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Bats of the Boston Harbor Islands
Joshua B. Johnson1,2,* and J. Edward Gates1
Abstract - Insectivorous bats are an integral part of ecosystems because they consume
significant quantities of nocturnal insects. White-nose syndrome is decimating populations
of susceptible bat species in North America; thus, inventorying and monitoring bats are
critical first steps in managing these important populations. We inventoried bat species at
Boston Harbor Islands National Recreation Area (BOHA), MA, from 2010 to 2011. Using
a combination of capture and acoustic methods, we documented 6 bat species, including
Eptesicus fuscus (Big Brown Bat), Lasiurus borealis (Eastern Red Bat), Lasiurus cinereus
(Hoary Bat), Lasionycteris noctivagans (Silver-haired Bat), Myotis lucifugus (Little Brown
Bat), and Myotis septentrionalis (Northern Long-eared Bat). Bats occurred at all inventoried
islands, although most activity of Northern Long-eared Bat, a species Federally listed
as threatened, was documented at a mainland site in Worlds End, near Ice Pond. Although
the full extent of bat use on the islands remains unclear, we provide evidence of bats roosting
and foraging on the islands. During long-term acoustic monitoring at Thompson and
Lovells Islands, we assessed the effects of weather and season on bat activity; the latter
analysis provided evidence of bats migrating through the area in spring and autumn.
Introduction
Much research has focused on the conservation and management of bats
because of their beneficial roles in ecosystems; for example, bats consume a wide
variety of insects, including harmful forest and crop pests (Boyles et al. 2011,
Griffith and Gates 1985). However, some populations have been detrimentally
affected by a variety of factors, including hibernacula and maternity-roost disturbances,
landscape degradation, wind-energy development, and white-nose
syndrome (WNS) (Fenton 2003, Frick et al. 2010, Hein and Schirmacher 2016,
Kunz et al. 2007, O’Shea et al. 2003, Pierson 1998). The latter 2 factors have caused
the deaths of millions of bats (Frick et al. 2010, Hein and Schirmacher 2016).
Wind-energy developments primarily affect migrating tree bats, i.e., Lasionycteris
noctivagans (LeConte) (Silver-haired Bat), Lasiurus borealis (Müller) (Eastern
Red Bat), and Lasiurus cinereus (Beauvois) (Hoary Bat) (Hein and Schirmacher
2016). White-nose syndrome, for which the psychrophilic fungus Pseudogymnoascus
destructans (Blehert and Gargas) Minnis and Lindner has been identified as
the causative agent (Lorch et al. 2011), mostly affects populations of cave-dwelling
bat species, including Eptesicus fuscus (Beauvois) (Big Brown Bat), Myotis leibii
(Audubon and Bachman) (Eastern Small-footed Bat), Myotis lucifugus (LeConte)
(Little Brown Bat), Myotis septentrionalis (Trouessart) (Northern Long-eared Bat),
1University of Maryland Center for Environmental Science, Appalachian Laboratory, 301
Braddock Road, Frostburg, MD 21532. 2Current address - Pennsylvania Game Commission,
2001 Elmerton Avenue, Harrisburg, PA 17110. *Corresponding author - joshujohns@pa.gov.
Manuscript Editor: Joseph Johnson
Research at the Boston Harbor Islands NRA
2019 Northeastern Naturalist 25(Special Issue 9):90–109
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Myotis sodalis (Miller and Allen) (Indiana Bat), and Perimyotis subflavus (Cuvier)
(Tri-colored Bat) (Frick et al. 2010). This syndrome has affected bat species’ distribution,
community composition, and relative abundance across landscapes (Ford et
al. 2011, Francl et al. 2012).
Many bat species of special concern, threatened, or endangered status occur on
federal lands, including those administered by the National Park Service (NPS)
(Johnson and Gates 2007, Johnson et al. 2005, Rodhouse et al. 2016). To implement
informed management decisions regarding bat conservation on NPS lands,
which can serve as contiguous tracts of protected land in otherwise fragmented
landscapes, collecting baseline inventory data is an important and necessary initial
undertaking (Johnson et al. 2008). Although a general assessment of bat-species
composition for a given area can be determined by examining geographic ranges
and historic records, verifying the presence and relative abundance of species
through an inventory process facilitates more informed and accurate management
decisions. Simultaneous use of different survey methods, e.g., capture and acoustic
recordings, can provide a more complete assessment of species composition, and
long-term acoustic monitoring may allow examination of possible weather and seasonal
influences on activity as well as timing of migration in an area (Hayes 1997,
Johnson et al. 2011a, Murray et al. 1999).
The NPS Inventory and Monitoring Program “assists park managers in developing
a broad-based understanding of the status and trends of park resources as
a basis for making decisions and working with other agencies and the public for
the long-term protection of park ecosystems” (Fancy et al. 2009:161). As a part
of this program, we conducted an inventory of bat species in Boston Harbor Islands
National Recreation Area (BOHA), MA, following discovery of WNS in the
region (MDFW 2017, Turner et al. 2011). Although bats are unique among terrestrial
mammals in their ability to move among islands, prior to our inventory, only
anecdotal observations of bats flying over BOHA were available, and none were
identified to species.
Regional bat-community species composition and abundance vary seasonally
because many bat species are migratory (Cryan 2003, Davis and Hitchcock 1965,
Griffin 1945). Seasonal trends in bat activity generally follow a pattern—activity
increases closer to summer in concert with increases in temperature, humidity, and
precipitation, and gradually decreases to a minimum in winter as bats either enter
hibernation or migrate south (Cryan 2003, Hayes 1997). In addition to these seasonal
patterns in activity rates, seasonal patterns in species presence and absence
also occur, with some species occurring in an area only during their spring and
autumn migration. Thus, bat use of BOHA is likely to change throughout the year.
The objectives of our inventory were to: (1) provide baseline information on bat
species and their relative abundance at BOHA, (2) identify seasonal and nightly
activity patterns in long-term acoustic monitoring data, and (3) detect possible migration
events. Based on occurrence in the northeastern US, including the State of
Massachusetts, we hypothesized that Big Brown Bat, Little Brown Bat, Eastern
Red Bat, Silver-haired Bat, Hoary Bat, Northern Long-eared Bat, and Tri-colored
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Bat would occur at BOHA (Kurta 1995, MDFW 2017, Merritt 1987, Whitaker and
Hamilton 1998). We did not envisage finding Eastern Small-footed Bat due to lack
of roosting habitat, i.e., rock outcroppings on the surveyed islands; nor, did we think
that we would detect Indiana Bat, which has not been reported in Massachusetts since
1939 (MDFW 2017). We hypothesized that long-term acoustic monitoring would
detect seasonal patterns in bat activity, i.e., higher activity levels May–September,
with spikes in activity associated with possible migration events, as previously documented
on the Atlantic Coast (Hatch et al. 2013, Johnson et al. 2011a, Miller 1897,
Sjollema et al. 2014). Further, we hypothesized that bat activity would be positively
correlated with temperature and relative humidity and negatively correlated with
wind speed, rainfall, and barometric pressure (Erickson and West 2002, Lacki 1984,
Paige 1995, Parsons et al. 2003, Reynolds 2006, Turbill 2008)
Field-site Description
Boston Harbor Islands National Recreation Area is located in the Seaboard Lowland
section of the New England physiographic province and consists of 34 islands
and peninsulas in Boston Harbor, MA (Fig. 1). Human population in the Boston
Metropolitan Statistical Area was ~4.5 million in 2010. Long-term mean summer
(June–August) temperature in Boston was 21.9 °C, and mean annual precipitation
was 108 cm. Based on our preliminary observations (Gates and Johnson 2009),
information provided by NPS staff, land area, presence of trees, and accessibility,
we selected 4 islands and 1 peninsula for our inventories. Oriented from the northwest
to the southeast, they were Thompson Island, Peddocks Island, Lovells Island,
Grape Island, and Worlds End peninsula (Fig. 1). The islands and peninsula varied
in area (upland and intertidal) from 41 ha to 111 ha and in maximum elevation from
21 m to 43 m (Table 1). Thompson Island was the only island in our inventory that
had fresh water (less than 0.1-ha patches of wetlands); however, standing water existed
only during spring months, and vegetation growing in the wetlands likely prevented
bats from using them as freshwater sources. There was a ~0.2-ha freshwater pond
(Ice Pond) at Worlds End peninsula that was a potential water source for bats.
Methods
We employed mist nets and a combination of active and passive acoustic-monitoring
to inventory the bat community at BOHA.
Mist netting
We conducted mist-net surveys in July and August 2010. To capture bats, we
used 50-denier, 2-ply, 38-mm–mesh mist-nets (Avinet, Dryden, NY) measuring 2.6
m high and 6 m, 9 m, or 12 m long. We erected mist nets over hiking trails and access
roads. The number of mist-net locations depended on size of islands, presence
of trees, and logistical constraints. We used 1-tier and 3-tier mist-net arrangements.
A 3-tier mist-net arrangement consisted of 3 mist-nets stacked vertically
(7.8 m total height) and suspended between a rope and pulley sy stem on two 10-m
telescoping poles. We typically deployed mist nets for ~5 h following sunset. No
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bat surveys were conducted during periods of heavy rain, high wind (≥20 kph), or
cold temperatures (less than 10 °C). We determined the species of each captured bat (Menzel
et al. 2002), and recorded the weight, forearm length, sex, age, and reproductive
condition of all specimens before release. We measured weight (g) and forearm
Figure 1. Map of BOHA showing Thompson, Peddocks, Grape, and Lovells Islands and
Worlds End peninsula (Image source: Tiner et al. 2003).
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length (nearest 0.5 mm) with a spring-scale (Pesola AG, Baar, Switzerland) and
bird-wing rule (Avinet, Dryden, NY), respectively. We determined age, i.e., adult
or juvenile, by examining the level of epiphyseal–diaphyseal fusion in finger bones
(Kunz and Anthony 1982). To determine the reproductive condition of female bats,
we palpated the abdomen and inspected the mammary glands (Racey 1988). We
marked captured bats on the forearm with a non-toxic marker (Newell Brands, IL)
to identify any recaptures. Bat-capture and handling protocols were approved by
the Institutional Animal Care and Use Committee of the University of Maryland
Center for Environmental Science and followed the guidelines of the American
Society of Mammalogists (Gannon et al. 2007). We followed US Fish and Wildlife
Service (USFWS) disinfection protocols to decontaminate mist-netting equipment
and bat-measuring and handling equipment to avoid potential spread of WNS between
captured bats (USFWS 2009).
Active acoustic-monitoring
We conducted active acoustic-monitoring in July and August 2010. We used
Anabat II (Titley Electronics, Ballina, Australia) broadband, frequency-division bat
detectors linked to compact flash-storage zero-crossing analysis interface modules
(ZCAIM) to actively monitor for bat activity in various cover types, including Ice
Pond, forests, and fields. The number of sample locations depended on island size
and variety of cover types, i.e., larger islands and those with a greater variety of
cover types had more sample locations. We conducted one 20-min survey at each
sampling location between sunset and 0100 h (Johnson et al. 2002). We remained
stationary at sampling locations while actively scanning with the bat detector for
bat activity. We examined active acoustic-monitoring data and capture data for bat
Table 1. Descriptions of islands and a peninsula surveyed for bats at Boston Harbor Islands National
Recreation Area, MA, 2010–2011.
Distance (km) to
Island or Area Maximum and name of # of
peninsula name (ha) elevation (m) nearest mainland buildings Vegetation description
Thompson 69 24 0.50 to Squantum 14 Quercus robur L. (English Oak),
Acer platanoides L. (Norway
Maple), open lawns, saltmarshes,
freshwater wetlands
Peddocks 85 24 0.39 to Hull 26 English Oak, Norway Maple,
Rhus typhina L. (Staghorn
Sumac)
Lovells 48 24 2.20 to Hull 0 Staghorn Sumac, Betula
populifolia Marshall (Gray
Birch)
Grape 41 21 0.47 to Webb Park 0 Staghorn Sumac, Gray Birch,
Populus tremuloides Michx.
(Quaking Aspen)
Worlds End 111 43 – 0 Oak and maple trees, fields,
brackish wetlands, freshwater
pond
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activity within 20 min of civil dusk. Bat activity occurring within this arbitrary
timeframe may indicate that bats were roosting on the islands.
Long-term passive acoustic-monitoring
From April 2010 to April 2011, we conducted long-term passive acoustic-monitoring
to investigate the possibility of bat migration at BOHA. We established 2
bat-monitoring stations (BMS)—1 each on Thompson and Lovells Islands, ~7 km
apart (Fig. 1). Each BMS consisted of an SD 1 Anabat bat detector (Titley Scientific,
Columbia, MO) contained in a weatherproof enclosure attached to a guyed
10-m pole. To the top of the pole, we attached a polyvinyl chloride tubing assembly
that protected an Anabat microphone. We positioned the microphone straight down
toward a plexiglass deflector, which was oriented at a 45° angle relative to the microphone.
The deflector redirected echolocation passes up to the microphone, which
was attached to the SD 1 Anabat detector via a 10-m audio cable. Both BMS were
>10 m from the nearest tree lines. Power for each BMS was maintained using an
external 12-V, 24-Ah battery recharged by a 50-W photovoltaic panel. The BMS
monitored bat activity from 1700 to 0700 hr nightly throughout the year (15 April
2010–15 April 2011). Bat echolocation-pass data were remotely uploaded daily by
each BMS to http://getmylog.com; we downloaded the data for analysis.
Echolocation identification
We used Analook 4.8p computer software to visually inspect bat passes and assign
identifications for both actively and passively collected acoustic data (Corben
2001). We used frequency and shape characteristics to manually identify echolocation
passes (Britzke et al. 2002, Fenton and Bell 1981, Murray et al. 2001, O’Farrell
et al. 1999). Echolocation passes were identified by comparing our recordings to a
library consisting of echolocation passes collected from hand-released bats marked
with chemiluminescent tags (US Geological Survey, Virginia Cooperative Fish and
Wildlife Research Unit, Blacksburg, VA, unpubl. data). We attempted identification
only of those echolocation passes containing ≥3 pulses (Johnson et al. 2002). We
characterized a bat pass as ≥1 pulse emitted by an individual bat within a call file.
We also noted feeding passes (rapid emission of echolocation pul ses, distinct from
search-phase pulses), which are evidence of bats actively foraging.
Modelling migration activity
To analyze long-term bat activity recorded at our 2 BMS for evidence of possible
bat migration, we used time-series analysis to account for effects of weather
and to model nightly and seasonal bat passes. To examine effects of weather on
bat activity, we obtained data from a remote automated weather station located at
Logan International Airport, Boston, MA (NOAA 2011). Data included nightly rain
accumulations (cm; Rainacc), number of nightly hours rainfall accumulated (Rainhr),
mean nightly air temperature (°C; Temphr), daily maximum air temperature (°C;
Tempmax), daily minimum air temperature (°C; Tempmin), mean nightly wind speed
(m/s; Windmean), mean nightly relative humidity (%; RelHum), and mean nightly
barometric pressure (kPa; Baro). We averaged hourly data during non-daylight
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hours to obtain nightly means. To achieve statistical normality, we used natural-log
transformations for the number of hours that rainfall accumulated within a night
(Rainhr) and square-root transformations for nightly rain accumulations (Rainacc)
and wind speed (Windmean) (Zar 1984).
Prior to analyzing effects of weather on bat activity, we tested explanatory
variables for collinearity to reduce model over-fitting. We computed Pearson’s
product-moment correlation coefficients for all pairs of variables and censored 1
member of any pair having a correlation >0.60 (Grewal et al. 2004). Collinearity
was significant for 4 variable pairs, including Rainhr and Rainacc (r = 0.81), Temphr
and Tempmax (r = 0.96), Temphr and Tempmin (r = 0.99), and Tempmax and Tempmin
(r = 0.96). We retained Rainhr because the periodicity of rain may have more of an
effect on bat activity than precipitation totals. We retained Temphr because it represented
mean temperatures recorded throughout the night when bats are active rather
than maximum and minimum temperatures recorded during a 24-h period. Seasonal
trends may follow a sine or cosine function (Montgomery et al. 2008); thus, we
incorporated a sinusoidal trigonometric function into our time-series analysis to
account for seasonal trends in bat passes and weather patterns.
Number of bat passes may be serially autocorrelated, i.e., bat passes are not independent
on successive nights (Hayes 1997, Milne et al. 2005). As with seasonal
trends, autocorrelation also must be accounted for in time-series analyses. We used
an autoregressive (AR) modeling approach to estimate autocorrelation structure
of bat passes (RDCT 2008). We iteratively incorporated AR (p) structures, where
p = lag, to estimate appropriate AR order, i.e., the number of nights elapsed between
independent nights of data. We used Akaike’s information criterion for small
sample sizes (AICc) to rank models. Candidate models separated by ≤3 AICc were
considered competing models. We used Akaike weights, wAICc, to select the most
parsimonious model in the candidate set. After selecting the best approximating
model, we incorporated the estimated correlation coefficient (Φ) in the final models
to account for nightly serial autocorrelation of bat passes.
We used generalized least squares to develop a predictive model of bat activity
and account for seasonal trends and effects of weather. Models followed the general
form of:
natural-log(Passesj) = β0 + β1 natural-log(Rainhr) + β2 (Temphr) +
β3 sqrt(Wind mean) + β4 (RelHum) + β5 (Baro) + β6 sin(2πj / T) + β7 cos (2πj / T) + εj,
where Passesj was the number of bat passes recorded on night j; Rainhr was the
number of hours of precipitation on night j; Temphr was the mean air temperature
on night j; Windmean was the mean nightly wind speed on night j; RelHum was the
mean nightly relative humidity on night j; Baro was the mean nightly barometric
pressure on night j; β0-7 were coefficients estimated by regression; sin and cos terms
described seasonality, where j was night and T was total number of nights per year;
and εj was an error term. For each BMS, we developed models for: (1) all passes,
including bat passes unidentifiable to species; (2) passes from tree bats, including
Eastern Red Bat, Hoary Bat, and Silver-haired Bat; and (3) passes from cave bats,
including Big Brown Bat, Little Brown Bat, and Northern Long-eared Bat.
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We examined model residuals (predicted–observed data) that exceeded 2 standard
deviations (SD) from the mean. Nightly bat-pass totals that exceed predicted
values by >2 SD may be evidence of migration events, particularly if these events
occurred during spring or autumn and occurred on the same nights at the 2 BMS
(Johnson et al. 2011a, Montgomery et al. 2008).
Results
Through a combination of mist netting, active acoustic-monitoring, and passive
long-term acoustic monitoring, we documented 6 bat species at BOHA. These
included Eastern Red Bat, Big Brown Bat, Hoary Bat, Little Brown Bat, Silver-
Haired Bat, and Northern Long-eared Bat.
Mist netting
From 26 July 2010 through 5 August 2010, we conducted mist-net surveys at
7 locations for 9 nights and captured 49 bats representing 4 species (Table 2). We
captured bats at all locations, with the exception of 1 location on Grape Island.
We captured reproductively active female Big Brown Bats, Eastern Red Bats, and
Northern Long-eared Bats. At Thompson Island, we captured 3 Eastern Red Bats
within <6 min of civil dusk; all other captures on islands were >20 min after civil
dusk. We did not recapture any bats.
Active acoustic-monitoring
We conducted active acoustic-monitoring at 30 locations over 5 nights (26–30
July 2010) (Table 3), recording activity of identifiable bat species at 23 (76.7%)
locations. There was no activity recorded at 3 locations, and bat passes were not
identifiable to species at 4 locations. During active acoustic-monitoring, we recorded
echolocation passes of 5 identifiable species—Big Brown Bat, Eastern Red
Table 2. Bats captured using mist nets at Boston Harbor Islands National Recreation Area, MA, July–
August 2010. EPFU = Eptesicus fuscus, LABO = Lasiurus borealis, MYLU = Myotis lucifugus, and
MYSE = Myotis septentrionalis.
Locations Nights Total Adult Juvenile Adult Juvenile
Field site sampled sampled Species capturesA male male female female
Thompson 3 3 EPFU 1 1 0 0 0
LABO 6 2 1 2 0
Peddocks 1 2 EPFU 11 6 0 2 2
LABO 2 2 0 0 0
MYSE 1 0 0 1 0
Grape 2 2 LABO 1 0 0 1 0
EPFU 1 0 0 0 0
Worlds End 1 2 EPFU 12 1 3 7 1
MYLU 1 0 0 0 1
MYSEB 13 4 0 5 2
ADiscrepancies in total number of bats captured and sum of males and females are because bats escaped
before sex or age could be determined.
BIncludes 1 male for which age was not determined.
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Bat, Hoary Bat, Little Brown Bat, and Northern Long-eared Bat. We recorded feeding
activity from Big Brown Bats and Eastern Red Bats (Table 3). Twenty minutes
before civil dusk, we recorded 2 Big Brown Bat echolocation passes at Thompson
Island, 7 Eastern Red Bat echolocation passes at Grape Island, and 6 Eastern Red
Bat echolocation passes at Peddocks Island.
Long-term passive acoustic-monitoring
The 2 BMS recorded 4320 bat passes from 6 identifiable species, including
Eastern Red Bat, Big Brown Bat, Hoary Bat, Little Brown Bat, Silver-Haired Bat,
and Northern Long-eared Bat (Table 4, Fig. 2). We identified 0.6% of bat passes
as Myotis spp. due to poor pulse-quality. We were unable to identify 32.1% of
bat passes to species because they consisted of less than 3 echolocation pulses or were
of poor quality. Bat-monitoring stations at both islands functioned during all
365 nights of the sample period. Although we documented the same species at
both Thompson and Lovells Islands, 1.73 times as many passes were recorded at
Thompson Island. Bat activity began to increase at the beginning of May, peaked
in July and August, and then declined through October (Fig. 2). Relatively few
passes were recorded from November to April. We observed these trends at both
Table 3. Bat-echolocation passes recorded using Anabat II bat detectors actively monitoring at Boston
Harbor Islands National Recreation Area, MA, July 2010. NOID = unidentifiable bat pass, EPFU =
Eptesicus fuscus, EPFUFP = Eptesicus fuscus feeding pass, LABO = Lasiurus borealis, LABOFP =
Lasiurus borealis feeding pass, LACI = Lasiurus cinereus, MYLU = Myotis lucifugus, MYSE = Myotis
septentrionalis, and MYSP = unidentifiable Myotis spp.
Locations Total Species
Field site sampled passes NOID EPFU EPFUFP LABO LABOFP LACI MYLU MYSE MYSP
Thompson 9 53 10 20 0 8 0 15 0 0 0
Peddocks 7 14 2 0 0 10 0 0 0 0 2
Grape 7 108 9 84 5 12 0 0 1 0 2
Worlds End 7 239 21 90 0 59 2 2 12 16 39
All 30 414 42 194 5 89 2 17 13 16 43
Table 4. Bat-echolocation passes recorded using Anabat SD 1 bat detectors set for continuous monitoring
(n = 365 nights) at Boston Harbor Islands National Recreation Area, MA, April 2010–April
2011. NOID = Unidentifiable bat pass, EPFU = Eptesicus fuscus, EPFUFP = Eptesicus fuscus feeding
pass, LABO = Lasiurus borealis, LABOFP = Lasiurus borealis feeding pass, LANO = Lasionycteris
noctivagans, LACI = Lasiurus cinereus, LACIFP = Lasiurus cinereus feeding pass, MYLU = Myotis
lucifugus, MYSE = Myotis septentrionalis, and MYSP = unidentifiable Myotis spp.
Species
Total EPFU LABO LACI
Field site passes NOID EPFU FP LABO FP LANO LACI FP MYLU MYSE MYSP
Thompson 2738 820 845 11 951 26 1 75 1 34 1 11
Lovells 1582 565 488 2 468 14 1 20 0 25 1 14
All 4320 1385 1333 13 1419 40 2 95 1 59 2 25
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islands for tree bats and cave bats. Eastern Red Bats were recorded mid-April–
October. Hoary Bats were recorded from May–early September. We recorded 2
passes from Silver-haired Bats: 1 at Thompson Island in April, and 1 at Lovells
Island in late-August. Big Brown Bats were recorded mostly from May–October,
but a few passes were recorded in November and mid-February. We recorded
Little Brown Bats mostly from mid-July–early November. We recorded 2 passes
from Northern Long-eared Bat; 1 at Thompson Island in early-June and 1 at
Lovells Island in early-August. Unidentifiable Myotis spp. were recorded mostly
from late July–October.
Figure 2. Echolocation passes of (a) Big Brown Bat, (b) Eastern Red Bat, (c) Silver-haired
Bat, (d) Hoary Bat, (e) Little Brown Bat, and (f) Northern Long-eared Bat recorded at
Anabat bat-monitoring stations on Thompson and Lovells Islands, Boston Harbor Islands
National Recreation Area, April 2010–April 2011. Note different scales on y-axes.
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Modelling migration activity
The best candidate AR function for the time-series models differed between
the BMS and species groups according to wAICc values. There were 3 or more competing
models for each island and species group (Table 5). For each island and
species group, we chose the model with the highest wAICc value: AR(12), AR(12),
and AR(3) for all bats, tree bats, and cave bats, respectively, at Thompson Island;
and AR(8), AR(11), and AR(8) for all bats, tree bats, and cave bats, respectively,
at Lovells Island. After accounting for seasonal trends and autocorrelation, mean
nightly temperature, mean nightly wind speed, and relative humidity significantly
affected total bat activity, but only at Thompson Island (Table 6). Bat activity was
positively related to mean nightly temperature, and negatively related to mean
Table 5. Autoregressive (AR) model selection using Akaike information criteria (AICc) difference
with correction for small sample sizes (ΔAICc), and model weight (wAICc) for determining temporal independence
of bat-echolocation passes recorded at 2 bat monitoring stations at Boston Harbor Islands
National Recreation Area, April 2010–April 2011. Only candidate models less than 3 ΔAICc are included. p
= order of AR model
Bat monitoring station Bat groupA AR(p) model AICc ΔAICc wAICc
Thompson Island All 12 707.50 0.00 0.367
11 707.58 0.08 0.352
13 709.14 1.65 0.161
Tree bats 12 570.98 0.00 0.297
13 571.30 0.32 0.253
11 571.53 0.55 0.225
14 573.09 2.11 0.104
Cave bats 3 739.10 0.00 0.394
7 740.61 1.51 0.185
4 740.91 1.81 0.159
Lovells Island All 8 713.90 0.00 0.329
7 714.99 1.09 0.191
9 715.86 1.95 0.124
2 716.35 2.44 0.097
13 716.43 2.53 0.093
Tree bats 11 536.19 0.00 0.195
9 536.38 0.19 0.177
8 536.41 0.22 0.174
12 536.90 0.71 0.137
7 537.05 0.86 0.127
13 537.83 1.64 0.086
10 538.26 2.07 0.069
Cave bats 8 599.97 0.00 0.547
9 601.64 1.67 0.237
11 602.93 2.96 0.125
AAll = all bat echolocation passes, including unidentifiable passes: tree bats = echolocation passes
from Lasiurus borealis, L. cinereus, and Lasionycteris noctivagans; cave bats = echolocation passes
from Eptesicus fuscus, Myotis lucifugus M. septentrionalis, and unidentifiable Myotis spp.
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Table 6. Effects of weather conditions on bat activity recorded at Boston Harbor Islands National
Recreation Area, April 2010–April 2011.
Bat monitoring station Bat groupA VariableB Coefficient SE P
Thompson Island All Intercept 7.520 5.519 0.174
Temphr 0.012 0.006 0.035
Rainhr -0.046 0.190 0.810
Baro -0.062 0.053 0.240
Windmean -0.212 0.075 0.005
RelHum -0.005 0.003 0.049
Sine -0.700 0.198 less than 0.001
Cosine -1.129 0.234 less than 0.001
Tree bats Intercept 8.989 4.450 0.044
Temphr 0.005 0.004 0.320
Rainhr 0.005 0.160 0.974
Baro -0.075 0.042 0.077
Windmean -0.230 0.063 less than 0.001
RelHum -0.006 0.002 0.004
Sine -0.563 0.175 0.001
Cosine -0.817 0.205 less than 0.001
Cave bats Intercept 4.784 5.613 0.395
Temphr 0.011 0.006 0.066
Rainhr -0.009 0.221 0.968
Baro -0.045 0.053 0.406
Windmean -0.052 0.084 0.539
RelHum -0.003 0.003 0.333
Sine -0.288 0.102 0.005
Cosine -0.476 0.150 0.002
Lovells Island All Intercept 4.373 5.607 0.436
Temphr 0.005 0.006 0.427
Rainhr -0.160 0.199 0.421
Baro -0.036 0.053 0.505
Windmean -0.036 0.076 0.636
RelHum -0.002 0.003 0.436
Sine -0.654 0.193 less than 0.001
Cosine -0.911 0.227 less than 0.001
Tree bats Intercept 8.392 4.281 0.051
Temphr 0.001 0.004 0.800
Rainhr -0.160 0.156 0.306
Baro -0.078 0.041 0.057
Windmean -0.027 0.061 0.659
RelHum -0.001 0.002 0.532
Sine -0.456 0.169 0.007
Cosine -0.484 0.198 0.015
Cave bats Intercept 4.948 4.657 0.289
Temphr 0.005 0.005 0.343
Rainhr 0.004 0.174 0.982
Baro -0.044 0.044 0.323
Windmean -0.076 0.065 0.241
RelHum -0.003 0.002 0.191
Sine -0.251 0.127 0.049
Cosine -0.497 0.159 0.002
AAll = all bat echolocation passes, including unidentifiable passes: tree bats = echolocation passes
from Lasiurus borealis, L. cinereus, and Lasionycteris noctivagans; cave bats = echolocation passes
from Eptesicus fuscus, Myotis lucifugus M. septentrionalis, and unidentifiable Myotis spp.
BTemphr = mean nightly air temperature; Rainhr = number of hours of precipitation; Windmean = mean nightly
wind speed; RelHum = mean nightly relative humidity; Baro = mean nightly barometric pressure.
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nightly wind speed and relative humidity. Tree-bat activity at Thompson Island was
negatively affected by mean nightly wind speed and relative humidity (Table 6). No
weather variables significantly affected cave-bat activity, nor did they significantly
affect overall bat activity at Lovells Island (Table 6). For Thompson Island, fits of
final models for all bat activity (adjusted r2 = 0.708), tree-bat activity (adjusted r2 =
0.612), and cave-bat activity (adjusted r2 = 0.411) were generally better than final
models for Lovells Island for all bat activity (adjusted r2 = 0.558), tree-bat activity
(adjusted r2 = 0.409), and cave-bat activity (adjusted r2 = 0.369).
Final models used to predict seasonal trends in bat activity varied by night, location,
and among species groups. Residuals that exceeded 2 SD (n = 19) in models
for total bat activity occurred at both islands during documented bat-migration periods,
i.e., April–May and late-July–October, and on the same nights at both islands
of 1 May, 24 and 27 July, and 4 and 10 August (Fig. 3). At both islands, residuals
that exceeded 2 SD (n = 22) in models for tree-bat activity occurred during autumn
migration periods, i.e., late-July–October, and on the same nights of 27 July, 18 and
19 August, and 16 September. Residuals that exceeded 2 SD (n = 31) in models for
cave-bat activity occurred at both islands May–September, and on the same nights
of 1 May; 6, 24, and 27 July; and 4 and 10 August (Fig. 3). From November through
April, no residuals exceeded 2 SD at either island or for any species group.
Discussion
It is important to note that our inventory took place after WNS was confirmed
in Massachusetts in winter 2007–2008 (MDFW 2017). Nevertheless, we detected
6 of 9 bat species that potentially could occur at BOHA. At the time of our inventory,
all 6 taxa were considered globally secure or apparently secure (Harvey et al.
1999). Since then, the Northern Long-eared Bat has been listed as a threatened species
by the US Fish and Wildlife Service and endangered under the Massachusetts
Endangered Species Act. This forest-interior–dwelling species occurred throughout
Massachusetts; however, because of its susceptibility to WNS, its population
has declined 90–100% (Blehert et al. 2009, Caceres and Barclay 2000, MDFW
2017). Coastal areas in the Northeast, including Martha’s Vineyard, Cape Cod,
Nantucket, and Long Island, however, continue to support small breeding populations
(BiodiversityWorks 2016). The state-endangered Little Brown Bat also was
once widespread throughout Massachusetts; its populations have been reduced by
90–100% by WNS (MDFW 2017). It is likely that, prior to WNS, we would have
observed higher numbers of Northern Long-eared Bats and Little Brown Bats and
in more locations than we did in our inventory.
As we hypothesized, we did not capture or record Eastern Small-footed Bat or
Indiana Bat; both are endangered in Massachusetts. Unique habitat, e.g., extensive
rock outcrops, required by Eastern Small-footed Bat does not exist at BOHA (Johnson
and Gates 2008); furthermore, within Massachusetts it has only been found in
2 counties in the western part of the state. Although habitat conditions may exist
in BOHA that are suitable for Indiana Bat (Silvis et al. 2016), this rare species has
not been documented in Massachusetts since 1939 (USFWS 2007). We also did
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2019 Vol. 25, Special Issue 9
Figure 3. Standard
deviations
between actual
and predicted
nightly echolocation
passes from
(a) all bat species,
(b) tree-bat
species, and (c)
cave-bat species
recorded at Anabat
bat-monitoring
stations on
Thompson (triangles)
and Lovells
(circles) Islands,
Boston Harbor
Islands National
Recreation Area,
April 2010–April
2011. Note different
scales on
y-axes.
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not document the Tri-colored Bat. Tri-colored Bats had a widespread distribution
in Massachusetts, but populations in the Northeast have suffered losses averaging
90% from WNS (MDFW 2017). Tri-colored Bats may be locally extirpated or exist
in such low abundance that they were difficult to detect.
High bat-species diversity at Boston Harbor Islands National Recreation Area
is likely due to the mosaic of forests and open areas found at BOHA (Ford et al.
2005, Krebs 1999). The location with highest bat activity (both active acoustic
echolocation-call activity and number of captures) was at Ice Pond at Worlds End
peninsula. This freshwater source likely is the most accessible and dependable at
BOHA, attracting bats from within and outside the unit. Furthermore, mature intact
forests at Worlds End may provide a refuge in an otherwise heavily developed
area, similar to findings in Rock Creek Park located in Washington, DC (Johnson
et al. 2008). Captures of Northern Long-eared Bats at Worlds End and Peddocks
Island indicate BOHA is providing habitat in an otherwise urbanized setting for
this species, though the extent to which bats are using islands at BOHA warrants
further research. Our inventory included only a portion of BOHA, but other islands
and peninsulas may provide roosting and foraging habitats for bats as well. For
example, bats have been observed flying over Bumpkin Island, which we did not
survey (M. Albert, NPS, BOHA, MA, pers. comm.).
Our active acoustic-monitoring and capture data suggest Eastern Red Bats and
Big Brown Bats may be roosting on BOHA islands. Interestingly, the islands we
inventoried did not have available freshwater sources. Bats roosting on the islands
must either fly to freshwater sources on the mainland, e.g., Ice Pond at Worlds End,
or perhaps partly maintain water balance by intake of seawater, as documented in
marine Myotis vivesi Menegaux (Fish-eating Bat) in Mexico (Carpenter 1968).
Distances between the islands we inventoried and the mainland are within known
home-range distances of Big Brown Bats (Menzel et al. 2001) and Eastern Red Bats
(Walters et al. 2007) in urban settings. Further research could elucidate the home
ranges and habitat use by bats that may be roosting on the islands.
Long-term acoustic monitoring answered many questions regarding bat species
occurrence and activity patterns at BOHA. For example, we documented Silverhaired
Bats only through use of BMS in our inventory, though we caution that
echolocation-call characteristics of Silver-haired Bats and Big Brown Bats are
similar. We gained a broader knowledge of the seasonality of bat use at BOHA;
information that would not have been obtained through our capture and active
acoustic-monitoring efforts. Indeed, seasonality of bat activity was more consistent
than weather variables in terms of predicting bat activity. It is unclear why effects
of weather variables on bat activity at BOHA were inconsistent, and insignificant in
most cases, between islands and bat groups. Perhaps overall differences in bat activity,
and consequently model robustness, between Thompson Island and Lovells
Island could be a result of more roosting habitat on the former. Regardless, when
bat activity was significantly associated with weather variables, the associations
were consistent with past research, with the exception of relative humidity, which
we found was negatively associated with bat activity (Erickson and West 2002,
Lacki 1984, Paige 1995, Parsons et al. 2003).
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It appears that bats may be migrating through BOHA, mostly in late July and
early August, known migration periods for tree bats and perhaps cave bats (Cryan
2003, Davis and Hitchcock 1965, Griffin 1945). Annual patterns of tree-bat activity
were largely in agreement with museum records for the area, indicating that these
bat species arrive or migrate through the area in May and stay through October
(Cryan 2003). It has been hypothesized that bats follow linear landscape features
when migrating (Cryan and Brown 2007, Kunz et al. 2007). Furthermore, Eastern
Red Bats have been observed flying near the Atlantic Coast during migration periods
(Hatch et al. 2013, Peterson et al. 2014, Sjollema et al. 2014). Consequently,
the geographic position of BOHA may be in migratory flight paths.
It is difficult to say if bats are moving directly between the Deer Island and
Hull peninsulas, using Lovells Island as a stopover site, or if they are using any
other islands as they cross over Boston Harbor. It is assumed that tree bats travel in
a north-south direction during autumn, but cave bats may migrate in any direction
(Davis and Hitchcock 1965, Griffin 1945). In a banding study in New England,
Little Brown Bats typically traveled in a southeast–northwest direction. One bat’s
banding and recovery sites were on opposite sides of Boston Harbor, indicating
possible migration through the area (Davis and Hitchcock 1965).
Our results indicated that bats may migrate through BOHA, but the total number
of echolocation passes recorded suggest the number of migrants passing through
BOHA may be relatively small compared to other areas of the US (Arnett et al.
2008; Johnson et al. 2011a, 2011b; Sjollema et al. 2014). Though bats may not
always echolocate during migration, the number of echolocation passes recorded
and number of fatalities at wind-energy facilities have been shown to be correlated
(Johnson et al. 2011b).
At minimum, our results add to and corroborate the findings of prior research
focused on bats migrating along the coast of Massachusetts (Cryan 2003, Miller
1897). Indeed, Eastern Red Bats, Hoary Bats, and Silver-haired Bats have been documented
along the Atlantic coast since the 1800s, according to museum records, as
well as other observations and studies (Cryan 2003, Hatch et al. 2013, Miller 1897,
Peterson et al. 2014). During our study, Silver-haired Bat activity was much lower
than for Eastern Red Bats and Hoary Bats, a difference that has remained consistent
for decades (Cryan 2003, Johnson et al. 2011a, 2011b, Miller 1897). Similar to
historical reports of tree bats in Massachusetts, our findings also showed increased
activity levels of tree-bat species during autumn, a season known for migration of
these species. However, more definitive research is warranted to confirm migration
of tree bats through BOHA.
Acknowledgments
We appreciate the hard work of C. Daggett and J. Torzewski during the summer field
season. We are grateful for the help of numerous National Park Service (NPS) staff, particularly
M. Albert, S. Colwell, D. Hayes, C. Martin, B. Masson, S. Walasewicz, G. Waters,
and volunteers who assisted us at all the NPS units that we inventoried. We thank A.
Kozlowski for developing the MS Access database. We appreciate J. Scully and B. Dowd
of Outward Bound, Thompson Island, for providing housing and assistance. University
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of Massachusetts, Boston, graciously provided transportation at Boston Harbor. We thank
several reviewers for their comments on this manuscript. Funds were provided by the
Maryland Department of Natural Resources, Power Plant Research Program, to help with
bat-monitoring on Thompson and Lovells Islands. The NPS provided funding for this inventory.
This article is Scientific Contribution No. 5494 of the University of Maryland Center
for Environmental Science, Appalachian Laboratory.
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