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Ecology, management and conservation in natural and modified habitats
RESEARCH ARTICLE (Open Access)

Foraging habitat locations of flatback (Natator depressus) and olive ridley turtles (Lepidochelys olivacea) in northern Australia

Justin S. Smith A , Colin J. Limpus B , Takahiro Shimada A B , Laurie Booth C , Eve C. Hinchliffe https://orcid.org/0009-0004-5289-3733 A , Mariana M. P. B. Fuentes D , Frank Loban A , Shane Preston A and Mark Hamann https://orcid.org/0000-0003-4588-7955 A *
+ Author Affiliations
- Author Affiliations

A College of Science and Engineering, James Cook University, Townsville, Qld 4811, Australia.

B Queensland Department of Environment and Science, PO Box 2454, Brisbane, Qld 4001, Australia.

C Mapoon Land and Sea Rangers, P.O Box 213, Weipa 4874, Qld, Australia.

D Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL 32306-4320, USA.

* Correspondence to: mark.hamann@jcu.edu.au

Handling Editor: Adam Stow

Wildlife Research 51, WR24054 https://doi.org/10.1071/WR24054
Submitted: 8 April 2024  Accepted: 4 November 2024  Published: 22 November 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Context

Understanding the spatial ecology of endangered species is important for their management. With flatback turtles (Natator depressus) Vulnerable and the olive ridley turtle (Lepidochelys olivacea) Endangered under Australia’s EPBC Act 1999, it is important to understand their movement activity to assess exposure to threats better and appropriately manage population demographics.

Aims

Describe, quantify, and compare the foraging patterns of flatback turtles from the Arafura Sea genetic stock and olive ridley turtles from the eastern Gulf of Carpentaria (GoC) genetic stock.

Methods

Satellite telemetry was used to track post-nesting flatbacks (n = 16) and olive ridleys (n = 8) to identify foraging-activity behaviour and locations between 2013 and 2017.

Key results

Overall, core foraging home ranges showed considerable variability from strong site fidelity to extensive spatial movement (flatback: 1–1065 km2, olive ridley: 2–113 km2). Foraging areas for both species were identified to cross over state and international boundaries (Torres Strait, eastern GoC, western GoC, Kakadu coast, Joseph Bonaparte Gulf and the Arafura Sea within Australia and Indonesia), with nine individuals foraging in Indonesian waters and five foraging in both Indonesian and Australian waters.

Conclusions

Flatback and olive ridley turtles in northern Australia have a large, widespread spatial distribution with varying use levels across the space. Foraging hot spots identified in this study can improve and guide the designation of biologically important areas. Inter- and intra-specific overlaps between foraging grounds were consistent with previous research, strengthening the understanding of foraging hot spots for flatbacks and olive ridleys in Indonesia and the Joseph Bonaparte Gulf.

Implications

This study thus emphasises the importance of area-based management to benefit highly mobile species from multiple populations and taxa, potentially from all life-cycle phases.

Keywords: competition, distribution, flatback, foraging, management, movement, olive ridley, satellite-tracking, spatial ecology.

Introduction

Understanding the spatial ecology of threatened migratory species is a priority for conservation and management (Hyrenbach et al. 2000; Shuter et al. 2011). The spatial distribution of migratory species varies extensively, within and among species, particularly throughout foraging periods (Hussey et al. 2015). Foraging areas can support several genetic stocks of multiple taxa, occurring across administrative and legislative boundaries (Blumenthal et al. 2006; Whiting et al. 2007; Whittock et al. 2016) or representing strong fidelity with highly localised, well-defined feeding locations (Hawkes et al. 2006; Schofield et al. 2010).

It is challenging to manage threats to species or populations that undertake large-scale movements or use large home ranges, such as marine turtles, because they can occur across jurisdictional boundaries and often overlap with multiple anthropogenic stressors (Hays et al. 2019; Miller et al. 2019). Further, travel between various habitats, such as those used for breeding and foraging, could mean that turtles move between areas with different levels of threat exposure, such as protected breeding areas and foraging areas with high shipping traffic or fishery pressures (Blumenthal et al. 2006; Pendoley et al. 2014; Thums et al. 2017). As such, understanding spatial movements of individuals or species can provide robust information for conservation by detailing specific habitats and migration corridors, while highlighting potential threats and population implications (Lucchetti et al. 2016; Fuentes et al. 2020).

Satellite telemetry provides an advanced understanding of spatial distribution and movement behaviours of marine species (Hays and Hawkes 2018). Individuals can be tracked over extended periods, but briefly within the overall life span of the turtles, and their fine-scale movements can be monitored with high position accuracy (Godley et al. 2008). Satellite telemetry, such as fastloc GPS, coupled with data-filtering measures and application techniques, allows finer-scale detail of movement characteristics, indicating specific spatial and temporal attributes of movement behaviour, such as home ranges and movement within them (Godley et al. 2002; Polovina et al. 2004). Consequently, satellite-tracking is increasingly able to provide the information necessary to inform management and conservation policies (Hays et al. 2019; Armstrong et al. 2020; Santos et al. 2021). Increases in available data can aid implementation and inform management initiatives at local and regional scales. They may indicate specific threat implications and species interactions at remote localities within complex environments such as the broad expanse of neritic waters of northern Australia–New Guinea continental shelf (Shimada et al. 2017).

Olive ridley (Lepidochelys olivacea) and flatback (Natator depressus) marine turtles are generally less understood than are other marine turtle species breeding within Australia, with knowledge of their foraging ecology in northern Australia particularly lacking (Limpus 2009; Department of Environment and Science 2021). The paucity of information is likely to be due to remote nesting locations, foraging areas and non-specific migratory paths (Limpus 2009). In general, both species typically inhabit the broad expanse of subtidal neritic waters of the continental shelf of remote, tropical, northern Australia and southern New Guinea (Robins et al. 2002; Whittock et al. 2016), restricting available survey methods (Whiting et al. 2007), except via fisheries bycatch data (Poiner et al. 1990). Efforts to determine spatial coverage and abundance in northern Australia have been made for both flatback and olive ridley turtles, and, although limited, these data have provided a generic understanding of species distribution, foraging areas and areas that are exposed to threats (Robins 1995; Dryden et al. 2008; Wilcox et al. 2013; Riskas et al. 2016). However, ecological information at a smaller habitat-use scale and migration routes are lacking, hindering targeted protection/management efforts or designation of critical habitat.

Consequently, this study aims to determine and describe the foraging locations of flatback turtles from the Arafura Sea (AS) genetic stock and olive ridley turtles of the eastern Gulf of Carpentaria (GoC) genetic stock (FitzSimmons and Limpus 2014) by using satellite telemetry. To achieve these aims, we attached satellite-tracking tags to post-nesting female turtles to discover the spatial and temporal characteristics of their post-nesting foraging activity. This will provide insight into the spatial ecology of these species that can be used to develop and implement management strategies that mitigate adverse anthropogenic pressures on marine turtle populations in northern Australia.

Materials and methods

Study species and study sites

Between 2008 and 2017 (predominantly 2013–2017), satellite transmitters were attached to 16 flatback turtles (Waral Kawa [=Deliverance Island] n = 11, Greenhill Island n = 2, Jardine River n = 2 and Crab Island n = 1) and olive ridley turtles (Western Cape York Peninsula/eastern GoC (n = 8) (Table 1)). All turtles were tagged and tracked during the peak of their nesting season.

Table 1.All marine turtles included in the study identified by species and turtle ID.

SpeciesTurtle IDLocationTransmitter typeRelease dateTime tracked (days)
N. depressus108468WKWC Splash10 – GPS26/2/2013413
N. depressus54530WKWC Splash10 – GPS26/2/2013133
N. depressus64208WKWC Splash10 – GPS26/2/2013223
N. depressus95894WKWC Splash10 – GPS26/2/2013586
N. depressus95896WKWC Splash10 – GPS26/2/2013593
N. depressus133406WKWC Splash10 – GPS4/3/201469
N. depressus133407WKWC Splash10 – GPS4/3/201495
N. depressus133410WKWC Splash10 – GPS4/3/201495
N. depressus140117JRWC Splash10 – GPS1/4/2014344
N. depressus140119JRWC Splash10 – GPS12/9/201461
N. depressus111064GIWC SPOT5 – Argos11/7/2013332
N. depressus129555GIWC SPOT5 – Argos10/7/2013266
N. depressus88239CISirtrack – PTT5/11/2008871
N.depressus133409WKWC Splash10 – GPS4/03/201443
N. depressus133405WKWC Splash10 – GPS4/03/201450
N. depressus133408WKWC Splash10 – GPS4/03/201476
L. olivaceaK65252_48845FBSirtrack – GPS5/08/201343
L. olivaceaK90229_133765FBWC Splash10 – GPS3/08/201762
L. olivaceaQA39899_140118SWBWC Splash10 – GPS24/7/201482
L. olivaceaK90108_48850FBSirtrack – GPS7/08/201575
L. olivaceaQA14005_48850FBSirtrack – GPS16/8/201380
L. olivaceaQA14046_48845FBSirtrack – GPS1/08/201461
L. olivaceaQA23520_48850FBSirtrack – GPS15/8/201474
L. olivaceaQA57043_48845FBSirtrack – GPS5/8/201592

Tagging location of the turtle (WK, Waral Kawa; JR, Jardine River; GI, Greenhill Island; CI, Crab Island; FB, Flinders Beach; SWB, South Wik Beach), transmitter type (WC, Wildlife Computers), release date and time tracked (days) are specified.

Transmitter application

After a successful nesting attempt, satellite tags were attached using one of two methods. Units were attached to flatback turtles by using a specialised harness with a pre-attached transmitter (see Sperling and Guinea 2004). The harness was adjusted to have the transmitter positioned above the top vertebral scute for best transmission performance (Whittock et al. 2014). Turtles were retained on the beach for ~30 min after they had laid eggs and released after transmitter deployment. Transmitters were directly attached to olive ridley turtles on the top vertebral scute by using fibreglass tape and Sika Anchorfix 3+ resin covering five surrounding scutes to maximise adhesion and unit retention (Gredzens et al. 2014; Gredzens and Shaver 2020). Before attachment, the carapace scutes of the olive ridleys were cleaned of algae and barnacles. Anti-fouling paint was applied to the transmitters to reduce biofouling and premature loss of tag function. For both species, only turtles bearing no flipper or carapace damage were selected for tag attachment. Each turtle was measured for curved carapace length and fitted with titanium flipper tags to provide identification to each turtle. PIT tags were also injected into the upper left shoulder of the olive ridley turtles.

Tags and transmission

The following three different models of transmitter were used in the study: SPOT5 (Argos) and Splash10 (Argos-Fastloc GPS) from Wildlife Computers and Argos only and Argos-fastloc-GPS units from Sirtrack Ltd (Table 1). Each GPS tracking unit was programmed to run for 24 h every day for the first 4 months and then every second day for the remainder of its deployment. The tags were programmed to record two positions every hour, with up to 10 repeated attempts following a failed record.

Data processing

Data were collected via Argos and/or Wildlife Computer Internet systems. To remove erroneous data implausible for marine turtle movement, locations were filtered and screened by spatial and temporal duplicates and a data-driven filter as described in Shimada et al. (2012, 2016) by using the R package SDLfilter (Shimada et al. 2012, 2016). Filtering criteria included the following: (1) only using location data for Argos (LC 1, 2 and 3) and only using more than five satellites for GPS; (2) travel between two successive points could not exceed 5 km/h; and (3) locations with turning angles between two successive locations of <25° were dismissed. Data are presented as means ± s.d.

Foraging behaviour was identified when the turtle was deemed to have finished migrating from her nesting site. This was determined using daily movement data, and the end of migration was designated when movement ceased to be in a uniform direction and when the daily speed of movement (using distance and time between successive points) decreased, and daily locations became aggregated in a particular location (as per Barr et al. 2021).

Foraging home ranges

Location data of specific foraging periods were filtered (processed as above) for each turtle to generate fixed kernel density (FKD) estimates for individual foraging areas. This non-parametric analysis highlights areas of use within a home-range boundary. Utilisation distributions (UD) of 50% and 95% were calculated to represent the core areas of foraging (50%), while providing a representation of total home-range movements (95%). UD estimates were calculated for each turtle by using movement-based kernel-density estimation with biased random bridges, by using the adehabitatHR package (version 0.4.21) in R software (version 4.2.1)(Calenge 2006; Benhamou 2011), and all polygons were mapped using ArcGIS Pro (ver. 3.0.0).

Seasonal foraging

The data from two individual flatback turtles (ID: 95894 and 95896) that were tracked using GPS tags for more than a year were examined to determine whether there was a difference in spatial use patterns over longer time scales. Data were filtered and processed (as above), and then home ranges were constructed to achieve 50% and 95% UD for every 3 months of data for each turtle, aligning with the seasons in the southern hemisphere (summer: December–February; autumn: March–May; winter: June–August; and spring: September–November). Overlap in the foraging area across successive seasons was quantified in ArcGIS Pro (ver. 3.0.0) by overlaying 50% and 95% UDs of the foraging areas from successive seasons and calculating the area of the new foraging areas for each change in season.

Bathymetry

The bathymetry layers (100 m horizontal resolution) of the study region were sourced and downloaded from General Bathymetric Charts of the Ocean (available at gebco.net, accessed 21 April 2023). However, foraging area and depth use were quantified by combining turtles’ positions with associated depth data from bathymetry information in ArcGIS Pro to calculate a depth corresponding to each location and then an average water depths (m) for individual home ranges.

Ethics statement

This research was conducted in part within the Queensland Department of Environment and Science Queensland Turtle Conservation Project and James Cook University Permits WISP12408113 and A1804 respectively.

Results

Foraging home range

Flatback turtles were tracked for a mean of 264 ± 61.39 days (range: 43–871), and olive ridley turtles were tracked for a mean of 71 ± 5.40 days (range: 43–92) (Table 1). Most individuals of both species showed comprehensive movement (i.e. 95% UD) around a core (50% UD) foraging areas, which ranged from 1 to 1065 km2 (mean value 173 km2, n = 16) (Fig. 1) and from 2 to11 km2 (mean value 33 km2, n = 8) (Fig. 2) for flatback and olive ridley turtles respectively (Table 2).

Fig. 1.

Distribution of flatback turtle migration and foraging areas (50% and 95% utilisation distributions) for individuals tracked from northern Australian rookeries. Tagging sites L–R; Greenhill Island, Waral Kawa, Jardine River.


WR24054_F1.gif
Fig. 2.

Distribution of olive ridley turtle migration and foraging areas (50% and 95% utilisation distributions) for individuals tracked from north-eastern Gulf of Carpentaria (western Cape York Peninsula) rookeries. Inserted boxes represent foraging areas identified by prior studies: (a) McMahon et al. (2007) and Whiting et al. (2007); (b) Whiting et al. (2007); (c) Whiting et al. (2007); Fukuoka et al. (2022); (d) McMahon et al. (2007); Fukuoka et al. (2022); and (e) McMahon et al. (2007). Tagging site is Mapoon.


WR24054_F2.gif
Table 2.The foraging time (days), core foraging area (50% UD), foraging area (95% UD) and average depth of foraging (m).

SpeciesTurtle IDForaging time (days)Core foraging area 50% UD (km2)Foraging area 95% UD (km2)Average depth used (m)
N. depressus1084682152575811−27.73
N. depressus54530582121375−28.75
N. depressus642081622572795−62.39
N. depressus95894521106512410−69.97
N. depressus9589656753211369−56.73
N. depressus1334063252253−14.24
N. depressus1334076331162−57.87
N. depressus133410801251103−49.31
N. depressus14011710367530−3.66
N. depressus1401194732306−6.18
N. depressus11106426947250−34.26
N. depressus12955523231232−15.17
N. depressus88239808174−20.7
N. depressus1334091730218−17.91
N. depressus1334055025114−2.28
N. depressus13340881077−53.71
L. olivaceaK65252_4884513211−14.54
L. olivaceaK90229_13376510320−16.61
L. olivaceaQA39899_1401187712328−2.81
L. olivaceaK90108_488505219600−60.61
L. olivaceaQA14005_4885030113623−51.74
L. olivaceaQA14046_4884561281134−12.94
L. olivaceaQA23520_48850221671−14.25
L. olivaceaQA57043_4884532761099−110.90

The tracking data identified foraging areas for flatbacks in regions of the northern Torres Strait, south-eastern GoC, central GoC, Kakadu coast, Northern Territory, Joseph Bonaparte Gulf, Western Australia, and Indonesia (Fig. 1). Home-range analyses for the olive ridleys identified four separate foraging areas, namely, two in Indonesian waters, one in eastern GoC and one in the central GoC (Fig. 2). Of the four olive ridley foraging areas identified in this study, two were within a previously identified foraging area (Fig. 2).

All individuals demonstrated multiple interconnected core foraging areas (Figs 1, 2). Seven individuals had foraging areas in Indonesian waters of the Arafura Sea (flatback: 64208, 95896, 108468, 54530, 133406; olive ridley: QA14005_48850, QA57043_48845) and two had foraging areas in the Papua New Guinean region of the coral sea (133405, 140119); five of these individuals also recorded foraging areas in Australian waters. Overall, we identified foraging areas in Indonesian waters for flatback (n = 7) and olive ridley (n = 2) turtles from breeding sites in northern Australia.

There was an overlap in the overall home range between the two species (95% UD) at three separate locations. First, there is an area of 54.8 km2 in Indonesian waters approximately 180 km west of Indonesia and Papua New Guinea, shared by a flatback individual from Waral Kawa (64208) and an olive ridley individual from Flinders Beach (QA14005_48850) (Figs 1, 2). Second, there is an area in the central GoC, 320 km north of the Northern Territory coastline and 250 km off the Queensland coastline, which supports foraging by both species. Flatback 95896 and olive ridley (K90108_48850) overlapped 21.7 km2 in this area. The third area utilised by both species is located in the eastern GoC, approximately 10 km from the Queensland coast, covering 56.7 km2. Here, there was an overlap between a flatback tracked from Crab Island (140117) and an olive ridley tracked from Mapoon (QA14046_48845). The area of overlap specified in Indonesian waters has also been used by turtles tracked in previous studies (Fig. 2; Whiting et al. 2007; Fukuoka et al. 2022).

Seasonal foraging

Two flatback individuals (95894 and 95896) used large foraging areas over the study duration (Table 3). Analysis of seasonal changes in foraging activity indicated that turtles 95894 (Fig. 3) and 95896 (Fig. 4) show distinct seasonal shifts in the location of the 50% UD area, with most consecutive seasons showing more than 90% of season-to-season shifts of core foraging to have changed (Table 4). However, the overlap of 95% UD is more prevalent for both individuals between seasons and a lower percentage, but still >60%, the percentage of area occupied has changed (Table 5). For both individuals, there was little consistency in the use of space across corresponding seasons when examining core foraging (50%UD) activity (Figs 3, 4).

Table 3.Total area used by flatback individuals 94894 and 95896 over 50% and 95% utilisation distributions (km2).

Season95894 UD 95 (UD 50) (km2)95896 UD 95 (UD 50) (km2)
Autumn 20132168 (211)1757 (88)
Winter 20133184 (191)2906 (125)
Spring 20133296 (321)1988 (207)
Summer 2013/20141724 (258)1372 (66)
Autumn 20142927 (473)2964 (150)
Winter 20141711 (191)1199 (211)
Spring 20141587 (222)1333 (211)
Fig. 3.

Individual foraging core area (50% UD) for flatback individual 95894 in the Joseph Bonaparte Gulf, highlighting space use among and within seasons.


WR24054_F3.gif
Fig. 4.

Individual foraging core area (50% UD) for individual 95896 in the Gulf of Carpentaria among seasons, highlighting space use among and within seasons.


WR24054_F4.gif
Table 4.Proportion of new core foraging (50% UD) area relative to the area used between consecutive seasons for flatback individuals 95894 and 98596.

Consecutive seasons95894 UD 50 (%)95894 UD 50 (km2)95896 UD 50 (%)95896 UD 50 (km2)
Autumn 2013 – winter 201399189100125
Winter 2013 – spring 20139931898203
Spring 2013 – summer 2013/2014902339663
Summer 2013/2014 – autumn 201489422100105
Autumn 2014 – winter 201470136100211
Winter 2014 – spring 201410022291190
Table 5.Proportion of new 95% UD foraging relative to the area between consecutive seasons for individuals 95894 and 95896.

Consecutive seasons95894 UD 95 (%)95894 UD 95 (km2)95896 UD 95 (%)95896 UD 95 (km2)
Autumn 2013 – winter 2013892822962776
Winter 2013 – spring 2013902959881758
Spring 2013 – summer 2013/2014811391891220
Summer 2013/2014 – autumn 2014792341992946
Autumn 2014 – winter 2014611037981169
Winter 2014 – spring 201499157875996

Bathymetry

The foraging grounds of each flatback and olive ridley differed in the average bathymetry profile, ranging from 2 m to 69 m and 2 to 110 m of depth respectively (Table 2). There were two flatbacks and one olive ridley that had foraging home ranges close to the coastline, and thus, the average depth uses of these turtles was <10 m. In contrast, four flatbacks and two olive ridleys used mean water depth >50 m. The average seabed depth was similar across foraging habitats used by both species, with flatback foraging areas averaging 32 ± 5 m deep and olive ridleys foraging areas averaging 35 ± 13 m deep.

Discussion

Post-nesting flatback and olive ridley turtles in northern Australia have large spatial distributions and widely dispersed foraging grounds across different jurisdictions. In the longest flatback dispersal, one turtle moved 1660 km over 55 days from Waral Kawa in Torres Strait to a foraging area in north-western Western Australia. The longest olive ridley migration was 844 km over 50 days from Mapoon, Queensland, into Indonesian waters. Our data are similar to other data from the species elsewhere in Australia, which collectively demonstrates that both species move long distances between nesting and foraging grounds and variable-sized foraging areas are distributed exclusively within neritic continental shelf waters of northern Australia–southern New Guinea (McMahon et al. 2007).

Home-range analysis for flatbacks showed high inter-individual variation in the size of the core (50% UD) foraging area, ranging from 1 to 1065 km2 (mean = 173 km2). It consequently demonstrated that flatback turtles in this region can move extensively during foraging across large areas, and, in general, more than any other marine turtle species tracked for similar durations in Australia (Block et al. 2011; Gredzens et al. 2014; Shimada et al. 2016, 2020; Barr et al. 2021). Similarly, analysis of olive ridley home ranges showed a large variation in core (50% UD) areas of 2 to 113 km2 (mean = 34 km2) for four individuals throughout the GoC (n = 2) and Indonesian waters (n = 2). The upper limit of the home-range area is similar to that found for individuals tracked from the Northern Territory, where Whiting et al. (2007) found olive ridley home ranges to vary between 138 and 1260 km2. Together, these results demonstrate that olive ridley turtles can forage over large areas. Still, the results of the present study also indicated that individual olive ridley and flatback turtles can constrict their foraging activity to a small specific region, presumably if resources allow.

When comparing the foraging areas identified in this study to results from other studies, the partial overlap of foraging areas between females from genetically distinct populations is evident (Whittock et al. 2016). In particular, the collective research conducted on the spatial ecology of flatback and olive ridley turtles in northern Australia has indicated that the central and northern waters of the Arafura Sea, including those in Indonesian waters, are important foraging sites for both species, with nine individuals using multiple foraging core areas (50% UD). In addition, it has given additional strength to justify a regionally significant foraging area in the Joseph Bonaparte Gulf region of Northern Territory, Western Australia, and the adjacent Commonwealth waters. This strengthens the need for cooperation in the management or development of regional-focused strategies for managing pressures on the marine environment across the northern Australian and southern Indonesia region (Miller et al. 2020; Pilcher and Welly 2021).

Two flatback individuals, tracked for over a year, displayed seasonal-based variations in their foraging home ranges. In both cases, turtles used separate 50% UD core foraging areas across seasons, highlighting the potential for temporal variation in foraging areas. Previous evidence of seasonal influence on adult marine turtle foraging habitat use was recorded for green and loggerhead turtles in southern Queensland and loggerhead turtles in the Mediterranean (Shimada et al. 2016; Dujon et al. 2018). Although the spatial scales are different, and the green turtles moved only short distances, in this study, the general pattern of our results is similar in that the tracked turtles used different foraging areas across seasons. Flatback turtles seem to require large areas relative to some other hard-shelled turtles (e.g. greens, loggerheads, hawksbills), presumably because their primary diet is sparsely distributed or less predictable benthic and planktonic soft-bodied invertebrates (Limpus 2009). That said, while there are no data from any study to indicate whether flatback turtles have the capacity to react to changes in food accessibility, if they are like other hard-shelled species, they will tend to remain in their familiar home habitats, possibly because shifting locations to unknown areas could be too risky, for example, because of poor knowledge of food locations or shelter from predators in the new habitat. Therefore, despite the occupancy of large areas, flatback turtles are likely to be vulnerable to aperiodic changes in habitat quality or availability of food.

From bathymetry projections, we can infer that flatback and olive ridleys typically reside in habitats deeper than 10 m, which supports knowledge from previous research and studies of bycatch (Poiner et al. 1990; Robins 1995; Whittock et al. 2016; Wildermann et al. 2017). All home ranges indicated a foraging depth range that extended from 2 to 70 m for flatbacks and from 3 to 111 m for olive ridley turtles. However, correlating spatial-use data with spatial bathymetric data does not provide information on an individual’s diving behaviour and depth use. Future studies could combine telemetry with depth recorders to obtain specific data on dive behaviour and foraging (e.g. Hounslow et al. 2023). However, our data concur with those of studies by Whiting et al. (2007), Whittock et al. (2016) and Thums et al. (2017), which indicated that flatbacks from the Pilbara populations use mean water depths of 36.5 ± 22.5 m, whereas olive ridley populations from Northern Territory rookeries are reported to forage in water depths between 20 and 150 m, also on the basis of bathymetry information rather than diving data.

Foraging data show that flatbacks and olive ridleys use coastal and open-water habitats from nearshore areas and up to 225 km offshore. From previous tracking overlap, we can confirm that the foraging areas identified within the Joseph Bonaparte Gulf are remote, difficult to access and comprise various habitat types (Whiting et al. 2007; Whittock et al. 2016). Given the remoteness of the area, little information is available on bathymetry and biophysical features of this region. Inference of resource quality and availability can be made only in certain areas concerning fisheries’ productivity or satellite-derived chlorophyll layers, and this will not illuminate the trophic structure and complete available food source. Flatbacks feed primarily on benthic and planktonic soft-bodied invertebrates (Limpus 2009), reacting to specific environmental predictors influencing prey distribution (Wildermann et al. 2017). Benthic-community variability may significantly affect species distribution and foraging behaviours, because individuals must constantly move to follow mobile or unreliable food sources or seek specific habitats. Information on the triggers of community variability in particular regions may be used to indicate potential population movement and behaviour. Further dietary-analysis details will help highlight and determine the significant resources of both species, providing possible insight into population distribution patterns and may aid in management initiatives of specific populations and habitat areas.

Further research into the links between space use and foraging ecology may explain and determine resource use and availability for marine turtles in the northern Australian region. Identifying the predictors that drive responses can help determine species and population distribution patterns. However, telemetry-tracking of a small number of turtles from restricted breeding sites within a stock will almost certainly underestimate the actual foraging range of marine turtles (Shimada et al. 2021; Perez et al. 2022). Flipper-tag recoveries (n = 3) from flatback turtles tagged while nesting at eastern Gulf of Carpentaria nesting beaches for the AS genetic stock have been recorded within Papua New Guinea coastal waters up to 500 km east of Torres Strait (C. J. Limpus, unpubl. data). Overall, this study has shown that flatbacks and olive ridleys of northern Australia are capable of large-scale movement patterns, reside in large foraging habitats and exhibit intra-annual shifts in their core habitats. Future research should concentrate on elucidating the factors influencing these behaviours. Focusing on spatial population ecology, resource type, and availability will help develop a management protocol to aid species recovery by outlining potential threats from known spatial and temporal movement characteristics, identifying the resources that may influence specific distribution and setting boundaries of areas such as biologically important areas, or as a basis for other spatial-based threat mitigation.

Data availability

Data are available on request.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Declaration of funding

The work conducted at Waral Kawa was part of a project funded by NERP to understand marine turtles in northern Torres Strait by the Torres Strait Regional Authority and Rangers of Boigu Island. The olive ridley tracking was funded by the Queensland Department of Environment and Science.

Acknowledgements

We acknowledge the Traditional Owners of the land and sea country in which the study took place. We thank Janine Ferguson for technical support and the Mapoon Land and Sea Rangers and the Torres Strait Regional Authority Land and Sea Rangers for facilitating approvals, transport and participation in fieldwork. The work conducted at Waral Kawa was part of a larger Land and Sea Management project of the Torres Strait Regional Authority and Rangers of Boigu Island.

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