THE NORTHERN WATERTHRUSH: ANALYZING THE DISTRIBUTION AND
ABUNDANCE OF A SECRETIVE SONGBIRD IN PENNSYLVANIA

By

Justin R. Clarke, B.S.
Keystone College

A Thesis Submitted in Partial Fulfillment of
the Requirements for the Degree of
Master of Science in Biology
to the Office of Graduate and Extended Studies of
East Stroudsburg University of Pennsylvania

May 10, 2019

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ABSTRACT
A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master
of Science in Biology to the Office of Graduate and Extended Studies of East
Stroudsburg University of Pennsylvania
Student’s Name: Justin R. Clarke, B.S.
Title: The Northern Waterthrush: Analyzing the Distribution and Abundance of a
Secretive Songbird in Pennsylvania
Date of Graduation: May 10, 2019
Thesis Chair: Terry L. Master, Ph.D.
Thesis Member: Thomas C. LaDuke, Ph.D.
Thesis Member: Emily J. Rollinson, Ph.D.
Thesis Member: Jerry M. Skinner, Ph.D.
Abstract
The northern waterthrush (Parkesia noveboracensis) experienced a drastic decline
between the first and second Pennsylvania Breeding Bird Atlases despite higher sampling
effort during the second atlas. Atlas data suggested a slight northward range contraction
and detectable increase in elevation of occupied blocks, potentially caused by climate
change. This study investigates factors that may be responsible for any detected changes
in distribution in northeastern Pennsylvania (Pike, Monroe and Northampton counties). In
spring of 2017 and 2018, wetland surveys were conducted to detect singing males. At
each of 53 sites, point counts were conducted to characterize the avian community.
Vegetative, physical, and hydrological characteristics were also recorded. Sites occupied
by northern waterthrush were compared to unoccupied sites in apparently suitable habitat.
Shrub height and upturned tree roots were found to be significantly different between site
types as was the avian community and the herbaceous plant community. It was also
found that there was a range contraction at both the northern and southern end of the
NOWA range between the two atlases in the study area. These results suggest that
changes in vegetation structure due to deer overbrowsing and eastern hemlock decline are
contributing to the decline observed between atlases.

ACKNOWLEDGEMENTS
I would like to start by thanking my academic advisor and thesis chair Terry
Master. I have learned a lot from you and your guidance and advice throughout my time
at ESU has been invaluable. I will keep in mind that I need to “broaden my horizons.” I
would also like to thank Emily Rollinson who patiently dealt with my never-ending
statistical questions as well as my amateur poetry. Also, thank you for giving me a quiet
place to work for the past few months. Thank you, Jerry Skinner, for encouraging my
passion as an undergraduate and on to graduate school and Tom LaDuke for teaching me
how valuable it is to be a true naturalist.
Thank you, Andy Wilson, for giving me all of the NOWA breeding bird atlas
data. None of this would have been possible without you. Thank you to the faculty and
staff at ESU, especially Heather Dominguez who helped me with anything I could
possibly need from funding for conferences to coffee so I could get through the day. I
would like to thank my family and friends for all of your support and encouragement
over the past few years, especially my mother who has been my biggest supporter from
the start. I couldn’t have done it without you.
I would like to thank my fellow graduate students, Krissy Bentkowski, Jon
Adamski, and Joseph Schell, who took the time to help me with my field work even
though they were all incredibly busy. Lastly, I would like to thank all of the
undergraduate who came out to assist me, including Elizabeth Romberger, Lewis Wolff,
Reannon Zangakis, and Emily Lind.

TABLE OF CONTENTS
LIST OF FIGURES ........................................................................................................ III
LIST OF TABLES ........................................................................................................... V
LIST OF APPENDICES .............................................................................................. VII
CHAPTER I ...................................................................................................................... 1
Introduction ....................................................................................................................... 1
Study Justification ........................................................................................................... 1
Taxonomy........................................................................................................................ 2
General Natural History .................................................................................................. 3
Conservation and Management ..................................................................................... 13
Wetlands ........................................................................................................................ 15
Importance of Wetlands............................................................................................. 15
Status of Pennsylvania Wetlands ............................................................................... 16
Climate Change ............................................................................................................. 18
Global Trend .............................................................................................................. 18
Avian Range Shifts .................................................................................................... 19
Project Rationale ........................................................................................................... 21
CHAPTER II ................................................................................................................... 22
Methods ............................................................................................................................ 22
Study Sites ..................................................................................................................... 22
Mapping ..................................................................................................................... 22
Pennsylvania Breeding Bird Atlas ................................................................................ 23
Vegetation Surveys and Analyses ................................................................................. 26
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Physical Parameters and Analyses ................................................................................ 29
Nest Searching ........................................................................................................... 32
Climate Change and Analyses ....................................................................................... 32
CHAPTER III ................................................................................................................. 35
Results .............................................................................................................................. 35
Study Sites ..................................................................................................................... 35
Vegetation Analysis ...................................................................................................... 37
Physical Parameters ....................................................................................................... 46
Avian Point Count Analysis .......................................................................................... 46
Nests .......................................................................................................................... 54
Climate Analysis ........................................................................................................... 56
CHAPTER IV.................................................................................................................. 60
Discussion......................................................................................................................... 60
Future Studies and Issues of Concern Highlighted by This Study ................................ 74
Conclusion ..................................................................................................................... 76
LITERATURE CITED .................................................................................................. 78
APPENDICES ................................................................................................................. 88

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List of Figures
Figure 1. NOWA displaying the characteristic marks used to identify it. The widening
superciliary strip and buffy yellow color (left) as well as the heavily streaked
throat (right) (photo credit Justin Clarke). .............................................................. 2
Figure 2. NOWA distribution map (distribution data from BirdLife International)........... 4
Figure 3. Bear Swamp field site (left) shows more open NOWA habitat while Cranberry
Bog (right) shows the more typical dense understory of NOWA habitat (photo
credit Justin Clarke). ............................................................................................... 5
Figure 4. NOWA brings insects back to the nest (photo credit Terry Master). .................. 7
Figure 5. Adult NOWA flying from the nest at Bear Swamp in 2017 carrying a fecal sac
(photo credit Terry Master). .................................................................................... 9
Figure 6. A typical NOWA nest site at Grass Lake (photo credit Justin Clarke). ............ 10
Figure 7. Confirmed and probable blocks for NOWA in 1st and 2nd PBBA. ................. 24
Figure 8. Study sites and PBBA blocks from both atlases covered during the 2017 and
2018 field season................................................................................................... 36
Figure 9. NMDS ordinations of plant communities at each field site with 95% confidence
ellipses. The top is the abundance of each species and the bottom is
presence/absence (ANOSIM, p = 0.019, 0.028, R = 0.138, 0.138, 3D-stress =
0.13, 0.13, respectively). ....................................................................................... 42
Figure 10. NMDS ordinations of tree communities at each field site with 95% confidence
ellipses. The top is the abundance of each species and the bottom is

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presence/absence (ANOSIM, p = 0.184, 0.21, R = 0.048, 0.048, 3D-stress = 0.09,
0.09, respectively). ................................................................................................ 43
Figure 11. NMDS ordinations of shrub communities at each field site with 95%
confidence ellipses. The top is the abundance of each species and the bottom is
presence/absence. (ANOSIM, p = 0.095, 0.087, R = 0.072, 0.073, 3D-stress =
0.04, 0.04, respectively). ....................................................................................... 44
Figure 12. NMDS ordinations of herbaceous plant communities at each field site with
95% confidence ellipses. The top is the abundance of each species and the bottom
is presence/absence (ANOSIM, p = 0.005, 0.002, R = 0.177, 0.177, 3D-stress =
0.12, 0.12, respectively). ....................................................................................... 45
Figure 13. NMDS ordinations of avian communities at each field site with 95%
confidence ellipses. The top is the abundance of each species and bottom is
presence/absence. (ANOSIM, p = 0.001, 0.009, R = 0.238, 0.139, 3D-stress =
0.17, 0.19, respectively). ....................................................................................... 52
Figure 14. NMDS ordinations of avian communities at each field site with distant species
removed and 95% confidence ellipses. The top is the abundance of each species
and the bottom is presence/absence (ANOSIM, p = 0.008, 0.013, R = 0.133,
0.125, 3D-stress = 0.14, 0.14, respectively).......................................................... 53
Figure 15. NOWA nest with chicks at Bear Swamp in 2017 (photo credit Justin Clarke).
............................................................................................................................... 54
Figure 16. NOWA in nest at Grass Lake in 2018 (photo credit Justin Clarke). ............... 55
Figure 17. PBBA blocks that were gained or lost from the 1st to the 2nd PBBA. ........... 59
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List of Tables
Table 1. Classification of blocks during the 1st and 2nd PBBA. ..................................... 25
Table 2. Top 10 vegetation Shannon diversity indices for all 2018 field sites (mean of
occupied sites = 2.29 ± 0.05) ................................................................................ 37
Table 3. Top 10 vegetation Shannon diversity indices for unoccupied field sites (mean of
unoccupied sites = 2.05 ± 0.07). ........................................................................... 38
Table 4. Mean vegetative parameters of occupied and unoccupied sites (asterisk indicates
significant differences).......................................................................................... 39
Table 5. Wetland areas of occupied and unoccupied sites (hectares). .............................. 46
Table 6. Avian Shannon diversity index for all 2017 field sites (mean = 2.54 ± 0.06). ... 47
Table 7. Top 10 avian Shannon diversity index for occupied sites in 2018 (mean = 2.67 ±
0.04). ..................................................................................................................... 47
Table 8. Top 10 avian Shannon indices for unoccupied 2018 field sites (mean = 2.64 ±
0.05). ..................................................................................................................... 48
Table 9. Top 10 avian species frequencies of 2017. ......................................................... 49
Table 10. Top 10 avian species frequencies of 2018 at occupied sites (not including
NOWA). ................................................................................................................ 49
Table 11. Top 10 avian species frequencies of 2018 at unoccupied sites......................... 50
Table 12. Average elevation of occupied and unoccupied sites. ...................................... 56
Table 13. Average elevation of PBBA blocks gained, lost, and with no change between
the 1st and 2nd PBBA. .......................................................................................... 56

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Table 14. Mean temperatures and precipitation amount for occupied and unoccupied sites
over the intervening period between the two atlas time periods. .......................... 57
Table 15. Mean temperatures and precipitation amount for the two atlas time periods for
blocks gained, lost, and those with no change between the first and second PBBA.
............................................................................................................................... 58

vi

List of Appendices
Appendix I. Field Site Locations. ..................................................................................... 88
Appendix II. Average percent of plant species found at occupied and unoccupied sites. 90
Appendix III. Species richness at occupied and unoccupied sites during the 2017 and
2018 field season................................................................................................... 94
Appendix IV. Shannon diversity Index of plant communities for all field sites. ............. 96
Appendix V. Frequency of plant species found at occupied and unoccupied sites. ......... 98
Appendix VI. SIMPER results showing the contribution of each species to the overall
Bray-Curtis dissimilarity between occupied and unoccupied sites with all plants
included (asterisk indicates significance). .......................................................... 101
Appendix VII. SIMPER results showing the contribution of each species to the overall
Bray-Curtis dissimilarity between occupied and unoccupied sites including only
herbaceous vegetation (asterisk indicates significance). .................................... 104
Appendix VIII. Warton et al. (2012) results for all plant species (asterisk indicates
significance). ....................................................................................................... 106
Appendix IX. Warton et al. (2012) results with only shrub species (asterisk indicates
significance). ....................................................................................................... 109
Appendix X. Warton et al. (2012) results with only herbaceous species (asterisk indicates
significance). ....................................................................................................... 110
Appendix XI. Avian species abundance and frequency found across all sites in 2017
(only occupied). .................................................................................................. 112
Appendix XII. 2018 Avian species found across occupied and unoccupied sites. ......... 114
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Appendix XIII. Species richness of the 2017 field sites. ................................................ 116
Appendix XIV. Species richness for occupied and unoccupied sites in 2018. ............... 117
Appendix XV. Shannon diversity Index of avian communities for 2018 field sites. ..... 119
Appendix XVI. Frequency of avian species at occupied and unoccupied sites in 2018. 121
Appendix XVII. Avian SIMPER results showing the contribution of each species to the
overall Bray-Curtis dissimilarity between occupied and unoccupied (asterisk
indicates significance). ........................................................................................ 123
Appendix XVIII. Avian SIMPER results showing the contribution of each species to the
overall Bray-Curtis dissimilarity between occupied and unoccupied excluding
distant species (asterisk indicates significance). ................................................. 126
Appendix XIX. Warton et al. (2012) results for the 2018 occupied and unoccupied sites
(asterisk indicates significance). ......................................................................... 128
Appendix XX. Warton et al. (2012) results for the 2018 occupied and unoccupied sites
excluding distant species (asterisk indicates significance). ................................ 130

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CHAPTER I
Introduction
Study Justification
The northern waterthrush (Parkesia noveboracensis, NOWA) is a cryptic species
that prefers habitat that is often very difficult to access. Therefore, relatively little is
known about its life history, especially regarding nesting, specific habitat preferences and
its avian community associates. NOWA is also an excellent candidate to use to examine
how climate change is affecting avian populations because this species is at the southern
edge of its range in Pennsylvania and prefers cooler, high elevation peatlands for the
most part. Highly vagile species such as birds, especially those with this habitat
preference, are expected to be the first to respond to climate change (DCNR 2015).
Lastly, this species has already experienced a 40.7% decline between the 1st and 2nd
Pennsylvania Breeding Bird Atlas (PBBA) (Wilson et al. 2012). Thus, there are several
compelling reasons to conduct in-depth studies of this species in Pennsylvania

1

Taxonomy
The NOWA is a small, dark colored warbler with dark streaking on a white
breast. It belongs to the family Parulidae and is one of the New World’s most widely
ranging warblers (Bent 1963, Craig 1987, Whitaker and Eaton 2014, NatureServe 2017)
(Figure 1). Between 1880 and 1948, this species was divided into four subspecies, based
on various studies of color variation and morphometric distinctions, which were
ultimately lumped into a single species (Molina et al. 2000). In the early 2000s,
phylogenetic evidence supported a separation of the two waterthrush species, northern
and Louisiana (Parkesia motacilla, LOWA) from the genus (Seiurus) because of
differences in morphology and phylogeny from the ovenbird (Seiurus aurocapilla). In
order to make Seiurus a monophyletic group, the two waterthrushes were moved into
their current genus, Parkesia, as established by Sangster (2008).

Figure 1. NOWA displaying the characteristic marks used to identify it. The widening
superciliary strip and buffy yellow color (left) as well as the heavily streaked
throat (right) (photo credit Justin Clarke).
Ridgeway described a western subspecies that ranged from northwestern Alaska
to western Quebec (Bent 1963, Ridgeway 1880, 1902). Seiurus noveboracensis notabilis
2

is distinguishable by a larger bill, whiter ventral coloration, and a more gray and olive
dorsal coloration. He also described a subspecies, S. n. noveboracensis, that ranged from
western Quebec to Newfoundland. McCabe and Miller (1933) proposed another
subspecies, S. n. limnaeus, which was restricted to northwestern and central British
Columbia and showed an intermediate form that was paler than S. n. noveboracensis but
darker than S. n. notabilis (Bent 1963). A fourth subspecies, S. n. uliginosus, was
described by Burleigh and Peters (1948) and found on the islands of Newfoundland,
Saint-Pierre, and Miquelon in Canada. This subspecies was defined by a longer wing and
tail than the other populations. There have been many studies done that contradict these
findings due to extensive geographic overlap in some of the size differences. It was found
however, that western specimens typically had longer tails and shorter wings than eastern
specimens and P.n.notabilis, P.n.limnaeus, and P.n.uliginosus were lumped together into
P. noveboracensis (Molina et al. 2000).

General Natural History
The breeding range of this small warbler (Figure 2) extends from western Alaska
through most of southern and central Canada and into the northern portion of the United
States. The range extends as far south as northwestern Wyoming in the west and extreme
northwestern Virginia, West Virginia, all of Pennsylvania (except the southwest and
southeast), and northwestern New Jersey in the east. During winters, it migrates south to
northern Mexico, the Caribbean, and as far as Venezuela (Eaton 1957, Bent 1963,
NatureServe 2017).

3

Figure 2. NOWA distribution map (distribution data from BirdLife International).
Throughout its northern breeding range, NOWA favor wooded areas with slow
moving or stagnant water such as bogs or swamps with dense cover near ground level
(Bent 1963, Craig 1985, Whitaker and Eaton 2014). In Pennsylvania, especially on the
Allegheny Plateau, NOWA prefers rhododendron thickets (Rhododendron ponticum)
with high concentrations of eastern hemlock (Tsuga canadensis) in swamps and along
slow-moving streams, e.g., hemlock benches (Figure 3). In other parts of the state, as well
as in New York, nesting has occurred in swamps with spruce (Picea), tamarack (Larix),
and balsam fir (Abies) (Craig 1985, Wilson et al. 2012, Whitaker and Eaton 2014).The
southern wintering range consists of swampy areas, especially the mangroves
4

(Rhizophora, Avicennia, and Laguncularia) (Whitaker and Eaton 2014). These habitats
seem relatively secure throughout most of the breeding range but some of this range was
lost in Pennsylvania, New York, and the lower peninsula of Michigan due to
deforestation and destruction of wetlands in the past (Whitaker and Eaton 2014,
NatureServe 2017).

Figure 3. Bear Swamp field site (left) shows more open NOWA habitat while Cranberry
Bog (right) shows the more typical dense understory of NOWA habitat (photo
credit Justin Clarke).
NOWA are most easily confused with the Louisiana waterthrush but the two can
be confidently distinguished from one another using a combination of physical, auditory,
and habitat characteristics (Dunn and Alderfer 2017). LOWA prefer areas that have faster
moving water such as streams and rivers whereas NOWA prefer more stagnant swamps

5

and bogs (Bent 1963, Whitaker and Eaton 2014). However, there are areas such as
hemlock benches with braided streams where the two species intermingle. They can also
be identified based on differences in their songs. LOWA have a song with much more
slurred and drawn out notes than NOWA which incorporate relatively short, staccato
notes in their song (Bent 1963, Brown 1975, Whitaker and Eaton 2014). They can also be
distinguished by plumage characters. Adult NOWA underparts are white but often with a
noticeable yellowish wash below while LOWA are always nearly pure white. Streaking
on the breast and belly is darker in NOWA and streaks typically extend onto the throat
whereas LOWA have lighter streaking on the breast and usually none on the throat. The
bill of a LOWA is distinctly larger than a NOWA but this may be difficult to distinguish
in the field. The supercilliary stripe in NOWA can be white or buff and narrows behind
the eye whereas LOWA have a white supercilliary stripe that either does not narrow or
more often broadens behind the eye (Whitaker and Eaton 2014).
NOWA are insectivorous and get most of their prey from the water. They feed
mainly by wading and walking along logs or branches at the water’s edge picking benthic
or swimming organisms out of the water (Figure 4). They forage alone and will typically
pick up leaves and toss them aside to uncover the insects beneath (Bent 1963, Whitaker
and Eaton 2014). They have also been observed feeding on terrestrial invertebrates and
will hawk and glean insects from the air and vegetation, respectively (Craig 1984,
Whitaker and Eaton 2014).

6

Figure 4. NOWA brings insects back to the nest (photo credit Terry Master).
During the breeding season, their diet is composed predominantly of insects,
spiders and snails but they can be generalists during migration where they have even been
seen feeding on small minnows (Bent 1963, Whitaker and Eaton 2014). Their diet during
the breeding season consists of Coleoptera (beetles) larvae, adult Lepidoptera (moths and
butterflies), adult Odonata (dragonflies), larval Neuroptera (lacewings), adult Plecoptera
(stoneflies), Ephemeroptera (mayflies), and many other insect orders. In wintering
habitat, their diet is composed of small snails, clams, Atlantic mangrove fiddler crabs
(Uca thayeri), small spiders, adult snout beetles, small ants, flies, and other insect larvae
(Whitaker and Eaton 2014).
Arrival on the breeding grounds occurs from mid-April to late-May with pairs
forming as soon as the females arrive (Whitaker and Eaton 2014). Singing begins in late
7

April and continues until late June in the more southern parts of their range while more
northern individuals will continue singing until mid-July. After establishing territories
and selecting mates, NOWA typically start building nests in mid to late May and lay eggs
during the first week of June (Craig 1987, Wilson et al. 2012, Whitaker and Eaton 2014,
NatureServe 2017). Incubation begins after the third egg is laid and will continue for
about 12 days. Brooding then lasts for approximately 5 days. The young hatch in the last
week of June and are cared for until approximately the last week of July (Craig 1987,
Wilson et al. 2012, Whitaker and Eaton 2014, NatureServe 2017). The earliest departure
from the breeding grounds is approximately July 15th with the peak occurring in
September. Earliest departure from Pennsylvania is July 24th (Whitaker and Eaton 2014).
They arrive on the wintering grounds from early August to early November (Whitaker
and Eaton 2014) and are among the earliest fall migrants, along with LOWA.
This neotropical migrant is essentially monogamous although there is evidence of
extra-pair mating (Whitaker and Eaton 2014). NOWA are single brooded and it is very
rare to see them reuse a nest. This behavior was only seen in 1 of 91 nests in a study done
in Ontario, however, they will re-nest and build a new nest following failure caused by
depredation (NatureServe 2017). NOWA lay one clutch of four to five eggs once per
season (Craig 1987, Wilson et al. 2012, Whitaker and Eaton 2014, NatureServe 2017).
Eggs are laid early in the morning on successive days and, while the adults will feed in
the area, they will not return to the nest until the female lays the next egg (Whitaker and
Eaton 2014). Both parents feed chicks and females are cryptic when leaving the nest.
They will land on the ground and slowly walk about 10 meters away before standing up
8

and flying off to feed (Whitaker and Eaton 2014). Both parents remove fecal sacs and
during the first few days will eat them, but later take them away from the nest for
disposal (Figure 5) (Whitaker and Eaton 2014). They are known to be territorial
throughout the year and can be intensely aggressive towards conspecifics (Craig 1984,
NatureServe 2017).

Figure 5. Adult NOWA flying from the nest at Bear Swamp in 2017 carrying a fecal sac
(photo credit Terry Master).
Nest site selection is up to the female. It will most often be placed on the ground,
in a hollow of a bank or among the roots of overturned trees (Bent 1963, Wilson et al.
2012, Whitaker and Eaton 2014) (Figure 6). NOWA nests are cups that are typically
hidden from above with an opening on one side, and they sometimes have an
entranceway of leaves similar to LOWA nests. The outside of the cup is composed of
leaves and lined on the inside with grass stems, twigs, and/or pine needles (Bent 1963,
9

Whitaker and Eaton 2014). Mean dimensions of nests are: diameter 10.7 cm, height 5.6
cm, inside diameter of cup 6.2 cm, depth of cup 3.1 cm (Whitaker and Eaton 2014).

Figure 6. A typical NOWA nest site at Grass Lake (photo credit Justin Clarke).
Eggs are white with brown/gray blotches or spots. Spotting density can vary and
all markings are concentrated toward the larger end of the egg. Mean dimensions of the
eggs are 19.1 mm long and 14.6 mm in width (Bent 1963, Whitaker and Eaton 2014).
Eaton (2014) reports that after egg laying only the female incubates, sometimes for
periods of 30 minutes on, 10 minutes off from 09:50 to 19:30, for approximately 12 days.
Young are able to leave the nest at nine days old before they can fly. For 2-3 days
they will hide in dense vegetation and are able to fly approximately eight days after
leaving the nest. They continue to be cared for by both adults for approximately four
weeks after hatching. By 30 days old, they are indistinguishable from adults and can
10

breed during their first spring after fledging (Wilson et al. 2012, Whitaker and Eaton
2014).
Little research has been done on dispersal/site fidelity of hatch-year individuals,
but a study conducted in Newfoundland found that 7/103 individuals were re-sighted or
recaptured in subsequent years. However, this remains the only study of this type and
encounter effort was uneven so it may not accurately reflect dispersal patterns (Whitaker
and Eaton 2014). The impression is that site fidelity is relatively high (as is the case with
LOWA, especially males), but more studies need to be conducted to determine fidelity
accurately.
A study in Newfoundland found that 16.3% of 141 individuals banded returned to
their previous breeding territory. This number was biased towards males because song
playbacks were used during the surveys and most of the individuals sighted were males.
During the last few years of the study, it was found that 75% of 20 individuals banded
were observed for 3 years (Whitaker and Eaton 2014). In their wintering range, they
appear to have high site fidelity as well. One study in Costa Rica found individuals
returning up to five years after they were first banded and individuals in better condition
were more likely to return to the same site (Whitaker and Eaton 2014).
The oldest recorded NOWA was 8 years and 11 months old (Klimkiewicz and
Futcher 1989). The average annual survival rate on the breeding grounds is very high
(64%) but this drops in the northeast where the regional survival rate is 46%. Most of the
losses appear to occur on the wintering grounds where the survival rate can be as low as
37% in Panama, Costa Rica, and Mexico (Saracco et al. 2008). Many of these losses are
11

attributed to hurricanes and other storms that are encountered during migration and on
wintering grounds. This pattern, where most losses occur during migration and wintering,
is typical for neotropical migrants (Saracco et al. 2008, Whitaker and Eaton 2014). The
Mayfield estimate for survival rate of nests during incubation is 50.4% but increases
during the nesting stage to 90.3% for an overall survival rate of 45.5% (Warkentin et al.
2003, Whitaker and Eaton 2014). It is believed that nesting success is most affected by
how well a nest is concealed early in the breeding season before leaf-out when nests are
most vulnerable (Warkentin et al. 2003, Whitaker and Eaton 2014). There is very little
data on predation of NOWA. However, their ground nesting habit makes this species
vulnerable to snakes. In one study, a ribbon snake (Thamnophis sauritus) was seen eating
a nestling in Washington Co., RI (Whitaker and Eaton 2014).
NOWA can be recognized on their breeding grounds by a very distinct, 3-parted
song commonly represented as sweet sweet sweet swee wee wee chew chew chew chew
(Bent 1963, Brown 1975, Whitaker and Eaton 2014). Brown (1975) examined 139
NOWA individuals and 158 recordings and found that, while there is variation in song
type, this song was heard from 76.92% of the individuals examined. Other variations are
a 2-parted song (2.31%), 4-parted song (16.15%), and 5-parted song (2.31%) (Brown
1975). One example of these variations can be reproduced as chWhitt chWhit chWhit whit
whit whit tcheew or chit chit chit chit chit weeOoo weeOoo weeOoo chblit where the first
two parts have distinct syllables and the final part is shortened (Bent 1963, Brown 1975,
Whitaker and Eaton 2014). While establishing territories, males will sing from perches
that can vary from 8-15 m in height in more dense areas to canopy height in more open
12

habitats (Brown 1975, Whitaker and Eaton 2014). After establishing territories singing
will decline throughout the season. While these songs are most often heard on the
breeding ground, they can occur on occasion on the wintering grounds as well as is also
the case with LOWA (Whitaker and Eaton 2014, T. Master, pers. comm.).
The flight song of NOWA is a sharp, loud chip that can be intermixed with
jumbled and truncated song notes. Subdued songs can also be heard from non-territorial
males and from territorial males while the female is incubating (Whitaker and Eaton
2014). The call note of a NOWA is a sharp and steely chick and is given throughout the
year on both the breeding, migratory and wintering grounds (Whitaker and Eaton 2014).

Conservation and Management
Pennsylvania Breeding Bird Atlas (PBBA) surveys were conducted by thousands
of volunteers searching nearly 5,000 atlas blocks in Pennsylvania for various levels of
breeding evidence for species observed in each block. Fieldwork for the first atlas took
place between 1983 and 1989 and for the second atlas from 2004 to 2009, 20 years later.
The atlases utilized the “block” as their survey unit which was defined as “one-sixth of a
standard U.S. Geological Survey 7.5-minute topographic map” (Wilson et al. 2012). This
allowed them to cover the state in a coordinated and organized fashion. Blocks were 24.8
km 2 (9.6 mi 2) in extent. Effort was greater during the second atlas for a variety of
reasons, thus, results from the second atlas had to be adjusted to take into account the
change in effort between the two atlases (Wilson et al. 2012).
Based on USGS Breeding Bird (BBS) routes, NOWA have shown an increase of
0.9% per year from 1966 to 2011 across their entire range (Sauer et al. 2013, Whitaker
13

and Eaton 2014). In Pennsylvania, a 40.7% decline in block occupancy for NOWA
occurred between atlas periods, one of the largest declines of any Pennsylvania breeding
species (Brauning 1992, Wilson et al. 2012). Although all blocks were surveyed during
the first atlas, effort, as mentioned above, was more extensive during the second atlas,
which lends credence to the veracity of the decline. Due to NOWA habitat preference,
several potential stressors may be affecting their abundance and distribution including
habitat degradation and destruction, vegetative succession, hemlock decline due to
woolly adelgid (Adelges tsugae) (HWA) infestation, and climate change. The 2nd PBBA
reported a range contraction to the north that appeared to be altitudinally driven (Wilson
et al. 2012). The southern edge of their overall range moved north 1 km and the northern
edge moved south by 21 km (probably from the loss of low elevation sites) between the
two atlases (Wilson et al. 2012). The blocks that remain occupied were more northerly
and/or higher which implicates climate change as a possible cause. Other biotic and
abiotic factors that may affect NOWA conservation status will need to be investigated to
assess all possible causes for the decline. Isolating, analyzing and extrapolating these
factors across wetlands will provide a basis for understanding the species’ range
dynamics and predicting future impacts on population abundance and distribution.
The major threats to NOWA, as listed in the Pennsylvania Wildlife Action Plan,
are habitat loss due to forest fragmentation and hydrological changes associated with this
development and perhaps with climate change as well (PGC-PFBC 2015). Yahner (2003)
showed that 97% of wetland and riparian species in Pennsylvania were restricted in their
distribution because of scarcity of their habitats. This study determined that habitat loss
14

or degradation in wetland and riparian habitats affected up to 64.5% of species that reside
in these habitats (Yahner 2003). Between 1956 and 1979, Pennsylvania averaged a loss
of 1,200 acres of vegetated wetlands per year (Tiner 1990).
The main goal of the Pennsylvania Wildlife Action Plan is to increase the
population by 10% in at least 250 breeding bird atlas blocks. This will be accomplished
by establishing better management practices and acquiring land and water rights and
protections for suitable habitat (PGC-PFBC 2015). However, there is a more pressing
threat on its wintering grounds where preferred habitat, mangrove swamps, are cut down
and drained for fuel, space, and food (NatureServe 2017). Even with these imminent
threats, the population seems stable and has even shown a slight increase in certain areas
across their entire range (Whitaker and Eaton 2014, NatureServe 2017).

Wetlands
Importance of Wetlands
Wetlands are one of the most productive ecosystems in the world and offer a
variety of services that can’t be easily replaced. The productivity of wetlands is tied to a
unique set of characteristics that they share including shallow water, high levels of
nutrients, and high levels of primary productivity (Flynn 1996). This primary
productivity is due to the unusually high efficiency that wetland plants have for
converting sunlight, nutrients, and water into biomass (Flynn 1996). Wetlands also
provide services such as water quality improvement, flood protection, and shoreline
erosion control (Hemond and Benoit 1988, Sheehan and Master 2010, United States
Environmental Protection Agency 2018). More than one-third of threatened and
15

endangered species in the U.S. are endemic to wetlands and approximately half use
wetlands during at least a part of their life cycle (United States Environmental Protection
Agency 2018).
Status of Pennsylvania Wetlands
Wetlands are not easily defined, and the definitions vary greatly. The most widely
accepted definition is “areas that are inundated or saturated by surface or ground water at
a frequency and duration sufficient to support, and that under normal circumstances do
support, a prevalence of vegetation typically adapted for life in saturated soil conditions”
(Cowardin et al. 1979, Pennsylvania Department of Environmental Protection 2014).
Wetland classification depends on three environmental components including hydrology,
hydric soils, and obligate or facultative hydrophytic vegetation. At least two of these
three factors must be present for an area to be legally considered a wetland (Cowardin et
al. 1979, Tiner 1990).
Approximately 95% of the 44.6 million ha (110.1 million acres) of wetlands in
the conterminous U.S. are freshwater wetlands. This translates to 42.2 million ha of
freshwater wetlands (Dahl 2011). Wetlands have been in decline for centuries, but in
recent years this decline has slowed from 185,346 ha per year between 1954 and 1970 to
5,590 ha per year between 2004 and 2009 with most of the loss being due to silviculture
(124,376 ha lost from 2004-2009) (Dahl 2011). Loss of freshwater vegetation has
declined as well by about 50% since the 1950s. There were 256,320 ha of forested
wetlands lost between 2004 and 2009. Most of this loss was due to clear-cutting
associated with silviculture, converting forested wetlands to other wetland types (Dahl
2011). However, this is a much slower rate of loss than occurred in the 1950-1970s when
16

almost 2,428,113 ha were lost resulting in the greatest loss of forested wetlands in the
U.S. (Tiner and Finn 1986, Dahl 2011).
Pennsylvania wetlands have been disappearing since European colonization. It is
estimated that Pennsylvania, prior to colonization, had approximately 1,127,000 ha of
wetlands of which only 403,924 acres remain, a loss of about 56% of the original
wetlands ( Tiner 1990, Pennsylvania Department of Environmental Protection 2014).
More recently, between 1956 and 1979, Pennsylvania lost 11,331 ha, or six percent of its
vegetated wetlands. This loss is attributed to conversion to other wetland types through
human-induced changes (Tiner and Finn 1986). Almost 1/3 of this loss took place in the
northeastern portion of the state with the heaviest losses occurring in the northern Pocono
region (2,144 ha) (Tiner and Finn 1986).
Currently, 1.4% of the state is still covered by wetlands and most of these (~40%)
are found in the glaciated northeastern and northwestern corners of the state. Pike and
Monroe counties have the highest proportion of wetland area within their boundaries of
any Pennsylvania county with the estimates of 6.7% and 6.4% of their total area
respectively (Tiner 1990).
Approximately 97% (392,728 acres) are freshwater wetlands. Deciduous forested
wetlands compose 36% of the total palustrine wetlands followed by about 15% open
water, 13% emergent, and 12% shrub wetlands with the remainder a mix of these groups
(Tiner 1990). These wetlands are found at approximately 160,000 sites which indicates
that most are small and isolated. Cowardin et al. (1979) defines these as “nontidal
wetlands that are dominated by trees, shrubs, persistent emergents, emergent mosses or
17

lichens, and all such wetlands that occur in tidal areas where salinity due to oceanderived salts is below 0.5%”. These wetlands can be divided into categories such as
marshes, swamps, bogs, fens, and prairies depending mainly on hydrology, pH and
vegetation structure (Cowardin et al. 1979, Zimmerman et al. 2012) .
The three greatest threats to wetlands in Pennsylvania are loss, fragmentation, and
degradation. One of the biggest factors contributing to these problems is urbanization.
Degradation can occur in a variety of ways including pollution, improper management by
land owners (e.g., mowing and cutting), and invasion by exotic species ( Zimmerman et
al. 2012, PGC-PFBC 2015). Pennsylvania is ranked as the 2th highest state for total
sprawl (the amount of rural land lost to development) estimated at 341 square miles from
2002 to 2010. When the states were ranked based on their sprawl from 1982 to 2010,
Pennsylvania jumped to 6th with a total sprawl of 2,529 square miles showing that the
rate cities are expanding in Pennsylvania has slowed in recent years compared to other
states (Kolankiewicz, Beck, and Manetas 2014).

Climate Change
Global Trend
Scientists have recorded a global change in the mean surface air temperature of
0.9 ºC (1.62 ºF) since the nineteenth century (NASA Jet Propulsion Laboratory 2018). In
Pennsylvania, the increase is greater than 1º C in the past 110 years with anthropogenic
factors being the major cause (DCNR 2015). The greatest seasonal warming over land
has been observed in the northern hemisphere during the winter and spring seasons. The

18

maximum spring temperatures in the northern hemisphere have increased 1.1 degrees ºC
between 1954 and 2004 (Hitch and Leberg 2007).
Avian Range Shifts
Hitch and Leberg (2007) showed that the northern range margins of breeding
birds in North America have been shifting northward over recent decades. They
concluded that some of this movement may be due to other factors, but it is difficult to
explain the drastic shift of so many species without invoking some discussion of climate
change. In this same study, NOWA had a mean shift north of 9.28 ± 42.67 km/yr. This
study is consistent with the results of Thomas and Lennon (1999) who did a similar study
in Great Britain on multiple species of birds.
Langham et al. (2015) predicted that there will be drastic changes in the breeding
ranges of many birds. Peak areas of loss will be along the U.S. - Canadian border, which
is composed mainly of eastern deciduous forests, prairie potholes, and where the high
elevations of the Rockies and Cascade ranges occur. This is because this area could gain
as many as 80 species and lose up to 69 species due to breeding range shifts as the
average global temperature increases (Langham et al. 2015). Plants and animals have
already begun a migration to higher elevations at a rate of 36 ft/decade and they have
been moving to higher latitudes at a rate of 10.5 mi/decade (Groffman et al. 2017).
Pounds et al. (1999) demonstrated an increase in elevation of bird ranges from climate
change in Monteverde Cloud Forest in Costa Rica.
The model made by Langham et al. (2015) predicted that climate change will tend
to push species toward higher elevations through the end of the century although many
species are still projected to move downslope which emphasizes the importance of
19

looking at how individual species respond (Langham et al. 2015). This downslope shift
could be caused by a variety of factors. Lenoir et al. (2010) examined multiple studies
that showed a downslope shift and found that it could be due to less competition,
disturbance, habitat modification or a combination of other environmental factors that
have been overlooked.
The Pennsylvania Ornithology Technical Committee (part of the Pennsylvania
Biological Survey) climate change survey states that the first species to respond to
climate change are wetland species that have a southern range limit in Pennsylvania and
prefer high elevation/cooler microclimates (Pennsylvania Biological Survey Technical
Committee 2013). Due to NOWA’s preference for both northerly breeding grounds and
higher elevations, it is a species likely to be affected by climate change, especially in
Pennsylvania, which is at the extreme southern limit of its breeding range in the eastern
half of the state (Wilson et al. 2012).
NOWA was used as a flagship species by Sneddon and Hammerson (2014) in the
climate change vulnerability assessments of selected species in the North Atlantic
Landscape Conservation Corporation (LCC) region. They were used to represent species
at the southern edge of their range in the region. This plan listed NOWA as moderately
vulnerable in the mid-Atlantic states because it is already at the edge of its range and
there is a predicted loss in its preferred habitat, both potentially exacerbated by climate
change (Sneddon and Hammerson 2014). The Pennsylvania Wildlife Action Plan (2015)
states that NOWA are expected to have a drastic suitable habitat reduction of up to 70%
within the state (PGC-PFBC 2015).
20

Project Rationale
The general objectives of this study are: (1) to refine the accuracy of the second
PBBA with regard to NOWA distribution in the three-county study area, (2) characterize
NOWA habitat with regard to avian community, vegetative and hydrological conditions
by comparing occupied and unoccupied but apparently suitable sites, (3) investigate the
cause(s) of decline between the first and second PBBA with emphasis on what climate
change data can tell us about atlas block occupancy patterns between the 1st and 2nd atlas
and between both atlases and this study, and (4) gather natural history information on this
understudied species.
These goals translate to the following working hypotheses: (1) atlas block
occupancy will be higher than reported in the 2nd PBBA, (2) there will be distinctive and
measurable differences in avian community composition, vegetation parameters, and
physical characteristics between occupied and unoccupied territories in apparently
suitable habitat, and (3) changes in NOWA block occupancy patterns, both between the
1st and 2nd atlas and between both atlases and this study, will reflect the effects of climate
change with regard to the elevation and northerly progression of currently occupied
blocks.

21

CHAPTER II
Methods
Study Sites
This study was conducted in Northampton, Monroe, and Pike counties which
encompass most of the core breeding range of NOWA in northeastern Pennsylvania.
Within these counties, as many sizeable hemlock/rhododendron swamps as possible were
located by comparing eBird® hotspots, the 2nd PBBA, topographical maps and digital
maps with Quantum GIS® version 2.18.21 with GRASS 7.4.1 (QGIS Development
Team, open source). Most wetlands were already named on maps but if not, they were
named based on the road nearest to the site.
Mapping
A study site map was made with digital elevation models (DEM) with 1/3 arcsecond resolution (United States Geological Survey 2017) for Pike, Monroe, and
Northampton counties using the Hillshade tool in QGIS® (QGIS Development Team,
open source) to create a 3D layer and overlaying a DEM of each county that was
classified based on elevation and color coded accordingly (United States Geological
Society 2018). Atlas block coordinates were available from atlas coordinators. A map of
22

Pennsylvania hydrology (United States Fish and Wildlife Service 2016) was also added
after sorting out only the forested swamps, the preferred habitat of NOWA, from the
dataset.

Pennsylvania Breeding Bird Atlas
Occupied (territorial) blocks from the 1st PBBA (1984-1989) were compared to
those from the 2nd PBBA (2004-2009) (Figure 7) to determine elevation and/or latitudinal
shifts over the intervening period between atlas efforts (Wilson et al. 2012). Data from
both sets of atlas blocks were also compared in a similar manner to that collected during
this project (Wilson et al. 2012).
In the PBBAs, the blocks were classified into one of four breeding code
categories. These utilized safe dates and breeding behaviors defined by the atlas (Table
1). The first category, “Observed”, requires the least amount of effort and is when a bird
is seen or heard during the safe dates. The second category, “Possible”, is when a species
is observed in suitable habitat, within the safe dates but not exhibiting any breeding
behaviors. The third category, “Probable”, is the same as Possible except breeding
behaviors are observed. The last category, “Confirmed”, is used for birds exhibiting more
definitive breeding behaviors (Wilson et al. 2012). Thus, these categories define the level
of confidence for breeding within a block in the two atlases. Only Probable and
Confirmed blocks were used in all analyses because of their more robust indication of
breeding.

23

Figure 7. Confirmed and probable blocks for NOWA in 1st and 2nd PBBA.

24

Table 1. Classification of blocks during the 1st and 2nd PBBA.

Confirmed

Probable

Classification

Category

Behavior

Pair

Pair seen in close proximity and/or
interacting non-aggressively

Territorial Behavior

Counter-singing, aggressive interactions
between same sex individuals, singing
male in the same location on visits
separated by 5 days or more
Aerial displays, courtship, etc. or
copulation observed

Ritualized Courtship
Used Nest
Agitated

Only species with unique nests
Anxiety calls or agitated behavior due to
observer or predator presence

Carrying Nest
Material

Adult carrying nesting materials

Physical Evidence of
Breeding Condition

Observed for birds in hand, specifically
brood patch and/or visibly gravid
condition
Adult observed building a nest
Especially injury feigning or apparent
direct defense of unobserved nest/young

Nest Building
Distraction Display
Recently Fledged
Young

Recently fledged young observed with an
adult

Adult Carrying Food
or Fecal Sac

Adult carrying food or a fecal sac

Adult Feeding
Fledged Young

Adult seen feeding fledged young

Nest Containing
Eggs

Nest of species was found containing
eggs

Occupied Nest

Occupied nest found but contents are not
known because adults are on the nest or
the nest placement prevents examination
of the nest
Nest of species found containing young

Nest Containing
Young

25

Vegetation Surveys and Analyses
Vegetative surveys were conducted using a modified BBird Protocol (Martin et al.
1997) from the last week of June to the third week of July in 2017 and 2018 to minimize
disturbance during the point count/nesting period (see below). Vegetative parameters
measured included canopy coverage measured using a densiometer (%), shrub and
herbaceous plant coverage (%) (subjective, estimated from shore due to the difficulty of
navigating through the swamps), tree and shrub height measured using a clinometer (m),
and the number of tree throws or root overturns within sight from the nest or dominate
song perch. Trees were defined as any woody plants that originated from one stem and
shrubs as woody plants that arose from multiple stems. Herbaceous plants were defined
as herbaceous plants that grew in or near the edge of the water. These include both
emergent and submergent plants that are rooted in the substrate (Cowardin et al. 1979,
Texas A&M 2018).
During vegetation surveys, the percent coverage (subjective, visual estimate for
each group) of all tree, shrub, and herbaceous plants was recorded within a 10 m diameter
circle of the point count location. The coverage of categories could total more than 100%
because categorical overlap in coverage can occur. A timed meander search procedure,
defined as when a meandering path is followed within a designated field unit and every
species encountered is recorded, was used to record the species present in each
designated plant group. The transect may meander in any way as long as it covers all
unique habitats in the area (Goff et al. 1982). An hour was spent at each site recording
every plant group present and the percent coverage each species contributed to the overall
26

coverage. This method was selected because of the difficulty associated with moving
through swamps. Cynthia (2007) found that it was the most accurate method at
representing species present at each site but, due to observer bias, was not necessarily the
best measure of abundance.
Canopy cover was measured with a spherical densiometer model-C (Forest
Densiometers, Barlesville, OK). A reading was taken at each cardinal direction from as
close to the dominant song perch as possible by counting the number of equidistant dots
within the etched squares on the densiometer that were not covered by vegetation and
multiplying by 1.04 for the percent of sky not occupied by forest canopy. This number
was then subtracted from 100 to get canopy coverage (%). The mean of the four
measurements was taken to determine the average percent canopy coverage in each
swamp.
Tree height was measured with a Suunto® Tandem clinometer. A meter tape was
used to measure the distance to the tree from the observer and the clinometer was pointed
to the apex of the tree and the angle (%) recorded. Shrub height was measured using a
visual estimate. The angle was then multiplied by the distance to the tree and the
observer’s height in meters added to get the total tree height (m).
Ordinations were used to visualize the differences between occupied and
unoccupied sites for the overall plant communities and subsets (all plants, trees, shrubs,
herbaceous plants) using non-metric multidimensional scaling (NMDS) in the R package
vegan (Oksanen et al. 2018). An ordination is a multivariate analysis where sites are
plotted in three dimensions based on a predetermined set of characteristics with the
27

distance between points indicating how similar or dissimilar two sites are. (Goodall 1954,
Gotelli and Ellison 2013). A separate NDMS was done with only presence/absence data
for each of the four groups (all plants, trees, shrubs, and herbaceous vegetation). NMDS
ordinations used Bray-Curtis dissimilarity for abundances and presence/absence analyses.
The Bray-Curtis dissimilarity is a measure of distance or dissimilarity that is most often
used for continuous numerical data (Gotelli and Ellison 2013).
Differences in plant community composition between the two types of sites were
assessed using analysis of similarities (ANOSIM) in the R package vegan (Oksanen et al.
2018) to complement the NMDS visualization. Similarity percentages (SIMPER) in the R
package vegan (Clarke 1993, Oksanen et al. 2018) was used to determine which taxa
contributed most to overall dissimilarity between the groups. SIMPER is a tool developed
by Clarke (1993) that determines what percentage that each species contributes to the
overall Bray-Curtis dissimilarity. Warton et al. (2012) found that SIMPER may confound
the mean between groups and within group variation and can single out variable species
instead of distinctive species. Therefore, I verified the SIMPER results using the
multivariate ANOVA technique described in Warton et al. (2012).
Canopy cover, shrub cover, and herbaceous plant cover were compared between
occupied and unoccupied sites with an ANOVA. The Shannon-Weaver Index was
calculated to describe plant diversity at each site. Shannon-Weaver Index is defined in
this case as 𝐻 = ∑𝑠𝑖 𝑝𝑖 ln(𝑏) 𝑝𝑖 , where 𝑠 is the species richness, 𝑝𝑖 is the proportion
abundance of species 𝑖 , and 𝑏 is the base of the logarithm.

28

Physical Parameters and Analyses
Physical parameters, including elevation (m) and area (m2), which were
determined using GIS, as well as mean water depth (cm), were compared between
occupied and unoccupied blocks. Wetland size data was taken from the National Wetland
Inventory (2017). Total wetland area was divided into forested and scrub-shrub wetlands.
The area of these two wetland types was compared between occupied and unoccupied
sites using an analysis of variance (ANOVA) as was the total wetland area.
PBBA blocks were classified as gained (1st unoccupied, 2nd occupied), lost (1st
occupied, 2nd unoccupied), or unchanged (remains occupied or remains unoccupied) from
the 1st to the 2nd PBBA. The zonal statistics tool in QGIS® was used to determine the
mean elevation for atlas blocks and the elevations among groups were then compared
using an ANOVA. Occupied and unoccupied site elevations from this field season were
compared using an ANOVA.
Spatial distribution of occupied blocks in this study was compared to the
distribution of 2nd PBBA block locations to estimate the degree to which the species was
under or over-counted during the atlas effort. Comparison of currently occupied atlas
blocks from my field work to those occupied in both the 1st and 2nd PBBA will provide
the opportunity to determine if there has been a noticeable northward and/or elevational
range shift in block occupancy.
Wetland size and water depth were also compared between occupied and
unoccupied field sites. Wetland size was determined using data from the National

29

Wetland Inventory (2017) and compared using an ANOVA. Water depth was gathered
during the field season and analyzed using an ANOVA.
Avian Point Counts and Analyses
A preliminary search of wetlands within the study area was done in the first three
weeks of May in both years to determine what swamps were suitable habitat (a forested
wetland with an understory of shrubs) for NOWA. Two variable circular plot point
counts were conducted at each swamp within suitable habitat during the height of the
breeding season within the safe dates (last week of May to the first week of July) for
most breeding species as determined from the 2nd PBBA. Point counts were conducted
from 6:00 AM to 10:00 AM during the period of most singing activity but sites were
visited until 12:00 PM to determine occupancy. All sites were visited once during the
first round of point counts before being visited a second time for the second round.
Sites were classified as occupied if a NOWA was seen or heard within the safe
dates and a site was classified as unoccupied if there was no evidence of a NOWA within
the safe dates. Sites were considered occupied if a NOWA was present in at least two
visits. In occupied sites, plot center points were located as close to the dominant male
song perch as possible. In unoccupied sites, plot centers were located in an area
determined as the most suitable habitat in the swamp. These counts recorded any bird
species, using American Ornithology Society (AOS) codes (Matsuoka et al. 2014), heard
or seen each minute during a ten-minute count period. Any species heard that were
greater than seventy-five meters away were noted as distant observations. Lynch (1995)
found that 55 percent and 82 percent of species were detected within the first 5 to 10 min
30

of a point count, respectively, regardless of what time of morning a point count was
conducted. Using a slightly longer count of 10 minutes rather than 5 minutes also
increases the detectability of more cryptic species such as NOWA (Lynch 1995).
Counts were performed following a 5-minute acclimation period during which
environmental data (including sky condition, precipitation and wind speed as determined
subjectively by observer), temperature and noise level (using the Beaufort scale) were
recorded to characterize survey conditions. To increase the certainty that a site was
unoccupied, song playback was used in an attempt to elicit a response by any male in the
area when determining occupancy (playback was not used for point counts). This has
been shown to substantially increase detectability of species that vocalize infrequently
(Lynch 1995).
Species richness was determined by pooling the data from all visits during the
field season for a complete list of all species detected at each field site for 2017 and 2018
separately (Sheehan and Master 2010). The Shannon-Weaver Index was used for this
calculation because of its emphasis on evenness among species (Shannon 1948).
Frequency of occurrence was determined for each species by dividing the number of sites
a species was found at by the total number of sites surveyed for 2017 and 2018 separately
(Sheehan and Master 2010). All statistical analyses were done using R (R Core Team
2017).
Ordinations were used to visualize any differences in the avian community
between occupied and unoccupied sites. NMDS was used to visualize the differences
between NOWA-occupied and unoccupied sites in the abundance and presence/absence
31

of bird species. This was repeated for a subset of the data excluding all species heard
farther than seventy-five meters away, and for presence/absence rather than abundance
data (again excluding the distant species).
An ANOSIM was performed on the two groups to statistically test for differences
between occupied and unoccupied sites to complement the NMDS visualization.
SIMPER was used to determine which taxa contributed the most to the dissimilarity seen
between the two groups (Clarke 1993). The method described by Warton et al. (2012)
was used to confirm SIMPER results. Only 2018 data was used to compare occupied and
unoccupied sites because all sites in 2017 were visited again in 2018, although locations
differed slightly as NOWA territories were not in the exact same location at the swamp.
Nest Searching
Singing males were located by a combination of auditory and visual surveying.
Once singing males were located, each individual was observed and audio playback used
as needed to determine the territorial boundary of the pair. Pair movements were
observed to attempt to determine the location of nests with careful attention paid to any
nesting material or food being brought to a specific location. Nest locations, if found,
were recorded with a handheld Garmin® 60cxs GPS unit (Garmin, Olathe, KS)., and
GPS-mapped using QGIS®.

Climate Change and Analyses
Climate NA v5.21 (Wang et al. 2016) was used to gather average, maximum, and
minimum temperatures as well as precipitation data for the decades during which the two
PBBAs were conducted (1980-1990 and 2000-2010). Block centroids were used as the
32

location and average elevation for each of the blocks for PBBA comparisons. Field site
location and elevations were used for field site comparisons. Only temperature and
precipitation data from the breeding months (May – July) were used because they are the
months when the arrival and breeding of migratory species such as NOWA would be
most affected (Virkkala et al. 2018). Change in maximum, minimum, and average
temperature as well as average temperature were calculated between the two atlas periods
for both field sites and PBBA block centroids. Occupied and unoccupied field sites were
then compared for each of the climate indices using an ANOVA.
PBBA blocks were categorized into three groups: blocks that had no change,
blocks that were gained in the second atlas, or blocks that were lost in the second atlas. A
gain was classified as moving from observed or possible in the 1st atlas to probable or
confirmed in the 2nd atlas. A loss was classified as going from probable or confirmed in
the 1st atlas to possible or observed in the 2nd atlas. A change from probable to confirmed
or possible to observed and vice versa were both classified as unchanged. These
categories were chosen because probable and confirmed represent both the most effort
and hence highest probability of being accurate with respect to occupancy. These
categories were also more likely to be truly occupied sites in either of the atlases.
Changes in climate indices were then compared using an ANOVA for each of these three
categories.
Shifts in latitude between the 1st and 2nd PBBA were also calculated. This was
done using the same method as Thomas and Lennon (1999). Mean latitudes for the ten
northernmost and ten southernmost atlas blocks were calculated for both the first and
33

second atlas. Distances were then calculated between mean latitudes of the centroids of
northernmost and southernmost blocks.

34

CHAPTER III
Results
Study Sites
Fifty-three wetlands identified as having appropriate habitat were surveyed during
the current project in Northampton, Monroe and Pike counties in northeastern
Pennsylvania. Thirty-five of these were occupied with NOWA and 18 were unoccupied.
Thirteen of these sites were identified during the 2017 field season and the other 40 were
identified during the 2018 field season (Figure 8). Together, these sites covered all
PBBA blocks that were classified as either probable or confirmed (26) in both atlases
except five due to inaccessibility or lack of suitable habitat (Appendix I). Of the PBBA
blocks surveyed during this study, I found 22 that were occupied (85% of probable and
confirmed). Three of these overlapped confirmed (breeding) atlas blocks, 9 overlapped
probable atlas blocks, 5 overlapped possible blocks, and 5 were entirely new blocks.

35

Figure 8. Study sites and PBBA blocks from both atlases covered during the 2017 and
2018 field season.
36

Vegetation Analysis
Across both field seasons, a total of 93 plant species were counted with 82 species
at occupied sites and 61 species at unoccupied sites (Appendix II). Plant species richness
in occupied sites was 14.32 ± 0.64 (mean SE), while it was 11.29 ± 0.75 in unoccupied
sites (Appendix III). Tree species richness at occupied sites was 3.73 ± 0.25, while it was
3.53 ± 0.34 at unoccupied sites (Appendix III). Shrub species richness was 2.50 ± 0.15 at
occupied sites and 1.76 ± 0.26 at unoccupied sites. Herbaceous plant richness was 8.00 ±
0.47 in occupied sites and 6.00 ± 0.46 in unoccupied sites (Appendix III).
The Shannon Diversity Index for the occupied sites ranged from 2.76 (Turner
Swamp 2) to 1.78 (Lost Lakes – Lake 1) (Table 2) while the unoccupied sites ranged
from 2.59 (Ice Lake) to 1.62 (Plank Road) (Table 3) (Appendix IV). Shannon Diversity
between occupied and unoccupied sites was significantly different (ANOVA, df = 1, 49,
F = 9.13, p = 0.004).
Table 2. Top 10 vegetation Shannon diversity indices for all 2018 field sites (mean of
occupied sites = 2.29 ± 0.05)
Site

Shannon Index
2.76
2.72
2.70
2.69
2.66
2.58
2.53
2.50
2.49
2.49

Turner Swamp 2
Whitaker Farm Road 2
Turner Swamp
Grass Lake
Bear Swamp 2
Painter Swamp
Turner Swamp 3
Cranberry Bog – Boardwalk
Cranberry Bog – Parking Lot 2
Brady’s Lake

37

County
Pike
Pike
Pike
Monroe
Northampton
Pike
Pike
Monroe
Monroe
Monroe

Table 3. Top 10 vegetation Shannon diversity indices for unoccupied field sites (mean of
unoccupied sites = 2.05 ± 0.07).
Site

Shannon Index
2.59
2.35
2.31
2.30
2.28
2.22
2.11
2.11
2.07
2.07

Ice Lake
Beaver Run
Tobyhanna Road
Merry Hill Wet Meadow
Brady’s Lake – Parking Lot
Shohola Swamp
Grange Road
Hell Hollow 2
Dwarfskill
Hemlock Way

County
Monroe
Pike
Monroe
Monroe
Monroe
Pike
Monroe
Monroe
Pike
Monroe

The most frequently encountered species at occupied sites were red maple (Acer
rubrum) (100%), sphagnum moss (Sphagnum sp.) (85%), and high-bush blueberry
(Vaccinium corymbosum) (79%) while 25 different species were tied for least frequent
being observed in only 3% of the field sites (Appendix V). The most frequent species
encountered at unoccupied sites were red maple (94%), sphagnum moss (76%), and highbush blueberry (76%), and sedges (Carex sp.) (76%). There were 30 species tied for least
frequent, found in only 6% of the unoccupied sites (Appendix V).
Mean percent canopy coverage between occupied and unoccupied sites was not
significantly different (ANOVA, df = 1, 49, F = 1.21, p = 0.28) with occupied sites
averaging 88% ± 0.02 and unoccupied sites 83% ± 0.05. Mean percent shrub coverage
also was not significantly different (ANOVA, df = 1, 49, F = 0.86, p = 0.36). The mean
shrub coverage for occupied sites was 54% ± 0.04 and for unoccupied sites was 46% ±
0.06. Herbaceous plant coverage was also not significantly different (ANOVA, df = 1,

38

49, F = 1.62, p = 0.21). The mean herbaceous plant coverage for occupied sites was 78%
± 0.03 and 70% ± 0.06 for unoccupied sites. (Table 4).
The mean tree height for occupied sites was 16.56 m ± 1.05 and for unoccupied
sites was 16.57 m ± 1.08; there was no significant difference between the two (ANOVA,
df = 1, 49, F = 0, p = 1.00). Mean shrub height for occupied sites was 2.72 m ± 0.08 and
2.31 m ± 0.09 for unoccupied sites and it was significantly different between the two
(ANOVA, df = 1, 49, F = 10.08, p = 0.0026). The mean number of root overturns for
occupied sites was 2.64 ± 0.32 and for unoccupied sites was 1.06 ± 0.35. The ANOVA
revealed that there was a significant difference between the two site types (ANOVA, df =
1, 49, F = 9.55, p = 0.0033) (Table 4).
Table 4. Mean vegetative parameters of occupied and unoccupied sites (asterisk indicates
significant differences).
Vegetative Structure
Canopy Coverage (percent)
Shrub Coverage (percent)
Herbaceous Plant Coverage (percent)
Tree Height (m)
*Shrub Height (m)
*Root Overturns

Occupied Unoccupied
0.88
0.83
0.54
0.46
0.78
0.70
16.56
16.57
2.72
2.31
2.64
1.06

Twenty-six species of trees, 15 species of shrub, and 52 species of herbaceous
plants were identified across all field sites for both field seasons (Appendix II). The
overall plant community was significantly different between occupied and unoccupied
sites. An ANOSIM on the abundance of each species present at occupied and unoccupied
sites revealed a significant difference (ANOSIM, R = 0.14, p = 0.02). Presence/absence

39

of species across both site types also revealed a significant difference (ANOSIM, R =
0.14, p = 0.03) (Figure 9).
The ANOSIM on trees revealed no significant difference for either the number of
individuals of each species or the presence/absence of each species between the two site
types (ANOSIM, R = 0.09, 0.09, p = 0.18, 0.21, respectively) (Figure 10). There was no
significant difference in shrub community composition, either based on abundance
(ANOSIM, R = 0.07, p = 0.10) or presence/absence (ANOSIM, R = 0.07, p = 0.11).
(Figure 11). There were significantly more individuals of each herbaceous plant species
(ANOSIM, R = 0.18, p = 0.005) at occupied sites and presence/absence of each species
was also significantly different across the two groups (ANOSIM, R = 0.18, p = 0.002)
(Figure 12).
Looking at all plants, high-bush blueberry (Vaccinium corymbosum), rosebay
rhododendron (Rhododendron maximum), red maple, sphagnum moss (Sphagnum sp.)
and sedges (Carex sp.) contributed most to the Bray-Curtis dissimilarity seen between
occupied and unoccupied sites. In addition, high-bush blueberry (p = 0.02), hay-scented
fern (Dennstaedtia punctilobula) (p = 0.001), and asters (Asteraceae) (p = 0.05) had
significant differences in abundance between site types (Appendix VI).
Sphagnum, sedges, cinnamon fern (Osmundastrum cinnamomeum), jewelweed
(Impatiens capensis), and sensitive fern (Onoclea sensibilis) contributed most to the
Bray-Curtis dissimilarity seen between site types for herbaceous plants. Hay-scented fern
(p = 0.001), asters (p = 0.03), and false hellebore (Veratrum californicum) (p = 0.02) also

40

had a significant difference in abundance between occupied and unoccupied sites
(Appendix VII).
This contrasted with the Warton et al. (2012) multivariate ANOVA method.
Using this method, the overall plant communities were still significantly different (p =
0.002) with spicebush (p = 0.04) contributing a significant amount to the difference seen
between site types (Appendix VIII). Trees remained non-significant between site types (p
= 0.31). Conversely, shrubs differed between site types (p = 0.004), with spicebush
contributing significantly to the difference (p = 0.02) and winterberry less so (p = 0.05)
(Appendix IX). Herbaceous vegetation remained significant (p = 0.04) but hay-scented
fern (p = 0.09) was not (Appendix X).

41

Number of Individuals

Presence/Absence

Figure 9. NMDS ordinations of plant communities at each field site with 95% confidence
ellipses. The top is the abundance of each species and the bottom is
presence/absence (ANOSIM, p = 0.019, 0.028, R = 0.138, 0.138, 3D-stress =
0.13, 0.13, respectively).
42

Number of Individuals

Presence/Absence

Figure 10. NMDS ordinations of tree communities at each field site with 95% confidence
ellipses. The top is the abundance of each species and the bottom is
presence/absence (ANOSIM, p = 0.184, 0.21, R = 0.048, 0.048, 3D-stress = 0.09,
0.09, respectively).
43

Number of Individuals

Presence/Absence

Figure 11. NMDS ordinations of shrub communities at each field site with 95%
confidence ellipses. The top is the abundance of each species and the bottom is
presence/absence. (ANOSIM, p = 0.095, 0.087, R = 0.072, 0.073, 3D-stress =
0.04, 0.04, respectively).
44

Number of Individuals

Presence/Absence

Figure 12. NMDS ordinations of herbaceous plant communities at each field site with
95% confidence ellipses. The top is the abundance of each species and the bottom
is presence/absence (ANOSIM, p = 0.005, 0.002, R = 0.177, 0.177, 3D-stress =
0.12, 0.12, respectively).
45

Physical Parameters
The mean wetland area was 63.30 ha ± 19.83 for occupied sites and 19.27 ha ±
7.79 for unoccupied sites (ANOVA, df = 1, 37, F= 2.88, p = 0.098). The occupied
wetlands were composed of means of 47.91 ha ± 14.88 of forested and 15.39 ha ± 6.41 of
scrub-shrub wetlands. In comparison, unoccupied sites had a mean forested wetland area
of 15.75 ha ± 6.63 and 3.51 ha ± 1.49 of scrub-shrub wetland (ANOVA: forests df = 1,
37, F= 2.69, p = 0.11, scrub-shrub df = 1.37, F= 2.09, p = 0.16) (Table 5). There was also
no significant difference between occupied and unoccupied sites with respect to water
depth. Occupied sites had a mean water depth of 4.82 cm ± 0.68 in comparison to 6.72
cm ± 1.81 for unoccupied sites (ANOVA, df = 1, 49, F= 1.43, p = 0.24).
Table 5. Wetland areas of occupied and unoccupied sites (hectares).
Status
Occupied
Unoccupied

Forested
47.91
15.75

Scrub-shrub
15.39
3.51

Total
63.30
19.27

Avian Point Count Analysis
Across both field seasons, a total of 80 species were identified with 49 species in
the first year and 70 species in the second year (Appendix XI, Appendix XII). The mean
number of species observed across sites was 15.46 ± 1.04 in 2017 (Appendix XIII) and
16.97 ± 0.62 at occupied sites and 16.56 ± 0.71 at unoccupied sites in 2018 (Appendix
XIV). There were 64 total species at occupied sites in 2018 and 58 total species at
unoccupied sites (Appendix XII). The Shannon Diversity Index for 2017 ranged from
46

2.26 - 2.99 for occupied sites (Table 6). In 2018, it ranged from 1.98 - 2.99 (Table 7) for
occupied sites and 2.16 - 2.95 for unoccupied sites (Table 8) (Appendix XV).
Table 6. Avian Shannon diversity index for all 2017 field sites (mean = 2.54 ± 0.06).
Sites
Hobday Road
Bear Swamp - Nest
Cranberry Bog – Edge
Cranberry Bog - Boardwalk
Lost Lakes- Lake 1
Grass Lake
Whitaker Road
Brady’s Lake
Bear Swamp - Boardwalk
Cranberry Bog – Parking Lot
Bear Swamp
Lost Lakes – Swamp Alley
Brady’s Lake – 7 Mile Road

Shannon Index
2.99
2.81
2.64
2.61
2.57
2.55
2.54
2.48
2.45
2.38
2.34
2.31
2.26

County
Pike
Northampton
Monroe
Monroe
Monroe
Monroe
Pike
Monroe
Northampton
Monroe
Northampton
Monroe
Monroe

Table 7. Top 10 avian Shannon diversity index for occupied sites in 2018 (mean = 2.67 ±
0.04).
Sites
Long Pond Swamp
Tarkill Demo
Turner Swamp 3
Cranberry Bog - Boardwalk
Hobday Road
Bear Wallow
Valley Road
Whitaker Road 2
Bear Swamp 2
Cranberry Bog – Parking Lot 2

Shannon Index
2.99
2.95
2.94
2.92
2.89
2.87
2.84
2.81
2.78
2.76

47

County
Pike
Pike
Pike
Monroe
Pike
Pike
Pike
Pike
Northampton
Monroe

Table 8. Top 10 avian Shannon indices for unoccupied 2018 field sites (mean = 2.64 ±
0.05).
Sites
Hemlock Way
Plank Road
Lake Greeley
Brady's Lake - Parking Lot
Hell Hollow Road 2
Merry Hill Wet Meadow
Lake Road
Shohola Creek
Indian Swamp
Beaver Run

Shannon Index
2.95
2.93
2.80
2.79
2.78
2.78
2.74
2.73
2.66
2.63

County
Monroe
Monroe
Pike
Monroe
Monroe
Monroe
Monroe
Pike
Pike
Pike

The species detected most often among the 12 sites in 2017 was the veery
(Catharus fuscescens) (Table 9) while thirteen species were least frequent (Appendix XI).
At the 35 occupied sites in 2018, the most frequently detected species was the red-eyed
vireo (Vireo olivaceus) with the ovenbird (Seiurus aurocapilla) and veery close behind
while nine species were least frequent (Table 10, Appendix XVI). Several species
competed for the most frequent species detected at the 18 unoccupied sites in 2018
including the veery, ovenbird, and red-eyed vireo whereas the red-eyed vireo was clearly
the most frequent species at all unoccupied sites (Table 10, Table 11) (Appendix XVI).

48

Table 9. Top 10 avian species frequencies of 2017.
Species
Veery
Gray Catbird
Red-eyed Vireo
Ovenbird
Black-and-white Warbler
Blue Jay
Wood Thrush
Common Yellowthroat
Northern Waterthrush
American Crow

2017 Frequency
1.00
0.92
0.92
0.85
0.77
0.77
0.77
0.69
0.69
0.54

Table 10. Top 10 avian species frequencies of 2018 at occupied sites (not including
NOWA).
Species
Veery
Ovenbird
Red-eyed Vireo
Black-and-white Warbler
Gray Catbird
Blue Jay
Canada Warbler
Common Yellowthroat
Black-capped Chickadee
Eastern Towhee

49

2018 Frequency
1.00
0.97
0.93
0.90
0.80
0.77
0.63
0.60
0.57
0.57

Table 11. Top 10 avian species frequencies of 2018 at unoccupied sites.
Species
Red-eyed Vireo
Gray Catbird
Ovenbird
Blue Jay
Common Yellowthroat
Veery
Black-capped Chickadee
Eastern Towhee
Tufted Titmouse
American Crow

2018 Frequency
1.00
0.83
0.83
0.72
0.72
0.72
0.67
0.67
0.61
0.55

The NMDS ordination and ANOSIM among the avian communities at occupied
and unoccupied sites in 2018 showed a significant difference in species composition
between the two site types for abundance and presence/absence (ANOSIM, R = 0.24,
0.14, p = 0.001, 0.009, respectively) (Figure 13). The ovenbird, common yellowthroat,
veery, red-eyed vireo, and Canada warbler contributed the most to the Bray-Curtis
dissimilarity seen. In addition, ovenbird (p = 0.02), common yellowthroat (p = 0.04),
veery (p = 0.002), black-and-white warbler (p = 0.01), swamp sparrow (Melospiza
georgiana (p = 0.02), tufted titmouse (p = 0.02), red-winged blackbird (Agelaius
phoeniceus) (p = 0.04), and eastern phoebe (Sayornis phoebe) (p = 0.03) showed
significant differences in abundance between the two site types (Appendix XVII).
The species composition for both site types was significantly different when
species heard > 75 m away were eliminated for abundance and presence/absence
(ANOSIM, R = 0.13, 13, p = 0.008, 0.015, respectively) (Figure 14). ovenbird, veery,
blue jay (Cyanocitta cristata), red-eyed vireo, and common yellowthroat contributed
50

most to the Bray-Curtis dissimiliarity seen between groups. The SIMPER test revealed
that tufted titmouse (p = 0.03), black-throated blue warbler (Setophaga caerulescens) (p
= 0.03), and hermit thrush (Catharus guttatus) (p = 0.05) exhibited significant differences
in abundance between site types (Appendix XVIII).
Conversely, following the Warton et al. (2012) method, the avian community
between occupied and unoccupied sites was significantly different (p = 0.004) with the
Canada warbler (p = 0.001) contributing most to the difference seen between the groups
(Appendix XIX). When the species further than seventy-five meters were removed,
groups were no longer significantly different (p = 1.0) (Appendix XX). Canada warblers
were seen at 21 of the 35 (60%) of the sites that were occupied by NOWA.

51

Number of Individuals

Presences/Absence

Figure 13. NMDS ordinations of avian communities at each field site with 95%
confidence ellipses. The top is the abundance of each species and bottom is
presence/absence. (ANOSIM, p = 0.001, 0.009, R = 0.238, 0.139, 3D-stress =
0.17, 0.19, respectively).
52

Number of Individuals

Presences/Absence

Figure 14. NMDS ordinations of avian communities at each field site with distant species
removed and 95% confidence ellipses. The top is the abundance of each species
and the bottom is presence/absence (ANOSIM, p = 0.008, 0.013, R = 0.133,
0.125, 3D-stress = 0.14, 0.14, respectively).
53

Nests
Two nests were found, one each in 2017 and one in 2018. The 2017 nest was
found at Bear Swamp. The nest was located about 0.6 m above water level in the roots of
an overturned green ash (Fraxinus pennsylvanica) with another green ash facing the
opposite way to form two walls with the two overturned root systems. This nest was
found on 13 June 2017 and contained five chicks that appeared to be about 7 days old (T.
Master, pers. comm.). The nest was empty on 15 June 2017 (Figure 15). There was no
sign of disturbance and the chicks did not appear ready to fledge so the cause of nest
failure is unknown.

Figure 15. NOWA nest with chicks at Bear Swamp in 2017 (photo credit Justin Clarke).
54

The second nest was found on 7 May 2018 in the roots of an overturned red maple
at Grass Lake (Figure 16). This nest was located about 0.30 m above the water level and
the red maple was slanted slightly so the top hung over the bottom. The parent was seen
going to and from the nest when it was first discovered and was later seen sitting on the
nest but there was no sign of eggs or chicks at the nest. The nest was checked once per
week for two weeks after which the parents were no longer visiting. There was no
indication of predation or disturbance to the nest so perhaps this was a false or decoy nest
but whether NOWA have been known to do this or not is unknown.

Figure 16. NOWA in nest at Grass Lake in 2018 (photo credit Justin Clarke).
55

On 25 June 2018, as we were leaving Maple Run after a point count, we noticed
two juvenile NOWA with an adult in the brush, likely evidence of another nest that was
not found. The two juveniles were chipping in the underbrush and looked like the adult
but the superciliary stripe was slightly buffier and the underparts were less defined
(personal observation).

Climate Analysis
The average elevation of the occupied sites was 420.91 m ± 21.90 while the
average elevation of the unoccupied sites was 429.35 m ± 24.56 (Table 12). There was no
significant difference in the elevation between occupied and unoccupied field sites from
both field seasons (ANOVA, df = 1, 50, F= 0.059, p = 0.81). Comparisons between the
two atlases also revealed no significant difference (ANOVA, df = 2, 55, F= 0.76, p =
0.47), the mean elevation for blocks gained during the 2nd PBBA was 420.46 m ± 37.09,
the mean for blocks lost was 422.35 m ± 30.75, and mean elevation for blocks that were
unchanged was 381.45 m ± 21.75 (Table 13).

Table 12. Average elevation of occupied and unoccupied sites.
Status
Average of Elevation (m)
Occupied
420.91
Unoccupied
429.35
Table 13. Average elevation of PBBA blocks gained, lost, and with no change between
the 1st and 2nd PBBA.
Status
Gain
Loss
None

Average of Elevation (m)
420.46
422.35
381.45
56

At occupied sites, the mean temperature change from the first (1980-1990) to the
second atlas (2000-2010) was -0.11° C ± 0.01 and the mean unoccupied site temperate
change was -0.13° C ± 0.01. An ANOVA showed that there was no significant difference
in temperature change between the occupied and unoccupied sites (df = 2, 50, F= 0.22, p
= 0.80). Maximum and minimum temperature changes were also not significant across
site types (ANOVA, df = 2, 50, 2, 50, F = 2.68, 0.06, p = 0.08, 0.94, respectively). The
maximum temperature change for occupied sites was -0.43° C ± 0.01 while the minimum
temperature change was 0.20° C ± 0.01. Unoccupied sites had a maximum temperature
change of -0.45° C ± 0.01 and a minimum of 0.19° C ± 0.02. The mean precipitation
change between those two periods was 13.54 mm ± 0.34 for occupied sites and 14.32
mm ± 0.28 for unoccupied sites (ANOVA, df = 2, 50, F= 1.93, p = 0.16) (Table 14).
Table 14. Mean temperatures and precipitation amount for occupied and unoccupied sites
over the intervening period between the two atlas time periods.
Climate Indices

Occupied

Unoccupied

Average Temperature Change (°C)

-0.11

-0.13

Max Temperature change (°C)

-0.43

-0.45

Min Temperature Change (°C)

0.20

0.19

13.54

14.32

Average Precipitation Change (mm)

The PBBA blocks did not exhibit any significant differences in the climate
variables examined. The average temperature change for blocks gained between the two
atlases was -0.13° C ± 0.02, blocks lost had an average temperature change of -0.10° C ±
0.01, and blocks that remained unchanged had an average temperature of -0.12° C ± 0.01.
There was no significant difference in the temperature change between these three block
57

groups (ANOVA, df = 2, 55, F = 0.50, p = 0.61). Maximum temperature change only
varied slightly (-0.43° C ± 0.03, -0.42° C ± 0.01, and -0.42° C ± 0.01, respectively) and
was not significantly different among the three block groups (ANOVA, df = 2, 55, F =
0.25, p = 0.78). Minimum temperature change was 0.19° C ± 0.02 for blocks gained,
0.21° C ± 0.02 for blocks lost, and 0.18° C ± 0.01 for blocks that were unchanged
between the two atlases. Maximum and minimum temperatures were not significantly
different from one another for the three block groups (ANOVA, df = 2, 55, F = 0.15, p =
0.47). Precipitation change was not significantly different between the three block groups
either (ANOVA, df = 2, 55, F = 0.59, p = 0.87). The average precipitation change was
13.88 mm ± 0.67 for blocks gained, 13.68 mm for blocks lost ± 0.47 , and 14.00 mm ±
0.35 for blocks that were unchanged between the two atlases (Table 15).
Table 15. Mean temperatures and precipitation amount for the two atlas time periods for
blocks gained, lost, and those with no change between the first and second PBBA.
Climate Index

Gain

Loss

None

Average Temperature Change (°C)

-0.13

-0.10

-0.12

Max Temperature Change (°C)

-0.43

-0.42

-0.42

Min Temperature Change (°C)

0.19

0.21

0.18

Average Precipitation Change (mm)

13.88

13.68

14.00

Between the first and second PBBA, 24 blocks changed in occupancy status.
Seven blocks were gained (newly occupied) in the second atlas and 17 were lost (no
longer occupied) from the first to the second atlas (Figure 17). This resulted in a
noticeable contraction in NOWA range between the first and second PBBA. The northern

58

margin of the NOWA range moved about ten km south and the southern margin moved
about nine km north.

Figure 17. PBBA blocks that were gained or lost from the 1st to the 2nd PBBA.

59

CHAPTER IV
Discussion
The goal of this study was to investigate NOWA distribution and decline
indicated by block occupancy patterns between the 1st and 2nd PBBA (Wilson et al. 2012)
and investigate potential causes for the decline. I was only able to cover 53 of the
hundreds of wetlands in the study area, mainly because many of the potential wetlands I
found, were located on private land. However, by focusing on PBBA blocks rather than
each individual wetland, I was able to cover much of the study area and confirm almost
every block that was considered probable or confirmed in both PBBAs in addition to
finding new swamps inhabited by NOWA.
During the 2017 and 2018 field season, NOWA were found in 35/53 swamps
surveyed (Figure 8). There were 73 total detections of individual NOWA throughout the
two field seasons. Since individuals were not banded and point counts were taken from
the same point at each site, it is possible that individuals could have been counted
multiple times but not likely given the distance between point counts.
Throughout the breeding season, I was able to confirm three blocks as breeding
blocks while the others were defined as probable based on the territorial and agitated
behavior categories defined in the 2nd PBBA (Wilson et al. 2012). Confirming breeding
60

behavior based on 2nd PBBA categories was extremely difficult for two reasons: (1) many
of the sites found had very dense understory that impeded sight and made it difficult to
keep track of NOWA individuals, and; (2) because of the dense understory and the thick
layer of mud beneath the water, it was very difficult to move about without disturbing
birds.
The three confirmed blocks were all open areas where I was able to observe
NOWA movements more easily. Visibility is one explanation for the lack of confirmed
blocks seen in both the 1st (3 blocks) and 2nd PBBA (4 blocks) (Wilson et al. 2012).
However, it fails to explain the drastic decline in probable blocks between the two atlases
(15 and 4 blocks, respectively), especially considering that effort was more extensive
during the 2nd PBBA. Another explanation for the observed decline is detectability of this
species. NOWA singing ends in mid to late -June so it is difficult to accurately sample
many different locations within their relatively abbreviated singing period. I tried to
mitigate this issue by visiting every site once before revisiting sites but it still limited the
amount of time I had to survey as many wetlands within the three-county study area as I
could. This issue was also noted by Stephen Eaton during the first New York Atlas of
Breeding Birds (Eaton 1988, McGowan and Corwin 2008).
However, even with difficulty detecting and observing this species, I was able to
confirm occupancy in twenty-two of the original atlas blocks (Figure 8) in the study area.
This was more than both the 1st (8 blocks) and 2nd PBBA (18 blocks) (Figure 7) which
suggests that the species may have been underrepresented, especially in the 2nd PBBA in
spite of the increased effort. Eaton (1988) mentioned the difficulty associated with
61

detecting this species may have resulted in underrepresentation in the New York atlas as
well. The actual population decline is difficult to estimate though because the density of
NOWA within each block was not measured in the first atlas and was not able to be
measured in the second atlas because detections during point counts were too few. I had
several blocks with multiple sites and many NOWA within them and so if there is a
decline in blocks, it likely translates to an even larger decline in population size within
the state.
I observed a contraction in NOWA range from the first to the second atlas with
the northern margin moving south approximately 10 km and the southern margin moving
north about 9 km from the 1st to the 2nd atlas (Figure 17). This supports the range
contraction observed in the atlas. However, I was unable to find evidence that this range
shift was driven by climate change or that the range contraction was due to a shift to
higher elevations (Table 13). My results show that the 1st PBBA occupied blocks were
about 20 m lower in elevation than the blocks occupied in the 2nd PBBA (Table 13)
(406m and 430m, respectively).
Although not statistically significant, the observed difference in elevation could
very well be meaningful with regard to the influence of climate change and suggestive of
the initial stages of a shift to higher elevation that is ongoing. A larger sample size might
aid in determining significance, but it must be recognized that vertical relief in this
region, while greater than in some parts of Pennsylvania, may not be sufficient for birds
to move high enough to reflect a statistically significant change in elevation. Without
coordinates for exact sites used in the first PBBA, I was forced to use mean elevations for
62

the blocks in that atlas which likely does not reflect the actual elevation at the detection
sites and consequently does not reflect more precise measures of elevational change
between atlases.
This is in contrast to other studies that have found breeding birds moving north
due to climate change ( Thomas and Lennon 1999, Hitch and Leberg 2007, Sneddon and
Hammerson 2014, Langham et al. 2015). However, these studies were modeling changes
that will be seen in the future. Pounds et al. (1999) did find that species were moving
higher based on climate change. This study was conducted in cloud forest at Monteverde,
Costa Rica and the change in elevation was highly correlated with dry-season-mist
frequency and cloud deck elevation. Again, significant changes in elevation may be more
difficult to detect at lower elevations with generally less relief in the Appalachians of
Pennsylvania.
Water depth was also not significantly different between occupied and
unoccupied sites and thus the difference between relatively shallow and deeper sites was
not sufficient to provide more protection from predators (Table 4). Hoover (2006) found
a link between larger differences in water depth and predation on nests. Over 75% of the
nests studied in shallow water (0-30 cm) were depredated as opposed to 24% in deep
water (greater than 60 cm). While the predators varied, raccoons were responsible for
73% of all of nest predation in the study (Hoover 2006).
Changes in wetland size could also play a role in population decline but it is not
likely there has been any significant change in the area of individual wetlands between
the two atlas periods. However, there was a large wetland size difference between
63

occupied and unoccupied sites and so area could be important with respect to NOWA
habitat selection. Occupied sites were over 40 ha larger than unoccupied sites on average
although this large difference was not significant (Table 5). Occupied sites had a standard
deviation of 19.83 ha while unoccupied sites had a standard deviation of just 7.79 ha.
This suggests that there is a lot more variation in the occupied sites and a larger sample
size may help to create a more robust analysis of occupied and unoccupied wetland sizes.
Wilcove (1985) found a linear trend between forest size and predation rate with
larger forest tracts having less predation than smaller tracts (Wilcove 1985). Another
factor affecting predation rates is fragment shape. One of the larger sites (283 ha) in
Wilcove’s (1985) study had a 48% nest predation rate which may have been because it
was a very long and narrow corridor that could easily be penetrated by predators. Winter
et al. (2000) found that meso-predators were more active near the edge of grasslands than
interiors. Since smaller wetlands have proportionally more edge than interior, predation
pressure would be increased. Many studies consider these smaller forest fragments to be
population “sinks” where the mortality rates are higher than the reproduction rates
(Donovan et al. 1995, Robinson et al. 1995).
The Biological Dynamics of Forest Fragments Project (BDFFP),the largest and
longest-running experimental study of habitat fragmentation, found that edges can change
a lot in smaller, more fragmented forests (Laurance et al. 2011). Fragmentation affects
patchily distributed species such as NOWA more than other species because of sampling
effects. The sampling effect states that species that were not present when the fragment
was isolated would not be present in the fragment after isolation (Laurance 1991, 2004,
64

Laurance et al. 2011). These effects can change not just NOWA distribution directly by
removing habitat or access to habitat, but they can have indirect effects by changing the
characteristics of preferred NOWA habitat.
Edge effects also include increased desiccation stress that can be especially
stressful to species dependent on wetlands like NOWA. The effects on the microclimate
of the forest understory can extend at least 40 m into the interior and, in some cases, as
much as 200 m into the forest interior from edges (Betts et al. 2006, Kopos 1989,
Laurance 1991, 2004, Laurance et al. 2011). Such desiccation could affect the availability
of the macroinvertebrates that NOWA feed on and increase predation on NOWA nests by
increasing accessibility to the nest (Hoover 2006).
Unlike forest fragments that are usually surrounded by suburbia and agriculture,
as in the examples above, wetlands inhabited by NOWA are embedded within a larger
forested landscape and so population dynamics and predation threat imposed by size are
likely different than those at work in typical forest fragments. For example, do predators
take advantage of the increased access provided by the proportionally greater edge of
smaller wetlands given the difficulty of moving around once inside the wetland? Is the
relative habitat quality of a smaller wetland embedded within a large forest fragment
different from a small or a large wetland found within a smaller forest fragment?
Additional considerations like these, cloud the effects and dynamics of wetland size on
NOWA populations.
Size could directly affect the amount/availability of nesting substrate; thus, this is
a much more likely and discernable effect of wetland size on NOWA distribution and
65

abundance. I found that occupied sites had significantly more root overturns than the
smaller unoccupied sites on an absolute basis. The typically larger occupied wetlands
would therefore more likely provide tree root overturns at the right stage of decay for
nesting (stages of decay affect the number of suitable nesting sites in an overturn) than
would the smaller unoccupied wetlands (Mattingly 2016) The number of root overturns
was 2.5 times greater on occupied vs. unoccupied sites. However, this was not relativized
for wetland size since I only recorded overturns inside or close to each territory and not
through the entire wetland. Finally, perhaps size is important simply because NOWA
have an intrinsic minimum required area to breed successfully as is the case with many
grassland birds (Kobal et al. 1999, Douglas and Lawrence 2001) .
Although many studies attribute declines in songbird distribution and abundance
to climate change and fragmentation (Wilcove 1985, Thomas and Lennon 1999, Hitch
and Leberg 2007, Laurance et al. 2011, Sneddon and Hammerson 2014, Langham et al.
2015), our results suggest that changes in vegetation structure, and, to a lesser extent,
vegetation composition, may be driving the decline of NOWA most visibly. Two,
perhaps interacting factors are at play, over browsing by the White-tailed Deer
(Odocoileus virginianus) (deCalesta 1994a, Allombert et al. 2005a, Baiser et al. 2008)
and the devastating effect of Hemlock Woolly Adelgid infestations on the Eastern
Hemlock.
White-tailed deer were historically controlled by harsh winters, hunting by
natives, and predation by mountain lions (Felis concolor) and gray wolves (Canis lupus)
(McCabe and McCabe 1984, Witmer and deCalesta 1991, and deCalesta 1997).
66

Historically, white-tailed deer population density was estimated to be approximately 3-4
deer/km2 in Wisconsin prior to European arrival (McCabe and McCabe 1984). After
Europeans arrived, the deer population was almost brought to extinction by overhunting
by the early 1900s (McCabe and McCabe 1984, Witmer and deCalesta 1991, deCalesta
1997). With careful management and hunting regulations the deer population has
rebounded with current population densities of approximately 12 deer/km2 throughout
Pennsylvania (Julian and Smith 2001) .
The Pennsylvania Game Commission divides the state into wildlife management
units (WMU) for monitoring and managing the white-tailed deer population. The WMU
that this study takes place in covers 5,441 km2. During our 2017 and 2018 field season
this WMU had an average of 32,014 and 30,727 deer, respectively. This equals 5.88 and
5.65 deer/km, respectively, both above the historical estimate. In the annual deer
population report (Pennsylvania Game Commission 2018) the deer population was
considered stable with an average population density estimate of 6 deer/ km2 for the
WMU that overlaps the study area.
Vegetation changes are accompanied by deer over browsing and these changes,
especially with regard to structure, will affect avian communities (Casey and Hein 1983,
deCalesta 1994a, McShea and Rappole 2000, Allombert et al. 2005). Over browsing can
affect species in a variety of ways from increasing the efficiency of nest predators by
reducing vegetation available for nest concealment (Martin and Roper 2007) to reducing
abundance of invertebrates that birds feed on (Allombert et al. 2005b). These studies
suggest that such changes affect avian species that depend in particular on understory
67

vegetation, either for nesting or foraging, compared to those inhabiting the canopy
(Casey and Hein 1983, deCalesta 1994a, Allombert et al. 2005a). Allombert et al. (2005a)
found a 70% reduction of breeding pair density, and a 92% decline in species that depend
on understory vegetation due to over browsing in the Haida Gwaii Archipelago off the
coast of British Columbia, Canada.
In the SIMPER analysis, many of the differences in plants that were most obvious
between occupied and unoccupied sites involved high-bush blueberry, rosebay
rhododendron and red maple (Appendix VI, Appendix VII), two of which are understory
plants and all of which are typically associated with the swamps that NOWA prefer
(Craig 1985, Whitaker and Eaton 2014).

One of the species that stood out in the

SIMPER analysis that is associated with deer over browsing is hay-scented fern
(Appendix VI, Appendix VII). This species was found, on average, in higher abundance
at unoccupied sites than occupied sites (less than 1% coverage at occupied sites, 7%
coverage at unoccupied sites).
This fern colonizes areas that deer over browse because they will heavily graze
plants they find palatable, opening the understory allowing the fern to dominate the
ground cover, since they are largely unpalatable to deer (Horsley and Marquis 1983),
along with graminoids such as grasses and sedges (DeGraaf et al. 1991, Horsley et al.
2003, Rooney 2009). While grasses (3% coverage at occupied sites and 5% coverage at
unoccupied sites) and sedges (13% coverage at occupied and 21% coverage at
unoccupied sites) weren’t found to be significantly different between occupied and

68

unoccupied sites, they were found to occur, on average, in higher densities at unoccupied
sites in our study (Appendix II, Appendix V).
Rooney (2009) found that deer over browsing can result in a change in the
composition and structure of the avian community at a site without affecting species
richness or diversity. DeGraaf et al. (1991) found an increase in intermediate canopy
birds in contrast to McShea and Rappole (2000) who found an increase in both
intermediate canopy and ground dwelling birds. McShea and Rappole (2000) suggest this
may be due to both different sampling methods (mist netting vs point counts) and
different study areas. DeGraaf et al. (1991) conducted studies in a combination of forest
management types whereas McShea and Rappole (2000) conducted their study well
within protected forests.
DeGraaf et al. (1991) also found that over browsing by white-tailed deer did not
affect the richness or diversity of avian species in forested areas. McShea and Rappole
(2000) suggest that the reason there is no change in diversity is because avian species will
replace each other as the habitat changes. However, DeGraaf et al. (1991) did find that
three species in particular appeared to be very sensitive to vegetation changes associated
with over browsing. These species were the Canada warbler, chestnut-sided warbler, and
black-throated blue warbler (DeGraaf et al. 1991). This could explain why we did not see
a significant difference in avian richness or diversity but did find that both CAWA and
NOWA were absent from unoccupied sites.
Spicebush was the only plant that the Warton et al. (2010) method identified as
significantly different between site types (Appendix VIII, Appendix IX). This species
69

composed 12% of total shrub coverage at occupied sites and wasn’t seen at unoccupied
sites at all (Appendix II). It is known to be unpalatable to deer and typically only
undergoes moderate browsing if any (Randle and Wenzel 2014, Jenkins et al. 2015).
Horsley et al. (2003) found that over- browsed sites resulted in shorter trees and more
ground cover, especially grass, forbs, and ferns, than less browsed sites. This supports my
findings where there were less tall, woody, understory stems and more grasses, forbs, and
ferns at unoccupied sites indicating that NOWA may not utilize these sites because of the
effects of deer over browsing.
A study conducted by Baiser et al. (2008) found that white-tailed deer can alter
the composition of a site so it is no longer suitable habitat for understory birds. They also
determined that over browsing can open gaps that make it easier for invasive, or in this
case, native plants that are unpalatable to deer, to further transform the understory into a
matrix that is completely different from what these species deem suitable habitat. Baiser
et al. (2008) suggest that these two factors can transform even large tracts of habitat that
seem appropriate into unsuitable areas for understory birds.
White-tailed deer could be one explanation for why shrub height was higher at
occupied compared to unoccupied sites (Horsley et al. 2003) (Table 4). McShea et al.
(1995) showed that Kentucky warblers (Geothlypis formosa) were found at lower
densities in areas that were under high browsing pressure because deer were changing the
understory. However, they note that the lower densities observed at some sites may have
also been due to the decline of Kentucky warblers within the state in general. These

70

results agree with deCalesta et al. (1994b) who also found that avian species richness was
reduced in areas that were heavily browsed by deer.
Allombert et al. (2005b) observed that understory invertebrates were found in
lower densities in areas that were heavily browsed by deer, specifically edge habitats.
They suggest that a cascade effect could be occurring through the food web that is
manifested in the decline of many songbirds in North America.
Another potential explanation for the change in vegetation structure and certainly
a cause of concern for this species is eastern hemlock decline. This species was more
frequently encountered at occupied sites (62% of total at occupied sites) compared to
42% at unoccupied sites) (Appendix V). Most of the literature suggests that NOWA are
often associated with swamps containing eastern hemlock (Craig 1985, Wilson et al.
2012, Whitaker and Eaton 2014). Thus, loss of eastern hemlock could negatively affect
the NOWA population by changing vegetation structure and the microclimate within
these swamps in combination with the changes caused by deer over browsing (Becker et
al. 2008, Allen et al. 2009, Shelton et al. 2014).
Orwig et al. (2002) determined that within 15 years of entering the state of
Connecticut, HWA had infected hemlocks in every town as it travelled north through the
state. They found that The loss of hemlock results in a more homogenous environment
and the disappearance of important cooler microclimates that are created with the deep
shade cast by stands of this tree (Orwig et al. 2002, Brantley et al. 2013). Declines have
already been documented in some bird species that are closely associated with eastern
hemlock such as Acadian Flycatchers (Allen et al. 2009, Becker et al. 2008).
71

The mortality of HWA appears to vary greatly. McClure (1991) found that
hemlocks die rapidly (within 1 to 4 years) after infestation, but other studies have shown
that trees can live substantially longer and that mortality rates may be less than expected
(Orwig 2002, Eschtruth et al. 2013). Eschtruth et al. (2013) conducted the most complete
and long-term study on hemlock mortality in the Delaware Water Gap National Recreate
Area, PA. They calculated that survivorship of eastern hemlock average 73% after HWA
infestation.
Deer over browsing could also result in a loss of eastern hemlock in these
swamps. Hough (1965) found that deer can drastically alter the composition of the
understory in hemlock-mixed hardwood forests. He found that white-tailed deer will
heavily browse young hemlocks which will kill many and, if they manage to survive,
greatly reduce the vigor of remaining individuals. Rogers (1977) also found that deer will
readily eat eastern hemlock and can be one of the most important factors in preventing
reestablishment of this tree species. It is well documented that white-tailed deer will
readily eat hemlock and consume all seedlings and saplings in yarding areas during the
winter months (Hosley and Ziebarth 1935, Rogers 1977).
The loss of eastern hemlock will open gaps in wetlands that NOWA occupy and
over browsing by deer will prevent regeneration of trees. This will reduce the rate that
succession can progress at which will extend the life of these gaps. As has already been
explained, these gaps will cause changes in the microclimate of NOWA habitat and this
warming, along with the warming associated with climate change, may have an effect on
their food availability and abundance (Orwig et al. 2002, Baiser et al. 2008, Brantley et
72

al. 2013). Kamler (1965) found that species richness, specifically of the insect orders
Ephemeroptera and Plecoptera, was higher in cooler, more thermally stable environments
that are often associated with hemlock-dominated streams (Snyder et al. 2002). This is
especially important because Plecoptera and Ephemeroptera are two main food resources
of both LOWA and NOWA (Whitaker and Eaton 2014).
A study conducted by Adkins and Rieske (2015) compared the composition of
insects known as shredders in headwaters with hemlock dominated overstory to
headwaters dominated by deciduous species, the likely replacements following the loss of
eastern hemlock. They found that shredders, with Plecopterans being the dominant order,
were significantly more abundant during the summer in headwaters streams that were
near hemlock forests, possibly due to the constant litter output that these shredders feed
upon (Adkins and Rieske 2015). Eastern hemlock is a less nutritious but more constant
food source whereas deciduous trees are more nutritious but highly seasonal (Adkins and
Rieske 2015).
Confirming and understanding the possible reasons for NOWA decline is
important for continued existence of this species in Pennsylvania. NOWA can also be
considered an umbrella species for peatland habitats and other species found in this
habitat type. (Pennsylvania Biological Survey Technical Committee 2013, Sneddon and
Hammerson 2014). The most important “other” species is probably the Canada Warbler
(CAWA). CAWA and NOWA were seen together at 60% of the field sites and it was the
only species that was significantly different in both the SIMPER analysis (Appendix
XVII) and the Warton et al. (2012) method (Appendix XIX).
73

CAWA occupies higher elevation wetlands at the southern edge of its range,
which is in Pennsylvania, as is the case with NOWA (Reitsma et al. 2009). Based on the
2nd PBBA, CAWA appear to be stable within the state (Wilson et al. 2012) despite their
general, overall long-term decline due to fragmentation, loss of wetlands, and forest
maturation) (NatureServe 2017). In New York, CAWA experienced a 23% decline
between the first and second atlas there (McGowan and Corwin 2008). NOWA, on the
other hand, were found in low numbers throughout New York State but the population
appeared to be relatively stable between the two atlases (McGowan and Corwin 2008).
However, the decline of CAWA in the New York State Atlas appears to be a more
general decline.

Future Studies and Issues of Concern Highlighted by This Study
Previous research has documented changes in avian populations due to climate
change (Thomas and Lennon 1999, Hitch and Leberg 2007). NOWA and CAWA are
two species that are likely to be severely impacted by climate change because they are at
the southern edge of their range in an area that will lose a lot of potential habitat as
temperatures warm (Thomas and Lennon 1999, Reitsma et al. 2009, Whitaker and Eaton
2014). Our study did not support this finding, perhaps because the magnitude of
topographical relief in Pennsylvania is simply not great enough for detection of
significant elevationally driven range shifts. At the same time, this also makes such
species considerably more susceptible to climate change because the higher elevations
with cooler temperatures they will eventually require are quite limited in Pennsylvania
where the highest point, Mt. Davis, is only 3,200 ft above sea level. Further research
74

needs to be conducted at a broader scale, e.g. including more surrounding states, for this
species, and other peatland species, in order to truly determine whether climate change is
affecting their range, distribution and abundance.
Fragmentation effects on NOWA have proven difficult to establish but
nevertheless are another factor potentially affecting the decline of this species. The
influence of wetland size and shape on NOWA populations is probably not similar to the
dynamics associated with typical woodland fragments and bird populations. This is
because the habitat of concern, wetland, is embedded within larger forest fragments,
making it difficult to separate the effects of wetland size and shape from the size and
shape of the forest fragments that surround them. Thus, it is difficult to tease apart all of
the habitat size and shape influences acting on NOWA populations. One additional area
that could be investigated further with regard to fragmentation is the extent to which
second home development is having an impact on NOWA in areas where there was a
decline in block occupancy.
There has been a lot of research conducted on how deer over browsing affects
vegetation, but only recently have the effects on the avian community been examined in
detail using modern field methods (Hosley and Ziebarth 1935, Allombert et al. 2005a,
Baiser et al. 2008). An overabundance of deer throughout their range (McCabe and
McCabe 1984, deCalesta 1997) could be a major factor contributing to the decline of
NOWA. Specific factors that could be examined in further detail are increased predation
due to lack of concealing vegetation with regard to nests and how changes in the
vegetation structure affect the foraging behavior and reproductive success of NOWA.
75

Examination of the loss of hemlocks and how this is currently affecting NOWA
populations should be examined in more detail. Obvious factors related to hemlock loss
that could be investigated are how the microclimate of wetlands that no longer have
eastern hemlock is changing and how this loss affecting the macroinvertebrates that
NOWA feed on. Less obvious, but potentially very interesting to investigate in the
future, is the interplay, with regard to changes in vegetation structure and composition,
between deer over browsing and hemlock decline. Deer over browsing removes mostly
woody understory shrubs and some ground cover (e.g., native wildflowers) which opens
space typically usurped by invasive species such as hayscented fern and Japanese
barberry (Berberis thunbergii).

Hemlock decline affects both the canopy and the

understory, the latter not by freeing up space but by allowing light penetration to the
forest floor which then stimulates understory growth, probably more often composed of
native species, due to acidic soil conditions, than invasive species. Thus, the two impacts
may tend to counteract one another with regard to understory structure.

Conclusion
NOWA are potentially under pressure from many different negative impacts from
fragmentation to deer over browsing, changes in forest composition, hydrological
changes and climate change. However, the most pressing of these concerns currently
appears to be changes in vegetation structure. These changes appear to be influenced by
several factors and may be largely responsible for the current decline in NOWA
populations detected by the 2nd PBBA. Climate change, on the other hand, is likely the

76

most important future impact affecting this species in Pennsylvania (Sneddon and
Hammerson 2014, Langham et al. 2015).

77

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87

APPENDICES
Appendix I. Field Site Locations.
Name
Status
Bear Swamp Occupied
Bear Swamp - Boardwalk Occupied
Bear Swamp - Boardwalk 2 Occupied
Bear Swamp - Nest Occupied
Bear Swamp 2 Occupied
Bear Wallow Occupied
Beaver Run 2 Occupied
Brady's Lake Occupied
Brady's Lake - 7 Mile Road Occupied
Brady's Lake - 7 Mile Road 2 Occupied
Caughbaugh Road Occupied
Caughbaugh Road 2 Occupied
Cranberry Bog - Boardwalk Occupied
Cranberry Bog - Edge Occupied
Cranberry Bog - Parking Lot Occupied
Cranberry Bog - Parking Lot 2 Occupied
Dingmans Turnpike Occupied
Fivemile Meadow Occupied
Grass Lake Occupied
Hobday Road Occupied
Long Pond Swamp Occupied
Lost Lakes - Lake 1 Occupied
Lost Lakes - Lake 3 Occupied
Lost Lakes - Swamp Alley Occupied
Lower Lake Occupied
Maple Run Occupied
Painter Swamp Occupied
Tarkill Demo Occupied
Tobyhanna Road 2 Occupied
Turner Swamp Road Occupied
Turner Swamp Road 2 Occupied
Turner Swamp Road 3 Occupied
Valley Road Occupied
Whitaker Road Occupied
Whitaker Road 2 Occupied
Beaver Lake Unoccupied
88

Latitude Longitude
County
40.90325 -75.17834 Northampton
40.91027 -75.18654 Northampton
40.91085 -75.18800 Northampton
40.90428 -75.17796 Northampton
40.90415 -75.17802 Northampton
41.34683 -75.23599
Pike
41.24111 -75.07771
Pike
41.17997 -75.52119
Monroe
41.19946 -75.46296
Monroe
41.20090 -75.46190
Monroe
41.13772 -75.59298
Monroe
41.14313 -75.58611
Monroe
41.03838 -75.26625
Monroe
41.04008 -75.26655
Monroe
41.04173 -75.26471
Monroe
41.04149 -75.26749
Monroe
41.29476 -74.97618
Pike
41.28616 -75.00475
Pike
41.03388 -75.43866
Monroe
41.30896 -75.11485
Pike
41.34460 -75.14977
Pike
41.08410 -75.48576
Monroe
41.08319 -75.49067
Monroe
41.08126 -75.48526
Monroe
41.31104 -75.22452
Pike
41.31462 -75.09493
Pike
41.23410 -75.02780
Pike
41.30865 -75.10969
Pike
41.22018 -75.44351
Monroe
41.16269 -75.10042
Pike
41.16321 -75.10198
Pike
41.16229 -75.10381
Pike
41.38041 -75.06758
Pike
41.18290 -75.06086
Pike
41.17639 -75.07210
Pike
41.39140 -75.09140
Pike

Beaver Run
Brady's Lake - Parking
Dwarfs Kill
Grange Road
Hell Hollow Road
Hell Hollow Road 2
Hemlock Way
Ice Lake
Indian Swamp
Lake Greeley
Lake Road
Merry Hill Trail Wet Meadow
Plank Road
Seven Pines
Shohola Creek
Tobyhanna Road
Two Mile Run

Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied

89

41.23896
41.16169
41.29649
41.11560
40.95023
40.94794
41.20008
41.14940
41.25710
41.41600
41.19732
41.11525
41.22235
41.14141
41.37022
41.20481
41.13525

-75.07557
-75.53054
-74.93886
-75.34540
-75.54957
-75.54018
-75.22235
-75.29030
-75.12830
-75.01350
-75.21992
-75.31028
-75.52712
-75.29370
-75.05106
-75.44308
-75.57781

Pike
Monroe
Pike
Monroe
Monroe
Monroe
Monroe
Monroe
Pike
Pike
Monroe
Monroe
Monroe
Monroe
Pike
Monroe
Monroe

Appendix II. Average percent of plant species found at occupied and unoccupied sites.
Common Name
American Elm
Beech
Black Birch
Black Cherry
Black Spruce
Black Walnut
Black Willow
Blue Spruce
Eastern Hemlock
Gray Birch
Green Ash
Musclewood
Red Maple
Red Oak
Shagbark Hickory
Slippery Elm
Smooth Alder
Sycamore
Tamarack
Tulip
Tupelo
White Ash
White Birch
White Oak
White Pine
Yellow Birch
Buttonbush
European Elderberry
Fox Grape
High-bush Blueberry
Japanese Barberry

Latin Name
Ulmus americana
Fagus grandifolia
Betula lenta
Prunus serotina
Picea mariana
Juglans nigra
Salix nigra
Picea pungens
Tsuga canadensis
Betula populifolia
Fraxinus
pennsylvanica
Carpinus
caroliniana
Acer rubrum
Quercus rubra
Carya ovata
Ulmus rubra
Alnus serrulata
Platanus
occidentalis
Larix larcinia
Lirodendron
tulipifera
Nyssa sylvatica
Fraxinus
americana
Betula papyrifera
Quercus alba
Pinus strobus
Betula
alleghaniensis
Cephalanthus
occidentalis
Sambucus nigra
Vitis labrusca
Vaccinium
corymbosum
Berberis
thunbergii
90

Group
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree

Occupied
0.01
0.04
0.01
0.00
0.04
0.00
0.00
0.00
0.19
0.00
0.04

Unoccupied
0.00
0.07
0.04
0.01
0.01
0.00
0.01
0.00
0.11
0.00
0.01

Tree

0.00

0.00

Tree
Tree
Tree
Tree
Tree
Tree

0.39
0.00
0.00
0.00
0.06
0.00

0.46
0.00
0.01
0.00
0.05
0.00

Tree
Tree

0.01
0.00

0.00
0.01

Tree
Tree

0.02
0.01

0.06
0.00

Tree
Tree
Tree
Tree

0.00
0.00
0.02
0.14

0.01
0.01
0.06
0.07

Shrub

0.00

0.01

Shrub
Shrub
Shrub

0.00
0.01
0.43

0.01
0.00
0.63

Shrub

0.00

0.05

Mountain Holly Ilex mucronate
Multiflora Rose Rosa multiflora
Rhododendron Rhododendron
maximum
Serviceberry Amelanchier
arborea
Sheep Laurel Kalmia
angustifolia
Southern Arrowwood Viburnum
dentatum
Spicebush Lindera benzoin
Swamp Azalea Rhododendron
viscosum
Winterberry Ilex verticillata
Witch Hazel Hamamelis
virginiana
Arroweed Pluchea sericea
Aster Asteraceae
Bedstraw Gallium sp.
Bittercress Cardamine
hirsuta
Broadleaf Cattail Typha latifolia
Bugleweed Lycopus
americanus
Calla Lily Zantedeschia
aethiopica
Canada Maylily Maianthemum
canadense
Canadian Bunchberry Cornus
canadensis
Cinnamon Fern Osmundastrum
cinnamomeum
Common Blue Violet Viola sororia
Common Boneset Eupatorium
perfoliatum
Dewberry Rubus pubescens
Enchanter’s Nightshade Circaea lutetiana
False Hellebore Veratrum
californicum
Field Horsetail Equisetum
arvense
Golden Club Orontium
aquaticum
91

Shrub
Shrub
Shrub

0.02
0.00
0.20

0.01
0.01
0.17

Shrub

0.00

0.02

Shrub

0.00

0.00

Shrub

0.00

0.00

Shrub
Shrub

0.12
0.00

0.00
0.03

Shrub
Shrub

0.18
0.02

0.04
0.00

Herbaceous
Herbaceous
Herbaceous
Herbaceous

0.03
0.00
0.01
0.01

0.00
0.03
0.00
0.00

Herbaceous
Herbaceous

0.00
0.04

0.00
0.01

Herbaceous

0.01

0.00

Herbaceous

0.01

0.00

Herbaceous

0.00

0.00

Herbaceous

0.11

0.05

Herbaceous
Herbaceous

0.00
0.00

0.00
0.00

Herbaceous
Herbaceous
Herbaceous

0.00
0.00
0.00

0.01
0.01
0.01

Herbaceous

0.00

0.00

Herbaceous

0.00

0.00

Golden Saxifrage Chrysosplenium
americanum
Grass Poaceae sp.
Hay-scented Fern Dennstaedtia
punctilobula
Jack-in-the-Pulpit Arisaema
triphyllum
Japanese Stiltgrass Microstegium
vimineum
Jewelweed Impatiens
capensis
Marginal Wood Fern Dryopteris
marginalis
Marsh Fern Thelypteris
palustris
Marsh Marigold Caltha palustris
New York Fern Thelypteris
noveboracensis
Northern Blue Flag Iris versicolor
Poison Ivy Toxicodendron
radicans
Purple Pitcher Plant Sarracenia
purpurea
Ragweed Ambrosia
artemisiifolia
Royal Fern Osmunda regalis
Sedge Carex sp.
Sensitive Fern Onoclea sensibilis
Sideflowering Skullcap Scutellaria
lateriflora
Skunk Cabbage Symplocarpus
foetidus
Sphagnum Sphagnum sp.
St. John’s Marshwort Hypericum
perforatum
Starflower Trientalis borealis
Swamp Candle Lysimachia
terrestris
Tall Meadow Rue Thalictrum
dasycarpum
Threeleaf Goldenthread Coptis trifolia
Threeway Sedge Dulichium
arundinaceum
92

Herbaceous

0.00

0.00

Herbaceous
Herbaceous

0.03
0.01

0.05
0.07

Herbaceous

0.01

0.00

Herbaceous

0.02

0.03

Herbaceous

0.05

0.07

Herbaceous

0.00

0.00

Herbaceous

0.02

0.00

Herbaceous
Herbaceous

0.01
0.01

0.00
0.00

Herbaceous
Herbaceous

0.01
0.01

0.01
0.01

Herbaceous

0.00

0.00

Herbaceous

0.00

0.01

Herbaceous
Herbaceous
Herbaceous
Herbaceous

0.00
0.13
0.08
0.00

0.01
0.21
0.04
0.00

Herbaceous

0.01

0.01

Herbaceous
Herbaceous

0.24
0.01

0.22
0.00

Herbaceous
Herbaceous

0.01
0.01

0.01
0.03

Herbaceous

0.00

0.00

Herbaceous
Herbaceous

0.02
0.01

0.00
0.00

Virginia Chainfern Woodwardia
virginica
Virginia Creeper Parthenocissus
quinquefolia
Virginia Strawberry Fragaria
virginiana
Water Pennywort Hydrocotyle
ranunculoides
White Meadowsweet Spiraea alba
Wineberry Rubus
phoenicolasius
Wood Nettle Laportea
candensis
Wood Sorrel Oxalis stricta
Other

93

Herbaceous

0.00

0.02

Herbaceous

0.01

0.01

Herbaceous

0.00

0.00

Herbaceous

0.00

0.00

Herbaceous
Herbaceous

0.01
0.01

0.04
0.02

Herbaceous

0.00

0.00

Herbaceous
Herbaceous

0.00
0.02

0.00
0.03

Appendix III. Species richness at occupied and unoccupied sites during the 2017 and
2018 field season.
Name
Bear Swamp 2
Whitaker Farm Road 2
Grass Lake
Cranberry Bog - Boardwalk
Painter Swamp
Turner Swamp
Turner Swamp 2
Brady's Lake
Turner Swamp 3
Cranberry Bog - Parking Lot 2
Hobday Swamp
Caughbaugh Road
Bear Swamp - Boardwalk 2
Caughbaugh Road 2
Fivemile Meadow
Tarkill Demo
Valley Road
Lower Lake
Beaver Run 2
Brady's Lake - 7 Mile Road 2
Cranberry Bog - Parking Lot
Cranberry Bog - Edge
Bear Swamp - Boardwalk
Bear Wallow
Long Pond
Tobyhanna Road 2
Dingman's Turnpike
Lost Lakes - Lake 3
Brady's Lake - 7 Mile Road
Maple Run
Whitaker Farm Road
Bear Swamp - Nest
Lost Lakes - Swamp Alley
Lost Lakes - Lake 1
Ice Lake
Beaver Run
Shohola Swamp

Status
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Unoccupied
Unoccupied
Unoccupied
94

Species Richness
23
21
19
19
19
19
19
17
16
16
16
15
15
15
15
15
14
14
14
14
13
13
12
12
12
11
11
11
11
11
10
10
8
7
18
14
14

Merry Hill Wet Meadow
Dwarfskill
Brady's Lake - Parking Lot
Grange Road
Tobyhanna Road
Hemlock Way
Hell Hollow 2
Two Mile Run
Lake Road
Hell Hollow
Lake Greeley
Seven Pines
Indian Swamp
Plank Road

Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied

95

14
13
13
13
12
11
11
10
10
9
9
9
6
6

Appendix IV. Shannon diversity Index of plant communities for all field sites.
Site Name
Turner Swamp 2
Whitaker Farm Road 2
Turner Swamp
Grass Lake
Bear Swamp 2
Ice Lake
Painter Swamp
Turner Swamp 3
Cranberry Bog - Boardwalk
Cranberry Bog - Parking Lot 2
Brady's Lake
Caughbaugh Road 2
Bear Swamp - Boardwalk 2
Caughbaugh Road
Tarkill Demo
Lower Lake
Beaver Run
Cranberry Bog - Edge
Fivemile Meadow
Tobyhanna Road
Merry Hill Wet Meadow
Beaver Run 2
Brady's Lake - Parking Lot
Tobyhanna Road 2
Cranberry Bog - Parking Lot
Shohola Swamp
Hobday Swamp
Bear Swamp - Boardwalk
Bear Wallow
Valley Road
Brady's Lake - 7 Mile Road 2
Grange Road
Bear Swamp - Nest
Hell Hollow 2
Dwarfs Kill
Hemlock Way
Lost Lakes - Lake 3
Brady's Lake - 7 Mile Road

Status
Occupied
Occupied
Occupied
Occupied
Occupied
Unoccupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Occupied
Unoccupied
Occupied
Occupied
Unoccupied
Unoccupied
Occupied
Unoccupied
Occupied
Occupied
Unoccupied
Occupied
Occupied
Occupied
Occupied
Occupied
Unoccupied
Occupied
Unoccupied
Unoccupied
Unoccupied
Occupied
Occupied
96

Shannon Index
2.76
2.72
2.70
2.69
2.66
2.59
2.58
2.53
2.50
2.49
2.49
2.39
2.39
2.38
2.38
2.35
2.35
2.34
2.34
2.31
2.30
2.29
2.28
2.24
2.22
2.22
2.21
2.20
2.16
2.15
2.13
2.11
2.11
2.11
2.07
2.07
2.07
2.05

Whitaker Farm Road
Lake Road
Dingman's Turnpike
Hell Hollow
Long Pond
Maple Run
Lost Lakes - Swamp Alley
Lake Greeley
Two Mile Run
Lost Lakes - Lake 1
Seven Pines
Indian Swamp
Plank Road

Occupied
Unoccupied
Occupied
Unoccupied
Occupied
Occupied
Occupied
Unoccupied
Unoccupied
Occupied
Unoccupied
Unoccupied
Unoccupied

97

2.00
1.99
1.99
1.94
1.93
1.91
1.87
1.81
1.79
1.78
1.69
1.67
1.62

Appendix V. Frequency of plant species found at occupied and unoccupied sites.
Common Name Latin Name
American Elm
Arroweed
Aster
Bedstraw
Beech
Bittercress
Black Birch
Black Cherry
Black Spruce
Black Walnut
Black Willow
Blue Spruce
Broadleaf Cattail
Bugleweed
Buttonbush
Calla Lily
Canada Maylily
Canadian Bunchberry
Cinnamon Fern
Common Blue Violet
Common Boneset
Dewberry
Eastern Hemlock
Enchanter’s Nightshade
European Elderberry
False Hellebore
Field Horsetail
Fox Grape
Golden Club
Golden Saxifrage
Grass
Gray Birch
Green Ash
Hay-scented Fern
High-bush Blueberry
Jack-in-the-Pulpit

Ulmus americana
Pluchea sericea
Asteraceae
Gallium sp.
Fagus grandifolia
Cardamine hirsuta
Betula lenta
Prunus serotina
Picea mariana
Juglans nigra
Salix nigra
Picea pungens
Typha latifolia
Lycopus americanus
Cephalanthus occidentalis
Zantedeschia aethiopica
Maianthemum canadense
Cornus canadensis
Osmundastrum
cinnamomeum
Viola sororia
Eupatorium perfoliatum
Rubus pubescens
Tsuga canadensis
Circaea lutetiana
Sambucus nigra
Veratrum californicum
Equisetum arvense
Vitis labrusca
Orontium aquaticum
Chrysosplenium
americanum
Poaceae sp.
Betula populifolia
Fraxinus pennsylvanica
Dennstaedtia punctilobula
Vaccinium corymbosum
Arisaema triphyllum
98

Occupied
Frequency
0.06
0.26
0.06
0.09
0.21
0.09
0.06
NA
0.21
0.03
NA
0.03
0.03
0.62
NA
0.09
0.21
0.03
0.76

Unoccupied
Frequency
NA
NA
0.18
NA
0.24
NA
0.12
0.06
0.06
NA
0.06
NA
NA
0.12
0.06
NA
NA
NA
0.41

0.06
NA
0.03
0.62
0.03
0.03
NA
0.06
0.06
0.03
0.03

0.06
0.06
0.06
0.47
0.06
0.06
0.12
NA
NA
NA
NA

0.18
0.06
0.15
0.09
0.79
0.15

0.24
NA
0.12
0.53
0.76
0.06

Japanese Barberry
Japanese Stiltgrass
Jewelweed
Marginal Wood Fern
Marsh Fern
Marsh Marigold
Mountain Holly
Multiflora Rose
Musclewood
New York Fern
Northern Blue flag
Poison Ivy
Purple Pitcher Plant
Ragweed
Red Maple
Red Oak
Rhododendron
Royal Fern
Sedge
Sensitive Fern
Serviceberry
Shagbark Hickory
Sheep Laurel
Sideflowering Skullcap
Skunk Cabbage
Slippery Elm
Smooth Alder
Southern Arrowwood
Sphagnum
Spicebush
St. John’s Marshwort
Starflower
Swamp Azalea
Swamp Candle
Sycamore
Tall Meadow Rue
Tamarack
Threeleaf Goldenthread
Threeway Sedge
Tulip
Tupelo

Berberis thunbergii
Microstegium vimineum
Impatiens capensis
Dryopteris marginalis
Thelypteris palustris
Caltha palustris
Ilex mucronate
Rosa multiflora
Carpinus caroliniana
Thelypteris noveboracensis
Iris versicolor
Toxicodendron radicans
Sarracenia purpurea
Ambrosia artemisiifolia
Acer rubrum
Quercus rubra
Rhododendron maximum
Osmunda regalis
Carex sp.
Onoclea sensibilis
Amelanchier arborea
Carya ovata
Kalmia angustifolia
Scutellaria lateriflora
Symplocarpus foetidus
Ulmus rubra
Alnus serrulata
Viburnum dentatum
Sphagnum sp.
Lindera benzoin
Hypericum perforatum
Trientalis borealis
Rhododendron viscosum
Lysimachia terrestris
Platanus occidentalis
Thalictrum dasycarpum
Larix larcinia
Coptis trifolia
Dulichium arundinaceum
Lirodendron tulipifera
Nyssa sylvatica
99

0.03
0.03
0.50
0.03
0.35
0.09
0.06
NA
0.06
0.03
0.21
0.09
0.06
NA
1.00
0.03
0.41
0.06
0.68
0.59
NA
0.03
0.06
0.03
0.15
0.03
0.18
0.03
0.85
0.26
0.12
0.12
0.03
0.24
0.03
NA
0.03
0.32
0.06
0.09
0.15

0.12
0.18
0.47
NA
0.06
0.06
0.06
0.12
0.06
NA
0.06
0.06
NA
0.06
0.94
NA
0.24
0.06
0.76
0.35
0.06
0.12
NA
NA
0.06
NA
0.12
NA
0.76
NA
NA
0.12
0.06
0.06
NA
0.06
NA
NA
NA
0.12
0.29

Virginia Chainfern
Virginia Creeper
Virginia Strawberry
Water Pennywort
White Ash
White Birch
White Meadowsweet
White Oak
White Pine
Wineberry
Winterberry
Witch Hazel
Wood Nettle
Wood Sorrel
Yellow Birch
Other

Woodwardia virginica
Parthenocissus quinquefolia
Fragaria virginiana
Hydrocotyle ranunculoides
Fraxinus americana
Betula papyrifera
Spiraea alba
Quercus alba
Pinus strobus
Rubus phoenicolasius
Ilex verticillata
Hamamelis virginiana
Laportea candensis
Oxalis stricta
Betula alleghaniensis

100

NA
0.15
0.03
0.03
0.06
NA
0.06
0.06
0.12
0.15
0.62
0.12
0.03
0.03
0.47
0.15

0.06
0.06
0.06
NA
NA
0.06
0.18
0.06
0.29
0.18
0.18
0.06
NA
0.06
0.35
0.35

Appendix VI. SIMPER results showing the contribution of each species to the overall
Bray-Curtis dissimilarity between occupied and unoccupied sites with all plants
included (asterisk indicates significance).
Species Latin Name
High-bush Blueberry
Rhododendron
Red Maple
Sphagnum
Sedge
Eastern Hemlock
Winterberry
Yellow Birch
Spicebush
Smooth Alder
Beech
Cinnamon Fern
Jewelweed
Sensitive Fern
Hay-scented Fern
White Pine
Grass
Tupelo
Green Ash
Black Birch
Japanese Barberry
Bugleweed
Japanese Stiltgrass
Black Spruce
White Meadowsweet
Other
Swamp Candle
Swamp Azalea
Aster
Arroweed
Wineberry
Mountain Holly
Serviceberry

Vaccinium corymbosum
Rhododendron maximum
Acer rubrum
Sphagnum sp.
Carex sp.
Tsuga canadensis
Ilex verticillata
Betula alleghaniensis
Lindera benzoin
Alnus serrulata
Fagus grandifolia
Osmundastrum
cinnamomeum
Impatiens capensis
Onoclea sensibilis
Dennstaedtia punctilobula
Pinus strobus
Poaceae sp.
Nyssa sylvatica
Fraxinus pennsylvanica
Betula lenta
Berberis thunbergii
Lycopus americanus
Microstegium vimineum
Picea mariana
Spiraea alba
Lysimachia terrestris
Rhododendron viscosum
Asteraceae
Pluchea sericea
Rubus phoenicolasius
Ilex mucronate
Amelanchier arborea
101

Cumulative
Contribution
0.11
0.19
0.26
0.31
0.36
0.41
0.46
0.50
0.53
0.56
0.58
0.61

pvalue
0.02*
0.43
0.08
0.28
0.06
0.76
0.14
0.79
1.00
0.62
0.24
0.30

0.63
0.65
0.67
0.69
0.70
0.72
0.73
0.75
0.76
0.77
0.78
0.80
0.81
0.82
0.83
0.83
0.84
0.85
0.86
0.86
0.87

0.12
0.78
0.001*
0.08
0.19
0.06
0.83
0.19
0.10
0.31
0.36
0.82
0.13
0.21
0.31
0.33
0.05*
1.00
0.35
0.71
0.34

Virginia Chainfern Woodwardia virginica
Marsh Fern Thelypteris palustris
Virginia Creeper Parthenocissus
quinquefolia
Witch Hazel Hamamelis virginiana
Threeleaf Goldenthread Coptis trifolia
Poison Ivy Toxicodendron radicans
Skunk Cabbage Symplocarpus foetidus
Shagbark Hickory Carya ovata
Royal Fern Osmunda regalis
Northern Blue Flag Iris versicolor
Tulip Lirodendron tulipifera
St. John's Marshwart Hypericum perforatum
Threeway Sedge Dulichium arundinaceum
Fox Grape Vitis labrusca
Canada Maylily Maianthemum canadense
European Elderberry Sambucus nigra
Dewberry Rubus pubescens
Tamarack Larix larcinia
Multiflora Rose Rosa multiflora
Starflower Trientalis borealis
Jack-in-the-Pulpit Arisaema triphyllum
Calla Lily Zantedeschia aethiopica
White Ash Fraxinus americana
False Hellebore Veratrum californicum
Bittercress Cardamine hirsuta
White Oak Quercus alba
Marsh Marigold Caltha palustris
American Elm Ulmus americana
Enchanter's Nightshade Circaea lutetiana
White Birch Betula papyrifera
Black Cherry Prunus serotina
Black Willow Salix nigra
Buttonbush Cephalanthus occidentalis
Bedstraw Gallium sp.
Ragweed Ambrosia artemisiifolia
New York Fern Thelypteris noveboracensis
Common Blue Violet Viola sororia
Gray Birch Betula populifolia
102

0.87
0.88
0.89

0.34
0.94
0.69

0.89
0.90
0.90
0.91
0.91
0.91
0.92
0.92
0.92
0.93
0.93
0.94
0.94
0.94
0.95
0.95
0.95
0.95
0.96
0.96
0.96
0.96
0.97
0.97
0.97
0.97
0.97
0.97
0.98
0.98
0.98
0.98
0.98
0.98
0.98

0.89
0.89
0.35
0.71
0.10
0.33
0.67
0.13
1.00
1.00
1.00
1.00
0.58
0.57
1.00
0.12
0.56
0.92
1.00
1.00
0.10
1.00
0.41
0.80
1.00
0.34
0.35
0.35
0.35
0.34
1.00
0.31
1.00
0.72
1.00

Slippery Elm
Marginal Wood Fern
Virginia Strawberry
Wood Sorrel
Musclewood
Sheep Laurel
Field Horsetail
Southern Arrowwood
Purple Pitcher Plant
Golden Club
Water Pennywort
Golden Saxifrage
Common Boneset
Tall Meadow Rue
Sideflowering Skullcap
Blue Spruce
Sycamore
Black Walnut
Red Oak
Canadian Bunchberry
Broadleaf Cattail
Wood Nettle

Ulmus rubra
Dryopteris marginalis
Fragaria virginiana
Oxalis stricta
Carpinus caroliniana
Kalmia angustifolia
Equisetum arvense
Viburnum dentatum
Sarracenia purpurea
Orontium aquaticum
Hydrocotyle ranunculoides
Chrysosplenium
americanum
Eupatorium perfoliatum
Thalictrum dasycarpum
Scutellaria lateriflora
Picea pungens
Platanus occidentalis
Juglans nigra
Quercus rubra
Cornus canadensis
Typha latifolia
Laportea candensis

103

0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
1.00

1.00
1.00
0.58
0.58
0.73
1.00
1.00
1.00
1.00
1.00
1.00
1.00

1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00

0.34
0.33
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00

Appendix VII. SIMPER results showing the contribution of each species to the overall
Bray-Curtis dissimilarity between occupied and unoccupied sites including only
herbaceous vegetation (asterisk indicates significance).
Species Latin Name
Sphagnum Sphagnum sp.
Sedge Carex sp.
Cinnamon Fern Osmundastrum
cinnamomeum
Jewelweed Impatiens capensis
Sensitive Fern Onoclea sensibilis
Hay-scented Fern Dennstaedtia punctilobula
Grass Poaceae sp.
Bugleweed Lycopus americanus
Japanese Stiltgrass Microstegium vimineum
Other
Swamp Candle Lysimachia terrestris
White Meadowsweet Spiraea alba
Aster Asteraceae
Arroweed Pluchea sericea
Wineberry Rubus phoenicolasius
Virginia Chainfern Woodwardia virginica
Marsh Fern Thelypteris palustris
Virginia Creeper Parthenocissus quinquefolia
Threeleaf Goldenthread Coptis trifolia
Poison Ivy Toxicodendron radicans
Skunk Cabbage Symplocarpus foetidus
Royal Fern Osmunda regalis
Northern Blue Flag Iris versicolor
St. John's Marshwart Hypericum perforatum
Threeway Sedge Dulichium arundinaceum
Canada Maylily Maianthemum canadense
Dewberry Rubus pubescens
Starflower Trientalis borealis
Jack-in-the-Pulpit Arisaema triphyllum
Calla Lily Zantedeschia aethiopica
False Hellebore Veratrum californicum
Bittercress Cardamine hirsuta
Marsh Marigold Caltha palustris
104

Cumulative
Contribution
0.15
0.28
0.35

pvalue
0.24
0.08
0.33

0.40
0.46
0.51
0.56
0.59
0.63
0.65
0.68
0.70
0.73
0.75
0.76
0.78
0.80
0.81
0.83
0.84
0.85
0.86
0.87
0.88
0.89
0.90
0.91
0.92
0.93
0.93
0.94
0.94
0.95

0.13
0.82
0.001*
0.15
0.34
0.34
0.19
0.32
0.11
0.03*
1.00
0.39
0.06
0.96
0.65
0.92
0.34
0.71
0.21
0.65
0.97
0.94
1.00
0.21
0.55
0.90
0.96
0.02*
0.97
0.80

Enchanter's Nightshade
Ragweed
Bedstraw
New York Fern
Common Blue Violet
Virginia Strawberry
Wood Sorrel
Marginal Wood Fern
Field Horsetail
Common Boneset
Tall Meadow Rue
Purple Pitcher Plant
Golden Club
Water Pennywort
Golden Saxifrage
Sideflowering Skullcap
Canadian Bunchberry
Broadleaf Cattail
Wood Nettle

Circaea lutetiana
Ambrosia artemisiifolia
Gallium sp.
Thelypteris noveboracensis
Viola sororia
Fragaria virginiana
Oxalis stricta
Dryopteris marginalis
Equisetum arvense
Eupatorium perfoliatum
Thalictrum dasycarpum
Sarracenia purpurea
Orontium aquaticum
Hydrocotyle ranunculoides
Chrysosplenium
americanum
Scutellaria lateriflora
Cornus canadensis
Typha latifolia
Laportea candensis

105

0.96
0.96
0.96
0.97
0.97
0.97
0.98
0.98
0.98
0.98
0.99
0.99
0.99
0.99
1.00

0.16
0.06
0.95
0.92
0.64
0.56
0.57
1.00
0.94
0.06
0.07
0.94
0.92
0.91
0.92

1.00
1.00
1.00
1.00

1.00
0.92
0.93
0.92

Appendix VIII. Warton et al. (2012) results for all plant species (asterisk indicates
significance).
Species
American Elm
Beech
Black Birch
Black Cherry
Black Spruce
Black Walnut
Black Willow
Blue Spruce
Eastern Hemlock
Gray Birch
Green Ash
Musclewood
Red Maple
Red Oak
Shagbark Hickory
Slippery Elm
Smooth Alder
Sycamore
Tamarack
Tulip
Tupelo
White Ash
White Birch
White Oak
White Pine
Yellow Birch
Buttonbush
European Elderberry
Fox Grape
High-bush Blueberry
Japanese Barberry
Mountain Holly
Multiflora Rose
Rhododendron
Serviceberry

Scientific Name
Ulmus americana
Fagus grandifolia
Betula lenta
Prunus serotina
Picea mariana
Juglans nigra
Salix nigra
Picea pungens
Tsuga canadensis
Betula populifolia
Fraxinus pennsylvanica
Carpinus caroliniana
Acer rubrum
Quercus rubra
Carya ovata
Ulmus rubra
Alnus serrulata
Platanus occidentalis
Larix larcinia
Lirodendron tulipifera
Nyssa sylvatica
Fraxinus americana
Betula papyrifera
Quercus alba
Pinus strobus
Betula alleghaniensis
Cephalanthus occidentalis
Sambucus nigra
Vitis labrusca
Vaccinium corymbosum
Berberis thunbergii
Ilex mucronate
Rosa multiflora
Rhododendron maximum
Amelanchier arborea
106

Group
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Tree
Shrub
Shrub
Shrub
Shrub
Shrub
Shrub
Shrub
Shrub
Shrub

p-value
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.99
1
1
1
0.99
1
1
1
1
0.95
0.57
1
1
1
0.95

Sheep Laurel
Southern Arrowwood
Spicebush
Swamp Azalea
Winterberry
Witch Hazel
Arrowweed
Aster
Bedstraw
Bittercress
Broadleaf Cattail
Bugleweed
Calla Lily
Canada Maylily
Canadian Bunchberry
Cinnamon Fern
Common Blue Violet
Common Boneset
Dewberry
Enchanter s Nightshade
False Hellebore
Field Horsetail
Golden Club
Golden Saxifrage
Grass
Hay-scented Fern
Jack-in-the-Pulpit
Japanese Stiltgrass
Jewelweed
Marginal Wood Fern
Marsh Fern
Marsh Marigold
New York Fern
Northern Blue Flag
Poison Ivy
Purple Pitcher Plant
Ragweed
Royal Fern

Kalmia angustifolia
Viburnum dentatum
Lindera benzoin
Rhododendron viscosum
Ilex verticillata
Hamamelis virginiana
Pluchea sericea
Asteraceae
Gallium sp.
Cardamine hirsuta
Typha latifolia
Lycopus americanus
Zantedeschia aethiopica
Maianthemum canadense
Cornus canadensis
Osmundastrum
cinnamomeum
Viola sororia
Eupatorium perfoliatum
Rubus pubescens
Circaea lutetiana
Veratrum californicum
Equisetum arvense
Orontium aquaticum
Chrysosplenium americanum
Poaceae sp.
Dennstaedtia punctilobula
Arisaema triphyllum
Microstegium vimineum
Impatiens capensis
Dryopteris marginalis
Thelypteris palustris
Caltha palustris
Thelypteris noveboracensis
Iris versicolor
Toxicodendron radicans
Sarracenia purpurea
Ambrosia artemisiifolia
Osmunda regalis
107

Shrub
Shrub
Shrub
Shrub
Shrub
Shrub
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous

1
1
0.04*
0.99
0.17
1
0.95
0.99
1
1
1
1
1
1
1
1

Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous

1
1
1
1
1
1
1
1
1
0.39
1
1
1
1
1
1
1
1
1
1
1
1

Sedge
Sensitive Fern
Sideflowering Skullcap
Skunk Cabbage
Sphagnum
St. John's Marshwart
Starflower
Swamp Candle
Tall Meadow Rue
Threeleaf Goldenthread
Threeway Sedge
Virginia Chainfern
Virginia Creeper
Virginia Strawberry
Water Pennywort
White Meadowsweet
Wineberry
Wood Nettle
Wood Sorrel
Other

Carex sp.
Onoclea sensibilis
Scutellaria lateriflora
Symplocarpus foetidus
Sphagnum sp.
Hypericum perforatum
Trientalis borealis
Lysimachia terrestris
Thalictrum dasycarpum
Coptis trifolia
Dulichium arundinaceum
Woodwardia virginica
Parthenocissus quinquefolia
Fragaria virginiana
Hydrocotyle ranunculoides
Spiraea alba
Rubus phoenicolasius
Laportea candensis
Oxalis stricta

108

Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous
Herbaceous

1
1
1
1
1
1
1
1
1
0.99
1
0.90
1
1
1
1
1
1
1
1

Appendix IX. Warton et al. (2012) results with only shrub species (asterisk indicates
significance).
Species Scientific Name
p-value
Buttonbush Cephalanthus
0.98
occidentalis
European Elderberry Sambucus nigra
0.98
Fox Grape Vitis labrusca
0.85
High-bush Blueberry Vaccinium corymbosum
0.51
Japanese Barberry Berberis thunbergii
0.34
Mountain Holly Ilex mucronate
0.98
Multiflora Rose Rosa multiflora
0.79
Rhododendron Rhododendron
0.98
maximum
Serviceberry Amelanchier arborea
0.51
Sheep Laurel Kalmia angustifolia
0.98
Southern Arrowwood Viburnum dentatum
0.98
Spicebush Lindera benzoin
0.02*
Swamp Azalea Rhododendron viscosum
0.67
Winterberry Ilex verticillata
0.05
Witch Hazel Hamamelis virginiana
0.85

109

Appendix X. Warton et al. (2012) results with only herbaceous species (asterisk indicates
significance).
Species
Arrowweed
Aster
Bedstraw
Bittercress
Broadleaf Cattail
Bugleweed
Calla Lily
Canada Maylily
Canadian Bunchberry
Cinnamon Fern
Common Blue Violet
Common Boneset
Dewberry
Enchanter s Nightshade
False Hellebore
Field Horsetail
Golden Club
Golden Saxifrage
Grass
Hay-scented Fern
Jack-in-the-Pulpit
Japanese Stiltgrass
Jewelweed
Marginal Wood Fern
Marsh Fern
Marsh Marigold
New York Fern
Northern Blue Flag
Poison Ivy
Purple Pitcher Plant
Ragweed
Royal Fern
Sedge
Sensitive Fern

Scientific Name
Pluchea sericea
Asteraceae
Gallium sp.
Cardamine hirsuta
Typha latifolia
Lycopus americanus
Zantedeschia aethiopica
Maianthemum canadense
Cornus canadensis
Osmundastrum
cinnamomeum
Viola sororia
Eupatorium perfoliatum
Rubus pubescens
Circaea lutetiana
Veratrum californicum
Equisetum arvense
Orontium aquaticum
Chrysosplenium
americanum
Poaceae sp.
Dennstaedtia punctilobula
Arisaema triphyllum
Microstegium vimineum
Impatiens capensis
Dryopteris marginalis
Thelypteris palustris
Caltha palustris
Thelypteris noveboracensis
Iris versicolor
Toxicodendron radicans
Sarracenia purpurea
Ambrosia artemisiifolia
Osmunda regalis
Carex sp.
Onoclea sensibilis
110

p-value
0.65
0.73
1
1
1
0.90
0.99
0.95
1
0.84
1
1
1
1
0.97
1
1
1
1
0.09
1
1
1
1
0.95
1
1
1
1
1
1
1
0.90
0.98

Sideflowering Skullcap
Skunk Cabbage
Sphagnum
St. John's Marshwart
Starflower
Swamp Candle
Tall Meadow Rue
Threeleaf Goldenthread
Threeway Sedge
Virginia Chainfern
Virginia Creeper
Virginia Strawberry
Water Pennywort
White Meadowsweet
Wineberry
Wood Nettle
Wood Sorrel
Other

Scutellaria lateriflora
Symplocarpus foetidus
Sphagnum sp.
Hypericum perforatum
Trientalis borealis
Lysimachia terrestris
Thalictrum dasycarpum
Coptis trifolia
Dulichium arundinaceum
Woodwardia virginica
Parthenocissus quinquefolia
Fragaria virginiana
Hydrocotyle ranunculoides
Spiraea alba
Rubus phoenicolasius
Laportea candensis
Oxalis stricta

111

1
1
1
0.94
1
0.99
1
0.76
0.94
0.65
1
1
1
0.84
1
1
1
1

Appendix XI. Avian species abundance and frequency found across all sites in 2017
(only occupied).
Common Name
American Crow
American Redstart
American Robin
Black-and-white Warbler
Black-billed Cuckoo
Black-capped Chickadee
Black-throated Green Warbler
Blue Jay
Blue-headed Vireo
Canada Warbler
Carolina Wren
Cedar Waxwing
Chestnut-sided Warbler
Chipping Sparrow
Common Yellowthroat
Downy Woodpecker
Eastern Phoebe
Eastern Towhee
Eastern Wood-Pewee
Gray Catbird
Great-crested Flycatcher
Louisiana Waterthrush
Marsh Wren
Mourning Dove
Nashville Warbler
Northern Cardinal
Northern Flicker
Northern Harrier
Northern Parula
Northern Waterthrush
Ovenbird
Pileated Woodpecker
Prothonotary Warbler
Red-bellied Woodpecker
Red-eyed Vireo
Rose-breasted Grosbeak
Ruffed Grouse

Latin Name
Total Frequency
Corvus brachyrhynchos
8
0.54
Setophaga ruticilla
6
0.15
Turdus migratorius
2
0.15
Mniotilta varia
16
0.77
Coccyzus erythropthalmus
1
0.08
Poecile atricapillus
11
0.31
Setophaga virens
2
0.15
Cyanocitta cristata
35
0.77
Vireo solitarius
9
0.46
Cardellina canadensis
7
0.38
Thryothorus ludovicianus
1
0.08
Bombycilla cedrorum
5
0.08
Setophaga pensylvanica
6
0.23
Spizella passerina
2
0.15
Geothlypis trichas
20
0.69
Dryobates pubescens
6
0.46
Sayornis phoebe
5
0.23
Pipilo erythrophthalmus
8
0.31
Contopus virens
1
0.08
Dumetella carolinensis
28
0.92
Myiarchus crinitus
2
0.15
Parkesia motacilla
1
0.08
Cistothorus palustris
1
0.08
Zenaida macroura
2
0.15
Oreothlypis ruficapilla
6
0.31
Cardinalis cardinalis
5
0.23
Colaptes auratus
6
0.31
Circus cyaneus
1
0.08
Setophaga americana
6
0.31
Parkesia noveboracensis
20
0.69
Seiurus aurocapilla
39
0.85
Dryocopus pileatus
2
0.15
Protonotaria citrea
1
0.08
Melanerpes carolinus
2
0.08
Vireo olivaceus
23
0.92
Pheucticus ludovicianus
2
0.15
Bonasa umbellus
1
0.08
112

Scarlet Tanager
Song Sparrow
Tufted Titmouse
Veery
White-breasted Nuthatch
Winter Wren
Wood Thrush
Worm-eating Warbler
Yellow-bellied Sapsucker
Yellow-billed Cuckoo
Yellow-rumped Warbler
Yellow-throated Vireo

Piranga olivacea
Melospiza melodia
Baeolophus bicolor
Catharus fuscescens
Sitta carolinensis
Troglodytes hiemalis
Hylocichla mustelina
Helmitheros vermivorum
Sphyrapicus varius
Coccyzus americanus
Setophaga coronata
Vireo flavifrons

113

3
2
10
50
1
2
30
6
7
1
4
2

0.23
0.15
0.46
1.00
0.08
0.08
0.77
0.23
0.31
0.08
0.23
0.15

Appendix XII. 2018 Avian species found across occupied and unoccupied sites.
Common Name
Acadian Flycatcher
Alder Flycatcher
American Crow
American Redstart
American Robin
Baltimore Oriole
Black-and-white Warbler
Blackburnian Warbler
Black-capped Chickadee
Black-throated Blue Warbler
Black-throated Green Warbler
Blue Jay
Blue-gray Gnatcatcher
Blue-winged Warbler
Broad-winged Hawk
Brown-headed Cowbird
Canada Warbler
Cedar Waxwing
Chestnut-sided Warbler
Chipping Sparrow
Common Grackle
Common Raven
Common Yellowthroat
Dark-eyed Junco
Downy Woodpecker
Eastern Kingbird
Eastern Phoebe
Eastern Towhee
Eastern Wood-Pewee
Fish Crow
Golden-winged Warbler
Gray Catbird
Great Crested Flycatcher

Latin Name
Occupied Unoccupied
Empidonax virescens
3
0
Empidonax alnorum
10
8
Corvus
15
14
brachyrhynchos
Setophaga ruticilla
22
21
Turdus migratorius
10
9
Icterus galbula
0
1
Mniotilta varia
54
18
Dendroica fusca
24
6
Poecile atricapillus
40
21
Setophaga
10
5
caerulescens
Setophaga virens
11
9
Cyanocitta cristata
44
17
Polioptila caerulea
3
2
Vermivora cyanoptera
1
0
Buteo platypterus
1
2
Molothrus ater
3
4
Cardellina canadensis
46
6
Bombycilla cedrorum
9
13
Setophaga
24
16
pensylvanica
Spizella passerina
0
2
Quiscalus quiscula
3
0
Corvus corax
1
0
Geothlypis trichas
39
39
Junco hyemalis
1
2
Dryobates pubescens
1
1
Tyrannus tyrannus
0
2
Sayornis phoebe
0
3
Pipilo
27
16
erythrophthalmus
Contopus virens
11
2
Corbus ossifragus
1
1
Vermivora
1
3
chrysoptera
Dumetella
48
33
carolinensis
Myiarchus crinitus
5
7
114

Hairy Woodpecker Leuconotopicus
villosus
Hermit Thrush Catharus guttatus
Hooded Warbler Setophaga citrina
Least Flycatcher Empidonax minimus
Louisiana Waterthrush Parkesia motacilla
Magnolia Warbler Setophaga magnolia
Mourning Dove Zenaida macroura
Nashville Warbler Oreothlypis
ruficapilla
Northern Cardinal Cardinalis cardinalis
Northern Flicker Colaptes auratus
Northern Parula Setophaga americana
Northern Waterthrush Parkesia
noveboracensis
Ovenbird Seiurus aurocapilla
Pileated Woodpecker Dryocopus pileatus
Red-bellied Woodpecker Melanerpes carolinus
Red-eyed Vireo Vireo olivaceus
Red-shouldered Hawk Buteo lineatus
Red-winged Blackbird Agelaius phoeniceus
Rose-breasted Grosbeak Pheucticus
ludovicianus
Ruby-throated Hummingbird Archilochus colubris
Scarlet Tanager Piranga olivacea
Song Sparrow Melospiza melodia
Swamp Sparrow Melospiza georgiana
Tree Swallow Tachycineta bicolor
Tufted Titmouse Baeolophus bicolor
Turkey Vulture Cathartes aura
Veery Catharus fuscescens
White-breasted Nuthatch Sitta carolinensis
Wild Turkey Meleagris gallopavo
Wood Duck Aix sponsa
Wood Thrush Hylocichla mustelina
Worm-eating Warbler Helmitheros
vermivorum
Yellow Warbler Setophaga petechia
Yellow-bellied Sapsucker Sphyrapicus varius
Yellow-billed Cuckoo Coccyzus americanus
Yellow-rumped Warbler Setophaga coronate
Yellow-throated Vireo Vireo flavifrons
115

4

1

2
2
3
2
1
6
4

4
2
0
3
1
7
1

8
4
0
51

4
4
1
2

105
7
5
68
2
5
5

62
3
3
56
0
13
3

1
20
6
13
1
11
2
83
12
2
2
16
0

0
15
10
23
1
17
0
33
6
2
2
13
1

7
15
1
7
6

12
5
0
2
0

Appendix XIII. Species richness of the 2017 field sites.
Site Species Richness
Bear Swamp - Nest
23
Hobday Road
23
Cranberry Bog - Boardwalk
16
Cranberry Bog - Edge
16
Lost Lakes - Lake 1
16
Whitaker Road
16
Bear Swamp - Boardwalk
15
Brady's Lake
14
Grass Lake
14
Lost Lakes - Swamp Alley
13
Brady's Lake - 7 Mile Road
12
Cranberry Bog - Parking Lot
12
Bear Swamp
11

116

Appendix XIV. Species richness for occupied and unoccupied sites in 2018.
Site.Name
Long Pond Swamp
Cranberry Bog - Boardwalk
Tarkill Demo
Turner Swamp 3
Bear Wallow
Hobday Road
Valley Road
Whitaker Road 2
Bear Swamp 2
Brady's Lake
Cranberry Bog - Parking Lot 2
Turner Swamp 2
Bear Swamp - Boardwalk 2
Brady's Lake - 7 Mile Road 2
Caughbaugh Road 2
Fivemile Meadow Road
Grass Lake
Painter Swamp
Lost Lakes - Lake 1
Lost Lakes - Swamp Alley
Tobyhanna Road 2
Turner Swamp
Caughbaugh Road
Whitaker Road
Dingman's Turnpike
Lower Lake
Maple Run
Beaver Run 2
Lost Lakes - Lake 3
Brady's Lake - 7 Mile Road
Hemlock Way
Plank Road
Hell Hollow Road 2
Brady's Lake - Parking Lot
Lake Greeley
Merry Hill Wet Meadow
Shohola Creek
Lake Road

Status
Species Richness
Occupied
23
Occupied
22
Occupied
22
Occupied
22
Occupied
20
Occupied
20
Occupied
20
Occupied
19
Occupied
18
Occupied
18
Occupied
18
Occupied
18
Occupied
17
Occupied
17
Occupied
17
Occupied
17
Occupied
17
Occupied
17
Occupied
16
Occupied
16
Occupied
16
Occupied
16
Occupied
15
Occupied
15
Occupied
14
Occupied
14
Occupied
14
Occupied
13
Occupied
10
Occupied
8
Unoccupied
21
Unoccupied
21
Unoccupied
20
Unoccupied
19
Unoccupied
19
Unoccupied
19
Unoccupied
19
Unoccupied
17
117

Beaver Run
Hell Hollow Road
Indian Swamp
Beaver Lake
Dwarfskill
Tobyhanna Road
Seven Pines
Ice Lake
Grange Road
Two Mile Run

Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied
Unoccupied

118

16
16
16
15
15
15
14
13
12
11

Appendix XV. Shannon diversity Index of avian communities for 2018 field sites.
Sites
Long Pond Swamp
Tarkill Demo
Hemlock Way
Turner Swamp 3
Plank Road
Cranberry Bog - Boardwalk
Hobday Road
Bear Wallow
Valley Road
Whitaker Road 2
Lake Greeley
Brady's Lake - Parking Lot
Hell Hollow Road 2
Bear Swamp 2
Merry Hill Wet Meadow
Cranberry Bog - Parking Lot 2
Bear Swamp - Boardwalk 2
Brady's Lake - 7 Mile Road 2
Shohola Creek
Caughbaugh Road 2
Grass Lake
Turner Swamp 2
Painter Swamp
Lake Road
Brady's Lake
Fivemile Meadow Road
Tobyhanna Road 2
Indian Swamp
Lost Lakes - Swamp Alley
Beaver Run
Beaver Lake
Hell Hollow Road
Turner Swamp
Lost Lakes - Lake 1
Tobyhanna Road
Caughbaugh Road
Lower Lake
Dwarfskill

Status
Occupied
Occupied
Unoccupied
Occupied
Unoccupied
Occupied
Occupied
Occupied
Occupied
Occupied
Unoccupied
Unoccupied
Unoccupied
Occupied
Unoccupied
Occupied
Occupied
Occupied
Unoccupied
Occupied
Occupied
Occupied
Occupied
Unoccupied
Occupied
Occupied
Occupied
Unoccupied
Occupied
Unoccupied
Unoccupied
Unoccupied
Occupied
Occupied
Unoccupied
Occupied
Occupied
Unoccupied

119

Shannon Index
2.99
2.95
2.95
2.94
2.93
2.92
2.89
2.87
2.84
2.81
2.80
2.79
2.78
2.78
2.78
2.76
2.75
2.73
2.73
2.72
2.72
2.70
2.70
2.69
2.68
2.68
2.66
2.66
2.65
2.63
2.62
2.62
2.61
2.59
2.55
2.53
2.52
2.50

Dingman's Turnpike
Whitaker Road
Maple Run
Seven Pines
Ice Lake
Beaver Run 2
Grange Road
Lost Lakes - Lake 3
Two Mile Run
Brady's Lake - 7 Mile Road

Occupied
Occupied
Occupied
Unoccupied
Unoccupied
Occupied
Unoccupied
Occupied
Unoccupied
Occupied

120

2.50
2.49
2.47
2.45
2.43
2.43
2.37
2.18
2.16
1.98

Appendix XVI. Frequency of avian species at occupied and unoccupied sites in 2018.
Common Name Latin Name
Acadian Flycatcher
Alder Flycatcher
American Crow
American Redstart
American Robin
Baltimore Oriole
Black-and-white Warbler
Blackburnian Warbler
Black-capped Chickadee
Black-throated Blue Warbler
Black-throated Green Warbler
Blue Jay
Blue-gray Gnatcatcher
Blue-winged Warbler
Broad-winged Hawk
Brown-headed Cowbird
Canada Warbler
Cedar Waxwing
Chestnut-sided Warbler
Chipping Sparrow
Common Grackle
Common Raven
Common Yellowthroat
Dark-eyed Junco
Downy Woodpecker
Eastern Kingbird
Eastern Phoebe
Eastern Towhee
Eastern Wood-Pewee
Fish Crow
Golden-winged Warbler
Gray Catbird
Great Crested Flycatcher
Hairy Woodpecker
Hermit Thrush
Hooded Warbler
Least Flycatcher

Empidonax virescens
Empidonax alnorum
Corvus brachyrhynchos
Setophaga ruticilla
Turdus migratorius
Icterus galbula
Mniotilta varia
Dendroica fusca
Poecile atricapillus
Setophaga caerulescens
Setophaga virens
Cyanocitta cristata
Polioptila caerulea
Vermivora cyanoptera
Buteo platypterus
Molothrus ater
Cardellina canadensis
Bombycilla cedrorum
Setophaga pensylvanica
Spizella passerina
Quiscalus quiscula
Corvus corax
Geothlypis trichas
Junco hyemalis
Dryobates pubescens
Tyrannus tyrannus
Sayornis phoebe
Pipilo erythrophthalmus
Contopus virens
Corbus ossifragus
Vermivora chrysoptera
Dumetella carolinensis
Myiarchus crinitus
Leuconotopicus villosus
Catharus guttatus
Setophaga citrina
Empidonax minimus
121

Occupied Unoccupied
Frequency Frequency
0.07
0.00
0.23
0.28
0.33
0.56
0.40
0.56
0.17
0.22
0.00
0.06
0.90
0.56
0.47
0.17
0.57
0.67
0.17
0.17
0.27
0.17
0.77
0.72
0.10
0.11
0.03
0.00
0.03
0.11
0.13
0.17
0.63
0.17
0.23
0.39
0.43
0.50
0.00
0.06
0.07
0.00
0.03
0.00
0.60
0.72
0.03
0.06
0.03
0.06
0.00
0.11
0.00
0.17
0.57
0.67
0.23
0.11
0.03
0.06
0.03
0.11
0.80
0.83
0.13
0.22
0.13
0.06
0.10
0.11
0.03
0.11
0.03
0.00

Louisiana Waterthrush
Magnolia Warbler
Mourning Dove
Nashville Warbler
Northern Cardinal
Northern Flicker
Northern Parula
Ovenbird
Pileated Woodpecker
Red-bellied Woodpecker
Red-eyed Vireo
Red-shouldered Hawk
Red-winged Blackbird
Rose-breasted Grosbeak
Ruby-throated Hummingbird
Scarlet Tanager
Song Sparrow
Swamp Sparrow
Tree Swallow
Tufted Titmouse
Turkey Vulture
Veery
White-breasted Nuthatch
Wild Turkey
Wood Duck
Wood Thrush
Worm-eating Warbler
Yellow Warbler
Yellow-bellied Sapsucker
Yellow-billed Cuckoo
Yellow-rumped Warbler
Yellow-throated Vireo

Parkesia motacilla
Setophaga magnolia
Zenaida macroura
Oreothlypis ruficapilla
Cardinalis cardinalis
Colaptes auratus
Setophaga americana
Seiurus aurocapilla
Dryocopus pileatus
Melanerpes carolinus
Vireo olivaceus
Buteo lineatus
Agelaius phoeniceus
Pheucticus ludovicianus
Archilochus colubris
Piranga olivacea
Melospiza melodia
Melospiza georgiana
Tachycineta bicolor
Baeolophus bicolor
Cathartes aura
Catharus fuscescens
Sitta carolinensis
Meleagris gallopavo
Aix sponsa
Hylocichla mustelina
Helmitheros vermivorum
Setophaga petechia
Sphyrapicus varius
Coccyzus americanus
Setophaga coronate
Vireo flavifrons

122

0.07
0.07
0.17
0.10
0.20
0.13
0.00
0.97
0.23
0.13
0.93
0.07
0.10
0.10
0.03
0.53
0.13
0.33
0.03
0.23
0.07
1.00
0.27
0.03
0.03
0.53
0.00
0.20
0.27
0.03
0.20
0.17

0.11
0.00
0.33
0.06
0.22
0.17
0.06
0.83
0.17
0.17
1.00
0.00
0.28
0.17
0.00
0.33
0.28
0.50
0.06
0.61
0.00
0.72
0.22
0.11
0.06
0.44
0.06
0.33
0.22
0.00
0.11
0.00

Appendix XVII. Avian SIMPER results showing the contribution of each species to the
overall Bray-Curtis dissimilarity between occupied and unoccupied (asterisk
indicates significance).
Species
Ovenbird
Common Yellowthroat
Veery
Red-eyed Vireo
Canada Warbler
Gray Catbird
Black-capped Chickadee
Black-and-white Warbler
Swamp Sparrow
American Redstart
Blue Jay
Chestnut-sided Warbler
Scarlet Tanager
Tufted Titmouse
Eastern Towhee
Blackburnian Warbler
American Crow
Red-winged Blackbird
Wood Thrush
Cedar Waxwing
American Robin
Yellow Warbler
Black-throated Green Warbler
Song Sparrow
Yellow-bellied Sapsucker
Alder Flycatcher
White-breasted Nuthatch

Latin Name
Seiurus aurocapilla
Geothlypis trichas
Catharus fuscescens
Vireo olivaceus
Cardellina
canadensis
Dumetella
carolinensis
Poecile atricapillus
Mniotilta varia
Melospiza
georgiana
Setophaga ruticilla
Cyanocitta cristata
Setophaga
pensylvanica
Piranga olivacea
Baeolophus bicolor
Pipilo
erythrophthalmus
Dendroica fusca
Corvus
brachyrhynchos
Agelaius phoeniceus
Hylocichla
mustelina
Bombycilla
cedrorum
Turdus migratorius
Setophaga petechia
Setophaga virens
Melospiza melodia
Sphyrapicus varius
Empidonax alnorum
Sitta carolinensis
123

Cumulative
Contribution
0.06
0.11
0.16
0.20

p-value
0.02*
0.04*
0.002*
0.16

0.25

0.06

0.28
0.32
0.36

0.70
0.81
0.01*

0.39
0.42
0.45

0.02*
0.37
0.41

0.48
0.51
0.54

0.52
0.19
0.02*

0.56
0.58

0.93
0.78

0.61
0.63

0.16
0.04*

0.65

0.10

0.67
0.69
0.71
0.73
0.75
0.76
0.78
0.79

0.13
0.23
0.05
0.37
0.07
0.92
0.31
0.64

Black-throated Blue Warbler
Great Crested Flycatcher
Mourning Dove
Eastern Wood-Pewee
Northern Cardinal
Pileated Woodpecker
Northern Flicker
Rose-breasted Grosbeak
Yellow-rumped Warbler
Red-bellied Woodpecker
Brown-headed Cowbird
Hermit Thrush
Louisiana Waterthrush
Golden-winged Warbler
Yellow-throated Vireo
Blue-gray Gnatcatcher
Nashville Warbler
Hooded Warbler
Wild Turkey
Hairy Woodpecker
Eastern Phoebe
Wood Duck
Dark-eyed Junco
Broad-winged Hawk
Eastern Kingbird
Chipping Sparrow
Common Grackle
Least Flycatcher
Acadian Flycatcher
Fish Crow
Downy Woodpecker
Tree Swallow

Setophaga
caerulescens
Myiarchus crinitus
Zenaida macroura
Contopus virens
Cardinalis
cardinalis
Dryocopus pileatus
Colaptes auratus
Pheucticus
ludovicianus
Setophaga coronata
Melanerpes
carolinus
Molothrus ater
Catharus guttatus
Parkesia motacilla
Vermivora
chrysoptera
Vireo flavifrons
Polioptila caerulea
Oreothlypis
ruficapilla
Setophaga citrina
Meleagris gallopavo
Leuconotopicus
villosus
Sayornis phoebe
Aix sponsa
Junco hyemalis
Buteo platypterus
Tyrannus tyrannus
Spizella passerina
Quiscalus quiscula
Empidonax minimus
Empidonax
virescens
Corbus ossifragus
Dryobates
pubescens
Tachycineta bicolor
124

0.81
0.82
0.83
0.84

0.52
0.16
0.16
0.94

0.86
0.86
0.87

0.52
0.68
0.23

0.88
0.89

0.42
0.80

0.90
0.90
0.91
0.92

0.58
0.41
0.27
0.12

0.92
0.93
0.93

0.09
0.97
0.46

0.94
0.94
0.95

0.63
0.25
0.27

0.95
0.95
0.96
0.96
0.97
0.97
0.97
0.97
0.98

0.78
0.03*
0.29
0.25
0.16
0.07
0.24
0.80
0.68

0.98
0.98

0.80
0.25

0.98
0.99

0.48
0.47

Baltimore Oriole
Magnolia Warbler
Turkey Vulture
Red-shouldered Hawk
Worm-eating Warbler
Northern Parula
Common Raven
Blue-winged Warbler
Yellow-billed Cuckoo
Ruby-throated Hummingbird

Icterus galbula
Setophaga magnolia
Cathartes aura
Buteo lineatus
Helmitheros
vermivorum
Setophaga
americana
Corvus corax
Vermivora
cyanoptera
Coccyzus
americanus
Archilochus
colubris

125

0.99
0.99
0.99
0.99

0.16
0.78
0.80
0.81

1.00

0.19

1.00
1.00

0.25
0.64

1.00

0.66

1.00

0.68

1.00

0.67

Appendix XVIII. Avian SIMPER results showing the contribution of each species to the
overall Bray-Curtis dissimilarity between occupied and unoccupied excluding
distant species (asterisk indicates significance).
Species Latin Name
Ovenbird
Veery
Blue Jay
Red-eyed Vireo
Common Yellowthroat
Eastern Towhee
Wood Thrush
American Crow
Red-winged Blackbird
Mourning Dove
Black-capped Chickadee
Tufted Titmouse
Black-throated Blue Warbler
Song Sparrow
Chestnut-sided Warbler
Scarlet Tanager
Swamp Sparrow
Eastern Wood-Pewee
Black-throated Green Warbler
Hermit Thrush
Gray Catbird
Canada Warbler
American Redstart
Pileated Woodpecker
Rose-breasted Grosbeak
Alder Flycatcher
Hooded Warbler
Red-bellied Woodpecker
Yellow Warbler
Turkey Vulture
American Robin
Wood Duck
Wild Turkey
Yellow-bellied Sapsucker

Seiurus aurocapilla
Catharus fuscescens
Cyanocitta cristata
Vireo olivaceus
Geothlypis trichas
Pipilo erythrophthalmus
Hylcichla mustelina
Corbus brachyrhynchos
Agelaius phoeniceus
Zenaida macroura
Poecile atricapillus
Baeolophus bicolor
Setophaga caerulescens
Melospiza melodia
Setophaga pensylvanica
Piranga olivacea
Melospiza georgiana
Contopus virens
Setophaga virens
Catharus guttatus
Dumetella carolinensis
Cardellina canadensis
Setophaga ruticilla
Dryocopus pileatus
Pheucticus ludovicianus
Empidonax alnorum
Setophaga citrina
Melanerpes carolinus
Setophaga petechia
Cathartes aura
Turdus migratorius
Aix sponsa
Meleagris gallopavo
Sphyrapicus varius
126

Cumulative
Contribution
0.11
0.21
0.27
0.32
0.37
0.42
0.47
0.52
0.56
0.59
0.62
0.65
0.67
0.70
0.72
0.75
0.77
0.79
0.81
0.82
0.84
0.85
0.86
0.87
0.88
0.89
0.90
0.91
0.92
0.93
0.94
0.94
0.95
0.96

p-value
0.13
0.44
0.94
0.39
0.07
0.91
0.67
0.09
0.10
0.08
0.87
0.03*
0.03*
0.08
0.65
0.25
0.40
0.80
0.81
0.05*
0.52
0.75
0.27
0.36
0.20
0.97
0.58
0.15
0.63
0.92
0.05
0.07
0.05
0.99

Broad-winged Hawk
Northern Flicker
Northern Cardinal
Black-and-white Warbler
Yellow-billed Cuckoo
Red-shouldered Hawk
Blackburnian Warbler
Great Crested Flycatcher
Least Flycatcher
Nashville Warbler

Buteo platypterus
Colaptes auratus
Cardinalis cardinalis
Mniotilta varia
Coccyzus americanus
Buteo lineatus
Dendroica fusca
Myiarchus crinitus
Empidonax minimus
Oreothlypis ruficapilla

127

0.96
0.97
0.98
0.98
0.98
0.99
0.99
1.00
1.00
1.00

0.05
0.05
0.97
0.98
0.90
0.90
0.07
0.07
0.94
0.96

Appendix XIX. Warton et al. (2012) results for the 2018 occupied and unoccupied sites
(asterisk indicates significance).
Species
Acadian Flycatcher
Alder Flycatcher
American Crow
American Redstart
American Robin
Baltimore Oriole
Black-and-white Warbler
Blackburnian Warbler
Black-capped Chickadee
Black-throated Blue Warbler
Black-throated Green Warbler
Blue Jay
Blue-gray Gnatcatcher
Blue-winged Warbler
Broad-winged Hawk
Brown-headed Cowbird
Canada Warbler
Cedar Waxwing
Chestnut-sided Warbler
Chipping Sparrow
Common Grackle
Common Raven
Common Yellowthroat
Dark-eyed Junco
Downy Woodpecker
Eastern Kingbird
Eastern Phoebe
Eastern Towhee
Eastern Wood-Pewee
Fish Crow
Golden-winged Warbler
Gray Catbird

Latin Name
Empidonax virescens
Empidonax alnorum
Corvus
brachyrhynchos
Setophaga ruticilla
Turdus migratorius
Icterus galbula
Mniotilta varia
Dendroica fusca
Poecile atricapillus
Setophaga
caerulescens
Setophaga virens
Cyanocitta cristata
Polioptila caerulea
Vermivora cyanoptera
Buteo platypterus
Molothrus ater
Cardellina canadensis
Bombycilla cedrorum
Setophaga
pensylvanica
Spizella passerina
Quiscalus quiscula
Corvus corax
Geothlypis trichas
Junco hyemalis
Dryobates pubescens
Tyrannus tyrannus
Sayornis phoebe
Pipilo
erythrophthalmus
Contopus virens
Corbus ossifragus
Vermivora chrysoptera
Dumetella carolinensis
128

p-value
1
1
1
1
1
1
0.25
0.60
1
1
1
0.80
1
1
1
1
0.004*
1
1
1
1
1
1
1
1
0.97
0.57
1
1
1
1
1

Great Crested Flycatcher Myiarchus crinitus
Hairy Woodpecker Leuconotopicus
villosus
Hermit Thrush Catharus guttatus
Hooded Warbler Setophaga citrina
Least Flycatcher Empidonax minimus
Louisiana Waterthrush Parkesia motacilla
Magnolia Warbler Setophaga magnolia
Mourning Dove Zenaida macroura
Nashville Warbler Oreothlypis ruficapilla
Northern Cardinal Cardinalis cardinalis
Northern Flicker Colaptes auratus
Northern Parula Setophaga americana
Ovenbird Seiurus aurocapilla
Pileated Woodpecker Dryocopus pileatus
Red-bellied Woodpecker Melanerpes carolinus
Red-eyed Vireo Vireo olivaceus
Red-shouldered Hawk Buteo lineatus
Red-winged Blackbird Agelaius phoeniceus
Rose-breasted Grosbeak Pheucticus
ludovicianus
Ruby-throated Hummingbird Archilochus colubris
Scarlet Tanager Piranga olivacea
Song Sparrow Melospiza melodia
Swamp Sparrow Melospiza georgiana
Tree Swallow Tachycineta bicolor
Tufted Titmouse Baeolophus bicolor
Turkey Vulture Cathartes aura
Veery Catharus fuscescens
White-breasted Nuthatch Sitta carolinensis
Wild Turkey Meleagris gallopavo
Wood Duck Aix sponsa
Wood Thrush Hylocichla mustelina
Worm-eating Warbler Helmitheros
vermivorum
Yellow Warbler Setophaga petechia
Yellow-bellied Sapsucker Sphyrapicus varius
Yellow-billed Cuckoo Coccyzus americanus
Yellow-rumped Warbler Setophaga coronata
Yellow-throated Vireo Vireo flavifrons
129

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.84
1
0.71
1
0.35
1
1
1
1
1
1
1
1
1
0.66

Appendix XX. Warton et al. (2012) results for the 2018 occupied and unoccupied sites
excluding distant species (asterisk indicates significance).
Species
Alder Flycatcher
American Crow
American Redstart
American Robin
Black-and-white Warbler
Blackburnian Warbler
Black-capped Chickadee
Black-throated Blue Warbler
Black-throated Green Warbler
Blue Jay
Broad-winged Hawk
Canada Warbler
Chestnut-sided Warbler
Common Yellowthroat
Eastern Towhee
Eastern Wood-Pewee
Gray Catbird
Great Crested Flycatcher
Hermit Thrush
Hooded Warbler
Least Flycatcher
Mourning Dove
Nashville Warbler
Northern Cardinal
Northern Flicker
Ovenbird
Pileated Woodpecker
Red-bellied Woodpecker
Red-eyed Vireo
Red-shouldered Hawk
Red-winged Blackbird
Rose-breasted Grosbeak
Scarlet Tanager
Song Sparrow
Swamp Sparrow

Latin Name
Empidonax alnorum
Corbus brachyrhynchos
Setophaga ruticilla
Turdus migratorius
Mniotilta varia
Dendroica fusca
Poecile atricapillus
Setophaga caerulescens
Setophaga virens
Cyanocitta cristata
Buteo platypterus
Cardellina canadensis
Setophaga pensylvanica
Geothlypis trichas
Pipilo erythrophthalmus
Contopus virens
Dumetella carolinensis
Myiarchus crinitus
Catharus guttatus
Setophaga citrina
Empidonax minimus
Zenaida macroura
Oreothlypis ruficapilla
Cardinalis cardinalis
Colaptes auratus
Seiurus aurocapilla
Dryocopus pileatus
Melanerpes carolinus
Vireo olivaceus
Buteo lineatus
Agelaius phoeniceus
Pheucticus ludovicianus
Piranga olivacea
Melospiza melodia
Melospiza georgiana
130

p-value
0.99
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.96
1
1
1
1
1
1
1
1
1
1
1
1
1

Tufted Titmouse
Turkey Vulture
Veery
Wild Turkey
Wood Duck
Wood Thrush
Yellow Warbler
Yellow-bellied Sapsucker
Yellow-billed Cuckoo

Baeolophus bicolor
Cathartes aura
Catharus fuscescens
Meleagris gallopavo
Aix sponsa
Hylcichla mustelina
Setophaga petechia
Sphyrapicus varius
Coccyzus americanus

131

0.93
1
1
1
1
1
1
0.99
1