels (Askins and others 1987; Richards and
others 2002).
The spatial pattern of high-conservation-value lands
may vary due to forest ownership. Public and private
owners may consider values of forests from multiple per-
spectives, such as production, conservation, family legacy,
ecological biodiversity, and aesthetics. While private
industrial owners are more likely to emphasize short-term
financial goals, opportunistic harvesting and other finan-
cially motivated behaviors can characterize other private
landowner groups (Jones and others 1995; Egan 2007).
Consequently, owners implement different strategies in
managing their forestlands. Even within private ownership
in the New England (NE) region, individuals owning rel-
atively small forested tracts behave differently from those
individuals and organizations with larger holdings (Butler
Previous studies have demonstrated that spatial distri-
butions of forest AGB vary substantially with human
introduced disturbances, and various management strate-
gies (Johnson and others 2000; Khera and others 2001). It
is of particular interest to understand the geographic rela-
tionship between late-developmental forests, other rela-
tively high-biomass forests (including younger unmanaged
forests), and their ownership in the NE region. Such
understanding may help inform policy that would influence
landscape management over substantial areas, with impli-
cations for regional biodiversity conservation and carbon
stocks. In addition, a great deal of time, money, and effort
has been invested in the development of spatially explicit
techniques for identifying candidate areas for conservation
assessment and action (Knight and others 2008; Wallace
and others 2008). These techniques enhance the effec-
tiveness of implemented conservation actions and provide
scientifically defensible information for better management
of natural resources, which is ecologically and socially
beneficial to the environment and communities.
The overall goal of this study is to examine relationships
between forest AGB stocks and major ownership groups in
the six NE states to examine if forest AGB differs by owner
group, including landscape dynamics and distribution pat-
terns of AGB. This information could help identify
opportunities for improved management of regional forest
ecosystems. Detailed steps include: (1) stratifying a MO-
DIS-derived 1-km AGB map based on the Protected Areas
Database (PAD) and comparing AGB distribution patterns
among different ownerships; (2) quantifying landscape
structures for different ownerships based on National Land
Cover Dataset (NLCD) and their relationships to regional
AGB distribution; (3) examining owner effect on different
management practices and therefore on landscape dynam-
ics between 1992 and 2001; and (4) illustrating how scaling
process can influence landscape pattern analyses.
Materials and Methods
This study was conducted in the 6 NE states of the USA:
Connecticut (CT), Massachusetts (MA), Maine (ME), New
Hampshire (NH), Rhode Island (RI), and Vermont (VT).
Forestland covered approximately 84% of this total terri-
tory based on the 2001 MODIS land-cover map. Major
inputs for this study include the biomass map, PAD map,
and land-cover maps from different sources.
Biomass Map
The 2001 AGB map used in this study was developed by
Zheng and others (2008b) for the region at 1-km resolution
using multi-scale methodology. In their study, ground-
based measurements from FIA were linked to remotely
sensed spectral information within a 30-m Landsat 7
Enhanced Thematic Mapper plus scene (ETM ?, about
180 9180 km in size) to develop an empirical AGB
model. The model was applied to the entire region using
1-km MODIS data after spectral calibrations with the
ETM ?data. The resulting spatially-explicit biomass map
takes advantage of integrity of spatial variation from RS
and unbiased county means of AGB observations devel-
oped from the larger sample sizes of FIA plots. The esti-
mated total regional forest AGB was 1,867 teragram (10
dry weight) in 2001, with a mean AGB density (dry
weight) of 120 Mg/ha (Standard deviation =54 Mg/ha)
ranging from 15 to 240 Mg/ha within a 95% percentile
(Zheng and others 2008b). At the state level, the average
difference in mean AGB densities between simulated and
FIA (as reference) was -2.0% ranging from 0% to -4.2%
with a standard error of 3.2% in absolute value.
High-AGB late-developmental secondary forests are of
particular conservation interest in the Northern Forest
region because centuries of land use history have left them
relatively scarce. However, current land use and manage-
ment is leading to an increasing representation of high-
AGB forests, including some forests with more advanced
developmental characteristics, as well as passively man-
aged forests of moderate age. These two categories of
forests may experience different AGB trajectories in the
future, depending not only on stand dynamics but on
landowner objectives and behavior. Spatially identifying
those high-AGB forests associated with major ownership
groups across the region is useful information.
378 Environmental Management (2010) 45:377–386
Ownership Identification
General ownership information was obtained from the
PAD map (2006 version 4) that was the result of a col-
laborative effort between the Conservation Biology Insti-
tute and the World Wildlife Fund U.S. (DellaSala and
others 2001). The database was developed as a geographic
information system (GIS) dataset that identifies protected
areas including publicly and privately owned lands in the
conterminous United States (
projects/PAD/index.htm). The PAD-US Partnership (www. defines protected areas as, ‘‘lands ded-
icated to the preservation of biological diversity and to
other natural, recreation and cultural uses, and managed for
these purposes through legal or other effective means’’. In
other words, protected areas are in general protected from
land development (permanent conversion to developed
land use) but not from unplanned disturbances or related
to management. The PAD is a national database with
somewhat generalized definitions that may be interpreted
differently from region to region across the country.
Regrouping original ownership categories may be neces-
sary depending on study purposes because a perfect naming
system may not even exist. We aggregated the original
PAD ownership classes that occurred in our region into
four broader groups: (1) public (federal, state, and local),
(2) regulated private (protected-private), (3) other private
(private-inholding, tribal, and all other forested lands not
designated in the PAD), and (4) others (joint ownership and
unknown) based on our best knowledge about the regional
land-use history and ownership behavior (Table 1). For
example, ‘‘Tribal’’ land was considered to be similar to
other private than to the public and regulated private cat-
egories based on ownership behavior (not the name). Our
analyses were focused on the first three groups since the
last one represented very small proportion of regional
forestland (0.02%). Such generalization simplified the
analyses because we were not interested in differences of
forest AGB distributions within the public land owned by
government agencies at various levels. In some regions,
differences between government agencies would be
apparent; in this region there is little Federal land (&4%).
Our analyses, instead, were focused on (1) the difference
between public (as a whole) and private in general; and (2)
within the privately owned forests, what are the differ-
ences, in terms of landscape characteristics and AGB dis-
tribution, between the categories of ‘‘regulated private’’
and ‘‘other private’’. Our study design reflects that (1) these
three general groups owned more than 99% of the regional
forested land; and (2) more than 90% of the regional for-
estland were privately owned (Irland 1999).
Landsat-Derived Land-Cover Maps Used
for Landscape Pattern Analyses
We used NLCD 1992 and 2001 maps, developed from
Landsat 5 and 7 imagery at 30-m resolution under the
Multi-Resolution Land Characteristics Consortium
(MRLC) project ( The two maps
were not used for pixel-to-pixel change detection, rather,
they were used for distinguishing forestland from non-
forestland after being aggregated to these 2 very broad
categories for the purposes of (1) landscape pattern anal-
ysis in 2001 to link the AGB distribution patterns in 2001;
(2) quantifying landscape dynamics between 1992 and
2001, and (3) examining how scaling process (from 30 m
to 1 km) can affect landscape pattern analyses. Landscape
pattern related analyses for all three ownerships were
conducted using FRAGSTATS after the NLCD maps were
stratified by the regrouped PAD map. It was noted that
detailed land-cover classes between the 1992 and 2001
NLCD maps were not identical for non-forest categories at
Anderson level II (Anderson and others 1976) with slightly
adjustment for agriculture, urban, and barren, but the
impact of these differences in our heavily forested region
was supposed to be very limited, especially at the broad
categories (i.e., forest versus non-forest) (Vogelmann and
others 2001; Homer and others 2004). We downloaded the
1992 and 2001 NLCD maps for the conterminous U.S.
nlcd_multizone_map.php) and extracted the NE area for
this study. We aggregated the Level II land-cover types of
41, 42, 43 into forest, and all other types into non-forest for
both years.
Table 1 Cross-walk table between original categories in the PAD
and reclassified classes involving forested lands in New England
Original records Reclassified classes
Federal Public
State Public
Local Public
Private-protected Regulated private
Private-inholding Other private
Tribal Other private
Forestlands not designated in PAD Other private
Joint Ownership Others
Unknown Others
A new version of PAD (although numbered version 1) was released
as this manuscript was through the review process.
Environmental Management (2010) 45:377–386 379
Quantifying Landscape Patterns and Dynamics
Landscape structures among the ownerships were quanti-
fied using FRAGSTATS – a spatial pattern analysis pro-
gram (version 3.3) (
fragstats/downloads/fragstats_downloads.html). Landscape
characteristics and patterns were evaluated in terms of four
representative indices at the class level: (1) patch density
(PD, number per 100 hectares, [0 without limit) calculated
as patch number within the corresponding status or own-
ership divided by total landscape area, larger PD indicating
more fragmented landscape; (2) edge density (ED, meters
per hectare, C0, without limit), as ED increases the land-
scape becomes more fragmented; (3) landscape shape
index (LSI, unitless, C1, without limit), LSI =1 when the
landscape consists of a single square or maximally compact
(i.e., almost square) patch of the corresponding type; LSI
increases without limit as the landscape becomes more
irregular; and (4) mean patch size (MPS, hectare, [0
without limit), larger MPS indicating less fragmented
landscape. The above indices, along with others, are widely
used for quantifying landscape dynamics and spatial pat-
terns (Zheng and others 1997; Buyantuyev and Wu 2007).
Illustration of Scaling Effects on Landscape Pattern
A subarea in Maine was used to demonstrate how scaling
process could affect quantifications of landscape charac-
teristics among the ownership categories (Fig. 1a). First,
the 30-m NLCD 2001 map for the subarea (forestland only)
was overlaid with our reclassified PAD map. Second,
landscape characteristics within each of the ownerships
were quantified using FRAGSTATS. The same procedures
were repeated for the analyses after the 30-m NLCD map
was aggregated to 1-km pixel size. Three represented
landscape indices quantified within the subarea based on
different pixel resolutions (30 m versus 1 km) were com-
pared to evaluate scaling effects on landscape pattern
analysis. Majority rule was used for spatial aggregation
from 30-m to 1-km resolution (ESRI 2008), which found
the value that appeared most often within the specified
windows (e.g. 1 91km
cells) and sent it to each of the
corresponding cells as the output grid.
Data Analyses and Statistics
Our initial tests in the subarea indicate that scaling process
can substantially affect landscape pattern analyses and
conclusions. Consequently, an appropriate pixel size
should be determined for the entire region. It is also
recognized that there is always a trade off between accu-
racy and efficiency in landscape studies by choosing an
appropriate pixel resolution that is consummated with the
study extent and purpose (Wu 1999). Previous studies have
demonstrated that the ‘noise’ in 30-m classified image can
be reduced by applying a certain cutting value for patch
size (e.g. C1 ha) for landscape structure analyses after a
rule-based merging algorithm is performed to eliminate the
‘salt and pepper’ effect (Ma 1995; Zheng and others 1997).
In forests, a patch is generally equivalent to a stand with a
homogeneous mixture of species, ages, sizes, and/or
stocking of trees (Waring and Running 1998). Heilman and
others (2002) applied minimum of 1 ha in size for
assessing forest fragmentation across the conterminous
U.S. For the above reasons, we aggregated the 30-m NLCD
maps to 90-m resolution (\1 ha) for the entire study area to
quantify landscape characteristics in 1992 and 2001 among
the 3 ownership groups using FRAGSTATS. Landscape
pattern analyses resulting from 90-m resolution data
retained the original patterns obtained from the 30-m data
while decreasing the time required for data processing and
simulations, and simplified the analyses. The FRAG-
STATS results for the 2001 landscape were linked to the
2001 AGB map to examine the relationships between AGB
distribution and landscape characteristics among the three
ownership groups. The FRAGSTATS results for the 1992
and 2001 landscapes were compared to illustrate differ-
ences in landscape dynamics among the 3 ownerships.
Image processing and spatial analyses were performed
using GIS packages (e.g. Imagine, ArcInfo, ArcView,
ArcMap). The Kruskal–Wallis test was used to test overall
significance of AGB distributions among groups, using
a=0.05. Then, the Wilcoxon rank sum test was used to
evaluate differences between each possible pair of groups.
Significance of the Wilcoxon tests was evaluated using a
Bonferroni-adjusted a =0.0083 (three pairs; experiment-
wise error rate was maintained at 0.05).Disturbance rates
in this study were defined as the relative changes for rep-
resentative indices calculated by FRAGSTATS between
the years 1992 and 2001. They are calculated as
– 1), and demonstrate how distur-
bance rates caused by different management practices can
affect landscape dynamics.
Privately owned forests accounted for about 90% of the NE
forested land whereas public land (e.g. owned by Federal,
state, and local governments) occupied 9% based on the
PAD map. This is very similar to the estimation of 87%
private ownership from FIA. Within the publicly owned
forest, federal ownership accounted for about 42% based
380 Environmental Management (2010) 45:377–386
on the PAD. Spatially, 82% of regional public lands were
within the 3 northern states with the maximum percentage
of 29.2% in NH, followed by 28.8% in ME, and 24.1% in
VT. In the meantime, 98% of regional regulated private
forests were concentrated in northern ME and 71% of other
private forests were in the 3 northern states (30%, 21%, and
Fig. 1 a Reclassified regional
ownership map based on the
national PAD. A sub area in the
rectangular box was used for
testing scaling effects on
landscape pattern analyses; and
b2001 forest aboveground
biomass (dry weight) map at
1-km resolution (Zheng and
others 2008b)
Environmental Management (2010) 45:377–386 381
20% for ME, NH, and VT respectively) followed by 17%
in MA, 11% in CT, and 2% in RI (Fig. 1a).
Clear trends of negative relationship were observed
between AGB values and degrees of landscape fragmen-
tation in 2001 between publicly and privately owned lands
in general, but less clear between regulated private and
other private (see discussion). The highest mean AGB was
observed in the public lands (156 Mg/ha), which was 43%
higher than the lowest AGB mean (109 Mg/ha) observed in
regulated private lands, or 30% higher than that in privately
owned lands on average (120 Mg/ha, after area weighting)
(Table 2). Within the private forests, however, mean AGB
density in other private forests was 19% greater than that in
regulated private forests. Mean AGB density in other pri-
vate forests featured the highest spatial variation, followed
by public forestland, with regulated private land showing
the lowest variation where more even-age management
could be expected. Our results agreed with the general
landscape ecological concept that higher forest biomass is
usually associated with more intact and less disturbed
forestlands (Chhetri 1999). A Kruskal–Wallis test sug-
gested that overall difference among AGB groups was
highly significant (K–W chi-squared =13693.64, df =2,
P-value \0.05) (Table 3). All pairs of groups were also
significantly different (P\0.05).
The forested lands with AGB density [200 Mg/ha
represented 7.8% of the total forested area (Fig. 1b). Of
these, 77% or 9,300 km
, were located outside the areas
designated in the PAD. These high-AGB forests were
mainly distributed in MA (41%), followed by VT (26%),
NH (19%), CT (11%), ME (3%), and RI (1%). Specifically,
they were concentrated in western MA, southern VT,
southwestern NH, and northwestern CT (Fig. 1b). Fur-
thermore, these high-AGB forests were unevenly propor-
tioned among the three major ownership groups across the
region: 19.6% of the public land, 0.8% of the regulated
private land, and 11.0% of the other private land. This
suggests potential impact of ownership behaviors on forest
carbon storage, conservation biology, and biodiversity
studies in the region.
Scaling processes could substantially affect landscape
pattern analysis. Three representative indices calculated
from 30-m and 1-km based maps within the subarea dif-
fered significantly in magnitude and showed inconsistent
patterns among the ownerships (Fig. 2). For example, 30-m
based results indicated that public land had lower PD than
that of other private land whereas the results from 1-km
based calculations showed an opposite pattern. Also 30-m
based results suggested that landscape shape was more
complex in regulated private land than that in other private
land but only differed slightly based on 1-km calculations.
Furthermore, values calculated from a 1-km map were
much smaller than those calculated from the 30-m map;
thus, a multiplier had to be used for comparison purposes
(Fig. 2).
Our landscape pattern analyses demonstrated that public
land in 2001 across the region had lower values of ED, PD,
and LSI than those in the private lands (Table 2), indicat-
ing a less fragmented landscape. Between the 2 private
ownerships, other private owned lands tended to be more
fragmented than those in the regulated private category.
This may reflect fragmentation and parcelization due to
residential and other development; the regulated private
forests occur in a portion of the region with relatively low
population density, and the regulating authority (Maine
2009) exercises some control over residential conversions
and other land use change.
Similarly, public forests on average experienced the
least disturbances between 1992 and 2001 while the
greatest disturbances were observed in regulated private
forests (Fig. 3). The disturbance rates expressed by the 4
indices in public land ranged from 12% in LSI to 19% in
PD with an average of 16% during the period whereas the
rates in regulated private land ranged from 38% in MPS (in
absolute value) to 85% in ED with an average of 66%.
Meanwhile, disturbance rates in other private land
(unprotected and non-industry related) ranged from 15%
(absolute value) in MPS to 24% in ED averaging 24%.
These results suggested substantial impact of ownership
and different forest management practices on landscape
dynamics in the region.
Table 2 Relationships between forest aboveground biomass (AGB,
Mg/ha) and landscape characteristics (resulting from the FRAG-
STATS) among major and ownership group in New England region
Public Regulated private Other private
2.0 7.5 16.4
0.015 0.022 0.066
56.4 116.4 189.7
) 7 15 9
AGB (Mg/ha) 156 (54) 109 (35
) 127 (59)
AGB range 1–483 1–376 1–363
Edge density,
Patch density,
Landscape shape index,
patch size,
Standard deviation
Table 3 Comparisons of aboveground biomass frequency distribu-
tions among major ownership groups using Kruskal–Wallis test
Public Regulated private Other private
Public * *
Regulated private *
Other private
* Indicates a significant difference at Pvalue \0.05. We only
marked half of the matrix because of its symmetry
382 Environmental Management (2010) 45:377–386
Our results agreed well with a previous study that about
90% NE forests were privately owned (Irland 1999).
Linkage between landscape pattern and AGB analyses
should be evaluated with caution due to scaling effects.
Similar results were also reported from other studies in
North America that forest disturbance rates were generally
lower in public lands than in private lands (Spies and others
1994; Turner and others 1996; Sachs and others 1998).
Although the MPS value in public land was smaller (more
fragmented according to the usual definition) than the
values in regulated and other private lands (Table 2), there
was a particular reason for this. Public lands represented a
small portion (9%) of the region, and they were selected
purposively for various considerations including watershed
protection, conservation value, historical significance,
national forest/park/monument/landmark, and recreational
and scenic values. This selection process has led to public
lands occurring as individual small patches scattered across
the region, and some public lands are interwoven with
private owner inholdings. By contrast, the 90% of regional
forests held by private owners were relatively continuous
and dominant over the landscape.
Forest disturbances included harvests in the regeneration
phase of even-aged silvicultural systems, which typically
lead to rapid redevelopment of forest cover and biomass in
this region, and terminal harvests for land use clearing due
to development and associated land cover changes, which
did not. The data used in this study did not allow unam-
biguous separation of the two types of disturbance, though
clearly they implied very different scenarios for future
AGB development in the region.
Between the 2 private ownership groups, forests within
the other private ownership category were more frag-
mented but had higher mean AGB than those in the regu-
lated private category. One should be cautious about causal
inferences, however. A partial explanation may be that
most regulated forests in Maine have in the past been
owned by industrial concerns that usually purchased lands
in large blocks (or aggregated ownerships by assembling
smaller holdings), while many other private forests were
owned by individuals holding small parcels. There has
been a trend in the region (as in the rest of the U.S.) since
the 1980s for industrial lands to be purchased by non-
industrial corporate owners, such as timber investment
management organization (TIMOs) and real estate invest-
ment trusts (REITs). The continuation of the observed
pattern will depend on the future harvesting and ownership
decisions of these organizations. Second, whereas indi-
vidual owners more likely used their properties for multiple
purposes (including forest harvest), forestland under
industrial ownership was managed with a different set of
financial objectives. One would expect a shorter harvesting
interval in such forests. For example, the harvest interval
of spruce-fir in northern ME has been about 70-year old
More intense and systematic harvesting pressure would
certainly attenuate high standing biomass accumulation.
AGB frequency curves clearly indicated that many fewer
hectares of forest in the regulated forestlands than in other
private land and public land currently reach AGB values
larger than 200 Mg/ha (Fig. 4).
30 m 1 km
Patch density (PD, # per 100 ha)
Public Regulated Privat
ther Private
Landscape shape index (LSI)
Edge density (ED, meters per ha)
Fig. 2 Evaluation of scaling effects (30 m vs. 1 km) on landscape
pattern analyses among major ownerships in a sub area of Maine,
USA by comparing the relative changes in some representative
landscape indices calculated from FRAGSTATS. Because the index
values calculated from different pixel resolutions are not at the same
magnitude, the values at 1 km have been multiplied by 10 for the
presentation purpose
Environmental Management (2010) 45:377–386 383
Another factor affecting AGB distributions is forest type
and composition. Most regulated private forests in northern
ME mainly consists of spruce-fir and northern hardwoods
with a lower expected productivity than in the oak and pine
forests occurring farther south. However, an influence of
ownership and forest practices on AGB distribution
remains evident because most of public forested lands that
have high AGB values are located in the 3 northern NE
states, and share their dominant forest types with the reg-
ulated private forests (Irland 1999). Partitioning the effects
of ownership, forest composition, and land use history on
the regional AGB distribution is necessarily difficult, as
these factors are intertwined in the New England
One source of potential error for this study is the use of
2 NLCD maps at different years (1992 and 2001), due
to different classification schemes applied in each year
(Vogelmann and others 2001; Homer and others 2004).
In general, water, urban, and forestedland covers have
relatively high classification accuracies while wetland,
rangeland, and barren have low accuracies (Hollister and
others 2004). Accuracies tend to increase as the classifi-
cation level becomes more broad (Stehman and Wickham
2006). For example, overall accuracies in different regions
across the eastern U.S. increase from 43%–66% at
Anderson Level II to 70%–83% at Level I whereas from
38%–70% to 74%–85% in different regions across the
western U.S. according to the 1992 NLCD map (Stehman
and others 2003; Wickham and others 2004). We expect
even smaller uncertainty from this perspective for this
study because our related analyses are conducted at even
broader categories (forest versus nonforest).
There are also some limitations in the national PAD
(V4) dataset used in this study. First, ideally and theoreti-
cally it should include protected private lands (such as
those under easements or held in fee by conservation
organizations), but it is difficult to maintain consistency
due to differences in various definitions among states. This
Public Regulated Private Other Private
Patch density Edge density Landscape shape Mean patch
Index size
Fig. 3 Relative disturbance
rates of forest landscapes
between 1992 and 2001 among
major ownerships across the
region by comparing four
representative class-level
indices calculated from
1 25 49 73 97 121 145 169 193 217 241 265 289 313 337 361 385 409 433 457 481
Above ground biomass density (Mg/ha)
Frequency distribution (%)
Public Regulated Private Other Private
Fig. 4 Frequency distributions
of forest aboveground biomass
density within major
ownerships in New England
region, USA. Statistical
analyses were based on raw data
and the curves drawn based on a
5-point running average
384 Environmental Management (2010) 45:377–386
remains true even in the newly available updated PAD-V1,
just released after this study was conducted (http:// Second, the PAD is not
designed to distinguish between industrial and non-indus-
trial private owners, although this distinction may be
inferred by forest type in our study in the State of Maine.
Further investigation on the strengths and limitations of the
PAD are needed but they are beyond the scope of this
study. Our experience with this study suggests that labeling
of a management choice in a national dataset should be
carefully implemented at the regional level, especially with
the designation ‘‘protected’’.
Ownership composition in the region is extremely
unevenly distributed, which tends to create confounding
between biophysical and ownership factors in understand-
ing the pattern of AGB distributions. This study, however,
illustrates how different broad ownership categories are
associated with regional landscape dynamics and AGB
distributions. Our results can also be used for comparison
with similar analyses for other regions in the country.
Our results have clearly revealed the impact of major
ownerships on regional biomass accumulation and land-
scape pattern dynamics. Uneven distributions (both spa-
tially and statistically) of high-AGB forests among the
major ownerships provide insight information on regional
forest resources management and policy implication. These
high-AGB forests can contribute important social and
ecological benefits to the community and society as a
whole including: (1) flood and erosion control and man-
agement of water quantity and quality while increasing
carbon storage in forest ecosystems; and, (2) preserving
unique aesthetic value and habitats of late successional
forest for recreational and biodiversity considerations. The
uneven distribution of high-AGB forests by ownership
suggests on the one hand that maintaining such forests on
the landscape may be a worthwhile conservation goal, but
also suggests there may be significant opportunities both to
conserve existing high-AGB forests and to create young
forests on privately-owned lands to provide goods and
services to meet societal demands. In terms of research
methodology, we found that determining a suitable pixel
resolution on raster-version FRAGSTATS simulations is
necessary to achieve meaningful and efficient analyses on
linking regional landscape characteristics and ecosystem
properties (e.g., AGB).
Acknowledgments This study is supported by the USDA Forest
Service, Northern Research Station through grant 05-DG-11242343-
ESRI ArcGIS 9.2 Desktop Help (2008)
desktop/9.2/index.cfm?TopicName=BlockMajority. Accessed 3
Jan 2008
Anderson JR, Hardy EE, Roach JT, Witmer WE (1976) A land use
and land cover classification system for use with remote sensing
data. US geological survey professional paper 964, Reston, VA,
28 p
Askins RA, Philbrick MJ, Sugeno DS (1987) Relationship between
the regional abundance of forest and the compostition of forest
bird communities. Biological Conservation 39:129–152
Butler BJ (2008) Family forest Owners of the United States, 2006.
Gen Tech Rep NRS-27. US Department of Agriculture, Forest
Service, Northern Research Station, Newtown Square, PA, 72 p
Buyantuyev A, Wu J (2007) Effects of thematic resolution on
landscape pattern analysis. Landscape Ecology 22:7–13
Chhetri DBK (1999) Comparison of forest biomass across a human-
induced disturbance gradient in Nepal’s Schima-Castanopsis
forests. Journal of Sustainable Forestry 9:69–82
Cleary DFR, Genner MJ, Boyle TJB, Setyawati T, Angraeti CD,
Menken SBJ (2005) Associations of bird species richness and
community composition with local and landscape-scale envi-
ronmental factors in Borneo. Landscape Ecology 20:989–1001
DellaSala DA, Staus NL, Strittholt JR, Hackman A, Iacobelli A
(2001) An updated protected areas database for the United States
and Canada. Natural Areas Journal 21:124–135
Egan AF (2007) Farm woodlots in northern New England, USA:
Characteristics, management, and contributions to the whole
farm system. Renewable Agriculture and Food Systems 22:67–
Franklin J, Hiernaux PHY (1991) Estimating foliage and woody
biomass in Sahelian and Sudanian woodlands using a remote
sensing model. International Journal of Remote Sensing
Heilman GE Jr, Strittholt JR, Slosser NC, Dellasala DA (2002) Forest
fragmentation of the conterminous United States: Assessing
forest intactness through road density and spatial characteristics.
BioScience 52:411–422
Hollister JW, Gonzalez ML, Paul JF, August PV, Copeland JL (2004)
Assessing the accuracy of National Land Cover Dataset area
estimates at multiple spatial extents. Photogrammetric Engi-
neering and Remote Sensing 70:405–414
Homer C, Huang C, Yang L, Wylie B, Coan M (2004) Development
of a 2001 National Land-cover Database for the United States.
Photogrammetric Engineering and Remote Sensing 70:829–840
Houghton RA (2005) Aboveground forest biomass and the global
carbon balance. Global Chang Biology 11:945–958
Irland LC (1999) The Northeast’s changing forest. Harvard University
Press, Cambridge, Massachusetts 401 pp
Johnson CM, Zarin DJ, Johnson AH (2000) Post-disturbance
aboveground biomass accumulation in global secondary forests.
Ecology 81:1395–1401
Jones SB, Luloff AE, Finley JC (1995) Another look at NIPFs: Facing
our ‘myths’. Journal of Forestry 93:41–44
Khera N, Kumar A, Ram J, Tewari A (2001) Plant biodiversity
assessment in relation to disturbances in mid-elevational forest
of Central Himalaya, India. Tropical Ecology 42:83–95
Knight AT, Cowling RM, Rouget M, Balmford A, Lombard AT,
Campbell BM (2008) Knowing but not doing: selecting priority
conservation areas and the research-implementation gap. Con-
servation Biology 22:610–617
Lefsky MA, Cohen WB, Harding DJ, Parker GG, Acker SA, Gower
ST (2002) Lidar remote sensing of above-ground biomass in
three biomes. Global Ecology and Biogeography 11:393–399
Environmental Management (2010) 45:377–386 385
Lu D (2005) Aboveground biomass estimation using Landsat TM data
in the Brazilian Amazon. International Journal of Remote
Sensing 26:2509–2525
Ma Z-K (1995) Using a rule-based merging algorithm to eliminate
‘salt/pepper’ and small regions of classified image. In: Ninth
annual symposium on geographic information systems, Vancou-
ver, British Columbia, Canada, pp 834–837
Maine (2009) Land use regulation commission. http://www.maine.
Muukkonen P, Heiskanen J (2007) Biomass estimation over a large
area based on standwise forest inventory data and ASTER and
MODIS satellite data: A possibility to verify carbon inventories.
Remote Sensing of Environment 107:617–624
Nelson R, Krabill W, Tonelli J (1988) Estimating forest biomass and
volume using airbone laser data. Remote sensing of environment
Richards WH, Wallin DO, Schumaker NH (2002) An analysis of late-
seral Forest connectivity in Western Oregon. U.S.A. Conserva-
tion Biology 16:1409–1421
Ryu S-R, Chen J, Zheng D, Bresee MK, Crow TR (2006) Simulating
the effects of prescribed burning on fuel loading and timber
production in managed northern Wisconsin forests. Ecological
Modeling 196:395–406
Sachs DL, Sollins P, Cohen WB (1998) Detecting landscape changes
in the interior of British Columbia from 1975 to 1992 using
satellite imagery. Canadian Journal of Forest Research 28:23–36
Smith JE, Heath LS (2007) Forest carbon sequestration and products
storage. The US agriculture and forestry greenhouse gas
inventory: 1990–2006. In: USDA, Office of the Chief Econo-
mist, Global Change Program Office, Washington DC
Spies TA, Ripple WC, Bradshaw GA (1994) Dynamics and pattern of
a managed coniferous forest landscape in Oregon. Ecological
Applications 4:555–568
Stehman SV, Wickham JD (2006) Assessing accuracy of net change
derived from land cover maps. Photogrammetric Engineering
and Remote Sensing 72:175–185
Stehman SV, Wickham JD, Smith JH, Yang L (2003) Thematic
accuracy of the 1992 National Land-Cover Data for the eastern
United States: Statistical methodology and regional results.
Remote Sensing of Environment 86:500–516
Turner MG, Wear DN, Flamm RO (1996) Land ownership and land
cover change in the Southern Appalachian highlands and
Olympic peninsula. Ecological Applications 6:1150–1172
Vogelmann JE, Howard SM, Yang L, Larson CR, Wylie BK, Van
Driel N (2001) Completion of the 1990s National Land Cover
Dataset for the conterminous United States from Landsat
Thematic Mapper data and ancillary data sources. Photogram-
metric Engineering and Remote Sensing 67:650–652
Wallace GN, Theobald DM, Ernst T, King K (2008) Assessing the
ecological and social benefits of private land conservation in
Colorado. Conservation Biology 22:284–296
Waring RH, Running SW (1998) Forest ecosystems: analysis at
multiple scales. Academic Press, San Diego
Wickham JD, Stehman SV, Smith JH, Yang L (2004) Thematic
accuracy of the 1992 National Land-Cover Data for the western
United States. Remote Sensing of Environment 91:452–468
Wu J (1999) Hierarchy and scaling: extrapolating information along a
scaling ladder. Canadian Journal of Remote Sensing 25:367–380
Zheng D, Wallin DO, Hao Z (1997) Rates and patterns of landscape
change between 1972 and 1988 in the Changbai Mountain area
of China and North Korea. Landscape Ecology 12:241–254
Zheng D, Rademacher J, Chen J, Crow T, Bresee M, LeMoine J, Ryu
S-R (2004) Estimating aboveground biomass using Landsat 7
ETM ?data across a managed landscape in northern Wisconsin,
USA. Remote Sensing of Environment 93:402–411
Zheng D, Heath LS, Ducey MJ (2007) Forest biomass estimated from
MODIS and FIA data in the Lake States: MN, WI, and MI, USA.
Forestry 80:265–278
Zheng D, Heath L, Ducey M (2008a) Satellite detection of land-use
change and effects on regional forest aboveground biomass
estimates. Environmental Monitoring and Assessment 144:67–
Zheng D, Heath LS, Ducey MJ (2008b) Spatial distribution of forest
aboveground biomass estimated from remote sensing and forest
inventory data in New England, USA. Journal of Applied
Remote Sensing 2:021502
386 Environmental Management (2010) 45:377–386
... Publicly owned forests generally appeared to be characterized by more pronounced old-growth or ancient woodland structures, a higher abundance of typical forest species, and less landscape fragmentation than privately owned forests (when holding sizes are not considered). In particular, this is true for forest bird species in Central Europe [24] and eastern North America [22,117], the amount of growing stock in eastern North America [125] and central Europe [126], the degree of landscape fragmentation in northern Europe [77] and eastern North America [113], and the amounts of deadwood or large-diameter trees in western North America [127] and Western and Central Europe [24,128,129]. ...
... Furthermore, these areas often stand out as old-growth or ancient woodland and are therefore characterized by long-term ecological continuity that makes them suitable for protected area designations. Consequently, large nature reserves, national parks, and other conservation areas are mostly associated with long-term public ownership both in Europe and in Northern America [24,49,125,[129][130][131]. Furthermore, the establishment of protected areas tends to be easier in publicly owned forests than in private land if the policy supports such efforts. ...
... Furthermore, the establishment of protected areas tends to be easier in publicly owned forests than in private land if the policy supports such efforts. The same is true for modern concepts of integrative multifunctional forest management and retention forestry, which are particularly implemented under public ownership [4,19,22,36,125,128,130]. For these reasons, the occurrence of species that are linked to old-growth structures and long-term ecological continuity is frequently associated with ancient, natural or semi-natural, publicly owned woodland under conservation-oriented forest management [19,24,132]. ...
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Purpose of Review Ownership patterns and the associated management characteristics are related to forest structures, biodiversity patterns, and their conservation worldwide. A literature review on this topic is missing so far. We fill this gap with an emphasis on the temperate forests of Europe and North America. Mixed-ownership landscapes are the special focus of the analysis. In a first step, historical effects of ownership patterns on forest structure and biodiversity are elucidated. Second, connections between present-time forest ownership patterns and both forest structural and biodiversity patterns are analyzed. Finally, implications for integrative conservation management are evaluated with a special focus on mixed-ownership forest landscapes. Recent Findings Close linkages between ownership type-specific forest management and particular forest structural and biodiversity patterns are identified for past and current forest landscapes. Both in Europe and North America, publicly and privately owned forests show comparable lines of historical development but with a time shift. Forest reserves and ancient woodland with long ecological continuity appear to be mainly connected with public ownership. A high diversity of management approaches and cultural landscape habitats is characteristic of non-industrial small private forests. In mixed-ownership landscapes, a more diverse mosaic of habitats has developed than in mono-ownership landscapes. Summary We conclude that cross-boundary ecosystem management is crucial for effective conservation in present-day mixed-ownership landscapes. Integrative forest management that considers biodiversity and social-ecological aspects across ownerships is indispensable. We present a framework of implications for conservation management in mixed-ownership forest landscapes that build on each other and may enhance cross-boundary ecosystem management.
... Despite widespread past clearing, the forests of the Northeast and Upper Great Lakes have recovered to the point that they are among the most intact and carbon-dense in the eastern U.S. (Zheng et al., 2008;Zheng et al., 2010;Foster et al., 2017). In addition, because these forests grow vigorously, decay slowly, and are, on average, less than 100 years old, they have centuries of growth ahead and enormous capacity for additional carbon storage (Pan et al., 2011;Williams et al., 2012) and climate stabilization. ...
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A campaign is underway to clear established forests and expand early-successional habitats—also called young forest, pre-forest, early seral, or open habitats—with the intention of benefitting specific species. Coordinated by federal and state wildlife agencies, and funded with public money, public land managers work closely with hunting and forestry interests, conservation organizations, land trusts, and private landowners toward this goal. While forest-clearing has become a major focus in the Northeast and Upper Great Lakes regions of the U.S., far less attention is given to protecting and recovering old-forest ecosystems, the dominant land cover in these regions before European settlement. Herein we provide a discussion of early-successional habitat programs and policies in terms of their origins, in the context of historical baselines, with respect to species’ ranges and abundance, and as they relate to carbon accumulation and ecosystem integrity. Taken together, and in the face of urgent global crises in climate, biodiversity, and human health, we conclude that public land forest and wildlife management programs must be reevaluated to balance the prioritization and funding of early-successional habitat with strong and lasting protection for old-growth and mature forests, and, going forward, must ensure far more robust, unbiased, and ongoing monitoring and evaluation.
... Our models are based on occurrence data and thus do not consider the effects of behaviour on other population-level differences, such as population density and reproductive rates (Hoy et al., 2018). High-biomass, late-successional forests are more common in the southern, warmer portion of the region because of forest management practices (Zheng et al., 2010). These habitats can provide thermal ref- ...
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Aim Populations of cold‐adapted species at the trailing edges of geographic ranges are particularly vulnerable to the negative effects of climate change from the combination of exposure to warm temperatures and high sensitivity to heat. Many of these species are predicted to decline under future climate scenarios, but they could persist if they can adapt to warming climates either physiologically or behaviourally. We aim to understand local variation in contemporary habitat use and use this information to identify signs of adaptive capacity. We focus on moose (Alces alces), a charismatic species of conservation and public interest. Location The northeastern United States, along the trailing edge of the moose geographic range in North America. Methods We compiled data on occurrences and habitat use of moose from remote cameras and GPS collars across the northeastern United States. We use these data to build habitat suitability models at local and regional spatial scales and then to predict future habitat suitability under climate change. We also use fine‐scale GPS data to model relationships between habitat use and temperature on a daily temporal scale and to predict future habitat use. Results We find that habitat suitability for moose will decline under a range of climate change scenarios. However, moose across the region differ in their use of climatic and habitat space, indicating that they could exhibit adaptive capacity. We also find evidence for behavioural responses to weather, where moose increase their use of forested wetland habitats in warmer places and/or times. Main conclusions Our results suggest that there will be significant shifts in moose distribution due to climate change. However, if there is spatial variation in thermal tolerance, trailing‐edge populations could adapt to climate change. We highlight that prioritizing certain habitats for conservation (i.e., thermal refuges) could be crucial for this adaptation.
... (Fry et al. 2011, Homer et al. 2015. The original NLCD is based on Anderson Level II cover types (Anderson 1976); for simplicity of interpretation, and to reduce confusion between spectrally similar cover types, we followed Zheng et al. (2010) in aggregating these types to Anderson Level I. The eight Level I land cover types include (1) open water, (2) urban, (3) barren, (4) forest, (5) grass/shrub, (6) agriculture, (7) wetland, and (8) snow/ice. ...
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The Great Lakes region contains productive agricultural and forest lands, but it is also highly urbanized, with 32 of its 52 million residents living in nine large metropolitan areas. Urbanization of undeveloped areas may adversely affect the productivity of agricultural and forest lands, and the provision of ecosystem services. We combine demographic and remote sensing data to evaluate land cover change in the region using a two-phase statistical modeling approach that predicts the incidence and extent of land cover change for each of the region’s 10,579 county subdivisions. Observed patterns are spatially uneven, and the probability of land cover change is influenced by current land use, human habitation, industry, and demographic change. Pseudo R² values varied from 0.053 to 0.338 for the first-phase logistic models predicting the presence of land cover change; second-stage beta models predicting the rate of change were more reliable, with pseudo R² ranging from 0.225 to 0.675. Overall, changes from agriculture or greenspace to development were much more predictable than changes from agriculture to greenspace or vice versa, and demographic variables were much more important in models predicting change to development. Although models successfully predicted the general location of land cover change, and models from before the Great Recession were useful for predicting the location but not the amount of change during the recession, fine-grained prediction remained challenging. Understanding where future changes are most probable can inform planning and policy-making, which may reduce the impact of development on resource production, environmental health, and ecosystem services.
... An emerging literature has framed forest ecosystems in terms of complex adaptive system properties (Filotas et al., 2014;Messier et al., 2015;Nocentini et al., 2017;Spies et al., 2014); specifically, heterogeneous conditions, hierarchical structure, ability to self-organize and adapt in response to changing external conditions, openness (not closed off from other systems), path dependency, non-linearity, and unpredictability (Levin, 1998). In addition, a growing body of empirical research has documented complex interactions between forest ecosystems, socio-economic changes, and land uses over space and time, specifically how new land uses can combine with legacies of past practices and ongoing climate change to give rise to large scale disturbance patterns (Allen, 2007;Barbier et al., 2010;Chapin et al., 2008;Lambin and Meyfroidt, 2010;Ravenscroft et al., 2010;Rudel et al., 2005;Spies et al., 2014;Stanfield et al., 2003;Vergara and Armesto, 2009;Zheng et al., 2010). These bodies of literature provide a foundation for framing forests as SESs. ...
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Many of the most pressing threats to forests result from complex interactions between multiple stressors and require management on large spatial and temporal scales. For this reason, many ecosystem managers have begun to recognize the need to consider the broader context of decisions, and how outcomes of past, present and future decisions in one location may interact with outcomes of such decisions in other locations nearby. The landscape has been put forth as an appropriate unit for such holistic approaches to management. However, as there are differing definitions of landscapes, it can be difficult to develop frameworks for management. Moreover, many definitions do not fully account for the many ways social and ecological conditions and processes interact within landscapes. Building on emerging theoretical and empirical literature, I offer a perspective on temperate forest landscapes as social-ecological systems: nested sets of coevolving social and natural subsystems connected through feedbacks, time lags, and cross-scale interactions. This interdisciplinary framing emphasizes the bio-geophysical and socio-cultural influences on landscapes and the need to consider these influences-and the interactions among them-in management. I discuss challenges to managing forest landscapes as social-ecological systems that stem from mismatches in the temporal and spatial scales on which ecological and social systems typically function, as well as opportunities for policies, formal organizations, and governance networks.
... We further studied forest attrition in two contextual landscape segmentations: i) urbanization levels to more closely assess forests' direct human benefits such as providing sources of fresh water [82], purifying air and reducing storm runoff [83], preventing erosion and damage to roads and structures [84], dampening the effects of urban heat island [85,86], and reducing Forest attrition spatial patterns in conterminous U.S. greenhouse gas emission [87][88][89][90]because urban areas represent immediate human influence and direct land conversion pressure from urban expansion and ii) land ownership types as forest ownership type impacts forest disturbance [91], forest landscape pattern and animal habitat [92][93][94], stand structure and carbon storage [95], forest aboveground biomass and landscape dynamics [96]. Forest attrition dynamics in each landscape stratum are reported in Fig 5. Results are further separated in six major ecoregions with different densities of forest cover. ...
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Forests are experiencing significant changes; studying geographic patterns in forests is critical in understanding the impact of forest dynamics to biodiversity, soil erosion, water chemistry and climate. Few studies have examined forest geographic pattern changes other than fragmentation; however, other spatial processes of forest dynamics are of equal importance. Here, we study forest attrition, the complete removal of forest patches, that can result in complete habitat loss, severe decline of population sizes and species richness, and shifts of local and regional environmental conditions. We aim to develop a simple yet insightful proximity-based spatial indicator capturing forest attrition that is independent of spatial scale and boundaries with worldwide application potential. Using this proximity indicator, we evaluate forest attrition across ecoregions, land ownership and urbanization stratifications across continental United States of America. Nationally, the total forest cover loss was approximately 90,400 km 2 , roughly the size of the state of Maine, constituting a decline of 2.96%. Examining the spatial arrangement of this change the average FAD was 3674m in 1992 and increased by 514m or 14.0% in 2001. Simulations of forest cover loss indicate only a 10m FAD increase suggesting that the observed FAD increase was more than an order of magnitude higher than expected. Furthermore, forest attrition is considerably higher in the western United States, in rural areas and in public lands. Our mathematical model (R 2 = 0.93) supports estimation of attrition for a given forest cover. The FAD metric quantifies forest attrition across spatial scales and geographic boundaries and assesses unambig-uously changes over time. The metric is applicable to any landscape and offers a new complementary insight on forest landscape patterns from local to global scales, improving future exploration of drivers and repercussions of forest cover changes and supporting more informative management of forest carbon, changing climate and species biodiversity.
Medicinal plants are important for human life and wellbeing. Worryingly, climate change and severe weather have become serious threats to the diversity and sustainable use of medicinal plants. The aim of this work is to present the most current information on the impact of climate change on the world’s medicinal plant species, with special emphasis paid on data provided by the IUCN Red List of Threatened Species. Using “Taxonomy: Plantae,” “Use and Trade: Medicine—human & veterinary,” and “Threats: Climate change & severe weather” filters on the advanced search of the IUCN Red List website, this work provides information on the diversity of medicinal plants (family, species, and growth form diversity) impacted by climate change, their use (diseases cured, plant parts used, active compound or secondary metabolites, and side effects), habitat ranges, geographical distribution, and conservation status according to the IUCN Red List Category and Criteria. We also inform conservation actions and research activities needed to ensure the future of medicinal plants and their sustainable uses.KeywordsConservation statusDroughtHabitat shiftingIUCN Red List category and criteriaTemperature extreme
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An assessment of annual land cover on publicly and privately managed lands across the conterminous United States (CONUS) from 1985-2018 was performed, including land cover conversions within their management category, to inform future policy and land-use decision-making in natural resource management. Synthesizing land cover data with land management delineations aids our ability to address effects of land management decisions by public or private entities. The U.S. Geological Survey (USGS) Protected Areas Database of the United States (PAD-US) version 2.1 data delineate land management categories and enable examination of land cover composition and change using the USGS Land Change Monitoring, Assessment, and Projection (LCMAP) reference data. Average composition of our delineated CONUS results using LCMAP land cover classes is 40% Grass/Shrub (GS), 29% Tree Cover (TC), 18% Cropland (CP), 5% Developed (DV), 5% Wetland (WL), 1.8% Water (WR), and 0.9% Barren (BN). Private (public) land is composed of 35% (52%) GS, 27% (36%) TC, 25% (1%) CP, 7% (1%) DV, 5% (5%) WL, 2% (2%) WR, and less than 1% (3%) BN. Land cover change averaged less than 1% per year. The largest net percentage gains across CONUS were in DV land and GS, and the greatest net losses were in CP and TC. Approximately 73% of CONUS is private land and, thus, land cover change across CONUS is largely a reflection of private land change dynamics. Private compositional changes show net gains from 1985-2018 in DV (2.3%), WR (0.2%), and GS (0.1%) classes, while net losses occurred in CP ( 1.9%), TC (-0.6%), WL (-0.1%), and BN (-0.01%). Public land cover changes show net gains in GS (1%), DV (0.2%), WR (0.01%), WL (0.05%), and BN (0.1%) classes, and net losses in CP (-0.3%) and TC (-1%). Our study reveals connections between land cover conversion, policy, and socioeconomic decisions.
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ContextProtected areas are a cornerstone of the global strategy for conserving biodiversity, and yet their efficacy in comparison to unprotected areas is rarely tested. In the highly fragmented forests of temperate regions, landscape context and forest history may be more important than protection status for plant species diversity. Objectives To determine whether there are differences in plant diversity between protected areas and private lands while controlling for landscape context, forest age, and other important factors. Methods We used a database of 156 one-hectare forest plots distributed over 120,000 km2 in the fragmented forests of southern Ontario to test whether protected areas and private forests differed in native species richness, relative abundance of exotic species, and the probability of finding species of conservation concern. ResultsPlots with more forest on the surrounding landscape had higher native species richness, lower abundance of exotic species, and greater probability of supporting at least one species of conservation concern. Young forests tended to have higher abundance of exotics, and were less likely to support species of conservation concern. Surprisingly, privately owned forests had greater native species richness and were more likely to support species of conservation concern once these other factors were accounted for. In addition, there were significant interactions between ownership type, forest history, and landscape context. Conclusions Our results highlight the importance of privately owned forests in this region, and the need to consider forest history and landscape context when comparing the efficacy of protected areas versus private land for sustaining biodiversity.
Since 2009, the US Department of Agriculture Forest Service has promoted an "all lands approach" to forest restoration, particularly relevant in the context of managing wildfire. To characterize its implementation, we undertook an inventory of what we refer to as fire-focused all lands management (ALM) projects, defined as projects in which fuels reduction treatments are planned or implemented across more than one landownership to reduce wildfire risk or increase forest resilience to wildfire. We focused on regions of Washington, Oregon, and California dominated by dry, fire-prone forests and documented 41 projects. From this sample we developed a typology with five project categories. We found that ALM takes many forms and occurs in diverse contexts, federal lands and land managers are frequently involved in them, and all projects foster relationship and capacity building for future ALM. Our typology provides a framework for better understanding of all lands approaches and suggests areas for further investigation.
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Multi-Resolution Land Characterization 2001 (MRLC 2001) is a second-generation Federal consortium designed to create an updated pool of nation-wide Landsat 5 and 7 imagery and derive a second-generation National Land Cover Database (NLCD 2001). The objectives of this multi-layer, multi-source database are two fold: first, to provide consistent land cover for all 50 States, and second, to provide a data framework which allows flexibility in developing and applying each independent data component to a wide variety of other applications. Components in the database include the following: (1) normalized imagery for three time periods per path/row, (2) ancillary data, including a 30 m Digital Elevation Model (DEM) derived into slope, aspect and slope position, (3) perpixel estimates of percent imperviousness and percent tree canopy, (4) 29 classes of land cover data derived from the imagery, ancillary data, and derivatives, (5) classification rules, confidence estimates, and metadata from the land cover classification. This database is now being developed using a Mapping Zone approach, with 66 Zones in the continental United States and 23 Zones in Alaska. Results from three initial mapping Zones show single-pixel land cover accuracies ranging from 73 to 77 percent, imperviousness accuracies ranging from 83 to 91 percent, tree canopy accuracies ranging from 78 to 93 percent, and an estimated 50 percent increase in mapping efficiency over previous methods. The database has now entered the production phase and is being created using extensive partnering in the Federal government with planned completion by 2006.
Full-text available
Multi-Resolution Land Characterization 2001 (MRLC 2001) is a second-generation Federal consortium designed to create an updated pool of nation-wide Landsat 5 and 7 imagery and derive a second-generation National Land Cover Database(NLCD 2001). The objectives of this multi-layer, multi-source database are two fold: first, to provide consistent land cover for all 50 States, and second, to provide a data framework which allows flexibility in developing and applying each independent data component to a wide variety of other applications. Components in the database include the following: (1) normalized imagery for three time periods per path/row, (2) ancillary data, including a 30 m Digital Elevation Model(DEM) derived into slope, aspect and slope position, (3) per-pixel estimates of percent imperviousness and percent tree canopy, (4) 29 classes of land cover data derived from the imagery, ancillary data, and derivatives, (5) classification rules, confidence estimates, and metadata from the land cover classification. This database is now being developed using a Mapping Zone approach, with 66 Zones in the continental United States and 23 Zones in Alaska. Results from three initial mapping Zones show single-pixel land cover accuracies ranging from 73 to 77 percent, imperviousness accuracies ranging from 83 to 91 percent, tree canopy accuracies ranging from 78 to 93 percent, and an estimated 50 percent increase in mapping efficiency over previous methods. The database has now entered the production phase and is being created using extensive partnering in the Federal government with planned completion by 2006.
Protecting biodiversity in a network of reserves has been a major goal of conservationists for more than a century. However, efforts in Canada and the United States to report on progress in meeting protection goals have been hampered by a lack of standardized protected areas inventories. We present an updated protected areas database that is useful for tracking protection goals at various spatial scales (e.g., state, province, country, ecoregion, and biome). Using the database, just 5.1% and 6.5% of the land area of the United States and Canada, respectively, have been set aside in strictly protected reserves; an additional 5.3% and 0.9% of each nation, respectively, is in more relaxed levels of protection characterized by greater human activities. Amount of protection for individual states ranged from <1.0% for most of the eastern and central United States to 35.3% for Alaska, and from 1.6% for Newfoundland and Labrador to roughly 11.0% for British Columbia. Thirty ecoregions considered to have globally outstanding levels of biodiversity totaled 8.2% of land area protected. Most (97%) individual protected areas were <10,000 ha, and only a small proportion (0.53%) were >100,000 ha. Our results illustrate the importance of standardizing and periodically updating national protected areas databases to accurately report on progress in meeting national conservation targets.
Net change derived from land-cover maps provides important information for environmental monitoring and modeling. To better target the objectives of net change accuracy, we require modifications of the sampling design and analysis protocols typically implemented for assessments focusing on single date or gross change maps. Mean absolute deviation estimated for user-defined reporting domains is suggested to characterize net change accuracy. Stratified sampling is often desirable to improve precision for high priority estimates (e.g., high net change domains), but decisions regarding the number and identity of strata must be made recognizing the precision trade-offs among the multiple estimates of interest in a net change assessment. The accuracy assessment strategy and a protocol for evaluating sampling design options are demonstrated using a population of map and reference net change derived from existing land-cover maps and representing change from 1990 to 2000.
Site-specific accuracy assessments evaluate fine-scale accuracy of land-use/land-cover (LULC) datasets but provide little insight into accuracy of area estimates of LULC classes derived from sampling units of varying size. Additionally, accuracy of landscape structure metrics calculated from area estimates cannot be determined solely from site-specific assessments. We used LULC data from Rhode Island and Massachusetts as reference to determine the accuracy of area measurements from the National Land Cover Dataset (NLCD) within spatial units ranging from 0.1 to 200 km2. When regressed on reference area, NLCD area of developed land, agriculture, forest, and water had positive linear relationships with high r2, suggesting acceptable accuracy. However, many of these classes also displayed mean differences (NLCD REFERENCE), and linear relationships between the NLCD and reference were not one-to-one (i.e., low r2, β0 ≠ 0, β1 ≠ 1), suggesting mapped area is different from true area. Rangeland, wetland, and barren were consistently, poorly classified.
Social and economic considerations are among the most important drivers of landscape change, yet few studies have addressed economic and environmental influences on landscape structure, and how land ownership may affect landscape dynamics. Watersheds in the Olympic Peninsula, Washington, and the southern Appalachian highlands of western North Carolina were studied to address two questions: (1) Does landscape pattern vary among federal, state, and private lands? (2) Do land-cover changes differ among owners, and if so, what variables explain the propensity of land to undergo change on federal, state, and private lands? Landscape changes were studied between 1975 and 1991 by using spatial databases and a time series of remotely sensed imagery. Differences in landscape pattern were observed between the two study regions and between different categories of land ownership. The proportion of the landscape in forest cover was greatest in the southern Appalachians for both U.S. National Forest and private lands, compared to any land-ownership category on the Olympic Peninsula. Greater variability in landscape structure through time and between ownership categories was observed on the Olympic Peninsula. On the Olympic Peninsula, landscape patterns did not differ substantially between commercial forest and state Department of Natural Resources lands, both of which are managed for timber, but differed between U.S. National Forest and noncommercial private land ownerships. In both regions, private lands contained less forest cover but a greater number of small forest patches than did public lands. Analyses of land-cover change based on multinomial logit models revealed differences in land-cover transitions through time, between ownerships, and between the two study regions. Differences in land-cover transitions between time intervals suggested that additional factors (e.g., changes in wood products or agricultural prices, or changes in laws or policies) cause individuals or institutions to change land management. The importance of independent variables (slope, elevation, distance to roads and markets, and population density) in explaining land-cover change varied between ownerships. This methodology for analyzing land-cover dynamics across land units that encompass multiple owner types should be widely applicable to other landscapes.