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Quantifying wedge-tailed shearwater (Ardenna pacifica) fallout after changes in highway lighting on Southeast O'ahu, Hawai'i


Abstract and Figures

Attraction to artificial light at night (ALAN) poses a threat to many fledgling seabirds leaving their nests for the first time. In Hawai'i, fledgling wedge-tailed shearwaters disoriented by lights may become grounded due to exhaustion or collision, exposing them to additional threats from road traffic and predation. While the timing and magnitude of shearwater fallout varies from year to year, little is known about how changing lighting and environmental conditions influence the risk of grounding for this species. We analyzed 8 years (2012-2019) of observations of road-killed shearwaters along the Kalaniana'ole Highway on O'ahu to quantify the timing and magnitude of fallout during the fledging season (November-December). Our goal was to compare fallout before (2012-15) and after (2016-19) a transition in highway lighting from unshielded high-pressure sodium (HPS) to full-cutoff light-emitting diode (LED) streetlights. To detect the shearwater response to the lighting regime, we also accounted for three potential environmental drivers of interannual variability in fallout: moon illumination, wind speed, and wind direction. The effects of these environmental drivers varied across years, with moon illumination, wind speed and wind direction significantly affecting fallout in at least one year. Altogether, the interaction between moon illumination and wind speed was the most important predictor, suggesting that fallout increases during nights with low moon and strong winds. The lack of an increase in fallout after the change from HPS to shielded 3000K-4000K LED streetlights suggests the new streetlights did not worsen the light pollution impacts on wedge-tailed shearwaters on Southeast O'ahu. However , due to potential species-specific disparities in the behavior and light attraction of petrels, similar studies are needed before energy saving LED lights are implemented throughout the Hawaiian archipelago.
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Quantifying wedge-tailed shearwater
(Ardenna pacifica) fallout after changes in
highway lighting on Southeast Oahu, Hawaii
Jennifer UrmstonID
*, K. David HyrenbachID
, Keith Swindle
1Hawai’i Pacific University, Waimānalo, HI, United States of America, 2Oikonos Ecosystem Knowledge,
Kailua, HI, United States of America, 3U.S. Fish and Wildlife Service (USFWS), U.S. Embassy, Nairobi,
¤Current address: Migratory Bird Permit Office, U.S. Fish and Wildlife Service (USFWS), Portland, OR,
United States of America
Attraction to artificial light at night (ALAN) poses a threat to many fledgling seabirds leaving
their nests for the first time. In Hawai‘i, fledgling wedge-tailed shearwaters disoriented by
lights may become grounded due to exhaustion or collision, exposing them to additional
threats from road traffic and predation. While the timing and magnitude of shearwater fallout
varies from year to year, little is known about how changing lighting and environmental con-
ditions influence the risk of grounding for this species. We analyzed 8 years (2012–2019) of
observations of road-killed shearwaters along the Kalaniana‘ole Highway on O‘ahu to quan-
tify the timing and magnitude of fallout during the fledging season (November–December).
Our goal was to compare fallout before (2012–15) and after (2016–19) a transition in high-
way lighting from unshielded high-pressure sodium (HPS) to full-cutoff light-emitting diode
(LED) streetlights. To detect the shearwater response to the lighting regime, we also
accounted for three potential environmental drivers of interannual variability in fallout: moon
illumination, wind speed, and wind direction. The effects of these environmental drivers var-
ied across years, with moon illumination, wind speed and wind direction significantly affect-
ing fallout in at least one year. Altogether, the interaction between moon illumination and
wind speed was the most important predictor, suggesting that fallout increases during nights
with low moon and strong winds. The lack of an increase in fallout after the change from
HPS to shielded 3000K - 4000K LED streetlights suggests the new streetlights did not
worsen the light pollution impacts on wedge-tailed shearwaters on Southeast O‘ahu. How-
ever, due to potential species-specific disparities in the behavior and light attraction of
petrels, similar studies are needed before energy saving LED lights are implemented
throughout the Hawaiian archipelago.
Light pollution is a concern for burrow-nesting seabirds globally, with documented impacts
on over 50 species of shearwaters, petrels, and puffins [1]. While coastal light pollution can
PLOS ONE | March 24, 2022 1 / 17
Citation: Urmston J, Hyrenbach KD, Swindle K
(2022) Quantifying wedge-tailed shearwater
(Ardenna pacifica) fallout after changes in highway
lighting on Southeast Oahu, Hawaii. PLoS ONE
17(3): e0265832.
Editor: Vitor Hugo Rodrigues Paiva, MARE –
Marine and Environmental Sciences Centre,
Received: September 26, 2021
Accepted: March 8, 2022
Published: March 24, 2022
Peer Review History: PLOS recognizes the
benefits of transparency in the peer review
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Copyright: This is an open access article, free of all
copyright, and may be freely reproduced,
distributed, transmitted, modified, built upon, or
otherwise used by anyone for any lawful purpose.
The work is made available under the Creative
Commons CC0 public domain dedication.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Information files.
disrupt adult seabirds provisioning their chicks on colonies [24], fledglings consistently
account for the majority (68% - 99%) of the grounded specimens [1]. Fledgling seabird “fall-
out” occurs when chicks leaving their nests are disoriented by onshore lighting and become
stranded on land instead of flying out to sea [1]. The magnitude of fallout is likely influenced
by the number of chicks fledging, the prevailing environmental and celestial conditions [4,5],
and the features of anthropogenic lights, which vary as a function of light fixture design and
bulb type [6,7]. To gauge the effectiveness of light pollution mitigation measures, wildlife
managers need to understand the influence of these biological and environmental drivers on
the timing and magnitude of fallout.
A conceptual model to explain fallout involves fledging seabirds being drawn toward well-
lit coastal areas, especially in the absence of moonlight [4,5,811] and when strong winds are
directed toward shore [10,11]. Birds are affected by bright light sources from vessels at sea and
urbanized areas on shore, including streetlights and sports fields [1,6,1213]. Moreover, colli-
sions with powerlines and other structure can lead to injury and grounding [14,15]. While our
understanding of the environmental drivers of fallout is growing, the influence of specific
design features of anthropogenic light sources remains understudied. In particular, lamp color
and directionality are two key streetlight features that can affect fallout [7,16]. Spurred by
efforts to improve energetic efficiency, many cities are replacing yellow high-pressure sodium
(HPS) lightbulbs commonly used in streetlights with white light-emitting diode (LED) bulbs
[1719]. Although LED bulbs decrease electricity consumption and maintenance costs, these
benefits could be costly to wildlife, as shearwaters may be more sensitive to LED lights [7]. A
study on the visual perception of Wedge-tailed Shearwaters (Ardenna pacifica–previously Puf-
finus pacificus) showed that they experience maximum light absorption of the wavelengths
emitted by white LED lights (406–566 nm) and have lower absorption of the wavelengths emit-
ted by HPS lights (560–620 nm) [20]. Moreover, a field-based experiment in Australia showed
that Short-tailed Shearwaters (Ardenna tenuirostris) show increased attraction to LED lights
over HPS lights, although the difference was not statistically significant [7].
Mitigation measures often target light directionality, whereby streetlights are shielded
through the use of a “full-cutoff” design, which inhibits light emission above the horizontal
plane of the fixture. This approach, when applied to HPS lights, reduced Newell’s Shearwater
(Puffinus newelli) fallout on Kauai (Hawai‘i) [16]. Although mitigation is being addressed
through shielding, the common use of optimized LEDs with broad spectra and Correlated
Color Temperature (CCT) greater than the maximum recommended value for wildlife (2200
K) may be a cause for concern [17]. While modern LED lights possess the flexibility to give off
a range of low to high CTT, short-wavelength light with high CCT is a common choice because
of its efficiency [19]. The effectiveness of light shielding coupled with the use of broad spec-
trum, high CCT LEDs is unknown.
On the island of O‘ahu (Hawai‘i), Wedge-tailed Shearwaters (hereafter referred to as
WTSH) experience fallout during the annual fledging season (November-December) [21,22].
A three-year study in the early 1990s, revealed that hundreds of chicks become grounded
every autumn, with the number varying widely from year to year [22]. Starting in 2002, U.S.
Fish and Wildlife Service initiated a program of opportunistic road surveys of the southeast
section of O‘ahu during the fledging season, which documented a fallout hotspot in the town
of Waimānalo, within 5 km from two WTSH colonies on offshore islets [21].
While there is evidence of interannual variability in WTSH fallout, little is known about the
influence of environmental (weather and oceanographic conditions) and biological (breeding
population size and reproductive success) drivers. To date, only one study has investigated the
environmental drivers of WTSH fallout, by comparing a “wreck” year of unusually high fallout
(1994), when WTSH groundings increased ten-fold from the two “normal” years prior [22].
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 2 / 17
Funding: This work was supported by Experiment.
com (Blinded by the light: reducing shearwater
deaths along a coastal highway in O ’ahu, Hawai’i)
and The Eppley Foundation for Research (Blinded
by the Light: Shearwater Deaths Along a Coastal
Highway in O’ahu). The funders had no role in
study design, data collection and analysis, decision
to publish, or preparation of the manuscript.
Competing interests: The authors have declared
that no competing interests exist.
This study suggested that anomalous southerly winds likely carried fledglings inland rather
than out to sea and scattered them throughout the windward coast of O‘ahu. While the south-
erly winds help explain why many birds were found inland, it is unclear to what extent low
ocean productivity during the breeding season and unusual weather conditions during the
fledging period caused the high fallout observed that year.
Over a decade later, Friswold et al. (2020) documented an increasing trend in annual fallout
numbers between 2003 and 2010, and a two-year cycle of alternating years of high and low fall-
out. Subsequently, an unusually large fallout event in 2011 was documented during a La Niña
year with high ocean productivity [23]. These results are suggestive of the potential influence
of breeding population size and reproductive success on fallout.
In 2012, we began conducting systematic road surveys along a 17.3-km section of the Kala-
niana‘ole Highway to document WTSH fallout. In 2016, the Hawai‘i Department of Transpor-
tation changed the streetlights on O‘ahu’s major roads from unshielded 2200 K HPS lights to
shielded 3000–4000 K LED lights, where Kelvin (K) is a unit of measurement for CCT. Lower
CCT indicates a warm yellow-orange appearance whereas higher CCT indicates cool blue light
[18]. The shift in lights halfway through our study provided a unique opportunity to compare
WTSH fallout under different street lighting conditions. To this end, we continued conducting
standardized surveys following the established protocol through 2019 and analyzed an 8-year
time series with four years before (2012–15) and four years after (2016–19) the change in light-
ing. This is the first study to compare changes in seabird groundings in response to HPS versus
LED streetlights, by repeatedly surveying a fallout hotspot during the fledging season.
The goal of this study is to quantify the magnitude of WTSH fallout under two contrasting
lighting regimes, to inform future coastal development and management of light pollution.
Although shielding of the LED streetlights may reduce initial WTSH attraction, we predicted
that disorientation caused by high intensity/shorter wavelength lights would outweigh the ben-
efits of shielding. Thus, we expected an increase in fallout after the installation of LED street-
lights (2016–2019). To detect the fallout response to the lighting regime, we also accounted for
three potential environmental drivers: moon illumination, wind speed, and wind direction.
Because WTSH rely on wind to take flight and may become disoriented in the absence of
moonlight, we predicted higher fallout during windy nights of low moon illumination. In par-
ticular, due to the location of our study area, southwest from two breeding colonies, we antici-
pated that strong northeasterly winds would drive the fledging birds towards shore.
Study area
This study focuses on the southeast section of O‘ahu, where a two-lane coastal highway runs
through a rural and developed landscape (Fig 1). The survey route was illuminated with HPS
streetlights until 2016, when the Hawai‘i Department of Transportation transitioned to LED
streetlights. The CCT of the LED streetlights is 3000 K on sections of the highway directly adja-
cent to the ocean, whereas inland lights are 4000 K.
The WTSH breeding colonies of Mānana Island and Kāohikaipu Island, where approxi-
mately 25,000 and 800 chicks were counted in 2019, are located 1.3 and 0.7 km offshore of our
study area, respectively [25]. Three additional WTSH colonies on offshore islets (Mokulua
Nui, Mokulua Iki, and Popoi‘a) lie approximately 6 km north of the study area (Fig 1), with
2019 chick count estimates of 3,500, 5,000, and 900, respectively [25].
Weather patterns on windward O‘ahu are dominated by the northeast trade winds, which
typically persist for 1 to 2 weeks, interspersed with no-wind periods or southerly storms. Peak
wind speeds occur in the afternoon, with lower wind speeds at night [26].
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 3 / 17
Intake records
Members of the public deliver grounded WTSH to Sea Life Park (SLP), a marine life center
located along our survey route in Waimānalo, for rescue and rehabilitation. SLP intake rec-
ords, involving the daily number of rescued WTSH chicks, have been used to document the
island-wide temporal variability in WTSH fallout during the fledging season and from year to
year [21,22]. To provide a broader context for our localized surveys of a known WTSH fallout
hotspot, we compared the timing and the magnitude of annual fallout documented in the SLP
intake records and our surveys.
Road surveys
We used a time series of standardized road surveys along a 17.3-km stretch of the Kalania-
na‘ole Highway, starting at the Olomana Golf Club, running through Waimānalo, and ending
at the Koko Marina Center (Fig 1). While this survey route is a subset of the area surveyed by
Fig 1. Map of the study area in southeast O‘ahu. Blue line shows the survey route, and crosses indicate the start and end
points. Black dots indicate WTSH breeding colonies. (PI = Popoi‘a Island, MOK = Mokulua Islands, MI = Mānana Island,
KI = Kāohikaipu Island, FSP = Freeman Seabird Preserve). Star marks the location of the Sea Life Park seabird rehabilitation
center. Inset maps show the island of O‘ahu, and the main Hawaiian Islands. Map features are overlaid on an ArcGIS Pro
Software Version 2.5 base layer [24].
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 4 / 17
USFWS from 2002–2010, it encompasses the main WTSH fallout hotspot in Waimānalo [21].
We conducted morning surveys by car, every 3 days, throughout the WTSH fledging season
(November 6 –December 21). We began surveys at sunrise (6:15–7:15 AM) and drove the
route once in each direction, at speeds between 25–35 mph, while visually searching for dead
birds in each lane and along the shoulder. Since these surveys were conducted in the morning,
likely a full 12 hours after fledging time, almost all the birds we observed were deceased. In 8
years of surveys, we observed 2 live birds, which were brought to SLP for rehabilitation and
not counted in our analysis. All dead birds sighted while driving were included in the surveys,
even if they were found on the shoulder, the median, or off the road.
Upon encountering a carcass, we recorded its position on the road, location (latitude and
longitude coordinates from a hand-held Garmin e-trex GPS unit), nearest street address, and
nearest utility pole using their unique id tags. We also took photos of each WTSH we encoun-
tered, showing diagnostic identification features (head and feet).
Environmental variables
We related WTSH fallout to two publicly-available environmental datasets: (i) wind speed
(knots) and wind direction (degrees) recorded on Moku Lo‘e (Kaneohe Bay) and provided by
PacIOOS [27], and (ii) the lunar cycle, quantified using the percent of the lunar disk that was
illuminated each night, from the U.S. Naval Observatory [28].
Because WTSH fledge during the night, we averaged the hourly wind data every night
(18:00–6:00 local time). To match our surveys to the preceding environmental conditions, we
related the number of grounded WTSH documented during a given road survey to the average
wind speed (knots), wind direction (degrees), and lunar disk illumination (%) from the three
nights prior.
Data analysis
We analyzed fallout across and within years using generalized linear models (GLM) built with
R version 3.5.1 and the stats and MASS packages [29]. We developed and fitted nine separate
models: a full model (involving all study years) quantified interannual variability, and eight
yearly models visualized the interannual differences documented by the full model.
We ran all models using both Poisson and negative binomial distributions. Because the
Poisson assumes that the variance equals the mean, the negative binomial is more appropriate
whenever there is overdispersion [30]. We used the Akaike Information Criterion corrected
for small sample size (AICc) to select the best-fitting distribution for each model [31].
Multi-year model of WTSH fallout. We related the number of WTSH observed during
128 surveys of the entire study area (16 per year times 8 years) to the light regime (unshielded
HPS / shielded LED), year (2012–2019), and four environmental variables: moon illumination
(% lunar disk illuminated), average wind speed (knots), average wind direction (degrees), and
Julian date (the number of days since the beginning of the year).
We used multi-model inference to test all possible combinations of these six explanatory
variables. Whenever two of three potentially interacting variables were included in a model,
we also considered their interaction (‘moondate’, ‘moonwind speed’, and ‘wind speeddate’).
We used the AICmodavg package [29] to assess the model fit using AICc, which prevents
over-fitting by penalizing models for each additional variable [31]. AICc assigns a value to
each model using the formula, AICc = -2log(L)+2K+(2K(K+1)/(n-K-1)), where Kis the num-
ber of parameters, nis the sample size, and Lis the maximum likelihood of obtaining the given
results with Kparameters. We used Akaike weights (w
) to calculate the likelihood of each
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 5 / 17
model as follows:
oi¼exp Di
 �
r¼1exp Dr
 �
where the numerator is the model likelihood with Δ
showing the change from the lowest AICc
model to the given model, and the denominator is the sum of all relative weights, as deter-
mined by Δ
the change in each contending model from the lowest AICc model. The lowest
AICc value indicates the model that best describes the patterns in the observed data without
over-fitting [31,32].
To test the influence of the streetlights, in the context of interannual variability, we built
two complementary sets of full models that either included “light regime” (comparing two
groups of years: 2012–15 vs 2016–19) or included individual “years”, regardless of their “light
regime”. This resulted in a total of 106 models: 36 included “light regimes”, 36 included
“years”, and 34 included neither. Individual models ranged from having one to eight predic-
tors (five variables and three interactions) (S1 Table). Following Michael et al. (2014), we
assessed the importance of each variable in terms of their scaled average weight, calculated
using the models where those variables were included.
Yearly models of WTSH fallout. We related the number of WTSH observed during 16
surveys of the entire study area (every three days during a single year) to the four aforemen-
tioned environmental variables: moon illumination, average wind speed, average wind direc-
tion, and Julian date (S1 File). We did not consider variable interactions, and calculated
pseudo R-squared values based on the standard errors using the ‘rsq’ package [29].
Fallout records
To interpret our road surveys in a broader context, we compared the number of grounded
WTSH we documented along the SE corner of O‘ahu with the SLP intake records, which pro-
vided an island-wide measure of fallout timing and magnitude. The SLP intake records of
fledging chicks spanned from November 2 to January 5, and our observations of grounded
shearwaters along the Kalaniana‘ole Highway spanned from November 6 to December 21.
Overall, only 2.3% of the SLP intake records fell outside of our road survey period (November
6 –December 21), with yearly proportions ranging from 1.3% to 6.3% (S1 Table).
The total number of rescued WTSH brought into SLP yearly across the 8-year study varied
by nearly an order of magnitude, ranging from 74 to 525 birds per year, with an average of
226.1 +/- 170.6 S.D. (median = 159.5) (S1 Table). The number of WTSH carcasses observed on
the survey route per year also varied widely, ranging from 7 to 60 birds, with an average of 24.1
+/- 18.7 S.D. (median = 17.5) (S1 Table). There was a positive correlation between the yearly
number of road-killed birds (our surveys) and rescued birds (SLP records), with 2012 and
2016 standing out as high-fallout years (r
= 0.85, df = 6, p <0.01) (Fig 2). There were 469 res-
cued birds in 2012 and 525 in 2016, with both years exceeding the median by over 300 birds.
Likewise, there were 60 road-killed birds in 2012 and 45 in 2016, compared to the median of
17.5 birds. The lowest numbers of rescued and road-killed birds occurred in 2018, with 74 and
7 birds respectively.
Fallout modeling
Over the 8-year study, the number of grounded WTSH observed per survey ranged from 0 to
10, with an overall average of 1.5 +/- 2.2 S.D. (median = 1) (Fig 3). Moreover, to account for
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 6 / 17
the large proportion (46%) of absences (0 WTSH detected during a road survey), we fitted the
fallout count data to Poisson (1<VMR <2) and negative binomial (VMR >2) distributions.
We developed and fitted a full model and eight single-year models.
Multi-year model of WTSH fallout. Because 9 different model formulations were
required to achieve an AICc weight of 0.90, this model set was used to ascertain the importance
of the driver variables. Of the 9 variables tested, only the interaction between moon illumina-
tion and wind speed (moonwind speed) achieved a scaled average weight >1 and was thus
deemed an “important” variable (S2 Table). Moon, wind speed, and year all had weights of 1,
because they contributed an average amount to each model’s weight. Date, wind direction,
(moondate), and (wind speeddate) had weights <1, and contributed less than the average
variable to each model’s weight. Light regime had a weight of 0, and did not appear in any of
the models required to achieve the AICc weight of 0.90.
The overall best-fitting model had a weight of 0.37 and included four explanatory variables:
moon, wind speed, year, and the interaction of moon and wind speed (moonwind speed)
(Table 1). All variables in this model were significant, except wind speed and year 2016 (not
significantly different from 2012). The negative coefficient for the moon variable in this model
(-2.9) indicates that, across the 8-year period, fewer birds were grounded when a greater per-
centage of the lunar disk was illuminated. All years except for 2016 were significantly different
Fig 2. Fallout comparison between Sea Life Park intake records and road surveys. Scatterplot showing the total rescued WTSH per
year from Sea Life Park intake records versus the total WTSH carcasses documented per year during road surveys (r
= 0.85).
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 7 / 17
Fig 3. Boxplots of WTSH carcasses observed during road surveys. Distribution (5, 25, 50, 75, 95 percentiles) of the number of
grounded WTSH observed each study year (n = 16 yearly surveys). Dots indicate outliers.
Table 1. Full model output.
Explanatory variable Estimate S.E. Z-value p-value
2.136 0.580 3.709 <0.001
Wind Speed -0.027 0.046 -0.576 0.565
Moon -2.884 0.827 -3.485 <0.001
Year2013 -1.711 0.447 -3.825 <0.001
Year2014 -1.685 0.406 -4.148 <0.001
Year2015 -1.490 0.365 -4.082 <0.001
Year2016 -0.373 0.324 -1.148 0.251
Year2017 -1.661 0.391 -4.247 <0.001
Year2018 -2.492 0.483 -5.153 <0.001
Year2019 -1.034 0.366 -2.824 0.005
Wind SpeedMoon 0.225 0.083 2.710 0.007
GLM results from best-fit full model, following a negative binomial distribution. Bold font denotes significance at alpha <0.05.
Reference year (intercept) is 2012.
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 8 / 17
from the reference year (2012). The interaction between wind speed and moon had a positive
coefficient (+0.23) suggesting that fallout was higher during periods of lower lunar illumina-
tion and higher wind speed (Fig 4).
Yearly models of WTSH fallout. In addition to the interannual variability in the number
of WTSH observed during road surveys (Fig 3), the temporal aggregation of fallout across sur-
veys was also highly variable, as evidenced by the varying dispersion (variance to mean ratio,
VMR) observed yearly (1.02–4.03) (Table 2)). Moreover, due to the large proportion (46%) of
absences (0 WTSH detected during a road survey), fallout counts followed a Poisson distribu-
tion (1<VMR <2) in every year, except for 2019 (VMR = 4.03), when the negative binomial
model yielded a lower AICc value.
Fig 4. Fallout as a function of moon illumination and wind speed. Scatterplot of the number of grounded WTSH
observed per survey, in relation to wind speed, and moon illumination. Open circles indicate the presence of fallout,
with the increasing radius ranging from 1 to 10. Small solid dots indicate the absence of fallout (0 birds).
Table 2. Yearly model output.
Year Dis. VMR Pseudo Adj. R
Estimate p-value
Int. WS WD Moon Date Int. WS WD Moon Date
2012 P 2.11 0.41 -29.293 -0.744 -0.032 -0.065 0.137 0.096 0.236 0.408 0.071 0.054
2013 P 1.50 0.51 -28.120 0.684 0.029 -4.944 0.065 0.146 0.028 0.016 0.006 0.211
2014 P 1.02 0.64 3.055 0.393 0.003 -1.659 -0.020 0.751 0.045 0.782 0.144 0.456
2015 P 1.14 0.33 -3.680 0.03 -0.001 1.993 0.008 0.575 0.818 0.902 0.006 0.720
2016 P 3.89 0.50 -0.169 0.268 0.002 0.439 -0.006 0.979 0.034 0.816 0.507 0.777
2017 P 1.20 0.18 8.690 0.099 -0.002 -0.854 -0.027 0.291 0.273 0.638 0.291 0.309
2018 P 1.20 0.57 -20.160 -0.190 -0.001 -1.592 0.064 0.183 0.546 0.959 0.261 0.178
2019 NB 4.03 0.26 42.940 -0.100 -0.022 -3.305 -0.115 0.056 0.543 0.196 0.004 0.055
GLM output of annual fallout models, based on 16 surveys (Nov. 6 –Dec. 21) and clumped data distributions (P = Poisson, NB = negative binomial), as evidenced by the
variance to mean ratio (VMR). In addition to the intercept (Int.), four explanatory variables were considered: wind speed (WS), wind direction (WD), lunar
illumination (Moon), and Julian Date (Date).
The bold font denotes significance at alpha <0.05. and the pseudo adjusted R-squared quantifies the model fit.
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 9 / 17
Overall, the yearly models explained a wide range of the variation in fallout throughout the
fledging season, with their pseudo R
values ranging from 18% (2017) to 64% (2014). More-
over, different variables were significant in different years (Table 2). Surprisingly, the influence
of moon illumination was not consistent across our study, with a significant effect in three
years: it was negative twice (2013 and 2019), and it was positive once (2015). Wind speed had a
significant positive effect in three years (2013, 2014, and 2016), whereby higher wind speeds
led to more fallout. Wind direction had a significant positive effect once (2013), whereby wind
blowing from the southwest led to more fallout. Julian date was never significant, suggesting
that fallout was variable throughout the survey period (November 6 –December 21).
Overall, while fallout was explained well (pseudo R
0.5) by wind speed alone in 2014
and 2016, it was explained moderately well (pseudo R
0.3) by moon illumination alone in
2015 and 2019. In 2013, about half of the fallout variation was explained by a combination of
wind speed, wind direction, and moon illumination. In three years (2012, 2017, and 2018), fall-
out was not significantly explained by any of the predictors.
Two years (2012 and 2016) showed significantly higher fallout compared to the other study
years (Fig 3) and together accounted for 55% of the WTSH found during road surveys. Those
same years were also responsible for 55% of all rescued birds brought to SLP, within the time-
frame of this study. While none of the predictor variables were statistically significant in 2012,
moon and date were marginally significant (0.10 <p<0.05) (Table 2). The highest yearly fall-
out occurred in 2012, when 60 WTSH were grounded during an early new moon period
(Julian days: 317–326, November 12–21), and a later one (Julian days: 344–353, December 11–
18) (Fig 5), both of which were accompanied by strong winds (Fig 6). In 2016, a new moon
period occurred in the middle of the fledging season, leading to a single peak in fallout (Fig 5),
which coincided with a period of high wind speeds (>12 knots), increasing the number of
birds grounding at this time (Fig 6).
Timing and magnitude of WTSH fallout
The strong positive correlation between the yearly numbers of grounded WTSH found during
our road surveys and rescued WTSH brought to SLP suggests that our small-scale surveys of a
fallout hotspot are indicative of island-wide fallout trends on O‘ahu. Both the rescue records
and the road surveys documented the highest fallout in 2012 and 2016, and the lowest fallout
in 2018. Moreover, only 2.3% of the WTSH brought to Sea Life Park during the fledging season
between 2012–2019 fell outside of our study period (November 6 –December 21), suggesting
that our survey window captures most of the fledging season fallout.
Interpretation of model results
Multi-year model of WTSH fallout. Our hypothesis that the LED streetlights would
increase shearwater groundings due to higher sensitivity to shorter wavelengths was not sup-
ported, as the light regime was not selected as a significant predictor variable in any of the top
models. It is possible that shearwater visual perception of LED lights was in fact greater, but
shielding reduced initial attraction, thus balancing out overall fallout. However, even if this
were the case, our analysis could not distinguish between these two factors, because the
changes in bulb type and shielding were not independent. Nonetheless, this finding has useful
implications for resource managers since LED lights are a common replacement for HPS lights
in Hawai‘i and elsewhere. While we encourage managers to seek lighting adjustments that will
mitigate fallout, our study shows that the change in streetlights from unshielded HPS to
shielded 3000 K– 4000 K LED did not exacerbate this problem for WTSH on O‘ahu.
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 10 / 17
It is possible that, even if there was an effect of light type on WTSH fallout, its influence was
marginal compared to the effect of the other environmental drivers. In particular, the higher
than average variable weight of the interaction between moon and wind speed suggests that
fallout is a dynamic process, driven by the synergy of low moon illumination and strong
winds, more so than by moon or wind alone (Fig 4,S2 Table). While previous studies have
identified the importance of moon and wind, this is the first time their interaction has been
This significant interaction underscores a conceptual model, whereby wind speed deter-
mines the magnitude of fledging birds departing their colonies, and the moon illumination
Fig 5. Moon illumination and fallout. Time series of the number of grounded WTSH observed per survey (bars) and nightly lunar illumination
(back line). The dates on the x-axis indicate the survey days.
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 11 / 17
Fig 6. Wind speed and fallout. Time series of the number of grounded WTSH observed per survey (bars) and nightly wind speed (back line). The
dates on the x-axis indicate the survey days.
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 12 / 17
determines the attraction of those fledglings toward onshore lighting. This conceptual model
can explain why years like 2016, when the peak of the fledging season coincided with a new
moon and high wind speeds, have greater fallout.
While the interaction of the lunar illumination and the wind speed was critical, the timing of
these variables, captured using their interactions with date, were less important. Together, these
results suggest that, within the time frame of our study, fallout is most dependent on the tempo-
ral overlap of low moon illumination and high winds, rather than on their specific timing.
Yearly models of WTSH fallout. The influence of the four predictor variables (wind
speed, wind direction, moon, and Julian date) were not consistent across all 8 study years.
While most previous studies have found strong negative relationships between moon illumina-
tion and fallout, our yearly models only documented this pattern in 2 years [4,8,10,11,33].
One possible explanation for this result could be a mismatch between moonrise / moonset
times and WTSH fledging. We used an average lunar disk illumination for the three nights
prior to each survey, assuming that this would be representative of visible moonlight while
WTSH were fledging. However, if most birds fledge shortly after sunset, before the moon rises
during waning moon phases, conditions will resemble a new moon [16,34]. Similarly, if island
topography or clouds obscure a rising moon from a given natal colony, the navigational bene-
fits provided by the lunar disk could be compromised until the moon rises over obscuring
landscape features. The peak fledging times of WTSH are unknown but could be useful to
improve our understanding of the influence of moonrise / moonset times on fallout. Further-
more, the lack of strong lunar trends in the yearly models could be due to small sample sizes,
with each year only involving 16 surveys.
Contrary to Rodrı
´guez et al. (2014), who documented a significant increase in fallout as the
fledging season progressed, our yearly models did not find a date effect. However, the likeli-
hood of finding an effect of date depends partly on the timing and the duration of the study
period. While opportunistic studies using intake records and citizen-science programs sample
a wider temporal window, spanning before and after the fledging season, our surveys spanned
a narrow temporal window during the WTSH fledging season. Thus, our results suggest that,
due to interannual variability in the timing and magnitude of fallout, on average it is distrib-
uted evenly throughout our study period (November 6 –December 21). Fledging primarily
occurs during this 6-week period, and is likely modulated by a variety of factors, including
breeding phenology, chick development, and environmental conditions [10,33,35].
The positive relationship between wind speed and fallout is likely related to the fledglings
using this environmental cue for fledging and relying on wind to take flight. One possible
explanation for why we observed more fallout with higher windspeeds is that intermediate to
strong windspeed enable WTSH to take flight, however a lack of flight experience and muscle
development may make it difficult for fledgling birds to navigate in strong winds, thus leading
to more fallout under higher wind speeds [36,37].
Although the model results suggest that wind speed is more important than wind direction,
an exception to this general pattern was observed in 2013, when peak fallout coincided with a
period of moderate to weak southerly winds (S1 Fig). A previous study on O‘ahu suggested
that winds from the southeast were more common during a year of very high fallout and
hypothesized that birds were advected to the northwest and deposited along the entire wind-
ward coast of the island [22]. The lack of significance of wind direction in years other than
2013 may be related to the prevailing wind patterns on windward O‘ahu, which rarely switch
from the northeast direction, thus limiting the comparison of different wind directions. Fur-
thermore, because south-westerly winds during the study are characterized by lower speeds,
any potential influence of direction is not independent from the wind speed effect discussed
previously (S2 Fig).
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
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Previous studies show an increase in fallout when prevailing winds are directed toward brightly
lit coastal areas [10,11]. Yet, the influence of wind direction is difficult to interpret since headings
are circular (0–360 degrees) and should be carefully considered on a case-by-case basis. Because
the prevailing winds in our study area are the northeasterly trade winds or southern (Kona)
storms, these bi-directional wind headings facilitated the analysis and simplified the interpreta-
tion. With the exception of 2013, peak fallout occurred during trade winds (Fig 6).
Although our study did not show a significant effect of Julian date on fallout, previous road
surveys from O‘ahu spanning ten years (2002 to 2010), revealed that November 25 was the
peak fallout date, with 67% of the grounded WTSH found during a one-week period (21–27
November) [21]. We hypothesize that the timing of the moon phase, in relation to this peak
fallout period could explain the interannual relationship of moon illumination and fallout.
Namely, higher fallout occurs in years when the new moon overlaps the peak fallout week (21–
27 November).
In 2015, the full moon occurred on November 28, whereas in 2013 and 2019 the moon
phase was closer to a new moon on that date. It appears that when peak fallout coincides with
a new moon, a single fallout peak occurs, thus causing a negative correlation with moon illu-
mination. However, if peak fallout coincides with a full moon, the unimodal pattern breaks
down, resulting in two smaller fallout peaks. Previous work yielded a quadratic relationship
between the timing of the full moon and the number of Newell’s shearwater (Puffinus newelli)
fallout, with fewer total groundings when the full moon occurred during the middle of the
month [5]. When we replicated this analysis for WTSH, the quadratic model was not signifi-
cant (R
= 0.038, F
= 1.140, p = 0.39), suggesting that annual fallout did not follow the same
pattern with the timing of the full moon. Although, other variables such as the timing of moon
rise, cloud cover, and topography blocking the moon were not taken into account and may
play a role in the moon’s influence on fallout. Demographic factors, involving the size of the
breeding population and the reproductive success likely influence the yearly supply of fledging
chicks [5].
Implications for fallout mitigation
Our results are reassuring because they suggest that the shielded LED streetlights did not
increase WTSH mortality due to fallout, as we hypothesized. Given the strong correlation
between the dead birds observed in our road surveys and the live birds brought to SLP, there is
no evidence suggesting that the shielded LED streetlights impacted the number of birds
affected by fallout overall. However, because these new lights did not reduce fallout, wildlife
managers may consider modifications such as dimming, wavelength alteration or motion sen-
sors, to mitigate negative impacts to fledging WTSH on O‘ahu [6,19].
A recent survey of lighting experts suggests that while LEDs can be adjusted to reduce light
pollution and minimize wildlife impacts, yet municipalities rarely capitalize on those benefits
[19]. For instance, although new-technology LED streetlights can filter out lower wavelengths
[17], full spectrum white LED lights maximize brightness, and are commonly chosen to
replace HPS streetlights. Furthermore, LEDs come in a variety of CCTs with options as low as
2200 K, the maximum temperature experts recommend for wildlife [17]. However, municipal-
ities commonly implement 3000–5000 K LED streetlights because of their efficiency for
human use [19]. Future studies should compare different LED lighting options in areas where
seabird fallout occurs to determine the characteristics that best mitigate negative impacts to
seabirds and other wildlife.
While it may be unfeasible to reduce light pollution wherever fallout occurs, areas near
breeding colonies could be targeted for localized management [21]. In addition to diminishing
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 14 / 17
light pollution during the fledging season, we also encourage community-based rescue efforts
for WTSH to target fallout hotspots on O‘ahu on nights with low moon illumination and
strong winds. Further documentation of fallout hotspots could help guide lighting manage-
ment and rescue efforts throughout the Hawaiian Islands.
Finally, predictive fallout models are limited by the lack of comprehensive annual popula-
tion estimates, which might have explained some of the interannual variation in the number of
grounded birds. Thus, annual WTSH breeding population sizes and reproductive success
would likely improve our understanding of fallout interannual variability and trends in
Hawai‘i. The findings and conclusions in this article are those of the authors and do not neces-
sarily represent the official views of the U.S. Fish and Wildlife Service.
Supporting information
S1 Table. Annual data from sea life park and road surveys. Comparison of annual WTSH
fallout magnitude (total number of grounded birds) and timing (date ranges) from Sea Life
Park intake records and road surveys (this study). Summary statistics (mean, median, and
range) refer to the number of grounded birds encountered yearly, based on 16 standardized
surveys spanning November 6 to December 21.
S2 Table. Variable importance in AICc analysis. Scaled average variable weights. (>1 values
indicate greater than average weight when variable was included in model; weights = 1 are
average, weights <1 less than average).
S1 Fig. Wind direction and fallout in 2013. Wind direction and fallout during the 2013 fledg-
ing season. Black line is wind direction and white bars are number of birds per survey.
S2 Fig. Wind speed and wind direction. Scatterplot of wind speed and wind direction during
the fledging seasons 2012–2019 (R
= 0.71).
S1 File. WTSH fallout data from road surveys. Data from road surveys (total = 128) includ-
ing variables year, Julian date, moon illumination (%), wind speed (knots), wind direction
(degrees), light regime (HPS = high pressure sodium, LED = light emitting diode), and num-
ber of grounded WTSH observed.
We would like to thank Jeff Pawloski for providing Sea Life Park intake records, David Field
and Susan Carstenn for input on the analysis and writing, and Pelagicos lab members who
assisted with the road surveys: Sarah Donahue, Michelle Hester, Angelica Moua, Anessa Mus-
grove, and Dan Rapp.
Author Contributions
Conceptualization: K. David Hyrenbach, Keith Swindle.
Data curation: Jennifer Urmston.
Formal analysis: Jennifer Urmston.
Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
PLOS ONE | March 24, 2022 15 / 17
Funding acquisition: K. David Hyrenbach.
Investigation: Jennifer Urmston.
Methodology: Jennifer Urmston, K. David Hyrenbach, Keith Swindle.
Project administration: K. David Hyrenbach.
Supervision: K. David Hyrenbach.
Visualization: Keith Swindle.
Writing – original draft: Jennifer Urmston.
Writing – review & editing: K. David Hyrenbach, Keith Swindle.
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Wedge-tailed shearwater fallout on O‘ahu, Hawai‘i
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... The most heavily affected species tend to be nocturnal and burrow-nesting (Rodríguez, Holmes, et al., 2017). Over the course of a fledging season, fallout may affect anywhere from a handful to a couple of thousand individuals (reviewed in Rodríguez, Holmes, et al., 2017;Wilhelm et al., 2021;Chevillon et al., 2022;Urmston et al., 2022). Among seabirds, at least 56 of 140 procellariiform species (40%; and one charadriiform species, Atlantic puffin, Fratercula arctica) have been affected (Rodríguez, Holmes, et al., 2017;Wilhelm et al., 2021). ...
... Young wedge-tailed shearwaters (Ardenna pacifica) are susceptible to stranding (e.g., Urmston et al., 2022) and are one of the only procellariiform species to have had its photoreceptors fully characterized to date. They have four cone-based visual pigments that are most sensitive to light wavelengths of 406, 450, 503, and 566 nm (Hart, 2004), approximately corresponding to violet, blueviolet, green, and yellow-green light, respectively. ...
Full-text available
A variety of anthropogenic threats cause mortality and population declines of procellariiform seabirds. Globally, fledglings of many colonial procellariiforms become stranded in towns and cities during their first flights from the nest, which occur at night. Since the 1960s, when the phenomenon became widely known, these strandings have been largely attributed to attraction toward artificial lights at night (ALAN). Artificial light attraction has been blamed due to the predictable, annual nature of strandings; the large numbers of birds found in lighted areas during stranding events; and the inexperience of fledglings in interpreting sensory stimuli. However, up‐to‐date, few alternative hypotheses to that of light attraction have been suggested, and few if any have been explored experimentally. In this paper, we do not seek to refute the light attraction hypothesis. Instead, our objectives are threefold. We wish to (1) highlight the current evidence for light attraction in procellariiforms; (2) identify where evidence may be lacking or subject to confirmation bias; and (3) suggest alternative hypotheses and possible experimental approaches to study them. Given the imperiled nature of many of the affected species and the need to explore and address this source of mortality, our goal in this review is to accelerate and diversify research efforts on this topic. A Leach's storm‐petrel (Oceanodroma leucorhoa) fledgling sits on a grassy lawn in Newfoundland after becoming stranded the previous night. Photo: Restoration Planet
... Likewise, rescue campaigns for grounded fledglings should be aware of not only the dates of the fledging period (covering a twomonth period, from the beginning of October to the end of November, with a peak in mid-October), but also the timing of fledging, which is often poorly known for seabird species, such as the related Wedge-tailed Shearwater (Urmston et al. 2022). For Newell's Shearwater, while there is a clear peak of fledging in the first few hours after dark, there is also a second peak a few hours before dawn. ...
The ‘a‘o, or Newell’s Shearwater Puffinus newelli, is an endangered shearwater species endemic to the Hawaiian Islands, with 90% of the world population found on Kaua‘i. Understanding the breeding phenology of the species is vital for identifying key periods for colony management actions and the timing and exposure frequency to infrastructure threats such as powerline collisions and light attraction. We used a combination of direct burrow monitoring and remote cameras at multiple colonies between 2012 and 2019 for a detailed assessment of the breeding phenology for this species. Breeding adults started arriving at the burrow in mid-April, some (but not all) underwent a two-week exodus in May and returned at the end of May to commence incubation. Incubation continued until mid-July. The chick-rearing period ran until the end of September. Fledging peaked in October with the last birds fledging towards the middle of November. Breeding was not synchronised, with a 59-day gap between the first and last fledging birds. The importance of this information to management actions is discussed, particularly in terms of directing management actions to key periods of vulnerability to introduced predators (such as peak incubation, chick emergence, and exercising prior to fledging), the precise timing of fledgling fallout related to light attraction, and directing colony-monitoring actions and translocation projects. We also consider the utility of the data in assessing species composition of powerline collisions and collision risk. Future work using acoustic monitoring is recommended for assessing the phenology of non-breeders and prospectors at colonies.
... Despite having the more intense light, HPS lights attracted and grounded the lowest number of fledglings, which was explained by the narrower range of wavelength emissions (Rodríguez et al., 2017a). However, a recent study did not find an increase in Wedge-tailed Shearwater fallout after the change from HPS to shielded 3000-4000K LED streetlights (Urmston et al., 2022). Intensity and color of the light play a role in the flying behavior of adults visiting the colony. ...
The attraction of seabirds to artificial lights leads to fallout and mortality events involving, in some cases, thousands of birds in a single breeding season. To mitigate light pollution-induced mortality the most common action is the rescue programs, but these programs rescue already grounded birds and do not address the cause of the problem. This chapter provides a summary of the mitigation actions to reduce the ecological consequences of light pollution based on the following management options, namely to (i) avoid or prevent the use of artificial light; (ii) limit the duration of lighting; (iii) reduce light spill; (iv) reduce the intensity of lighting; and (v) change light spectral composition. Finally, knowledge gaps and future research to better understand and mitigate this threat are identified. These are (i) the estimation of mortality and effects on populations; (ii) determination of threshold light levels and safe distances from light sources; (iii) documentation of the fate of rescued birds; (iv) improvement in rescue programs; and (v) research on seabird-friendly lights to minimize the attraction.
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There is increasing evidence for impacts of light pollution on the physiology and behaviour of wild animals. Nocturnally active Procellariiform seabirds are often found grounded in areas polluted by light and struggle to take to the air again without human intervention. Hence, understanding their responses to different wavelengths and intensities of light is urgently needed to inform mitigation measures. Here, we demonstrate how different light characteristics can affect the nocturnal flight of Manx shearwaters Puffinus puffinus by experimentally introducing lights at a colony subject to low levels of light pollution due to passing ships and coastal developments. The density of birds in flight above the colony was measured using a thermal imaging camera. We compared number of flying shearwaters under dark conditions and in response to an artificially introduced light, and observed fewer birds in flight during ‘light-on’ periods, suggesting that adult shearwaters were repelled by the light. This effect was stronger with higher light intensity, increasing duration of ‘light-on’ periods and with green and blue compared to red light. Thus, we recommend lower light intensity, red colour, and shorter duration of ‘light-on’ periods as mitigation measures to reduce the effects of light at breeding colonies and in their vicinity.
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ABSTRACT. Powerline collisions have been identified on Kaua'i as a potential contributing factor to the large-scale decline of both Hawaiian Petrel (Pterodroma sandwichensis) and Newell's Shearwater (Puffinus newelli), but the scale of the powerline collision problem is unknown. From 2012 to 2020 we conducted observations for seabird powerline collisions across Kaua'i, documented grounded seabirds, and assessed crippling and environmental biases - both poorly studied facets of powerline collision research. We directly observed 121 powerline collisions and detected 89 grounded seabirds. While some collisions resulted in birds falling lifelessly out of the sky, most resulted in seabirds flying or gliding outside of the search area. This means that traditional ground searches would underestimate total collisions by 78-88% if not accounting for crippling bias. We tested environmental bias by comparing our ability to conduct searches for grounded birds, "searchability", across multiple variables. Environmental bias resulted in significant reductions in searchability across regions, environment types, and powerline heights. Furthermore, observed collision rates were significantly higher at powerlines that had very low to zero searchability. Forty-three percent of observed collisions occurred at unsearchable powerlines (mainly spanning steep valleys), equating to an estimated 3170 seabird collisions that could not be detected through ground searches. We detected powerline collisions in every region of Kaua'i, in every environment type, and at all powerline heights monitored. Our results show that crippling bias and environmental bias are the mechanisms that concealed the geographic distribution of collisions and the scale of the powerline problem from grounded bird searches, ultimately preventing the detection of thousands of collisions. The data collected for this study are critical for assessing the scale of seabird powerline collisions and quantifying the biases inherent in traditional ground searches.
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This study evaluated temporal trends and spatial factors, such as fallout clustering near lights and proximity to colonies, to inform targeted management actions. Standardized surveys were conducted from 2002 to 2010 for Wedge-tailed Shearwater Ardenna pacifica (WTSH) fallout on the island of O‘ahu, Hawai‘i, USA. First, yearly fallout counts along the transect showed a two-year cycle and identified 25 November as the date with the highest fallout across years. Second, artificial lights and utility lines were present in 94% and 83% of fallout locations, leading to significantly higher fallout rates at these locations compared to random points along the transect. Third, fallout decreased significantly as the distance from the colonies increased and was negligible farther than 5 km from the nearest colony. Overall, 60% of all fallout occurred along a 1.7 km section of the survey route, with 27% of this fallout occurring within 8 m of two light poles, highlighting the need for targeted management. Finally, the disposition outcomes of rescued shearwaters from non-fatal fallout were analyzed. Among grounded individuals that were recovered alive, 78% were admitted for rehabilitation with no injury and released. This suggests that rescue efforts during high-risk periods that are focused within 5 km of colonies, in fallout hot spots, are likely to enhance survival. Because little is known about the environmental drivers of WTSH fallout, our results specify when, where, and how targeted management could be used most effectively to reduce fallout on O‘ahu. Our targeted approach may be applied in other regions where seabird fledging is heavily impacted by artificial lights.
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In Focus: Campioni L., Dias M. P., Granadeiro J. P., & Catry P. (2019). An ontogenetic perspective on migratory strategy of a long‐lived pelagic seabird: Timings and destinations change progressively during maturation. Journal of Animal Ecology, 89, 29–43. How migration routes develop in long‐lived migratory animals remains poorly understood. Campioni et al. (2019) tracked the migration of immature and breeding Cory's shearwaters and found that the timings and routes gradually changed with age. Young birds followed more exploratory routes at first, but gradually shortened and defined them as they matured, and they returned to the breeding grounds progressively earlier. These findings suggest that long‐lived species start by exploring potentially suitable areas for the non‐breeding season and progressively refine their migration route as they age. This paper looks in detail at the important findings of Campioni et al. (2019), which show that long‐lived birds explore and refine their migration routes with age, and discusses the implications of these findings for the field of animal migration.
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In the 21st century, the notion of “sustainable lighting” is closely associated with LED technology. In the past ten years, municipalities and private light users worldwide have installed light-emitting diodes in urban spaces and public streets to save energy. Yet an increasing body of interdisciplinary research suggests that supposedly sustainable LED installations are in fact unsustainable, because they increase light pollution. Paradoxically, blue-rich cool-white LED lighting, which is the most energy-efficient, also appears to be the most ecologically unfriendly. Biologists, physicians and ecologists warn that blue-rich LED light disturbs the circadian day-and-night rhythm of living organisms, including humans, with potential negative health effects on individual species and whole ecosystems. Can the paradox be solved? This paper explores this question based on our transdisciplinary research project Light Pollution—A Global Discussion. It reveals how light pollution experts and lighting professionals see the challenges and potential of LED lighting from their different viewpoints. This expert feedback shows that “sustainable LED lighting” goes far beyond energy efficiency as it raises complex design issues that imply stakeholder negotiation. It also suggests that the LED paradox may be solved in context, but hardly in principle.
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The introduction and widespread uptake of LEDs as outdoor lighting has caused no small amount of concern amongst conservation biologists. The prevailing impression that LEDs are always blue-white is well founded as adoption of LEDs for streetlights were invariably high color temperatures and with the deterioration of phosphors the blue wavelengths penetrated even more. But LEDs do have characteristics that differentiate them from other light sources and may allow for the reduction of environmental effects of lighting on species and habitats: direction, duration, intensity, and spectrum. Travis Longcore, Assistant Professor at the University of Southern California’s School of Architecture, sheds light on all these aspects.
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For many decades, the spectral composition of lighting was determined by the type of lamp, which also influenced potential effects of outdoor lights on species and ecosystems. Light‐emitting diode (LED) lamps have dramatically increased the range of spectral profiles of light that is economically viable for outdoor lighting. Because of the array of choices, it is necessary to develop methods to predict the effects of different spectral profiles without conducting field studies, especially because older lighting systems are being replaced rapidly. We describe an approach to predict responses of exemplar organisms and groups to lamps of different spectral output by calculating an index based on action spectra from behavioral or visual characteristics of organisms and lamp spectral irradiance. We calculate relative response indices for a range of lamp types and light sources and develop an index that identifies lamps that minimize predicted effects as measured by ecological, physiological, and astronomical indices. Using these assessment metrics, filtered yellow‐green and amber LEDs are predicted to have lower effects on wildlife than high pressure sodium lamps, while blue‐rich lighting (e.g., K ≥ 2200) would have greater effects. The approach can be updated with new information about behavioral or visual responses of organisms and used to test new lighting products based on spectrum. Together with control of intensity, direction, and duration, the approach can be used to predict and then minimize the adverse effects of lighting and can be tailored to individual species or taxonomic groups. The intersection of response curves and lamp spectra describes potential impacts of nighttime lighting on insects, sea turtles, Newell's Shearwater, and juvenile salmon, as well as their average, compared with equal brightness in lux of daylight (D65; 6500K) within the range 350–780 nm.
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Human disturbances are increasingly becoming a conservation concern for many populations of colonial seabirds. Colonially reproducing species are particularly vulnerable to localised disturbances because detrimental elements can simultaneously affect the entire population. Studies of petrels and shearwaters have shown that light pollution, in particular, can be harmful for both fledglings and adults, but little is known of the way such anthropogenic elements affect the quality of parental care at the nest. Chick provisioning in petrels and shearwaters occurs exclusively at night and is also negatively correlated with the amount of moonlight. We tested the hypothesis that high-intensity light and sound disturbances will disrupt nest attendance and thus affect weight gain in chicks but that the magnitude of such effects would be modulated by moonlight conditions. We measured the effect of two outdoor disco events on overnight weight gain in 26 chicks of Scopoli’s shearwaters (Calonectris diomedea) from a breeding colony on Linosa Island. The two disco events occurred under contrasting moonlight conditions (moonless vs moonlight). Chicks situated closer to the disturbance gained significantly less weight compared to conspecifics from nests further away but the effect was only evident on the moonless night.Our results suggest that light and sound disturbances can have a negative effect on parental care in C. diomedea but moonlight might moderate the bird’s perception and thus the magnitude of the disturbance. However, while occasional disturbances may impact short-term weight gain in C. diomedea chicks, such effects are not perceivable at fledging when measured as differences in the weight or the date at which they left the nest.
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Grounding of thousands of newly fledged petrels and shearwaters (family Procellariidae) in built-up areas due to artificial light is a global problem. Due to their anatomy these grounded birds find it difficult to take off from built-up areas, and many fall victim to predation, cars, dehydration or starvation. This research investigated a combination of several factors that may influence the number of Manx Shearwater Puffinus puffinus groundings in a coastal village of Scotland located close to a nesting site for this species. A model was developed that used meteorological variables and moon cycle to predict the daily quantity of birds that were recovered on the ground. The model, explaining 46.32% of the variance of the data, revealed how new moon, and strong onshore winds influence grounding. To a lesser extent, visibility conditions can also have an effect on grounding probabilities. The analysis presented in this study can improve rescue campaigns of not only Manx Shearwaters but also other species attracted to the light pollution by predicting conditions leading to an increase in the number of groundings. It could also inform local authorities when artificial light intensity needs to be reduced.