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Influence of industrial light pollution on the sea-finding behaviour of flatback turtle hatchlings

Authors:
  • Pendoley Environmental Pty Ltd

Abstract and Figures

Context. Numerous studies show that artificial light disrupts the sea-finding ability of marine turtle hatchlings. Yet very little has been published regarding sea-finding for flatback turtles. Given the current industrialisation of Australia's coastline, and the large potential for disruption posed by industrial light, this study is a timely investigation into sea-finding behaviour of flatback turtle hatchlings. Aims. We investigate sea-finding by flatback turtle hatchlings in relation to ambient light present in areas of planned or ongoing industrial development, and evaluate the fan and arena-based methods that are frequently used for quantifying hatchling dispersion. Methods. Using a combination of methods, we assessed the angular range and directional preference of sea-finding hatchlings at two key flatback turtle rookeries, Peak and Curtis Islands, during January–February 2012 and 2013, and at Curtis Island in January 2014. Relative light levels at each site were measured using an Optec SSP-3 stellar photometer, and moon phase, moon stage and cloud cover were also recorded. Key results. We found no evidence of impaired hatchling orientation, and observed very low levels of light at Peak Island. However, at Curtis Island, hatchlings displayed reduced sea-finding ability, with light horizons from the direction of nearby industry significantly brighter than from other directions. The sea-finding disruption observed at Curtis Island was less pronounced in the presence of moonlight. Conclusions. The reduced sea-finding ability of Curtis Island hatchlings was likely due to both altered light horizons from nearby industry, as well as beach topography. Both methods of assessing hatchling orientation have benefits and limitations. We suggest that fan-based methods, combined with strategically placed arenas, would provide the best data for accurately assessing hatchling sea-finding. Implications. Sky glow produced by large-scale industrial development appears detrimental to sea-finding by flatback turtle hatchlings. As development continues around Australia's coastline, we strongly recommend continued monitoring of lighting impacts at adjacent turtle nesting beaches. We also advise rigorous management of industrial lighting, which considers cumulative light levels in regions of multiple light producers, as well as moon phase, moon-stage, cloud cover and time of hatchling emergence. All these factors affect the likelihood of disrupted hatchling sea-finding behaviour at nesting beaches exposed to artificial light-glow, industrial or otherwise.
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Inuence of industrial light pollution on the sea-nding
behaviour of atback turtle hatchlings
Ruth L. Kamrowski
A,D
, Col Limpus
B
, Kellie Pendoley
C
and Mark Hamann
A
A
School of Earth and Environmental Sciences, James Cook University, Townsville, Qld 4811, Australia.
B
Department of Environment and Heritage Protection, PO Box 2454, Brisbane, Qld 4001, Australia.
C
Pendoley Environmental Pty Ltd, 12A Pitt Way, Booragoon, WA 6154, Australia.
D
Corresponding author. Email: ruth.kamrowski@my.jcu.edu.au
Abstract
Context. Numerous studies show that articial light disrupts the sea-nding ability of marine turtle hatchlings. Yet very
little has been published regarding sea-nding for atback turtles. Given the current industrialisation of Australias
coastline, and the large potential for disruption posed by industrial light, this study is a timely investigation into sea-
nding behaviour of atback turtle hatchlings.
Aims. We investigate sea-nding by atback turtle hatchlings in relation to ambient light present in areas of planned
or ongoing industrial development, and evaluate the fan and arena-based methods that are frequently used for quantifying
hatchling dispersion.
Methods. Using a combination of methods, we assessed the angular range and directional preference of sea-nding
hatchlings at two key atback turtle rookeries, Peak and Curtis Islands, during JanuaryFebruary 2012 and 2013, and at
Curtis Island in January 2014. Relative light levels at each site were measured using an Optec SSP-3 stellar photometer,
and moon phase, moon stage and cloud cover were also recorded.
Key results. We found no evidence of impaired hatchling orientation, and observed very low levels of light at Peak
Island. However, at Curtis Island, hatchlings displayed reduced sea-nding ability, with light horizons from the direction
of nearby industry signicantly brighter than from other directions. The sea-nding disruption observed at Curtis Island
was less pronounced in the presence of moonlight.
Conclusions. The reduced sea-nding ability of Curtis Island hatchlings was likely due to both altered light horizons
from nearby industry, as well as beach topography. Both methods of assessing hatchling orientation have benets and
limitations. We suggest that fan-based methods, combined with strategically placed arenas, would provide the best data
for accurately assessing hatchling sea-nding.
Implications. Sky glow produced by large-scale industrial development appears detrimental to sea-nding by atback
turtle hatchlings. As development continues around Australias coastline, we strongly recommend continued monitoring
of lighting impacts at adjacent turtle nesting beaches. We also advise rigorous management of industrial lighting, which
considers cumulative light levels in regions of multiple light producers, as well as moon phase, moon-stage, cloud cover
and time of hatchling emergence. All these factors affect the likelihood of disrupted hatchling sea-nding behaviour at nesting
beaches exposed to articial light-glow, industrial or otherwise.
Additional keywords: industrial development, marine turtle, Natator depressus, orientation, Port Curtis.
Received 2 May 2014, accepted 18 October 2014, published online 20 February 2015
Introduction
Neonate marine turtles surfacing from underground nests must
reach the ocean with minimal delays. This ability is dependent
upon visual cues (Lohmann et al.1997; Witherington and Martin
2000); hatchlings evaluate their surroundings by scanning the
visible horizon and crawling towards areas of low horizon
elevation and brighter light (Limpus 1971; Limpus and
Kamrowski 2013), and away from areas of high, dark
elevation (Salmon et al.1992; Salmon 2003). Articial
lighting close to the nesting beach can mask a hatchlings
ability to see natural light horizons and hence disrupt sea-
nding, reducing hatchling survival chances (Witherington and
Martin 2000; Tuxbury and Salmon 2005). Problematic light
sources include those directly visible to hatchlings, such as
streetlights (Sella et al.2006), but sky glow from indirect
sources of light can also inuence hatchling behaviour
(Salmon et al.1995; Salmon 2006). Sky glow is considered to
make a signicant contribution to ecological light pollution (Rich
and Longcore 2006; Kyba et al.2011), and turtle orientation
has been disrupted by light produced at distances of up to 18 km
CSIRO PUBLISHING
Wildlife Research,2014, 41, 421434
http://dx.doi.org/10.1071/WR14155
Journal compilation CSIRO 2015 www.publish.csiro.au/journals/wr
from the nesting beach (Hodge et al.2007). The relative
brightness, and therefore potentially disorienting impact, of
articial lighting also uctuates as a function of moon phase,
with sea-nding disruption generally greatest during new moon
conditions and much reduced when the moon is full (e.g. Salmon
and Witherington 1995; Tuxbury and Salmon 2005; Berry et al.
2013). This is thought to be because moonlight reduces the
directional light intensity gradients caused by articial
lighting, thereby allowing hatchlings to discern natural horizon
elevation cues (Salmon and Witherington 1995; Limpus and
Kamrowski 2013).
Hatchling sea-nding behaviour is typically assessed in
eld-based studies using arena and/or fan-mapping methods.
Arena methods are simulated emergence events where
directional movement of hatchlings can be assessed under
different environmental and lighting conditions, in a controlled
and staggered manner (e.g. Mrosovsky 1970; Witherington
and Bjorndal 1991a; Salmon et al.1995; Bertolotti and
Salmon 2005). In fan-mapping, tracks left in the sand
overnight during natural nest emergences are examined at
dawn the following morning for the angular range, and the
modal or central bearing of tracks (Salmon and Witherington
1995; Pendoley 2005; Berry et al.2013; Limpus and Kamrowski
2013). The choice of method used is likely dependent upon its
perceived appropriateness for the research question under
examination (e.g. Stewart et al.2001), and frequently both
methods are used within a study (e.g. Salmon and
Witherington 1995; Pendoley 2005; Berry et al.2013).
However, few studies specify why one or both methods were
selected for use (but see Pendoley 2005). As levels of articial
lighting continue to increase around the world (Elvidge et al.
2011; Pestalozzi et al.2013; Kamrowski et al.2014), light
pollution will likely impact previously unaffected nesting
beaches, and it is therefore important that the methods that are
used to assess such impacts are clearly understood and
appropriate. This will be possible only when fan and arena
methods are evaluated and the limitations of each understood
(e.g. Hargis et al.1998).
Furthermore, although disrupted sea-nding by hatchlings
due to articial lighting has been well studied, little of these
published data have originated from Australia despite large
nesting aggregations of marine turtles (Limpus 2009) (but see
Limpus 1985; Pendoley 2000,2005; Berry et al.2013). This is
of concern since caution is necessary when using well studied
populations and species to extrapolate behaviour to other
populations and species (Crossin et al.2004; Pulido 2007).
For example, loggerhead turtle hatchlings from separate
nesting groups within the same Florida subpopulation were
found to differ signicantly in initial offshore migratory
activity (Wyneken et al.2008), and the initial frenzyperiod
of hatchling green turtles from Malaysia (Chung et al.2009)
appears to be almost double that found for green turtles from
Florida (Wyneken and Salmon 1992; Salmon et al.2009). As
such, behavioural differences in the early orientation and
dispersion mechanisms of Australian turtle hatchlings may
exist; indeed, a recent study indicates that crawling Australian
turtle hatchings do not respond in the same way to certain
wavelengths of articial lights as their conspecics in the USA
(Fritsches 2012).
The atback turtle, Natator depressus, is a marine species
endemic to the Australian continental shelf, and all known nesting
sites occur within Australia (Limpus 2009). The life history of
the atback turtle is markedly different from that of the other
hard-shelled marine turtles (Salmon et al.2009). It is the only
species that lacks an oceanic phase in its life cycle (Walker and
Parmenter 1990), with the posthatchlings remaining within
pelagic continental shelf waters. Flatback turtle hatchlings are
also almost twice as large as other hard-shelled turtle hatchlings
(Walker and Parmenter 1990; Van Buskirk and Crowder 1994),
and they display a swimming strategy during offshore migration
that has not been seen in other species (Salmon et al.2009;
Hamann et al.2011; Pereira et al.2011,2012). Therefore, it is
crucial that the early orientation behaviour of atback turtle
hatchlings is documented to prevent management measures
being based on behavioural knowledge extrapolated from
different species and populations with potential differences in
behaviour (Dryden et al.2008).
Four distinct population management units (MU) are
currently recognised for atback turtles within Australia
(Limpus 2009). The smallest population is the eastern
Australian MU, where the largest rookeries support nesting
by between 100 and 500 females annually (Limpus 2009).
Census data indicate that the size of the eastern Australian
MU is stable at most of the index nesting sites; however, one
of the largest rookeries in eastern Australia (Peak Island) has
shown a declining nesting population across several decades of
taggingrecapture monitoring (Department of Environment and
Heritage Protection 2013) despite a high level of habitat
protection (GBRMPA 2008). The cause of this localised
decline is unclear; however, disturbance linked to adjacent
coastal development has been advanced as a possible
contributing factor (Department of Environment and Heritage
Protection 2013). Industrial development and urban areas are
both growing rapidly in Australia, particularly along the
Queensland coast (Australian Bureau of Statistics 2011;
Grech et al.2013), and recent studies have determined that
levels of articial light are both high (Kamrowski et al.2012)
and increasing signicantly faster at nesting areas for eastern
Australian atback turtles than for any other turtle population in
Australia (Kamrowski et al.2014). Since the successful
functioning of the eastern Australian atback MU is facing
an increased risk of disrupted hatchling orientation from
changing light horizons, an examination of sea-nding
behaviour of hatchlings in this MU is imperative.
In this study we examined sea-nding behaviour of atback
turtle hatchlings during dispersal from the nest at rookeries
located in areas of planned or ongoing industrial development
to (1) compare and evaluate arena- and fan-based methods to
provide insights into the optimum method for quantifying
hatchling dispersion from the nest, (2) compare sea-nding
ability of hatchlings relative to levels of ambient lighting
present at the nesting beach, (3) evaluate whether moonlight
moderates potential disruption of sea-nding by hatchlings in
the presence of industrial light-glow. In addition, since it was
necessary to collect hatchlings for arena trials, we also
documented time of nest emergence during this study because
no published data appear to exist regarding time of emergence
for atback hatchlings in eastern Australia.
422 Wildlife Research R. L. Kamrowski et al.
Materials and methods
Study sites and context
Data were collected at two key east Australian atback turtle
rookeries, where annual monitoring is conducted Peak Island
and Curtis Island (Fig. 1) (Limpus et al.2006; Limpus 2009)
during the 201112, 201213, and 201314 (Curtis Island only)
nesting seasons (Table 1). Moon phase during data collection is
summarised in Table 1, with moon phase data obtained from
www.timeanddate.com for Rockhampton, Queensland.
Peak Island supports the largest atback turtle nesting
population for the east Australian MU (Limpus 2009) and is
located ~13 km from the mainland in Keppel Bay. Nesting occurs
along a 300 m stretch of west-facing beach (Fig. 1i), by ~300
females annually (Parmenter and Limpus 1995). However, the
population is declining (Department of Environment and
Heritage Protection 2013). Most nesting occurs in the northern
half of the beach but does occur along the entire beach length.
The island has a National Park (Scientic) designation, which
is the highest level of habitat protection possible under the
State GovernmentsNature Conservation Act 1992. The
surrounding waters to a distance of 1 km are also protected to
a high level, classied as Preservation Zone in the Great Barrier
Reef Marine Park (GBRMP) zoning plan. This habitat
management provides strong localised protection (GBRMPA
2008). However, inshore from Peak Island there is coastal
urban and tourist development along the mainland coast of
Keppel Bay, as well as proposed industrial developments
within the adjacent Fitzroy River Delta. Xstrata Coal proposed
the development of a coal export facility at Balaclava Island in
the Fitzroy River Delta. Work on the Balaclava Island Coal
Export Terminal project began in 2009 and a draft
Environmental Impact Statement was developed before the
project was suspended in May 2013 in response to economic
concerns surrounding the Australian coal market. However,
expansion of another coal export facility in the same area, the
Fitzroy Terminal project, is still ongoing, with the Environmental
Impact Statement in development.
Curtis Island, which is part of the seaward margin to Port
Curtis at Gladstone, Queensland, supports a moderate-sized
atback turtle nesting population of 50100 females each year
(Limpus 2009). Nesting is mainly concentrated at the south-
eastern end of the island at the 5-km-long Southend Beach.
Most clutches are laid at the northern end of the beach
(between X and Y in Fig. 1ii). At-risk clutches laid on the
southern half of the beach, which is prone to substantial dune
erosion, are often relocated further north. Signicant industrial
development of Port Curtis has occurred since the 1960s, and
today the region contains more than 10 000 ha of industrial
land within the largest multicommodity port in Queensland.
It includes the States largest power station, an aluminium
renery and smelter, a cement production works, chemical
X
Y
Peak
Island
Queensland
0 150 300 m 02040 km
Southend Settlement
Gladstone
N
(i)(ii )
Curtis
Island
Queensland
Mainland
X
Y
Fig. 1. Study sites with dashed line indicating the nesting beach. (i) Peak Island: X denotes approximate
location of Arena 1 (2320.575S, 15056.006E), Y denotes approximate location of Arena 2 (2320.625S,
15056.108E). Inset: location in Australia. (ii) Curtis Island and Gladstone. Inset: location of Southend
Beach on Curtis Island. X denotes approximate location of Arenas 1 and 3 (2343.155S, 15117.738E),
Y denotes approximate location of Arena 2 (2343.926S, 15117.819E). Most nests naturally occurred
between X and Y. Grey star indicates approximate location of LNG plants; grey circle denotes location of
proposed tourist resort.
Table 1. Moon phase during data collection
Location Type of data collection Date of data collection Moon phase
Peak Island Fan-mapping, arena trials 23 January 2 February 2012 New moon and rst quarter
Light measurements 31 January 14 February 2013 Full moon and last quarter
Curtis Island Fan-mapping, 619 February 2012 Full moon and last quarter
Arena trials, light measurements 823 January 2013 New moon and rst quarter
Fan-mapping only 2125 January 2014 Last quarter
Flatback hatchlings and industrial light Wildlife Research 423
plants, and an international harbour (Duke et al.2003). Industrial
development of the port is ongoing (Danaher et al.2005) and the
regions urban population is also expected to rise over the next
decade (Duke et al.2003). More recently, three liqueed natural
gas (LNG) plants are currently under construction on the south-
western side of Curtis Island itself, with a fourth LNG
development recently approved. These plants are located
812 km inland from the Southend nesting beach. In addition,
a large tourist resort is planned for Turtle Street Beach, separated
by 6 km of rocky shore north from the nesting beach at Southend.
Light horizons were quantied in September 2011 during the
new moon (Pendoley Environmental 2011) and showed a skyline
highly modied by articial lighting.
Hatchling collection
The beaches at Peak Island and Curtis Island were patrolled each
afternoon preceding data collection; at nests where hatchling
emergence was imminent (characterised by a depression in the
sand indicating that eggs have hatched and hatchlings have begun
to crawl upwards: Salmon and Wyneken 1990), a plastic mesh
fence (gutterguard) was dug into the sand, forming a circle of
2 m diameter, to prevent hatchlings crawling away from the nest
site. These corralswere monitored every 30 min throughout
the night, and removed at sunrise. When an emergence event
occurred, up to 20 hatchlings were randomly selected from
the clutch and placed into an uncovered bucket containing a
shallow layer of damp sand, for immediate use in arena trials
(<30 min from collection to release).
At Peak Island, hatchlings were also collected using a drift-
fence-pit-trap system (after Limpus 1985). A plastic mesh fence
(gutterguard) and bucket were dug into the sand along 25 m of
beach, above the high-water mark (located approximately at X
in Fig. 1i). The square mesh formed a barrier 15 cm above the
beach surface, and was laid in a V-shaped manner that
intercepted hatchlings crossing the beach and directed them
towards a bucket buried in the sand, located in the centre of
the V. The trap was checked for hatchlings at 1-h intervals,
or sooner, for the duration of deployment. The trap also allowed
us to document time of hatchling emergence. The number of
individual hatchlings found in the bucket or along the fence was
recorded for 14 24-h periods between 31 January and 16 February
2013. The trap was located in the section of beach where the
highest density of nests occurred at Peak Island, to ensure a large
sample size.
Hatchling sea-nding ability: Arenas
Following the methodology of Bertolotti and Salmon (2005),
circles of 5-m diameter were created in the dry sand above the
high water mark, where beach slope was minimal (to avoid
hatchlings having slope as a seaward orientation cue: Salmon
et al.1992; Kawamura et al.2009). The sand was raked and
cleared until smooth and free from debris and vegetation, and a
small depression created in the centre. Arenas were located in
approximately the same locations in 2012 and 2013 (see Fig. 1).
At Peak Island, hatchlings were tested in arenas at both northern
and southern ends of the beach, ~250 m apart. The northern arena
was located in a section of the beach where most nests naturally
occurred. Both arenas were characterised by a high visible
horizon in a landward direction. At Curtis Island, the 2012
arenas were located at the northern (Arena 1) and southern
(Arena 2) boundaries of most turtle nesting, ~2 km apart. The
northern portion of the beach at Curtis Island was characterised
by two rows of dunes running approximately parallel to the
ocean with a prominent swale (trough) between them (Fig. 2),
and in 2013 an extra arena (Arena 3) was added at the base of
this swale in the northern section of the beach behind Arena 1.
During trials, we released groups of ve hatchlings in the
arenas central depression and gave them 3 min to crawl to the
edge. Any hatchlings remaining within the arena at the end of
3 min were excluded from the analysis. Two researchers,
remaining out of sight of the hatchlings, were positioned
landward and seaward of the arena. They collected hatchlings
after they exited the circle and recorded the compass bearings
from the centre of the arena to the exit point for each hatchling.
The sand was then swept smooth and the procedure repeated
with different hatchlings. No hatchling was tested more than
once, and after each trial hatchlings were released at the high
tide mark and all crawled to the ocean.
Hatchling sea-nding ability: Fans
Fan-mapping techniques were based on the methodology of
Pendoley (2005). All observed emergences at Peak and Curtis
Islands (Table 1) were examined at dawn. Dispersion patterns
for emergences with ve or more clear hatchling tracks were
recorded using fan spread angle (i.e. AB, where A and B are
compass bearings from the nest along the outside edges of
the track fan), and offset angle (the difference between the fan
spread angle midpoint and a compass bearing along the shortest
route to the ocean) (Fig. 3).
In 2012, the bearings of A, B and the shortest route to the
ocean, were recorded at a distance of 2 m from the nest origin. This
was closer to the nest than in previous studies that specied this
distance (Salmon and Witherington 1995; Limpus and
Kamrowski 2013), yet was necessary due to high nest and
hatchling emergence density at Peak Island (which was the
rst location visited in 2012). In 2013, we elected to measure
fans at both 2 m and 5 m, where possible, to determine whether
measurements differ depending upon the distance taken from the
nest origin. This was possible for all emergences at Curtis Island.
NOcean
Fig. 2. The northern portion of Southend Beach at Curtis Island. This section
of beach is characterised by two rows of dunes (dashedline), with a prominent
swale between them, running approximately parallel to the ocean.
424 Wildlife Research R. L. Kamrowski et al.
Data at Peak Island were collected later in the season in 2013,
following extreme weather, and, with the resultant reduced
nest density, we were able to measure fan angles at 2 m and
5 m from the nest origin for a large proportion of nests. We were
thus also able to make comparisons of fan orientation indices
between years at both study sites, and also with fan measurements
taken in previous studies. Since track fans expand as hatchlings
travel further from the nest, the difference between taking
compass bearings at 2 m versus 5 m was predicted to be
insignicant.
Ambient light
Relative light levels were measured in each of the eight cardinal
directions (N, NE, E, SE, S, SW, W, NW) at regular intervals
throughout the night (between 20 : 00 and 04 : 00 hours) and
immediately after each arena trial. We followed the
methodology employed by Bertolotti and Salmon (2005), and
used an Optec SSP-3 stellar photometer, with the V lter inserted
(wavelength range 480660 nm). The maximum sensitivity of
this lter, at 540 nm, is close to peak sensitivity to light of
atback turtle hatchlings, since they appear to have a
preference to light of ~500 nm, with a reduced sensitivity to
shorter wavelengths of light compared with other species
(Pendoley 2005). The photometer was attached to a tripod and
positioned 0.5 m above the sand surface, just outside the arena
boundary. The instrument was positioned at 15elevation in
the vertical plane (corresponding with light intensity just above
the horizon line, but within the generally accepted 30visual
cone of acceptancefor hatchlings: Witherington 1997), and
measurements recorded as the tripod was rotated in 45
increments, through 360. With an aperture of 0.002 inch
diameter, the instrument has a very small cone of visibility,
thus measurements taken in each direction did not overlap
with brightness measurements of any other direction.
Measurements taken when the photometer was pointed
directly at the moon (during rising or setting) were excluded
from further analysis since the very high light levels recorded
skewed the overall results. Light values were converted into a
log
10
scale, and relative light levels drawn as radiance octagons,
which spanned an intensity range of two log units. Each time
light measurements were collected, cloud cover was also
recorded qualitatively in oktas (a standard meteorological
measurement where one okta represents one-eighth of the
hemispherical sky being occupied by cloud) (Rogers and Yau
1989).
Although used in several studies for assessing lighting
impacts on marine turtles (Salmon et al.1992,1995; Salmon
and Witherington 1995; Bertolotti and Salmon 2005; Sella
et al.2006), stellar photometers have several limitations. First,
there are different gain settings available, and the instrument
set to a lower gain may show very little data variation despite
possible light differences, whilst a higher setting may show large
variations under the same atmospheric conditions. In addition,
ambient temperature interacts with gain settings, with warmer
conditions producing more electronic noise in the data
(A. Verveer, Perth Observatory, pers. comm.). Therefore, we
used the stellar photometer to record light levels using an identical
gain setting for all measurements, as a means of supporting
judgements of relative brightness made by researcher
observations. However, since it was not possible to control for
ambient temperature, we only made comparisons between light
measurements taken over a very short period. Thus we did
not directly compare measurements between locations or
across years of data collection.
Analysis
Data were analysed using the statistical software programs
IBM SPSS 20 and Oriana 3 for Windows. Standard circular
descriptive statistics were calculated for arena data (Zar 2010),
bimodal distributions were dealt with using an angle-doubling
procedure (Batschelet 1981) and the Rayleigh test was used to
determine whether hatchlings were signicantly oriented. The V
test, a variant of the Rayleigh test, was employed to compare
mean arena escape angle of hatchlings with the shortest route to
the ocean, and Watson U
2
tests were used to compare hatchling
orientation with and without a visible moon (Mardia and Jupp
2000). Fan and arena data, representing grouped and individual
hatchling orientation, respectively, were not compared using
statistical analysis, but were compared qualitatively using
angular range of tracks and the respective measure of central
tendency for hatchling orientation (i.e. fan midpoint and mean
bearing in arena trials).
Results
Hatchling sea-nding ability: Arenas
At Peak Island, 302 hatchlings from 19 clutches in 2012 and 98
hatchlings from 15 clutches in 2013 were tested in arena trials.
Two hatchlings each year failed to leave the arena within the
allotted time and were thus excluded from the analysis. At Curtis
Island, 87 hatchlings from 5 clutches were tested in 2012, and
213 hatchlings from 15 clutches in 2013 (Fig. 4and
supplementary material).
Hatchlings in all arenas showed signicant orientation
(Rayleigh test: P0.001), and in every arena except the swale
A
X
C
B
Offset angle (X-C)
Nest emergence point
Beach
Ocean
Spread angle (A-B)
Fig. 3. Fan mapping methodology for hatched nests. A and B represent
compass bearings marking the outer edges of the hatchling dispersion tracks. C
is the midpoint of the spread, and X is the shortest route to the ocean (redrawn
from Pendoley 2005).
Flatback hatchlings and industrial light Wildlife Research 425
arena (Arena 3) at Curtis Island, hatchlings were signicantly
oriented in the direction of the ocean (V-test: P<0.001).
Although hatchlings tested in arenas where hatchlings had an
unobstructed view of the ocean (1 and 2), at both locations, were
signicantly oriented towards the ocean, the circular standard
deviation of tracks and angular dispersion (r) of hatchlings at
Curtis Island were both higher than found at Peak Island (Fig. 4).
Hatchlings at Curtis Island in the swale arena (Arena 3: behind
the rst dune, with no view of the ocean) were not signicantly
oriented towards the ocean. Qualitative examination of Fig. 4
indicated that the distribution of hatchling exit points in the
swale arena (3) at Curtis Island was bimodal, roughly 180
apart. Lack of unimodality was conrmed with the Kuipers
test (von Mises V = 3, P<0.01). The dominant modes were in
the intervals 120150(n= 30), and 330360(n= 28).
Hatchling sea-nding ability: Fans
Hatchling fan orientation indices are summarised in Table 2.
Following log
10
-transformation of spread and offset angles
measured at 2 m in 2012 and 2013, multivariate analysis
of variance (MANOVA) was carried out with spread and
offset angles as dependent variables, and year and location as
independent variables. There was a signicant multivariate
Peak Is
Curtis Is
Curtis Is
2012 2013 2012 2013
Arena 1 (N) Arena 2 (S)
N
Arena 3 (swale)
^ = 236.5° (mean: 299.5° after angle doubling procedure)
n = 100
r = 0.616
^ = 21°
n = 35
r = 0.709
^ = 5°
n = 143
r = 0.958
^ = 21.5°
n = 48
r = 0.918
^ = 9°
n = 157
r = 0.97
^ = 16°
n = 48
r = 0.985
^ = 56°
n = 62
r = 0.619
^ = 6.5°
n = 52
r = 0.873
^ = 30°
n = 51
r = 0.872
Fig. 4. Rose diagrams showing dispersion of atback turtle hatchlings during arena trials at Peak and
Curtis Island in 2012 and 2013. Each grey wedge represents 10of the total circular range and wedge
area depicts the number of observations falling within that portion of the range. The straight black lines
indicate mean bearing, with mean bearing for Curtis Arena 3 shown following an angle-doubling
procedure (Batschelet 1981). Curved black lines show 95% condence intervals. The asterisk
indicates the direction of the ocean. ^ indicates the difference between mean bearing and the ocean
direction. r is a measure of angular dispersion where 0 = uniform dispersion, and 1 = concentrated in one
direction.
426 Wildlife Research R. L. Kamrowski et al.
effect of location (P<0.01) for the orientation indices taken
together, but no signicant effect of year (P= 0.11). The
interaction between year and location was also signicant
(P<0.05). Follow-up univariate analyses indicated a
signicant effect of location for both spread (P<0.001) and
offset angle (P<0.001), with no signicant effect of year for
both spread (P= 0.11) and offset (P= 0.1). There was no
signicant interaction between year and location for offset
angle (P= 0.08), indicating that offset angle did not differ
signicantly at either location between years, but was
signicantly higher for hatchlings at Curtis Island than at Peak
Island. There was a signicant interaction between year and
location for spread angle (P<0.05). Further examination of the
data indicated that spread angle was signicantly higher for
hatchlings at Curtis Island than at Peak Island in 2012, but
there was no signicant difference in spread angle between
Curtis Island and Peak Island hatchlings in 2013, and spread
angle was signicantly lower for Curtis Island hatchlings in
2013 than in 2012.
At Curtis Island, across all years of data collection, more than
20% of fans had an offset bearing of >90from the most direct
route to the ocean. In comparison, the maximum offset angle
recorded across both years at Peak Island was 70, i.e. zero
clutches had an offset angle of more than 90. In 2014,
although offset angle was reduced at Curtis Island, we believe
this was a result of extreme weather following data collection in
2013 modifying the nesting beach environment. Access to the
swale between the dunes in 2012 and 2013 was via a gradual slope
up the rst dune. This had been replaced with an almost vertical
erosion bank (height ~1.5 m) in 2014, which deterred females
climbing and nesting over the top of the rst dune (M. McLaren,
December 2013, pers. comm.). In 2014, 91% of fans were located
on the ocean-facing side or top of the rst dune, rather than
landward of the rst dune, compared with 76% in 2013, and
37% in 2012.
Evaluation of methods
At Peak Island, both arena- and fan-based methods recorded a
relatively narrow angular range of tracks (all arena rvalues >0.91,
all fan spread angles <56), and a seaward orientation (arena
V-test: P<0.001, difference between arena mean and ocean
bearing: 521.5; fan offset angles <20) (Table 2; Fig. 4and
supplementary material). Both methods therefore indicated
that hatchlings were orienting correctly at Peak Island.
At Curtis Island, however, during trials in Arenas 1 and 2
(where hatchlings had an unobstructed view of the ocean) all
hatchlings oriented seaward (arena V-test: P<0.001, difference
between arena mean and ocean bearing: 6.556), similar to
hatchlings at Peak Island, while fan-based methods indicated
that hatchlings at Curtis Island were less ocean-oriented than
hatchlings at Peak Island (fan offset angles between 23 and 67)
(Table 2; Fig. 4and supplementary material). Yet both arena-
and fan-based methods recorded larger angular ranges of
tracks at Curtis Island compared with Peak Island (all arena r
values <0.84; fan spread angles >53), and Curtis Island
hatchlings in the swale arena (with no view of the ocean) were
not ocean-oriented. Thus, although results differed slightly
between methods, overall both indicated hatchlings at Curtis
Island were showing a reduced ocean-nding ability compared
with hatchlings at Peak Island.
When measuring fan-orientation indices, 51 fans at Peak
Island and all 48 fans observed at Curtis Island in 2013 had
tracks that could be measured at both 2 m and 5 m distance from
the nest origin. No signicant difference was found between
offset angles measured at 2 m and 5 m (Wilcoxon Signed
Ranks: Peak: Z = 0.27, P= 0.79; Curtis: Z = 1.2, P= 0.23),
but spread angle was signicantly larger when bearings were
taken at 2 m compared with 5 m (Peak: Z = 2.99, P<0.01;
Curtis: Z = 3.56, P<0.001).
Ambient light levels
Very little light was observed by researchers at Peak Island.
Light levels recorded by the stellar photometer (Fig. 5)
indicated that there were no signicant differences in the light
visible in any direction from the nesting beach at Peak Island
in 2012 (KruskalWallis H
(7)
= 1.69, P= 0.98) or in 2013
(KruskalWallis H
(7)
= 10.41, P= 0.17).
In contrast, the eld team observed light levels at Curtis
Island that appeared visibly brighter than those observed at
Peak Island, with light horizons from the south, south-west
and east noticeably brighter than other directions. This was
supported by the photometer data: light levels recorded in
different directions were signicantly different in both 2012
(KruskalWallis H
(7)
= 90.77, P<0.001) and 2013 (Kruskal
Wallis H
(7)
= 232.2, P<0.001). In both years post hoc
comparisons using DunnBonferroni tests indicated that light
in a southerly direction was signicantly brighter than all
other directions except south-west. Light levels from the
south-west were signicantly higher than light in all directions
other than south, south-east and east, and light from the east
was signicantly higher than light levels from the north-west,
and north (Fig. 5). Light in an easterly direction was attributed
Table 2. Hatchling fan orientation indices at Peak and Curtis Islands, 201214
Location Year Measurement distance No. of nests Spread angle () Offset angle ()
Mean s.e. Mean s.e.
Peak 2012 2 m 68 55.1 4.5 18.3 1.9
2013 2 m 64 54.7 3.3 19.4 2.1
5 m 51 41.1 3.1 18.3 2.4
Curtis 2012 2 m 19 126.3 18.5 66.4 15.1
2013 2 m 48 91.2 11.2 46.3 7.8
5 m 48 66.7 6.6 38.5 7.7
2014 5 m 23 53 10.2 23 7.9
Flatback hatchlings and industrial light Wildlife Research 427
to the rising moon, as well as lights visible from ships anchored
outside Gladstone Harbour. These ships extended to the
south-east also. Light from the south and south-west was
attributed to Gladstone Port and city (see Pendoley
Environmental 2011).
There was a signicant positive correlation between light
levels and cloud cover at Curtis Island in both 2012
(r
s(47)
= 0.66, P<0.001) and 2013 (r
s(65)
= 0.78, P<0.01), i.e.
as cloud cover increased, so did horizon light levels. This
indicates that at Curtis Island, the primary source of visible
light was articial, since this light is reected back down to
earth from clouds (see Kyba et al.2011), with intensity levels
increasing as cloud cover increases. In contrast, there was no
signicant correlation between light levels and cloud cover at
Peak Island, which is unsurprising given the low levels of horizon
light recorded in this location. Moreover, in 2013 the data
indicated a negative relationship between light levels and
cloud cover, which just failed to reach signicance possibly as
a result of smaller sample size (r
s(38)
=0.28, P= 0.09). This
suggests that the primary source of light recorded at Peak Island
was celestial rather than articial, since celestial light is obscured
by clouds.
The Curtis Island data were analysed further in each year by
splitting the cloud cover into three categories: low cover (02
oktas), medium cover (35 oktas) and high cover (68 oktas).
Light levels differed signicantly between the three levels of
cloud cover in 2012 (KruskalWallis H
(2)
= 22.8, P<0.001) and
2013 (KruskalWallis H
(2)
= 7.9, P<0.05). In both years post
hoc analysis indicated that light levels were signicantly
higher when cloud cover was medium than when there was
low cloud coverage, but there was no difference in light levels
between medium and high cloud coverage.
Effect of moonlight on hatchling sea-nding in the
presence of industrial light
Since at Curtis Island the primary source of light visible from the
nesting beach was articial light, and moonlight is known to
have a moderating effect on sea-nding disruption in loggerhead
turtle hatchlings (Salmon and Witherington 1995; Berry et al.
2013), we examined atback turtle hatchling orientation in
arenas at Curtis Island in the presence and absence of a visible
moon. In 2012 there was no signicant difference in hatchling
orientation in the presence or absence of moonlight
(U
2
(30,57)
= 0.13, P>0.1); however, the mean direction of
travel when there was no moon was less ocean-oriented, in a
more southerly direction, than when the moon was visible, and
dispersion was also greater in the no-moon condition (Fig. 6).
In 2013, hatchling orientation was found to be signicantly
different with and without a visible moon (U
2
(29,45)
= 0.43,
P<0.001), and once again the mean direction of travel in the
no-moon condition was less ocean-oriented than when the moon
was visible, in a more southerly direction, and dispersion was
also greater when there was no moon. Thus sea-nding of
hatchlings at Curtis Island in Arenas 1 and 2 were less
disrupted in the presence of moonlight, and without moonlight
hatchlings appeared to be inuenced by the altered light horizons
from the south/south-west (Fig. 5). Examining the swale arena
(3) data at Curtis Island indicated that the hatchling exit point
distribution remained bimodal regardless of moon presence
(Fig. 6), and there was no signicant difference between the
two distributions (U
2
(29,41)
= 0.13, P>0.1).
Time of hatchling emergence
In total, 774 hatchlings were recorded in the pitfall trap at
Peak Island; of these, 92% emerged between 20 : 00 and
04 : 00 hours (Fig. 7). The median time of hatchling emergence
was 01 : 00 hours, and 50% of hatchlings emerged between
23 : 00 and 02 : 00 hours. This is later than that found in
atback turtle hatchlings from northern Australia (Koch et al.
2008), and green (Gyuris 1993) and loggerhead turtle hatchlings
(Limpus 1985) from eastern Australia. Very few atback turtle
hatchlings emerged during daylight hours (5.6% of total
hatchlings recorded). Daylight emergences occurred during
heavy rain and/or strong wind (>20 kn).
Discussion
We examined orientation behaviour of atback turtle hatchlings
during dispersion from the nest at two key eastern Australian
rookeries, using a combination of hatchling arena- and fan-based
methods. Data collected at Curtis Island were used to determine
the sea-nding behaviour of atback turtles exposed to altered
light horizons due to existing light-glow from a large industrial
centre. Data collected at Peak Island were used as a reference
site for Curtis Island, since very little anthropogenic light is
currently visible at night from the beach at Peak Island, whilst
also providing useful baseline data with respect to the proposed
Fitzroy Terminal Project.
Hatchling sea-nding ability
Hatchling atback turtles at Curtis Island showed reduced
sea-nding ability compared with hatchlings at Peak Island. In
fan-mapping, the hatchling orientation indexproposed by
Witherington et al.(1996) considers offset angles of 3090
and spread angles of 90180to indicate moderate sea-nding
disruption; and offset angles of more than 90and spread angles
greater than 180to indicate severe sea-nding disruption.
Thus, our ndings suggest that hatchlings at Peak Island were
2012
N
Peak Is
Curtis Is
2013
Fig. 5. Mean light levels (shown as relative radiance octagons, with each
concentric circle corresponding to one log unit) visible in all directions from
the nesting beaches at Peak and Curtis Islands in 2012 and 2013.
428 Wildlife Research R. L. Kamrowski et al.
not disrupted. However, both spread angle and offset angle were
higher at Curtis Island, and recorded offset and spread angles
of hatchlings in 2012 and 2013 indicate moderate disruption to
sea-nding ability.
The arena data also support our conclusion that at Peak
Island, hatchling sea-nding was not disrupted. In both years
the mean hatchling bearing was very close to the shortest
route to the ocean with relatively small standard deviation
from the mean, and hatchlings were signicantly oriented
towards the ocean. At Curtis Island, data from Arenas 1 and 2
indicated, in contrast to the fan data, that hatchling orientation
was not signicantly disrupted. Hatchlings in these arenas
n = 30
r = 0.688
n = 45
r = 0.581
n = 57
r = 0.869
n = 29
r = 0.903
2012 2013 2012 2013
No moon Moon visible
N
Curtis Is
arenas
1 & 2
Curtis Is
swale
arena 3
Fig. 6. Hatchling dispersion during arena trials at Curtis Island with no moon and with moon visible in
2012 and 2013 with data collected in the north and south arenas combined. Each grey wedge represents
10of the total circular range and wedge area depicts the number of observations falling within that
portion of the range. The straight black lines indicate mean bearing; curved black lines show 95%
condence intervals. The asterisk indicates the direction of the ocean, and r is a measure of angular
dispersion where 0 = uniform dispersion, and 1 = concentrated in one direction.
160
140
120
100
80
60
40
20
0
12:00
14:00
16:00
18:00
20:00
22:00
00:00
02:00
04:00
06:00
08:00
10:00
Time of emer
g
ence
Total number of hatchlings
Mean number of hatchlin
g
s
50
45
40
35
30
25
20
15
10
5
0
Fig. 7. Total (light grey) and mean (dark grey) number of hatchlings emerging over 24 h at Peak
Island between 31 January 2013 and 14 February 2013 for each hour of the day. Bars indicate 95%
condence intervals of the mean numbers. Median hatchling emergence was at 01 : 00 hours, with the
interquartile range of emergence occurring between 23 : 00 and 02 : 00 hours.
Flatback hatchlings and industrial light Wildlife Research 429
were found to be signicantly oriented towards the ocean in
both years. Yet the standard deviation from the mean and
the spread of tracks were both greater than we found at Peak
Island.
Evaluation of methods
Both arena and fan-based methods separately provided
evidence that hatchlings at Curtis Island were showing
reduced sea-nding ability in comparison to hatchlings at
Peak Island, implying that either method may be used with
condence as a means of assessing hatchling sea-nding.
However, we did observe a discrepancy in the degree of sea-
nding disruption at Curtis Island as suggested by the two
methods; and we hypothesised that this discrepancy may
have been a result of beach topography. Hatchling turtles
orient using both horizon elevation and brightness cues
(Salmon and Wyneken 1994;LimpusandKamrowski2013),
and the beach topography of Peak and Curtis Islands is very
different. The nesting beach at Peak Island is backed by a high
peak of land, whereas at Curtis Island the landward horizon
is relatively at (Coffey Environments 2012a) and the nesting
beach is characterised by a double row of dunes with a swale
running between them in an approximately northsouth
direction, parallel to the ocean (Fig. 2). In 2012, most nests
at Curtis Island naturally occurred landward of the rst dune
where the lowest horizon would not have been in a seaward
direction; therefore following analysis of the 2012 data, we
considered that the placement of arenas at Curtis Island
(Arenas 1 and 2 were constructed on attened sections of the
rst dune, giving hatchlings an unobstructed view of the ocean)
may have reduced hatchling sea-nding disruption relative to
naturally emerged nests (assessed with fan-based methods).
Consequently, in 2013 we also tested hatchlings in an arena
constructed at the base of the swale. Hatchling exit points from
Arena 3 followed a bimodal distribution which followed
the direction of the swale i.e. in a direction approximately
parallel to the ocean, thus suggesting a much greater sea-
ndingdisruptionthanobservedinArenas1and2,and
providing evidence that hatchlings in Arena 3 were orienting
using elevation cues.
The inuence of horizon elevation is also evident from the
arena data at Peak Island. In the north arena (Arena 1) in 2013,
although hatchlings remained strongly oriented towards the
ocean, their tracks showed a slight westerly shift in travel
direction compared with 2012, and the range of tracks
marginally increased. While subtle changes in the light
spillage from the coastal development of Keppel Bay should
not be discounted, we believe the small difference was due to
the arena being located a few metres further landward in 2013
than in 2012, due to dune erosion. The new arena placement
resulted in the large Pandanus tree that backed the arena in
2012 being located between 90and 150from the arena in
2013. The fact that the spread of hatchling tracks shifted around
to the west supports previous ndings that hatchlings orient
away from high, dark silhouettes (Salmon and Wyneken 1994;
Limpus and Kamrowski 2013).
As a result, when collecting hatchling orientation data using
arenas we recommend placing arenas in a variety of beach
locations where nests naturally occur, otherwise incomplete
orientation conclusions may be drawn. Yet, given hatchling
response to beach topography, arena-based methods are
valuable for quantifying hatchling dispersion at the nesting
beach in relation to environmental differences (such as the
presence of light of different intensities or spectral output, as
well as moon-stage etc.), either within or between species, whilst
controlling for topographical inuence.
It is not possible to standardise topographical inuence
when using fan-based methods to assess sea-nding. However,
our ndings do indicate that fan-based methods can reveal
horizon elevation effects. We found that mean offset angle in
each year was larger when a greater proportion of nests had been
laid landward of the rst dune, where no view of the ocean existed
and the lowest horizon elevation was in a non-sea-nding
direction. Fan measurements also have additional benets
since they are easy to perform, relatively quick, and they allow
the sea-nding of multiple clutches in one night to be recorded.
Thus multiple nights of fan-data may provide an indication of
spatial and/or temporal variations in hatchling sea-nding at a
particular beach. Moreover, fans do not involve the time-
consuming, logistical difculties associated with working at
night, maintenance of arenas, and collecting hatchlings for
arena trials (Pendoley 2005).
However, assessing light levels at the time of nest
emergence is more difcult with fan-monitoring, and when
monitoring occurs only at dawn emerged nests may be
missed due to overnight wind and/or rain erasing the shallow
tracks. Researchers must also take care to ensure that the fans
examined reect the total nesting environment, and not the
areasmost convenient to nd hatchling tracks (for example,
the presence of vegetation may obscure track observation).
Furthermore, it is important to explicitly consider the
distances over which fan measurements are taken. Previous
studies involving fan indices to infer hatchling orientation
(Salmon and Witherington 1995; Witherington et al.1996;
Pendoley 2005;Berryet al.2013; Limpus and Kamrowski
2013), although similar in most respects, measured track
bearings at different distances from the nest origin (i.e. 5 m,
10 m, to the high tide line, or to the point where the tracks
disappear), or did not specify this distance. At Peak Island
in 2012, nest density was very high and as a result it was
necessary to measure fan angles at 2 m from the nest origin,
since for most emerged nests at greater distances the
tracks became indistinguishable from those of adjacent nest
emergences. In 2013, a reduced nest density allowed
measurements to be taken at both 2 m and 5 m from the nest
origin in a large number of instances, and comparisons of
this data indicated that offset angle was not affected by the
distance over which the bearings were taken. However spread
angle was signicantly larger when the bearings were taken
closer to the nest origin, thus care must be taken when comparing
fan spread measurements between studies, and this nding
indicates that future studies must be clear in specifying
measurement distance.
Inuence of industrial light-glow
Very little anthropogenic light was observed at Peak Island,
and no differences were found in the amount of light recorded
430 Wildlife Research R. L. Kamrowski et al.
in different directions. In contrast, it was clear to observers that
light originating from the direction of Gladstone had signicantly
altered the light horizons of the nesting beach at Curtis Island
(Pendoley Environmental 2011), and the light levels we recorded
from the south and south-west were higher than in any other
direction visible from the nesting beach. This light appeared to
originate from Gladstone Port and city, since they lie south/south-
west from the nesting beach. While the light levels given in the
present study indicate relative, rather than absolute, levels of
ambient light, absolute levels of light visible from the nesting
beach at Curtis Island can be found in Pendoley Environmental
(2011), and we strongly recommend that similar light
measurements are made at Peak Island in the near future to
provide valuable baseline data. Examining our relative light
measurements in combination with hatchling dispersion data at
both study locations suggested that light produced from the
Gladstone region contributes to moderate sea-nding
disruption in atback turtle hatchlings at Curtis Island.
We also found that light levels were signicantly higher at
Curtis Island when cloud cover was present in both 2012 and
2013. This supports the ndings of Kyba et al.(2011), and
indicates that light mitigation measures may be more
important on cloudy compared with clear nights. Further
research is needed to determine whether hatchling
disorientation increased as cloud cover increased, but given
the disorienting effect of light on hatchlings, increased light
levels due to cloud cover may be expected to increase the
disorientation of hatchlings.
Previous research has indicated that moonlight smooth[s]
outsmall variations in background light intensity (Salmon and
Witherington 1995), reducing the disruptive inuence of articial
lighting whilst also negating the effect of light reected back
down to Earth by cloud coverage. Comparing the orientation of
hatchlings at Curtis Island in arena trials carried out with and
without a visible moon in 2012 did not show that hatchlings were
less able to nd the ocean in the absence of moonlight; however,
this may have been related to the small sample sizes tested.
Indeed, a visual examination of a plot of this data (Fig. 6)
indicated that hatchlings were more dispersed around the circle
and more likely to head in a southerly direction in the absence of
moonlight. In 2013, the same comparison with larger sample
sizes did nd a signicant difference. Thus, despite the fact
that hatchlings at Curtis Island tested in Arenas 1 and 2 were
signicantly oriented towards the ocean (Fig. 4and
supplementary material), in the absence of moonlight
hatchlings had a reduced sea-nding ability, and were more
oriented towards the altered light horizons to the south. Our
results therefore indicate that moonlight did moderate the
disruptive inuence of industrial light on sea-nding by
atback turtle hatchlings, supporting previous research
(Salmon and Witherington 1995; Tuxbury and Salmon 2005;
Berry et al.2013). Since we were interested in the potential
moderating effect of moonlight on disrupted sea-nding in the
presence of industrial light, and there was very little articial
light observed at Peak Island, we did not make detailed
observations of moon-stage during data collection at Peak
Island; thus a similar comparison of data was not possible.
Yet, hatchlings at Peak Island were all highly ocean-oriented
despite data collection between years taking place at different
phases of the moon. Future studies in dark locations would benet
from a comparison of sea-nding at different moon-stage,
because there should be little difference in hatchling
orientation without articial lighting in the presence or
absence of moonlight.
We found no difference in hatchling orientation in the
swale arena on Curtis Island with or without a visible moon,
and, unexpectedly, the mean direction of travel was in a north-
westerly direction. Previous research proposed that lowest
horizon elevation functions as the principal cue in guiding
hatchling orientation, but where multiple low horizons exist
then brightness cues would be utilised (Limpus and
Kamrowski 2013). Consequently, we expected hatchlings to
orient parallel to the ocean along the swale, and towards the
brighter, south-easterly direction. The reason hatchlings headed
more frequently towards the north-west is unclear, but possibly
the horizon elevation in that direction was marginally lower
than in the opposing direction. This nding further emphasises
the importance of elevation cues, as discussed above, and
supports the recommendation of Limpus and Kamrowski
(2013) that horizon elevation should be considered in any
investigation into the sea-nding ability of hatchling turtles.
Moreover, this indicates that although the altered light
horizons originating from industry located south of the nesting
beach at Curtis Island inuenced sea-nding by atback turtle
hatchlings (greater fan spread angles, and more southerly exit
bearings and greater dispersion in Arenas 1 and 2 in the absence of
moonlight), the topography of the beach also appeared to
inuence the reduced sea-nding ability of hatchlings at Curtis
Island. As such, we suggest that beach prole modications may
be a valuable management strategy for limiting the sea-nding
disruption of hatchlings at Curtis Island (Tuxbury and Salmon
2005; Limpus and Kamrowski 2013).
Additional considerations
Multiple LNG plants were approved or were in the early stages
of construction on Curtis Island at the time of data collection.
In the absence of effective light management in these LNG
plants, it is likely that light levels south and south-west of the
nesting beach will increase in the near future. Since hatchlings
preferentially orient towards light of higher intensities
(Mrosovsky 1972; Witherington and Bjorndal 1991b), the
cumulative light emissions from all LNG plants and the
proposed tourist resort in addition to existing light from
Gladstone Port and city, may therefore result in articial light
intensities high enough to cause an even greater disruption in
the sea-nding ability of atback hatchlings at Curtis Island
than we observed. Moreover, a review of the environmental
impact assessments for the individual LNG plants indicated
that whilst each operator recognises the need to minimise light
emissions due to the nearby presence of nesting turtles, the plans
do not address mitigation of potential cumulative impacts (URS
Australia 2009; WorleyParsons 2010; QGC 2011; Coffey
Environments 2012b).
We therefore strongly recommend rigorous light monitoring
and management of industry in the region, as well as continued
monitoring of hatchling orientation at Curtis Island. In addition,
given that we found lighting impacts are likely to be exacerbated
Flatback hatchlings and industrial light Wildlife Research 431
by the presence of cloud cover, we further recommend that
industrial light be managed to reduce emissions as far as
possible (see Kamrowski (2014) for a case study of
successfulindustrial lighting management in Western
Australia) since additional management and/or monitoring
effort on cloudy nights may be difcult to implement.
This study is the rst to report time of emergence for
atback hatchlings from eastern Australia. Since hatchlings
generally emerge at night (Mrosovsky 1968), knowledge of
the time at which core emergence may be expected will
contribute to guiding more effective management of articial
lighting close to nesting beaches. Similar to other populations
and species, we found that most hatchlings emerged during the
night. However, unlike green and loggerhead turtle hatchlings
from eastern Australia, for which core emergence occurs in the
rst part of the night (between 20 : 00 and 00 : 00 hours) (Limpus
1985; Gyuris 1993), we found that atback turtle hatchlings
emerge in eastern Australia predominantly in the early hours
of the morning. This is later than found for atback turtle
hatchlings in northern Australia (Koch et al.2008), and our
nding would thus benet from conrmation in future studies
and at different rookeries. Although beyond the scope of the
present study, Koch et al.(2008) found thermal cues to be
important for stimulating atback turtle emergence; thermal
cues may thus be related to the difference in emergence time
between populations (e.g. Glen et al.2005,2006). Future atback
turtle emergence studies would therefore also benet from an
examination of the thermal environment at the nesting beach.
This information could then be used to guide improved lighting
management (e.g. potentially stronger lighting restrictions
during the early hours of the morning in infrastructure located
adjacent to atback turtle nesting beaches in eastern Australia),
both for industry in the Gladstone area, and further aeld
wherever articial light may pose a problem for atback turtles.
Conclusions
Flatback turtle hatchlings at Peak Island appear to be unaffected
by light pollution; however, atback turtle hatchlings at
Southend Beach, Curtis Island, show evidence of moderately
impaired sea-nding ability. We conclude that this reduced sea-
nding ability is the result of altered light horizons from light-
glow produced by a large industrial centre, despite this light
originating from ~15 km away, as well as beach topography.
Arena- and fan-based methods each have advantages and
limitations. We suggest that using a combination of explicitly
described fan-based methods, in addition to strategically placed
arenas, would provide the best data for accurately assessing sea-
nding ability of hatchlings in future studies.
Given that multiple LNG plants and a large tourist resort are
either proposed or under development at Curtis Island, continued
monitoring of hatchling orientation at this beach is strongly
recommended. Our ndings also indicate that industrial
development in the Fitzroy River Delta could potentially
disrupt hatchling orientation at Peak Island in the future.
Light-management plans for industrial developments should
include consideration of moon phase, moon-stage, cloud cover
and hatchling time of emergence, as well as cumulative impact,
since all of these factors will affect the likelihood of hatchling
disruption at nesting beaches exposed to large-scale articial
light-glow.
Acknowledgements
We thank C. Kirby, C. Alvarez Roa, E. English, K. French, L. Jeremijenko,
K. Marsden, M. McLaren, G. McLaren, M. Payne, and M. Turner for
assistance with data collection, Queensland Parks and Wildlife Service for
logistical support whilst on the islands, and K. French for help with
transportation and equipment. We also thank M. Salmon for advice at
several stages of this project. Advice from two anonymous reviewers
improved the manuscript. This research was funded by grants from the
School of Earth and Environmental Sciences at James Cook University,
the Australian Geographic Society, the Wildlife Preservation Society of
Queensland, and Pendoley Environmental. Data collected during 2014
were a component of the Gladstone Port Authority regional marine turtle
monitoring program. This manuscript forms part of RLKs Ph.D. research at
James Cook University. RLK is supported by the Northcote Trust Graduate
Scholarship Scheme. This project was authorised by QPWS permits
WITK10277311 and NCIPI02340211, GBRMPA permit G11/34617.1,
and a James Cook University animal ethics permit (No. A1714).
References
Australian Bureau of Statistics (2011). 3218.0 Queensland regional
population growth, Australia, 20092010. Available at: http://www.
abs.gov.au/ausstats/abs@.nsf/Previousproducts/3218.0Main%20
Features62009-10?opendocument&tabname=Summary&prodno=3218.
0&issue=200910&num=&view=#PARALINK34 [accessed April 2013].
Batschelet, E. (1981). Circular statistics in biology.(Academic Press:
London.)
Berry, M., Booth, D. T., and Limpus, C. J. (2013). Articial lighting and
disrupted sea-nding behaviour in hatchling loggerhead turtles (Caretta
caretta) on the Woongarra coast, south-east Queensland, Australia.
Australian Journal of Zoology 61, 137145.
Bertolotti, L., and Salmon, M. (2005). Do embedded roadway lights protect
sea turtles? Environmental Management 36, 702710. doi:10.1007/
s00267-004-0288-2
Chung, C. F., Pilcher, N. J., Salmon, M., and Wyneken, J. (2009). Offshore
migratory activity of hawksbill (Eretmochelys imbricata L) hatchlings.
I. Quantitative analysis of activity, with comparisons to green turtles
(Chelonia mydas L) Chelonian Conservation and Biology 8,2834.
doi:10.2744/CCB-0715.1
Coffey Environments (2012a). 23. Landscape and visual. Arrow LNG Plant:
Environmental impact statement. Arrow CSG (Australia) Pty Ltd,
Brisbane.
Coffey Environments (2012b). 32. Cumulative impacts. Arrow LNG Plant:
Environmental impact statement. Arrow CSG (Australia) Pty Ltd.,
Brisbane.
Crossin, G. T., Hinch, S. G., Farrell, A. P., Higgs, D. A., Lotto, A. G., Oakes,
J. D., and Healey, M. D. (2004). Energetics and morphology of sockeye
salmon: effects of upriver migratory distance and elevation. Journal of
Fish Biology 65, 788810. doi:10.1111/j.0022-1112.2004.00486.x
Danaher, K. F., Rasheed, M. A., and Thomas, R. (2005). The intertidal
wetlands of Port Curtis. Information Series QI05031. Department of
Primary Industries and Fisheries, Queensland.
Department of Environment and Heritage Protection (2013). Monitoring of
coastal turtles in the Port Curtis and Port Alma region: gap analysis. Part 5:
Flatback turtles. Available at: http://www.westernbasinportdevelopment.
com.au/media/pdf/ERMP%20Final%20Report%20%20Part%205%
20Monitoring%20of%20Coastal%20Sea%20Turtles%20Gap%20Analysis.
pdf [accessed November 2013].
Dryden, J., Grech, A., Moloney, J., and Hamann, M. (2008). Rezoning of the
Great Barrier Reef World Heritage Area: does it afford greater protection
432 Wildlife Research R. L. Kamrowski et al.
for marine turtles? Wildlife Research 35, 477485. doi:10.1071/
WR07087
Duke, N. C., Lawn, P., Roelfsema, C. M., Phinn, S., Zahmel, K. N., Pedersen,
D., Harris, C., Steggles, N., and Tack, C. (2003). Assessing historical
change in coastal environments. Port Curtis, Fitzroy River Estuary and
Moreton Bay regions. Final Report to the CRC for Coastal Zone Estuary &
Waterway Management. Historical Coastlines Project, Marine Botany
Group, Centre for Marine Studies. The University of Queensland,
Brisbane.
Elvidge, C., Sutton, P., Baugh, K., Ziskin, D., Ghosh, T., and Anderson, S.
(2011). National trends in satellite observed lighting: 19922009. Remote
Sensing 3,117.
Fritsches, K. A. (2012). Australian loggerhead sea turtle hatchlings do not
avoid yellow. Marine and Freshwater Behaviour and Physiology 45,
7989. doi:10.1080/10236244.2012.690576
GBRMPA (2008). Keppel Bay and islands site management arrangements.
Available at: http://www.gbrmpa.gov.au/visit-the-reef/site-specic-
management/keppel-bay-and-islands-site-management-arrangements
Glen, F., Broderick, A. C., Godley, B. J., and Hays, G. C. (2005). Patterns in
the emergence of green (Chelonia mydas) and loggerhead (Caretta
caretta) turtle hatchlings from their nests. Marine Biology 146,
10391049. doi:10.1007/s00227-004-1492-6
Glen, F., Broderick, A. C., Godley, B. J., and Hays, G. C. (2006). Thermal
control of hatchling emergence patterns in marine turtles. Journal of
Experimental Marine Biology and Ecology 334,3142.
Grech, A., Bos, M., Brodie, J., Coles, R., Dale, A., Gilbert, R., Hamann, M.,
Marsh, H., Neil, K., and Pressey, R. (2013). Guiding principles for the
improved governance of port and shipping impacts in the Great Barrier
Reef. Marine Pollution Bulletin 75,820.
Gyuris, E. (1993). Factors that control the emergence of green turtle hatchlings
from the nest. Wildlife Research 20, 345353. doi:10.1071/WR9930345
Hamann, M., Grech, A., Wolanski, E., and Lambrechts, J. (2011). Modelling
the fate of marine turtle hatchlings. Ecological Modelling 222,
15151521. doi:10.1016/j.ecolmodel.2011.02.003
Hargis, C. D., Bissonette, J. A., and David, J. L. (1998). The behavior of
landscape metrics commonly used in the study of habitat fragmentation.
Landscape Ecology 13, 167186. doi:10.1023/A:1007965018633
Hodge, W., Limpus, C. J., and Smissen, P. (2007). Queensland turtle
conservation project: Hummock Hill Island nesting turtle study
December 2006. Conservation Technical and Data Report.
Environmental Protection Agency, Queensland.
Kamrowski, R. L. (2014). Coastal light pollution in Australia: insights and
implications for marine turtle conservation. Ph.D. Thesis, James Cook
University, Townsville, Queensland.
Kamrowski, R. L., Limpus, C., Moloney, J., and Hamann, M. (2012). Coastal
light pollution and marine turtles: assessing the magnitude of the problem.
Endangered Species Research 19,85
98. doi:10.3354/esr00462
Kamrowski, R. L., Limpus, C., Jones, R., Anderson, S., and Hamann, M.
(2014). Temporal changes in articial light exposure of marine turtle
nesting areas. Global Change Biology 20, 24372449. doi:10.1111/
gcb.12503
Kawamura, G., Naohara, T., Tanaka, Y., Nishi, T., and Anraku, K. (2009).
Near-ultraviolet radiation guides the emerged hatchlings of loggerhead
turtles Caretta caretta (Linnaeus) from a nesting beach to the sea at night.
Marine and Freshwater Behaviour and Physiology 42,1930.
doi:10.1080/10236240802663580
Koch, A. U., Guinea, M. L., and Whiting, S. D. (2008). Asynchronous
emergence of atback seaturtles, Natator depressus, from a beach
hatchery in northern Australia. Journal of Herpetology 42,18.
doi:10.1670/07-060.1
Kyba, C.C.M., Ruhtz, T., Fischer, J., and Holker, F. (2011). Cloud coverage
acts as an amplier for ecological light pollution in urban ecosystems
PLoS ONE 6, e17307. doi:17310.11371/journal.pone.0017307
Limpus, C. (1971). Sea turtle ocean nding behaviour. Search 2, 385387.
Limpus, C. (1985). A study of the loggerhead turtle, Caretta caretta,in
Queensland. Ph.D. Thesis, University of Queensland, Brisbane.
Limpus, C. (2009). A biological review of Australian marine turtles.
Environmental Protection Agency, Queensland Government,
Queensland.
Limpus, C. J., and Kamrowski, R. L. (2013). Ocean-nding in marine
turtles: the importance of low horizon elevation as an orientation cue.
Behaviour 150, 863893.
Limpus, C., McLaren, M., McLaren, G., and Knuckey, B. (2006).
Queensland Turtle Conservation Project: Curtis Island and Woongarra
Coast Flatback Turtle Studies, 20052006. Conservation technical and
data report. Environmental Protection Agency, Queensland Parks and
Wildlife Service, Queensland.
Lohmann, K. J., Witherington, B., Lohmann, C. M. F., and Salmon,
M. (1997). Orientation, navigation, and natal beach homing in sea
turtles. In The Biology of Sea Turtles. (Eds P. L. Lutz, and J. A.
Musick.) pp. 107135. (CRC Press: Boca Raton, FL.)
Mardia, K. V., and Jupp, P. E. (2000). Directional Statistics.(John Wiley &
Sons Ltd: Chichester, UK.)
Mrosovsky, N. (1968). Nocturnal emergence of sea turtles: control by
thermal inhibition of activity. Nature 220, 13381339. doi:10.1038/
2201338a0
Mrosovsky, N. (1970). The inuence of the suns position and elevated
cues on the orientation of hatchling sea turtles. Animal Behaviour 18,
648651. doi:10.1016/0003-3472(70)90008-4
Mrosovsky, N. (1972). The water-nding ability of sea turtles; behavioural
studies and physiological speculations. Brain, Behavior and Evolution 5,
202225. doi:10.1159/000123748
Parmenter, C. J., and Limpus, C. J. (1995). Female recruitment, reproductive
longevity and inferred hatchling survivorship for the atback turtle
(Natator depressus) at a major eastern Australian rookery. Copeia
1995, 474477. doi:10.2307/1446913
Pendoley, K. (2000). The inuence of gas ares on the orientation of green
turtle hatchlings at Thevenard Island, Western Australia. In Second
ASEAN Symposium and Workshop on Sea Turtle biology and
Conservation. Kotal Kinabalu. (ASEAN Academic Press.)
Pendoley, K. (2005). Sea turtles and the environmental management of
industrial activities in north west Western Australia. Ph.D. Thesis,
Murdoch University, Perth.
Pendoley Environmental (2011). Gladstone baseline sky cam light monitoring
2011. Prepared for Gladstone Ports Corporation. Available at: http://
www.westernbasinportdevelopment.com.au/media/pdf/Gladstone%
20Baseline%20Sky%20Cam%20Light%20monitoring%202011.pdf
[accessed May 2013].
Pereira, C. M., Booth, D. T., and Limpus, C. J. (2011). Locomotor activity
during the frenzy swim: analysing early swimming behaviour in hatchling
sea turtles. The Journal of Experimental Biology 214, 39723976.
doi:10.1242/jeb.061747
Pereira, C. M., Booth, D. T., and Limpus, C. J. (2012). Swimming
performance and metabolic rate of atback Natator depressus and
loggerhead Caretta caretta sea turtle hatchlings during the swimming
frenzy. Endangered Species Research 17,4351. doi:10.3354/esr00415
Pestalozzi, N., Cauwels, P., and Sornette, D. (2013). Dynamics and spatial
distribution of global nighttime lights. Swiss Finance Institute Research
Paper No. 13-02. Available at: http://ssrn.com/abstract=2237410 or http://
dx.doi.org/doi:10.2139/ssrn.2237410doi:10.2139/ssrn.2237410
Pulido, F. (2007). The genetics and evolution of avian migration. Bioscience
57, 165174. doi:10.1641/B570211
QGC (2011). Signicant species management plan. QGC Pty Ltd,
Queensland.
Rich, C., and Longcore, T. (Eds) (2006). Ecological Consequences of
Articial Night Lighting.(Island Press: Washington, DC.)
Rogers, R. R., and Yau, M. K. (1989). A Short Course in Cloud Physics.
(Pergamon Press: Oxford.)
Flatback hatchlings and industrial light Wildlife Research 433
Salmon, M. (2003). Articial night lighting and sea turtles. Biologist
(Columbus, Ohio) 50, 163168.
Salmon, M. (2006). Protecting sea turtles from articial night lighting at
Floridas oceanic beaches. In Ecological Consequences of Articial
Night Lighting. (Eds C. Rich, and T. Longcore.) pp. 141168. (Island
Press: Washington, DC.)
Salmon, M., and Witherington, B. (1995). Articial lighting and seanding
by loggerhead hatchlings: evidence for lunar modulation. Copeia 1995,
931938. doi:10.2307/1447042
Salmon, M., and Wyneken, J. (1990). Do swimming loggerhead sea
turtles (Caretta caretta L.) use light cues for offshore orientation?
Marine Behaviour and Physiology 17, 233246. doi:10.1080/
10236249009378774
Salmon, M., and Wyneken, J. (1994). Orientation by hatchling sea turtles:
mechanisms and implications. Herpetological Natural History 2,1324.
Salmon, M., Wyneken, J., Fritz, E., and Lucas, M. (1992). Seanding by
hatchling sea turtles: role of brightness, silhouette and beach slope as
orientation cues. Behaviour 122,5677. doi:10.1163/156853992X00309
Salmon, M., Tolbert, M. G., Painter, D. P., Goff, M., and Reiners, R. (1995).
Behavior of loggerhead sea turtles on an urban beach. II. Hatchling
orientation. Journal of Herpetology 29, 568576. doi:10.2307/1564740
Salmon, M., Hamann, M., Wyneken, J., and Schauble, C. (2009). Early
swimming activity of hatchling atback sea turtles Natator depressus:a
test of the predation riskhypothesis. Endangered Species Research 9,
4147. doi:10.3354/esr00233
Sella, K. N., Salmon, M., and Witherington, B. E. (2006). Filtered streetlights
attract hatchling marine turtles. Chelonian Conservation and Biology 5,
255261. doi:10.2744/1071-8443(2006)5[255:FSAHMT]2.0.CO;2
Stewart, K. E. J., Bourn, N. A. D., and Thomas, J. A. (2001). An evaluation
of three quick methods commonly used to assess sward height in ecology.
Journal of Applied Ecology 38, 11481154. doi:10.1046/j.1365-
2664.2001.00658.x
Tuxbury, S. M., and Salmon, M. (2005). Competitive interactions between
articial lighting and natural cues during seanding by hatchling marine
turtles. Biological Conservation 121, 311316. doi:10.1016/j.biocon.
2004.04.022
URS Australia (2009). Final report: GLNG environmental impact statement
EPBC controlled action assessment report. QGC Pty Limited on behalf
of Santos Ltd, Brisbane, Queensland.
Van Buskirk, J., and Crowder, L. B. (1994). Life-history variation in
marine turtles. Copeia 1994,6681. doi:10.2307/1446672
Walker, T. A., and Parmenter, C. J. (1990). Absence of a pelagic phase in the
life cycle of the atback turtle, Natator depressa (Garman). Journal of
Biogeography 17, 275278. doi:10.2307/2845123
Witherington, B. (1997). The problem of photopollution for sea turtles
and other nocturnal animals. In Behavioral Approaches to
Conservation in the Wild. (Eds J.R. Clemmons, and R. Buchholz.)
pp. 303328. (Cambridge University Press: Cambridge.)
Witherington, B., and Bjorndal, K. (1991a). Inuences of articial lighting
on the seaward orientation of hatchling loggerhead turtles Caretta caretta.
Biological Conservation 55, 139149. doi:10.1016/0006-3207(91)
90053-C
Witherington, B., and Bjorndal, K. A. (1991b). Inuences of wavelength
and intensity on hatchling sea turtle phototaxis: implications for sea-
nding behavior. Copeia 1991, 10601069. doi:10.2307/1446101
Witherington, B., and Martin, R. E. (2000). Understanding, assessing, and
resolving light-pollution problems on sea turtle nesting beaches. 2nd
(rev.) edn. Florida Fish and Wildlife Conservation Commission, Marine
Research Institute, Tech. Rep. TR-2., St Petersburg, FL.
Witherington, B., Crady, C., and Bolen, L. (1996). A hatchling orientation
indexfor assessing orientation disruption from articial lighting. In
Proceedings of the Fifteenth Annual Symposium on Sea Turtle Biology
and Conservation. (Comp. J. A. Keinath, D. Barnard, J. Musick and
B. Bell.) pp. 344347. NOAA Tech. Mem. NMFS-SEFSC-387.
WorleyParsons (2010). Appendix I Marine mammal and turtles
management plan. Australia Pacic LNG Project. WorleyParsons
Services Pty Ltd on behalf of Australia Pacic LNG Pty Ltd.
Wyneken, J., and Salmon, M. (1992). Frenzy and postfrenzy swimming
activity in loggerhead, leatherback, and green sea turtles. Copeia 1992,
478484. doi:10.2307/1446208
Wyneken, J., Madrak, S., Salmon, M., and Foote, J. (2008). Migratory activity
by hatchling loggerhead sea turtles (Caretta caretta L.): evidence for
divergence between nesting groups. Marine Biology 156, 171178.
doi:10.1007/s00227-008-1074-0
Zar, J. H. (2010). Biostatistical Analysis.(Prentice Hall: Upper Saddle
River, NJ.)
434 Wildlife Research R. L. Kamrowski et al.
www.publish.csiro.au/journals/wr
... We collected data equally across all areas for both species, resulting in a spatially random sample. In 2016-2018, we collected orientation data on hatchling tracks, following earlier studies (Salmon and Witherington 1995;Berry et al. 2013;Kamrowski et al. 2014;Dimitriadis et al. 2018, andespecially Hirama et al. 2021). Hatchling orientation data were collected from 180 loggerhead, 56 green and 15 leatherback turtle nests. ...
... From a hatchling emergence point, we marked a 10-m-radius circle (hereafter, testing circle) and measured the bearing of three hatchling tracks, one for a mode direction and two for calculating an angular range, where they intercepted the testing circle (Hirama et al. 2021). Kamrowski et al. (2014) considered the midpoint of bearing within an angular range as a mode direction. We determined mode direction by visually evaluating the tracks (Hirama et al. 2021). ...
... We collected data from a subsample of the marked nests because some nests were unsuccessful, with no emerging hatchlings. We ignored nests with fewer than five hatchling tracks (Pendoley 2005;Berry et al. 2013;Kamrowski et al. 2014;Hirama et al. 2021) or for which tracks had been erased by wind or trampling. The distance from a nest to the vegetation line that shows the toe of the dune (hereafter, distance from nest to dune) was measured at the time of hatchling emergence by using a laser range finder (Laser Technology: TruPulse 200). ...
Article
Context Sea turtle hatchlings generally emerge at night from nests on sand beaches and immediately orient using visual cues, which are believed to entail the difference in brightness between the light seen in the seaward direction and that seen in the duneward direction. Aim The aim of this study was to understand how dune proximity affected hatchling orientations in two sea turtle species that share a nesting beach 15 km long and 25.3 ± 9.4 m (N = 215) from dune to waterline, with low to moderate artificial light nearby. Methods For hatchling loggerhead and green turtles, we measured accuracy and precision of orientation, tested differences in distance from nest to dune, and investigated the effect of dune proximity on hatchling orientation. Key results We found a significant decrease in hatchling orientation accuracy and precision in both species as the distance increased from nests to dune. Loggerhead and green turtles showed similar orientation ability when in the same proximity to the dune. Conclusions We conclude that dune features provide important cues for hatchling orientation on sea turtle nesting beaches. Implications Restoring and maintaining natural beach profiles, especially dune systems, is likely to increase the accuracy and precision of sea finding in hatchling sea turtles.
... µm wavelength spectrum, VIIRS imagery can detect light intensity levels for up to 2×10 −9 watts per cm 2 steradian, with a resolution of up to 14 bits [13]. Researchers use the identical instrument gain setting for Stellar Photometer to observe longterm impacts of light pollution on marine animals [27]. ...
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Existing technologies for distributed light-field mapping and light pollution monitoring (LPM) rely on either remote satellite imagery or manual light surveying with single-point sensors such as SQMs (sky quality meters). These modalities offer low-resolution data that are not informative for dense light-field mapping, pollutant factor identification, or sustainable policy implementation. In this work, we propose LightViz -- an interactive software interface to survey, simulate, and visualize light pollution maps in real-time. As opposed to manual error-prone methods, LightViz (i) automates the light-field data collection and mapping processes; (ii) provides a platform to simulate various light sources and intensity attenuation models; and (iii) facilitates effective policy identification for conservation. To validate the end-to-end computational pipeline, we design a distributed light-field sensor suit, collect data on Florida coasts, and visualize the distributed light-field maps. In particular, we perform a case study at St. Johns County in Florida, which has a two-decade conservation program for lighting ordinances. The experimental results demonstrate that LightViz can offer high-resolution light-field mapping and provide interactive features to simulate and formulate community policies for light pollution mitigation. We also propose a mathematical formulation for light footprint evaluation, which we integrated into LightViz for targeted LPM in vulnerable communities.
... illumination falling on coastlines (Kamrowski et al., 2012(Kamrowski et al., , 2014(Kamrowski et al., , 2015. Artificial light at night (ALAN) frequently disrupts nesting female turtles and the sea-finding ability of emerging hatchlings (Lorne and Salmon 2007;Bourgeois et al., 2009;Berry et al., 2013). ...
... For example, bogong moths have migrated from winter breeding grounds throughout Queensland, New South Wales, and Western Victoria to the Victorian Alpine region for more than 7000 years (a known ecological phenomenon). In 2017, the moth numbers crashed from roughly 4 billion to being almost undetectable, and light pollution contributed to this radical disruption of the moths' migration [45]. Thus, an area with an 'excellent dark sky' (the Victorian Alpine region) experienced a degradation in its ecosystem service value. ...
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Light pollution has detrimental impacts on wildlife, human health, and ecosystem functions and services. This paper explores the impact of light pollution on the value of ecosystem services. We use the Simplified All-Sky Light Pollution Ratio (sALR) as a proxy for the negative impact of light pollution and the Copernicus PROBA-V Global Landcover Database as our proxy of ecosystem service value based on previously published ecosystem service values associated with a variety of landcovers. We use the sALR value to ‘degrade’ the value of ecosystem services. This results in a 40% reduction in ecosystem service value in those areas of the world with maximum levels of light pollution. Using this methodology, the estimate of the annual loss of ecosystem service value due to light pollution is USD 3.4 trillion. This represents roughly 3% of the total global value of ecosystem services and 3% of the global GDP, estimated at roughly USD 100 trillion in 2022. A summary of how these losses are distributed amongst the world’s countries and landcovers is also presented.
... Birds also become navigationally disoriented, with seabird fledglings grounded on roads and beaches near colonies [26] and nocturnally migrating birds are disoriented by ALAN [27]. Marine animals do not escape the problem of light pollution either; turtles' navigation becomes disrupted due to skyglow and lights from industrial areas [28]. Several works highlight ALAN's impact on protected areas and conservation efforts ( [29,30]). ...
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Artificial Light at Night (ALAN) significantly threatens protected areas from urbanization. As urbanization continues to grow, there is a need for forecasting future light pollution and ALAN for the protected areas in Indonesia. This study proposes a four-step computational model for forecasting spatial–temporal light pollution in nine protected areas in Indonesia via spatiotemporal modeling and linear models. The four steps for predicting spatial–temporal light pollution are (i) data collection, (ii) data pre-processing, (iii) model and prediction of population, and (iv) model and prediction of light pollution. Two critical data must be provided: population data from the review area and light pollution data generated by the Earth Observations Group (EOG) at the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environmental Information (NCEI). We are using nine conservation areas in Indonesia, including the Kuningan Botanical Gardens, Bosscha Observatory, Timau Kupang National Observatory, Sermo Reservoir, Mount Batur Geopark, Sewu Mountains Geopark, Mount Rinjani Geopark, Lake Toba Geopark, and Belitong Geopark. The developed model involves a linear model to predict ALAN with spatial–temporal modeling. We present long-term predictions for the next 20 years.
... At each location, particles were released at intervals of 4 h every night for 2 mo, beginning at 19:30 h and ending at 03:30 h local time, and then tracked for 30 d. This was designed to cover the time that hatchlings usually emerge (between 19:00 and 04:00 h; Kamrowski et al. 2014b) as well as covering a range of environmental conditions (high/low and spring/ neap tides) as the timing of release can influence distribution in particle tracking models (Wildermann et al. 2017). At each 4 h interval (i.e. each release), 1000 particles were released across all 12 sites, with the number of particles released at each site being proportional to the relative size of the nesting population (Fossette et al. 2021a). ...
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The lack of data on distribution of juvenile marine species can limit conservation efforts. As hatchlings, marine turtles are too small to track using satellite telemetry, so their at-sea distribution remains unknown. This knowledge gap is critical, as hatchlings already experience high mortality in coastal zones. In addition, further risks to their survival may occur beyond these areas, linked to threats associated with in-water artificial infrastructure and/or attraction to artificial lights and thus increased mortality from higher risk of predation or exhaustion from disorientation. To fill this gap, we used particle tracking forced by an ocean circulation model to predict the dispersal of flatback turtle Natator depressus hatchlings from 12 nesting sites off the coast of Western Australia. We used the model outputs to calculate the distribution of these ‘virtual hatchlings’ and infer the core area of hatchling use over 3 dispersal phases (1-4, 10-15 and 25-30 d). We then calculated the overlap between core areas and 2 anthropogenic threats (in-water artificial infrastructure and light pollution). Core areas were predominately located on the continental shelf during all dispersal phases, supporting the hypothesis that flatback turtles remain in neritic areas. Most (70-80%) of the core area during early dispersal (Days 1-4 and 10-15) contained at least one threat. However, less than half of the area used between Day 25 and 30 was exposed to threats. In the absence of empirical data on hatchling distribution, our results have predicted the core areas used by early life stage flatback turtles to assist in conservation management of these threatened species.
... In addition to the lighting directed to the water, artificially brighten skies might be a potent ALAN source, considering a case of the orientation of hatchling sea turtles that were disturbed by light-polluted skies even on a 15-km-distant beach from a light source (Kamrowski et al. 2015). For this reason, artificial sky brightness at the zenith (μcd m −2 ) was quantified using the New World atlas of artificial night sky brightness (Falchi et al. 2016) through the web application (https:// www. ...
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Full-text available
There is growing concern about the potential impact of artificial light at night (ALAN) on the ecology of various taxonomic groups and their associated ecological processes. Freshwater anguillid eels have nocturnal and crepuscular foraging behaviors in estuarine and riverine habitats that are likely affected by ALAN, but little is known about possible effects. We examined changes in foraging activity of Japanese eels, Anguilla japonica, in relation to ALAN using catch data collected during recreational fishing activities. There were significant differences in the relationship between the frequency of eel catches and times from sunset among different illuminance conditions. The frequency of eel catchs peaked at dusk in the lower illuminance conditions, whereas eel catch times were delayed and most eels were caught more than 120 min after sunset at fishing sites highly exposed to artificial lights. Eels were not caught in lighted conditions but were caught after the artificial lights were turned off, although it is not clear if foraging reduction in lighted duration could be compensated for. However, at two sites located near cylindrical refuge traps, eels were caught independent of the lighted durations and sunset times. These preliminary results suggest that ALAN has caused reductions or delay of foraging activity of Japanese eels in urbanized estuarine and riverine habitats, but the presence of preferable refuge habitats may influence the effects of artificial light. Future studies examining the abiotic and biotic environmental factors more rigorously are needed that can contribute to the effective conservation of eel populations and aquatic communities.
... In the recent years, obtrusive light has been found to affect the entire environmental equilibrium. The Artificial Light at Night (ALAN) can perturb health of many species (animals, insects and plants) including humans [1][2][3][4][5][6][7]. ALAN can be divided into two main components the direct and indirect ALAN. ...
Article
Full-text available
This paper is a technical report describing the use of an open source instrument called LANcube v2 to estimate a lighting devices inventory. The LANcube v2 is and instrument having 5 color sensitive sensors, each on a face of a cube. The instrument can be mounted on a car roof in order to create a map of the artificial light at night while roaming the streets and roads. Based on the temporal variations of the detected signal on various cube’s faces, we developed a method of finding the approximate position in 3D of each source. The lamp spectral types can be determined relatively well thanks to the color balance of the raw Red (R), Green (G), Blue (B), and Clear (C) color bands. If one assumes a typical angular photometry of a source with respect to its location, it is possible to estimate roughly its current luminous flux. Such information allows us to build a lighting devices inventory of a territory. One advantage of that new method is that it can provide information about the private sources that are always excluded from public lighting inventories. We compared the inventory extracted with that new methodology with an in situ lamp inventory made for two villages in Canada. This comparison allow us to emphasize the strengths and limitations of the method by comparing to the ground truth. We actually found that we were able to detect 99% of the sources with flux higher than 1000 lumen and located within 15 meters from the road. We also found that we generally overestimate the height of the devices by 21 to 51% depending on the lamp photometry. This overestimate surely reflect in an overestimate of the fluxes. Finally, we found that the proposed method is very efficient to recognize the spectral type of the devices with 99% of success.
... On one hand, the levels of concentration and distribution of LP imply new conditions in the selection of sampling methodologies, number of data, and frequency of sampling, besides an adequate statistical model to have reliable results [10] . On the other hand, the adverse risks derived from exposure to LP are a function of the pollutant source and the characteristics of the area where the exposed population is located [11][12][13] . Therefore, LP monitoring networks designed for environmental studies should consider both characteristics, those of the pollutant source and the exposed area. ...
Article
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La pollution lumineuse est un problème qui préoccupe les astronomes depuis plusieurs décennies. L’étude de ce phénomène repose sur des mesures de la brillance du ciel et des mesures des propriétés optiques de l’environnement nocturne, notamment la caractérisation de l’émission des sources lumineuses, et de la modélisation de la propagation de la lumière artificielle. Les récentes découvertes sur les impacts de la pollution lumineuse sur l’environnement et la santé humaine ont propulsé la recherche dans le domaine. Cette expansion met en évidence le besoin d’avoir des outils d’analyse et de mesures plus facilement utilisables par des chercheurs novices en la matière. Le présent travail répond en partie à ces besoins en proposant deux nouveaux outils : 1) une méthode de modélisation de la propagation de la lumière d’origine anthropique dans l’environnement nocturne simple d’utilisation et basée sur des principes physiques et 2) une méthode d’étalonnage d’appareils photographiques numériques nécessitant un minimum de matériel à coût prohibitif pour la caractérisation des propriétés des sources lumineuses qui contribuent à la brillance artificielle du ciel. Le premier article présenté dans ce travail décrit la méthode de modélisation élaborée. Elle repose sur l’utilisation d’une équation de transfert liant la brillance des sources lumineuses présentes sur le territoire étudié à la brillance du ciel en fonction de la distance à la source de lumière et le point d’étude. Des techniques de traitement d’image de convolution de fonction d’étalement de point (point spread fonction) sont utilisées pour convertir les cartes de brillance des sources de lumière en cartes de brillance du ciel. La particularité de cette approche est que la fonction de transfert est obtenue à l’aide du modèle de transfert radiatif le plus complexe au monde pour l’étude de la pollution lumineuse (Aubé et Simoneau, 2018; Aubé et al.,2020b), plutôt que des mesures in situ. Cela permet de définir des fonctions de transfert basées sur la physique du phénomène ainsi que sur les caractéristiques de l’environnement étudié. De plus, cette approche a le potentiel de décrire aisément des situations théoriques, comme de potentielles modifications à l’infrastructure d’éclairage, permettant ainsi d’évaluer l’impact de décisions administratives sur la pollution lumineuse. Cependant, cette versatilité requiert une bonne connaissance des propriétés optiques et géométriques de l’environnement, particulièrement les caractéristiques des sources lumineuses, des obstacles et des aérosols. Le second article décrit une méthode d’étalonnage de d’appareils photographiques numériques pour la caractérisation des émissions des sources de lumière artificielle. Cette méthode est conçue pour être utilisée en combinaison avec la méthode faisant l’objet de l’article précédent, tout en pouvant être utilisée à d’autres fins. L’étalonnage de ce type d’appareils photographiques se fait en plusieurs étapes. Tout d’abord, une correction par un cliché sombre est appliquée pour le biais du capteur ainsi que les effets thermiques. Puis, un champ plat est utilisé pour compenser la sensibilité réduite en bordure des images. Ensuite, la linéarité du capteur est étalonnée en variant le temps d’exposition d’une source de brillance constante. De plus, une procédure de photométrie synthétique stellaire sert à établir l’étalonnage absolu du capteur. Finalement, les distorsions géométriques du système optique sont établies à partir d’une photographie d’un champ stellaire. Des appareils photographiques étalonnés selon cette méthode installés à bord de plateformes aéroportées permettent d’établir les caractéristiques des sources de lumière artificielle étudiées.
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Natural transitions between light and darkness influence the biology and behaviour of many organisms. What happens when humans introduce light into darkness? Oceanic beaches, where sea turtles nest, provide an example of both the problem and approaches to its solution.
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Coastal development adjacent to sea turtle nesting beaches can result in an increase in exposure to artificial lighting at night. That lighting can repel nesting females and interfere with the orientation of hatchlings from the nest to the sea. Disrupted hatchling orientation is a serious source of turtle mortality, sufficient to reduce recruitment and contribute to a long-term marine turtle population decline. The purpose of this study was to assess whether artificial lighting disrupts hatchling sea-finding behaviour at the largest loggerhead rookery in the South Pacific, the Woongarra coast, southeast Queensland. The crawling tracks of hatchlings that emerged from nests, as well as staged emergences, were used to assess the effect of lighting conditions at several local beaches on hatchling sea-finding behaviour. Disrupted orientation was observed at only a few locations, excluding the majority of the main nesting beach at Mon Repos Conservation Park. At the sites where orientation was disrupted, normal orientation was restored when a full moon was visible, presumably because lunar illumination reduced the perceived brightness of the artificial lights. The controlled use of lights used for guided turtle-viewing tour groups within Mon Repos conservation Park did not interfere with the sea-finding behaviour of hatchling turtles. Further coastal development, especially at the nearby town of Bargara, requires that a light management plan be formulated to ensure that development does not adversely affect the marine turtles that utilise the local nesting beaches.
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