Protected Species Use of a Coastal Marine Migratory Corridor Connecting Marine Protected Areas

Mar Biol DOI 10.1007/s00227-014-2433-7

Original Paper

Protected species use of a coastal marine migratory corridor connecting marine protected areas

Kellie L. Pendoley · Gail Schofield · Paul A. Whittock · Daniel Ierodiaconou · Graeme C. Hays

Received: 2 October 2013 / Accepted: 21 March 2014 © Springer-Verlag Berlin Heidelberg 2014

Abstract The establishment of protected corridors link- marine wildlife in this region, humpback whale migratory ing the breeding and foraging grounds of many migra- tracks overlapped with 96 % of the core corridor, while the tory species remains deficient, particularly in the world’s tracks of three other species overlapped by 5–10 % (blue oceans. For example, Australia has recently established whales, olive ridley turtles, whale sharks). The overlap a network of Commonwealth Marine Reserves, supple- in the distribution ranges of at least 20 other marine ver- menting existing State reserves, to protect a wide range tebrates (dugong, cetaceans, marine turtles, sea snakes, of resident and migratory marine species; however, the crocodiles, sharks) with the corridor also imply potential routes used by mobile species to access these sites are often use. In conclusion, this study provides valuable information unknown. The flatback marine turtle (Natator depressus) towards proposing new locations requiring protection, as is endemic to the continental shelf of Australia, yet infor- well as identifying high-priority network linkages between mation is not available about how this species uses the existing marine protected areas. marine area. We used a geospatial approach to delineate a coastal corridor from 73 adult female flatback postnesting migratory tracks from four rookeries along the north-west Introduction coast of Australia. A core corridor of 1,150 km length and 30,800 km2 area was defined, of which 52 % fell within 11 Marine protected areas (MPAs) are now being widely intro- reserves, leaving 48 % (of equivalent size to several Com- duced around the world and are often designated, at least monwealth Reserves) of the corridor outside of the reserve partly, to help protect migratory animals where they sea- network. Despite limited data being available for other sonally aggregate to breed or forage (e.g. cetaceans, Hooker et al. 1999; sharks, Kinney and Simpfendorfer 2009; sea Communicated by R. Lewison. turtles, Schofield et al. 2013a). However, migratory species are also at risk during migration along corridors con- Electronic supplementary material The online version of this necting breeding and foraging habitats (Shillinger et al. article (doi:10.1007/s00227-014-2433-7) contains supplementary 2008; Womble and Gende 2013). Yet, while studies are material, which is available to authorized users. beginning to identify key corridors used by marine wild- K. L. Pendoley · P. A. Whittock life (Mumby 2006; Block et al. 2011; Olavo et al. 2011), Pendoley Environmental Pty Ltd, 12A Pitt Way, Booragoon, the protection ofsuch areas remains primarily hypothetical WA 6154, Australia (but see Lipcius et al. 2003; Fernandes et al. 2005; King and Beazley 2005; Guzman et al. 2008) or experimental G. Schofield (*) · D. Ierodiaconou · G. C. Hays Centre for Integrative Ecology, School of Life and Environmental (Holland 2012). The benefits of connecting protected habi- Sciences, Deakin University, Warrnambool, VIC 3280, Australia tats, including isolated areas, involve potentially reducing e-mail: [email protected] the risk of extinction by increasing species and population persistence, improving population sizes, enhancing species G. C. Hays Department of Biosciences, Swansea University, Singleton Park, diversity and/or raising genetic exchange (Newmark 1987; Swansea SA2 8PP, UK Parks and Harcourt 2002; Hilty et al. 2006).

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Failure to implement the protection of wildlife migra- and dolphins (e.g. Double et al. 2010, 2012a, b; Bejder et al. tory corridors on land, sea or air generally arises because 2012), sharks (Wilson et al. 2006; Heithaus et al. 2007; Speed of a combination of wildlife, logistical (capacity to enforce et al. 2010) and commercially important fish stocks (Fer- and associated economic costs), stakeholder and/or politi- nandes et al. 2005). This absence of corridors is partially cal issues (Boersma and Parrish 1999; Hyrenbach et al. explained by many species migrating to oceanic (pelagic) 2000; Shillinger et al. 2008; Womble and Gende 2013). For habitats (e.g. blue whales, Branch et al. 2007; whale sharks, instance, the consistency of animal migratory routes may be Sequeira et al. 2013; sea turtles, Wallace et al. 2010), rather subjected to variation at both individual and population-level than along the coast of Australia, making viable corridors scales, complicating the delineation of key protection zones difficult to establish. Furthermore, recent research has sug- (for overview, see Akesson and Hedenstrom 2007; Agardy gested that species occupying higher latitudes invest in more et al. 2011). This issue is exacerbated in avian or marine spe- extensive migrations compared with those occupying tropical cies that traverse open expanses of ocean (e.g. Shaffer et al. regions (i.e. lower latitudes) (Laurel and Bradbury 2006). 2006; Schofield et al. 2013b), because wind and ocean cur- Contradictory to these two statements, the flatback rents cause drift, with course correction being difficult in the marine turtle is endemic to the Australian continental shelf absence of visual cues, such as landmasses (e.g. Berger 2004; (Pritchard 1997), exhibiting both extensive longitudinal Alerstam et al. 2006; Broderick et al. 2007; Hays et al. 2010; (112–152°E) and latitudinal (4–27°S) migratory move- Hawkes et al. 2011). It is difficult to manage (i.e. monitor and ment between breeding and foraging grounds along the regulate) potentially detrimental human activities across vast west, north and east coasts of Australia (Marsh et al. 1993; areas (e.g. Hyrenbach et al. 2000; Hooker et al. 2011). Migra- Wallace et al. 2010), reaching as far as Papua New Guinea tory routes often traverse stakeholder properties (e.g. Innes (Limpus et al. 1983; Prince 1998). This species is consid- et al. 1998; Cherney and Clark, 2009), airways/waterways ered vulnerable in Western Australia (Wallace et al. 2010), heavily used by commercial shipping, natural energy sta- due to predation by wildlife (dingoes and introduced red tions (i.e. wind and wave) and areas used by the armed forces fox), fisheries bycatch and consumption (e.g. of eggs) by (e.g. Mullen et al. 2013; Firestone et al. 2008) or important indigenous peoples; however, the Red List of the Interna- fisheries resources (e.g. Zappes et al. 2013). Finally, migra- tionalUnion for Conservation of Nature (IUCN) catego- tory animals rarely remain within one country; hence, the rises this species as data deficient, and hence difficult to establishment of international management cooperation and assess. As the flatback sea turtle remains in coastal habitats agreed protocols is critical (Shillinger et al. 2008). Recently, throughout its life history, it could be used as a focal spe- more studies are tracking increasingly large numbers of ter- cies to model a coastal migratory corridor (King and Bea- restrial, avian and marine wildlife to accurately infer popu- zley 2005) connecting Australia’s MPAs and may inciden- lation-level movement patterns (e.g. Borger et al. 2006; Pin- tally encompass movement of other migratory species. aud 2007; Schofield et al. 2013b); however, most proposed Here, we analysed 73 adult female flatback tracking data- areas for protection continue to be based on the single-species sets from four rookeries located along the north-west coast approach, rather than at the ecosystem level (Hooker et al. of Australia between 2005 and 2012 to (1) delineate the 1999; King and Beazley 2005). At the governmental level, migratory corridor used by these individuals, (2) determine the minimal investment (or fewest hurdles to overcome) for the extent of connectivity and overlap of this corridor with the maximal output is logically sought (Shogren et al. 1999); existing State and Commonwealth Marine Reserves and (3) hence, the delineation of single corridors supporting multiple establish the potential benefits of such a corridor to other spe- species might be more likely to be considered over multiple cies through the evaluation of tracking/distribution data for corridors supporting single species (Baumgartner 2004). other wildlife in the published literature. Limited information In 2012, Australia announced the establishment of a net- about flatback sea turtles has previously been available until work of Commonwealth Marine Reserves, in addition to this study; hence, here, we evaluate the extent to which the existing State reserves, covering 36 % of the nation’s marine migratory route of an endemic species receives protection by area (Australian Government http://www.environment.gov. the existing and planned network of marine reserves along the au/marinereserves/; Supplementary Fig. 1). This network north-western continental margin of Western Australia. represents an ‘ecosystems’ approach to coastal marine management, by protecting a mosaic of interconnected ecosystem types/habitats and associated biota (McNeill 1994; Fernandes Materials and methods et al. 2005; Russ et al. 2008). Yet, many of these reserves are discontinuous, lacking connecting corridors, despite being Study area and target species designed to protect a number of highly mobile species (Marsh et al. 1993), such as dugong (Marsh et al. 1999), marine tur- An estimated 20 000 female flatbacks nest along the west, tles (e.g. Limpus et al. 1992; Wallace et al. 2010), whales north and east coasts of Australia, spanning latitudes of

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Fig. 1 a Major (red circles) and minor (yellow circles) flatback nesting sites inA ustralia (based on Wallace et al. 2010), b the flatback nesting sites from which the female flatback turtles departed in the current study and c an adult female flatback turtle carrying a transmitter

4–27°S (Fig. 1a; Wallace et al. 2010). Nesting occurs (for transmission details, see Pendoley et al. 2014). All during the austral summer months (November–Janu- transmitters were attached to the carapace of females on ary), with up to four clutches being laid at approximately the beaches immediately following nesting. All units were 13.8 0.6 day intervals in a single season (Pendoley et al. attached using a harness method adapted from Sperling and ± 2014), and females returning to breed every 1–3 years Guinea (2004; Fig. 1c). In brief, each unit was mounted on (Hamann et al. 2003; Limpus 2009). North-west Australia a polycarbonate plate lined with grooved neoprene padding hosts four major flatback breeding regions that fall within to allow water flow beneath the plate. The unit was then existing and/or planned MPAs (Fig. 1a; Wallace et al. positioned on the flatback turtle using a harness threaded 2010). However, several flatback nesting rookeries fall out- through six slots present on the polycarbonate plate. Each side of protection zones. Four such rookeries were stud- unit was positioned on the central anterior portion of the ied within the framework of various environmentalimpact flatback turtle carapace, covering approximately the first assessments of industrial activity (for more detail, see Pen- and second vertebral scutes. The harness had six straps doley et al. 2014). These rookeries included Barrow Island made from nylon seatbelt webbing, which were secured (20.81°S latitude, 115.45°E longitude), Mundabullangana using velcro. Zinc staples held the straps in place and (20.41°S, 118.07°E), Port Hedland (20.31°S, 118.58°S) served as a deliberate ‘weak link’ that gradually corroded. and Thevenard (21.46°S, 115.02°E) (Fig. 1b). A recent This method was provedviable by the return of females study has modelled that Barrow and Mundabullangana sup- between 1 and 3 years after unit attachment in 2005; how- port 1 512 and 1 461 nesting females annually, with insuf- ever, some individuals had evidence of carapace wear. ficient data being available to calculate this information for Hence, as with device attachments to sea turtles in general, the other two nesting sites (Pendoley et al. 2014). it is important to aim to quantify the impacts (e.g. drag) of the attachments on flatback turtles (e.g. Witt et al. 2011; Turtle instrumentation Jones et al. 2013). Units provided either Global Position- ing System (GPS) quality locations (n 65) and/or Argos = Between 2005 and 2012, 100 adult female flatback turtles quality locations (n 8) relayed either via the Argos satel- = were equipped with satellite transmitters at the four speci- lite system or relayed via the mobile phone network. Exter- fied rookeries on the north-west coast ofA ustralia (Barrow nal flipper tags and PIT identifiers were used to distinguish Island, n 59 turtles; Mundabullangana, n 3; Port Hed- individual turtles and confirm that no turtles were tracked = = land, n 30; Thevenard Island, n 8), of which 73 were for more than one season. Transmitters were not attached = = successfully tracked to foraging areas (see Supplemen- to turtles with signs of recent injury, emaciation or flipper tary Table 1 for turtle and transmitter information; Barrow trauma/loss (leeches werenot observed on any turtles). Island, n 44; Mundabullangana, n 2; Port Hedland, = = n 21; Thevenard Island, n 6). Four different models of Data processing = = satellite transmitter were attached to females: KiwiSat101 and Fastloc GPS-Argos transmitters from Sirtrack Ltd., To reconstruct migration tracks, we used the highest MK-10 from Wildlife Computers and Satellite-Relayed Argos quality location classes (1, 2 and 3; Hays et al. Data Loggers from St Andrews SeaMammal Research Unit 2001) and we used GPS quality locations based on six or

1 3 Mar Biol more satellites (Schofield et al. 2013a, b). In addition, we to produce a cumulative track for each turtle. A regular removed locations that necessitated an unrealistically high 20-km grid mesh was generated for the study area using the 1 speed of travel (>5 km h− ; Luschi et al. 1998) or turning Repeating Shapes ArcGIS extension tool (Jenness 2012). angles >25° (as acute turning angles are usually indica- To determine the cumulative track length of all turtles that tive of erroneous locations; Hawkes et al. 2011). Because passed through each 20 km vector grid, a spatial join was of differences in data volume per turtle, the datasets were used. Cumulative track length was used rather than the further filtered to allow comparative analysis among all tur- count of the number of individuals to better reflect corridor tle datasets. This adjustment is important to prevent data path use. This approach ensures that turtles in a given grid point bias to a specific site as a result of certain individuals. were not equally weighted, such as a turtle traversing just Hence, the median location within each day for transmit- 100 m versus a turtle transiting the entire 20 km cell. The ted and retrieved archival data was selected for each turtle results were classified into four categories based on class (Swihart and Slade 1985; Makowski et al. 2006; Tremblay breaks using intervals of 1 standard deviation from the et al. 2006; Schofield et al. 2013a) to conduct objective mean; specifically >1.5 very high use (termed core); 1.5– = analyses of spatial and temporal area use. In addition, we 0.5 high use; 0.5 to 0.5 intermediate use; less than = − = only retained the transiting portions of the tracks to remove 0.5 low use. The four raster categories generated here − = any bias to nontransiting sites, such as the breeding sites were used for the quantification of all subsequent analyses (including internesting movement) and foraging sites. Such (Supplementary Fig. 2). transient sites (where turtles remained for a few days to weeks during migration, possibly foraging) and final for- Migratory corridor overlap with MPAs aging sites were identified (and removed) by individuals slowing down and remaining in fixed areas for extended GIS layers for the State Marine Reserves intersecting with periods of time (minimum of 5 days; see Hays et al. 2010), the turtle track data were obtained from the Department using a combination of displacement distance and changes of Environment and Conservation (n 5, total area 10 = in speed of travel (Blumenthal et al. 2006; Schofield et al. 047 km2). The GIS layers for the Commonwealth Marine 2010). Depth values were extracted from the Australian Reserves (n 18, total area 487 477 km2) were obtained = bathymetry and topography grid (Whiteway 2009) to deter- from the Department of Sustainability, Environment, Water, mine mean seabed depth traversed by each turtle track. Population and Communities (http://www.environment. gov.au/marinereserves/resources.html). Cells with cumu- Migratory corridor delineation lative track values in the grid mesh that intersected with individual State and Commonwealth Reserves and within To delineate the corridor used by turtles, the filtered loca- zoning schemes were identified. Cumulative track length tions were plotted using the World Geodetic System and the proportion of marine reserve containing track cells (WGS84; 1984) in ArcGIS (version 10.1, ESRI®) software. were quantified. Data were projected using the GDA 1994 Geoscience Aus- tralia Lambert projection for spatial analysis. To create Migratory corridor benefit to other marine wildlife kernel density estimates (KDE), first, we conducted least square cross validation (LSCV) to determine smoothing All peer-reviewed literature in the Web of Knowledge and parameters (bandwidth) (Rodgers et al. 2007). We selected Google Scholar, along with publically available reports a 20 km cell size for the KDE analysis based on (1) the on the Internet, was searched for marine mammal, marine large geographical extent of the data analyses and track reptile and shark species in Australia to obtain information density, (2) the trade-off between computational speed and about species distributions and migratory tracking datasets. resolution and (3) because it provided a comparable resolu- When distribution ranges were not available from the pub- tion for the cumulative track length estimate described later lished literature, they were obtained from the Australian in this section. Turtle locations were combined, and the Government Species Profile and Threats Database (SPRAT, KDE grid was derived using the kernel density tool avail- http://www.environment.gov.au/cgi-bin/sprat/public/sprat. able in the Spatial Analyst ArcGISExtension (ESRI®). Grid pl). For the marine species for which tracking data were values were extracted to point turtle locations. Extracted available, the tracks were reconstructed and overlaid on the records were queried to determine the volume of the KDE corridor delineated from the flatback turtle tracks. distribution at 25, 50, 75 and 95 % and subsequently used The migratory tracks of other species (n 6) that were = to threshold the KDE raster to determine utilisation area located for this region were reconstructed using Google estimates for the polygons used for the display. Earth (Supplementary Fig. 3). Then, using ArcGIS (version To determine corridor use, the track locations were 10.1, ESRI®), we generated presence (value 1) and absence converted to polylines sequenced by logged time stamp cells (value 0) for each species, based on reconstructed

1 3 Mar Biol migratory track positions. We then added all species’ extents together to determine cumulative space use. For example, a cell value of seven would indicate tracks for all species (i.e. the six other species plus the flatback) intersecting that specific cell. We then calculated the percentage of migratory species tracks that intersected with turtle tracks and the proportion of tracking cells for each species falling within the marine reserve network.

Results

Migratory movement patterns

Of the 73 adult female flatback turtles tracked to their foraging grounds, 11 remained within 100 km of the fre- quented rookeries (i.e. residents, mean 65 25 km, range ± 10–95 km), four migrated south-west (all from Port Hed- land) and 58 migrated north-east (Fig. 2a; Supplemen- tary Table 1). The four turtles that travelled south-west from Port Hedland migrated an average 400 km (mean 405 29 km, range 370–440 km). Of the 58 turtles that ± migrated north-east, the majority (45 %, n 26) travelled = 500–1,000 km, 22 % (n 13) travelled 100–500 km, 24 % = (n 14) travelled 1,000–1,500 km and 9 % (n 5) trav- = = elled >1,500 km. All turtles combined had a latitudinal range of 10–22°S and longitudinal range of 114–141°E. In general, the females from all four nesting sites were of a similar size range, with anaverage curved carapace length of 90 cm (SD 2.5; range 85–99 cm). Postnesting migra- ± tion away from the rookeries spanned a period from 22 Fig. 2 a The postnesting migratory tracks of 73 adult female flat- November to 27 January, for all years combined. backs tracked from the four nesting sites (yellow circles from west to east: Thevenard, n 5; Barrow Island, n 44; Mundabullan- = = Migratory corridor delineation gana, n 2; Port Hedland, n 22) between 2005 and 2012. b The 25 % (red= ), 50 % (pink), 75 %= (orange) and 95 % (yellow) kernel density estimates (KDEs) of the migratory tracks using ArcGIS (ver- The 50 % KDE was biased to the marine area directly sion 10.1, ESRI®) software. The bandwidth was calculated using fronting the rookeries (Fig. 2b)because this is where the LSCV 35 km. Because the tracks were linear (i.e. unidirectional), = transmitters were attached , hence, where the maximum and all turtles did not depart from the same rookery or arrive atthe same foraging area, the 25–50 % KDEs were biased to the rooker- density of tracks occurred; therefore, this measure could ies (where all tracks began), and hence were not representative of the not be used to delineate a linear migratory corridor. In corridor; therefore, the 75 % KDE was more representative of the comparison, the 75 % KDE better presented the corridor, broader movement patterns of these four rookeries. c Area estimates extending a length of 1 200 km and covering an area of 89 based on cumulative track length using a 20-km grid mesh generated 2 by the Repeating Shapes ArcGIS extension. Cumulative track length 519 km . The maximum extent of the corridor (95 % KDE) was used rather than the count of the number of individuals to better extended 2 760 km in length and covered an area of 235 reflect corridor path use. Class breaks using intervals of 1 standard 488 km2. deviation from the mean were used to divide the data into four SD Cumulative track length in each 20 km vector grid pro- categories: very high use (termed core) >1.5 (red), high use 0.5–1.5 (pink), intermediate use 0.5–0.5 (orange) and low use less than duced a more refined corridor (Fig. 2c). For instance, the 0.5 (yellow) = − core-use area of the corridor (Fig. 2c) was 1 150 km in − length, which was similar to the 75 % KDE, but covered an area of 30 800 km2 (i.e. 66 % smaller than the 75 % KDE). The maximum seabed depth traversed by each track had The maximum extent of the corridor accounting for all grid a mean of 127 m ( 20; max. range 50–127 m), with the ± cells with turtle tracks present was 3 600 km in length and core corridor area ranging between 50 and 500 m seabed covered an area of 301 600 km2. depth, while the maximum depth of the overall corridor

1 3 Mar Biol extended to 1 000 m. All turtles remained on the continental margin, with a maximum track distance from shore of 125 km ( 35; max. range 36–125 km). ± Migratory corridor overlap with MPAs

The adult female flatback corridor connected from six (two State and four Commonwealth; core-use) to 11 (three State and eight Commonwealth; all cumulative track length categories) marine reserves along the west to north coast of Australia (Fig. 3a,b; Supplementary Table 2). Compared with the total extent of the corridor, we calculated that 52 % of the core area is encompassed by the existing/proposed marine reserved, and hence afforded protection. The corridor cells fell into 100 % of five of the reserves and 35–85 % of a further four reserves (Fig. 3b; Supplemen- tary Table 2). In comparison, the core corridor area covered 16–62 % of any given reserve (Fig. 3a,b; Supplementary Table 2). Therefore, an additional 14 800 km2 would be required to establish a core corridor that includes the red cells of the corridor that fall outside thereserves in Fig. 3a and connects the reserves. This addition is similar in size to the Eighty-Mile Beach or Arafura Commonwealth Reserves (Supplementary Table 2).

Migratory corridor benefit to other marine wildlife

The general species distribution ranges indicated that at least 20 species of marine mammals (dugong, cetaceans), marine reptiles (sea turtles, saltwater crocodile, sea snakes) and sharks overlapped with the corridor (Supplementary Fig. 3 a The locations of the State and Commonwealth Marine Table 3); however, this information does not confirm spe- Reserves (black outlined areas) in relation to the cumulative track length estimate for each 20 km grid in Fig. 2c delineating the adult cies use of this corridor. female flatback corridor. Numbering corresponds to the State and/or Limited published tracking information was available Commonwealth Reserves: 1 Shark Bay, 2 Carnarvon Canyon, 3 Gas- for marine wildlife traversing this region. We located, coyne, 4 Ningaloo, 5 Montebello, 6 Dampier, 7 Eighty-Mile Beach, 8 reconstructed and overlaid the tracking datasets of 79 indi- Argo-Rowley Terrace, 9 Mermaid Reef, 10 Roebuck, 11 Kimberley, 12 AshmoreReef, 13 Cartier Island, 14 Oceanic Shoals, 15 Joseph viduals; 40 humpback whales Megaptera novaeangliae; Bonaparte Gulf, 16 Arafura, 17 Arnhem, 18 Wessel, 19 Limmen, 20 two blue whales Balaenoptera musculus; eight pygmy blue Gulf of Carpentaria and 21 West Cape York. See Supplementary Fig. 1 whales Balaenoptera musculus brevicauda; 12 olive ridley for more detailed maps, b Percentage of State and Commonwealth turtles Lepidochelys olivacea; four hawksbill turtles Eret- Reserves (ordered from west to east) that encompassed the flatback corridor based on the cumulative track length estimate for each 20 km mochelys imbricata; and 13 whale sharks Rhincodon typus grid (black bars >1.5 SD, very high use (core); grey bars all (Fig. 3c; Table 1; Supplementary Fig. 3; Supplementary cumulative track =cells). See Supplementary Table 2 and Supplemen= - Table 3). Four of these species overlapped with the corridor tary Fig. 1 for the full terms of abbreviations and MPAinformation; (excluding the pygmy blue whales and hawksbill sea tur- numbers correspond to the reserves presented in part a. c Cumulative overlap of the migratory tracks of the other species’ in relation to the tles). The greatest overlap in species area use (four species; flatback corridor. Presence (1) and absence (0) cells were generated Fig. 3c) was recorded in the western section of the corridor for each species (n 7, including the female flatbacks of the current study) based on the= reconstructed track positions (n 79; Supple- (between the Gascoyne/Ningaloo and Montebello marine = reserves; Supplementary Fig. 1). Overall, 48 % of the corri- mentary Fig. 3) of published papers, and then, all species extents were added (1 species yellow grids; 2 species orange grids; 3 spe- dor was used by two species, 6 % by three species and 2 % cies pink grids;= and 4 species red grids).= The bold black perim- by four species. eter indicates= the 95 % KDE of the= flatback corridor

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Table 1 Tracking studies of other marine species in north-west Australia, showing the overlap with the flatback corridor delineated in the current study Group Common name Latin name Tracking information Overlap (%) Source Core Total

Mammal Humpback whale Megaptera 40 individuals 96 46 Gales et al. (2009), Double et al. novaeangliae (2010, 2012a,b) Mammal Blue whale Balaenoptera 2 individuals 6 5 Branch et al. (2007), Centre for Whale musculus Research http://www.cwr.org.au/ research/bluewhales/satellite.html Mammal Pygmy blue whale Balaenoptera muscu- 8 individuals 0 0 Gales et al. (2009), Double et al. lus brevicaudas (2012a) Reptile Olive ridley sea turtle Lepidochelys 12 individuals 0 9 Whiting et al. (2007), McMahon et al. olivacea (2007), Hamel et al. (2008) Reptile Hawksbill sea turtle Eretmochelys 4 individuals 0 0 Whiting et al. (2006), Hoenner et al. imbricata 2012 Fish Whale shark Rhincodon typus 13 individuals 9 5 Wilson et al. (2006), Sleeman et al. (2010), Sequeira et al. (2013)

The percentage overlap was calculated from the utilisation area estimates based on cumulative track length using a 20-km grid mesh generated by the Repeating Shapes ArcGIS extension. Core 1.5 SD category; Total all SD categories combined ≥ =

The humpback whale tracks (n 40 tracks) overlapped linear movement patterns along this stretch of coastline, = with 96 % of the core flatback corridor and with 46 % of which represented the final leg in their >7,000 km migra- the total flatback corridor. The whale shark and blue whale tion to breeding grounds off Kimberley after departing for- tracks (n 13, n 2) also overlapped with 9 and 6 % of aging grounds in Arctic waters (Gales et al. 2009; Double = = the core corridor, respectively (for both species, the overlap et al. 2010, 2012a, b). Based on the published literature with the total corridor was 5 %). The olive ridley sea tur- (Borger et al. 2006; Pinaud 2007; Schofield et al. 2013b), tle overlapped with 9 % of the eastern end of the corridor sufficient numbers of individuals from bothspecies were (n 12). However, these observations must be interpreted tracked to make reliable population-level inferences (King = with caution, because population-level datasets were only and Beazley 2005). Similar levels of route fidelity along available for humpbacks. coastal tracts have been demonstrated for other marine wildlife across the world (Broderick et al. 2007; Bailey et al. 2009; Hays et al. 2010; Block et al. 2011; Hawkes Discussion et al. 2011; Schofield et al. 2013b). This phenomenon is attributed to the presence of fixed geophysical refer- Based on the tracking data of 73 adult female flatbacks, we ences along the coast that enable the animals to maintain (1) demonstrated that individuals from four flatback marine a fixed course heading (Berger 2004; Alerstam et al. 2006). turtle rookeries show fairly consistent patterns of migra- In contrast, oceanic movement patterns tend to be highly tion along a coastal route separating breeding and forag- dispersed, asexemplified by the movement patterns of blue ing areas, (2) delineated a coastal corridor using geospatial whales, pygmy blue whales and whale sharks tracked in analysis tools, (3) established the utility of the corridor to our study region after departing the coast of Australia (Wil- connect existing and proposed marine reserves in the region son et al. 2006; Gales et al. 2009; Sleeman et al. 2010; and (4) confirmed that other highly mobile marine species Double et al. 2012a; Sequeira et al. 2013), and in the wider use this corridor. Through quantifying the extent to which Pacific (e.g. Block et al. 2011). The core route followed by this corridor is protected within an existing MPA network, the female flatbacks was around 1 500 km in length (with we provide valuable information towards proposing new one individual travelling 2 650 km along the coast), cov- locations for protection, as well as identifying high-priority ering broad longitudinal and latitudinal ranges of similar network linkages between existing MPAs. extents to other marine turtle species occupying more tem- Despite the adult female flatbacks in this study origi- perate latitudes (Broderick et al. 2007; Hawkes et al. 2011; nating from four rookeries separated by up to 350 km, all Hays andScott 2013; Schofield et al. 2013b). Thus, contra- tracked individuals moved along the same narrow tract dicting previous assumptions that species inhabiting lower of neritic waters in the north-west to northern regions of latitudes (tropical) invest in less extensive long distance Australia. Humpback whales also exhibited highly similar migrations (Laurel and Bradbury 2006). However, not all

1 3 Mar Biol turtles migrated long distances, with some remaining resi- transmission locations) at the seascape scale (Chetkiewicz dent around the breeding grounds, and an overall uniform et al. 2006; Block et al. 2011; Maxwell et al. 2011, 2013; distribution in migration distances. This observation indi- Robinson et al. 2011). cates that suitable foraging habitat was, in fact, available In Australia, many endangered marine species are pro- along the entire length of the coast; hence, maybe resources tected from targeted capture throughout much of their are easily exhausted or transient (Bestley et al. 2010), with range. For example, aside from a low level of indigenous it ultimately being more energetically beneficial for indi- aboriginal harvest, flatback turtles are listed as vulner- viduals to move to lower latitudes further from the breeding able (Commonwealth Environmental Protection and Bio- grounds where richer and more reliable alternative sites are diversity Conservation Act 1999 and the West Austral- available (Hays and Scott 2013). ian Wildlife Conservation Act 1950); however, specific Habitat-use maps from tracking data may be biased protection measures have not been implemented outside towards the tagging site, i.e. the tagging site emerges as a of MPAs. Hence, threats of mortality in unprotected cor- high-use area as an artefact; hence, alternative approaches ridors may still be high, for example from fishery bycatch are often designed to obtain less biased habitat-use esti- (e.g. Lewison et al. 2004), boat strike (Hazel and Gyuris mates (e.g. Maxwell et al. 2011), such as state-space mod- 2004) and industrial activity (Whiting et al. 2007). The els or fractal analysis. In addition, Maxwell et al. (2013) efficacy of marine reserves at protecting species remains used the time-weighting method developed in Block et al. a hot topic both for sea turtles and other taxa (e.g. Chape (2011) to weight later locations more than ones near the et al. 2005; Bagchi et al. 2013; Cantu-Salazar et al. 2013). tagging site. In the current study, we found the greatest Hence, it would be interesting to try to assess bycatch rates track density was, quite logically, at the rookeries where inside and outside the marine reserves, as well as inciden- the transmitters were attached, even after removing all tal boat strikes and other potential sources of mortality. In breeding site tracking locations prior to the onset of migra- north-west Australia, there is huge growth in shipping, as tion. Hence, we synthesised cumulative track lengths in part of mining activities, in addition to extensive petroleum 20 km grids, which were subsequently categorised into four and natural gas industrial activity in this region (Roberts categories based on standard deviation intervals. The core et al. 2003; Bejder et al. 2012). For instance, the core area category produced a corridor of similar length to the 75 % of the turtle migratory corridor falls directly over the Bar- KDE, but was much more refined (with a 66 % smaller area row and Thevenard area where the bulk of the North West compared with the 75 % KDE), making it much more via- Shelf oil and gas activity is focused, while Port Hedland ble in terms of potential conservation application. Defining is the largest shipping port in the country in terms of ton- methods to identify corridors is critical for conservation. nage, followed by Dampier (which was visited by over 3 Throughout the literature, the most commonly cited strat- 400 shipping vessels in 2006–2007). North-west Australia egy for long-term biodiversity conservation is increasing is also a major tourist destination, with associated boat- connectivity between protected areas (Heller and Zavaleta ing and recreational fishing activities. Hence, despite the 2009); however, relevant boundaries must be identified remoteness of these territories, there are still threats of (Agardy 1994; Hooker et al. 1999; Agardy et al. 2011) incidental mortality of turtles outside of protected areas; using analytical techniques that are reliable and repeatable therefore, the establishment of a protected coastal corri- for multiple species across multiple taxa (Chetkiewicz et al. dor would serve to safeguard the passage of these animals 2006; Redfern et al. 2006; Robinson et al. 2011). through high-risk areas (e.g. Hooker et al. 1999; Hyrenbach Tracking data may be used to delineate the relative et al. 2000; Parks and Harcourt 2002; Hilty et al. 2006). importance of habitats used by multiple species (Maxwell We found that the existing structure of the marine reserves et al. 2011, 2013). In the current study, we used presence/ (State and Commonwealth) along the west to north coast absence data from tracking datasets to identify the overlap of Australia encompassed 52 % of both the core and total in corridor use by various species. However, because of corridor area. Hence, this reserve network provides inter- small samples sizes from each species, this technique risks mittent protection to migrating marine turtles at certain legs delineating ‘hotspot’ areas that only overlap at the marginal of their journeys. However, even within these reserves, dif- edges of habitat (similar to the overlap of a 95 % utilisa- ferent zones exist with different levels of protection (Sup- tion distribution contour for multiple species; see Williams plementary Table 2), although it has been proposed that the et al. 2013). Alternatively, Maxwell et al. (2013) created use of gillnets, trawls and longline fishing activity be pro- utilisation distributions for each species that was tracked, hibited in all zoning categories, from multiple use to sanc- and then summed together to show where multispecies hot- tuaries (Australian Government http://www.environment. spots occur. Therefore, various methods are being devel- gov.au/marinereserves/). Yet, existing and/or proposed oped to delineate core-use of multiple populations, spe- regulations might require further adjustment and stronger cies and/or taxa that have different start and end points (or enforcement to provide any form of protection benefit for

1 3 Mar Biol flatbacks and other marine vertebrates transiting through network of Australia is pioneering on a worldwide scale these marine reserves. (Fitzsimons 2011); however, focus remains on protecting Furthermore, to provide continuous protection to migrat- areas where animals aggregate (i.e. breeding and foraging ing flatbacks (among other species), these reserves would areas, Australian Government 2008), rather than shared ideally need to be connected by a corridor. The core area of wildlife migratory routes connecting these sites. Here, we the corridor falling outside of the marine reserves covers an used an endemic species to Australia, to delineate a coastal area of 14 800 km2; while this area is large, it is actually of corridor that connects multiple MPAs and is used by other equivalent size to the Eighty-Mile Beach or Arafura Com- marine wildlife of conservation importance. We anticipate monwealth Reserves in this region. In addition, through our that, as the tracking datasets of other marine animals in analysis of tracks of other marine wildlife, we found that this region of Australia are published, the importance of humpback whale tracks overlapped with 96 % of the core this corridor (as a whole or as part of a much longer cor- flatback corridor, confirming the potential importance of ridor) connecting west and east Australia along the north- this linear zone for other wildlife. However, while the two ern coastline will be realised. In conclusion, other, simi- species used the same corridor, the timing of migration to larly overlooked, endemic species of other coastal regions and from breeding areas varies considerably. For instance, around the world might also fit this paradigm and could be the northward and southward humpback migrations along used in the establishment of multispecies corridors. the corridor occur between July and September (Gales et al. 2009; Double et al. 2010, 2012a, b), whereas flatback use Acknowledgments We thank Chevron Australia (D. Moro and extends from September to April (current study; Pendoley R. Lagdon) and BHP Billiton (S. Mavrick) for the funding and logistical support for this project. Thanks to staff and volunteers at Pen- et al. 2014). Consequently, year-round protection meas- doley Environmental for field support; notably, P. Tod, R. Murliss, ures would be required, taking the ecological needs of all N. Sillem, K. Ball, L. Claessen, T. Sunderland and N. Fitzsimmons. species that use this corridor into account to be effective We thank P. Tod of Crackpots Ltd for supply of harnesses and attach- (Chape et al. 2005; Cantu-Salazar et al. 2013). For instance, ment advice. Satellite attachment was conducted under the Depart- ment of Environment and Conservation Licence numbers: SF005670, it is also likely that a number of other species (at least 20, SF006705, SF006706, SF007088, SF007143, SF007144, SF007641 including mammals, reptiles and fishes) that have coastal and SF007643. GIS laboratory facilities at Deakin University, War- distributions also use this corridor to varying degrees (Aus- rnambool, Victoria were used for spatial analyses. We also thank the tralian Government 2008); hence, information is required anonymous reviewers for their constructive suggestions to improve the manuscript. about their habitat-use and movement patterns to establish optimal protection measures. 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