Abundance of Coastal Dolphins in Roebuck Bay, Western Australia

Cetacean Research Unit School of Veterinary and Life Sciences Murdoch University Murdoch WA 6150 www.mucru.org

Abundance of coastal dolphins in Roebuck Bay, Western Australia

Report to WWF-Australia

February 2014

Alexander M. Brown, Lars Bejder, Kenneth H. Pollock and Simon J. Allen

Please cite this document as: Brown, A.M., Bejder, L., Pollock, K.H. & Allen, S.J. (2014). Abundance of coastal dolphins in Roebuck Bay, Western Australia. Report to WWF-Australia. Murdoch University Cetacean Research Unit, Murdoch University, Western Australia, 25pp.

All photographs © WWF-Australia/MUCRU

Table of Contents

Non-technical summary ...... 1 Background ...... 2 Objectives ...... 3 Methods ...... 3 Ethics statement ...... 3 Study area...... 3 Data collection ...... 3 Distribution of sightings, group sizes and encounter rates ...... 5 Grading and scoring of photographic-identification images ...... 6 Proportion of distinctly marked individuals in the population ...... 7 Identification and resight rates ...... 7 Abundance estimates ...... 7 Potential movements of animals between study sites ...... 8 Results ...... 8 Effort ...... 8 Distribution of dolphin sightings and group sizes ...... 9 Encounter rates ...... 11 Identification and resight rates ...... 12 Abundance estimates ...... 13 Potential movements of animals between study sites ...... 14 Local and indigenous engagement and data dissemination ...... 14 Discussion ...... 15 Abundance of dolphins in Roebuck Bay ...... 15 Conservation and management implications ...... 16 Recommendations for future research ...... 17 Acknowledgements ...... 17 Literature cited ...... 18 Appendix 1 - Encounter rate maps of all species ...... 21 Snubfin dolphins ...... 21 Bottlenose dolphins ...... 21 Humpback dolphins ...... 22 Appendix 2 - Abundance estimate model outputs ...... 23 Appendix 3 - Dugong sightings ...... 25

Non-technical summary

The abundance of populations and species of animals is a key consideration in assessing their conservation status and determining suitable management strategies. For dolphins, abundance estimates and other baseline data are lacking throughout the majority of tropical northern Australian waters. This lack of data is impeding assessment of their conservation status and the development of appropriate management measures in the face of numerous anthropogenic threats.

Three species of dolphin regularly occur in the near-shore waters of tropical northern Australia - the Australian snubfin dolphin ( Orcaella heinsohni , ‘snubfin dolphin’ hereafter), the Indo-Pacific humpback dolphin (Sousa sp., ‘humpback dolphin’ hereafter) and the Indo-Pacific bottlenose dolphin ( Tursiops aduncus , ‘bottlenose dolphin’ hereafter). Murdoch University’s Cetacean Research Unit (MUCRU) is conducting research on these three species at several locations across north-western Australia. In 2013, MUCRU researchers were awarded funds by WWF-Australia to add to existing data on inshore dolphins in the Kimberley region by collecting data on the abundance of coastal dolphins in Roebuck Bay, with a focus on the snubfin dolphin.

In collaboration with Nyamba Buru Yawuru Pty Ltd., five weeks of survey effort took place in October- November 2013. A study area of approximately 100 km 2 was surveyed several times from a small research vessel following specific transect routes of around 60 km length. Photographic-identification was conducted on all groups of dolphins encountered, resulting in a database of individual animals, identifiable by unique patterns of notches on their dorsal fins. A total of 19 days of survey effort was completed, with the research team navigating over 400 km of transect. Over this period, 74 groups of snubfin dolphins were observed, along with four groups of bottlenose dolphins and one group of humpback dolphins. Group sizes of snubfin dolphins ranged from one to 16, with a mean of 4.4 individuals. Encounter rates of snubfin dolphins per transect ranged from 0.19 - 2.69 dolphins per km 2 survey effort, with a mean of 1.61 dolphins per km 2 survey effort. Encounter rates of snubfin dolphins were highest within the Inner Anchorage and over the extensive shallow flats on the eastern side of Roebuck Bay. The mean encounter rates of bottlenose and humpback dolphins were low at ≤ 0.1 dolphins per km 2 surveyed.

We photographically-identified a total of 100 different snubfin individuals (excluding calves) with distinctive markings on their dorsal fins. New animals continued to be identified throughout the study period, suggesting that only a subset of the total number of animals which may use the study area were observed during the study period. An open population model produced the best abundance estimate of 137 snubfin dolphins (excluding calves) using the study area over the five-week study period. This estimate had a narrow confidence interval (95% confidence intervals of 117-162; with standard error of 11.6) implying that the estimate is reliable.

At over 130 animals, this is the largest reported abundance of snubfin dolphins in Australia to date and should be considered of regional and, indeed, national significance. Despite this relative magnitude, it is small by conservation standards and sensitive to change. Given the abundance estimate presented here and our current understanding of snubfin dolphin distribution and genetic structure in the region, decision makers and resource management agencies should be prioritising measures to minimise anthropogenic threats to this population in the current planning of a marine protected area. We also recommend that further research be carried out at different times of the year and across a broader area, in order to investigate potential seasonal changes in abundance and to examine the relative importance of different areas within Roebuck Bay. Consideration should also be given to more regular monitoring in areas of importance to dolphins using local resources and personnel.

Background

The abundance of populations and species of animals is a key consideration in the assessment of their conservation status. Abundance estimates are, therefore, essential for management agencies in developing appropriate conservation measures to ensure the maintenance of biological diversity and ecosystem integrity. For delphinids, abundance estimates and other baseline data are lacking throughout the majority of tropical northern Australian waters. This lack of baseline data is impeding assessment of their conservation status and the development of appropriate management measures in the face of numerous anthropogenic threats (Parra et al., 2006, Bejder et al., 2012, Cagnazzi et al., 2013).

Three species of dolphin regularly occur in the near-shore waters of tropical northern Australia - the Australian snubfin dolphin ( Orcaella heinsohni , ‘snubfin dolphin’ hereafter), the Indo-Pacific humpback dolphin (Sousa sp., ‘humpback dolphin’ hereafter) and the Indo-Pacific bottlenose dolphin ( Tursiops aduncus , ‘bottlenose dolphin’ hereafter). All three species are listed as ‘migratory’ under the Environmental Protection and Biodiversity Conservation Act 1999 (EPBC Act) and, therefore, are considered ‘Matters of National Environmental Significance’.

Snubfin and humpback dolphins are of particular conservation concern due to their likely low numbers in Australian waters (Bejder et al., 2012), their apparent reliance upon near-shore waters, which are subject to the most human activity (Parra, 2006, Parra et al., 2006), and the paucity of information on their abundance, distribution and ecology throughout the majority of their range (e.g. Allen et al., 2012, Bejder et al., 2012). The International Union for Conservation of Nature (IUCN) list the snubfin and humpback dolphin as ‘near threatened’ throughout their distribution (Reeves et al., 2008a, Reeves et al., 2008b). However, recent attempts to have them listed as ‘ threatened’ under the EPBC Act have been unsuccessful due to data deficiencies. Similarly, insufficient data exist for either species to be listed as ‘threatened’ or ‘specially protected’ in WA State waters under the Wildlife Conservation Act 1950 , where they are currently listed as ‘migratory’ (Bejder et al., 2012).

Murdoch University’s Cetacean Research Unit (MUCRU) is conducting research on dolphins at several locations across north-western Australia. Specifically, a project funded by the Australian Federal Government through the Australian Marine Mammal Centre (AMMC) commenced in 2012 to estimate abundance, residency and genetic connectivity of snubfin and humpback dolphins in the Kimberley region of Western Australia 1. Over the past two years, we have conducted standardised surveys of inshore dolphins at Cygnet Bay and Beagle Bay, on the Dampier Peninsula, and also within the Cambridge Gulf in the eastern Kimberley.

In 2013, MUCRU researchers were awarded funds by WWF-Australia to augment existing data on inshore dolphins in the Kimberley region by collecting data on the abundance of coastal dolphins in Roebuck Bay, with a focus on the snubfin dolphin. To date, survey efforts within Roebuck Bay suggest that snubfin dolphins are frequently encountered, particularly along the northern shore, and that this area may represent important habitat for them (Thiele, 2010, Allen et al., 2012). However, estimates of the abundance of snubfin and other species of dolphins in this area are as yet unavailable in the published literature.

Based on biopsy samples collected from snubfin dolphins during earlier research efforts, analyses on the genetic diversity of snubfin dolphins within Roebuck Bay and Cygnet Bay, as well as the level of connectivity between these two areas, has been carried out and forms the basis of a forthcoming publication (Brown et al., in prep.). Such data will be used in combination with the results of this structured survey effort to provide critical information upon which to base future conservation management decisions.

1 http://mucru.org/research-projects/snubfin-and-humpback-dolphins-in-the-kimberley-region-western-australia/

Objectives (1) Estimate the abundance of snubfin dolphins within a ca. 100 km 2 area of Roebuck Bay, Western Australia. (2) Provide quantitative information (e.g. encounter rates) on the occurrence of any other dolphin species observed within the study area. (3) Investigate recent movements of animals between Roebuck Bay and Beagle and Cygnet Bays through the cross-referencing of photo-identification catalogues between sites.

Methods

Ethics statement

Field data collection took place under permits from the WA Department of Agriculture and Food (U6/2012- 2014), WA Department of Parks and Wildlife (SF009119), with approval from Murdoch University Animal Ethics Committee (W2342/10), and with the permission and active participation of Nyamba Buru Yawuru Pty Ltd. (NBY), the representative body for Traditional Owners of the area. A NBY representative assisted with data collection from the research vessel for a total of 12 days during the study period.

Study area

Roebuck Bay is a tropical embayment in north-western Australia, lying adjacent to the township of Broome (S 17°57’, E 122°14’). The bay consists of approximately 500 km 2 of subtidal and intertidal foreshore, the vast majority of which is shallow (< 10 m water depth at lowest astronomical tide, LAT). Indeed, the large tidal range of up to 10 m during peak spring tides results in over 200 km 2 of exposed foreshore flats at low tide and inundates numerous mangrove areas, tidal creeks and wetland habitats at high tide.

We surveyed approximately 100 km 2 of subtidal and intertidal foreshore in the northern section of Roebuck Bay (Figure 1). This area was selected as it represents known occurrence of snubfin dolphins (Thiele, 2010, Allen et al., 2012), it covers a range of water depths and was the most easily accessible from suitable vessel launch points. The size of the study area fluctuated with the state of tide, typically ranging between 110 and 90 km 2, with a minimum area of 60 km 2 at LAT. The study area included a range of water depths, from very shallow intertidal flats and banks (Middle Ground) to deeper channels of approximately 20 m water depth (Inner Anchorage and Port surrounds).

Data collection

A systematic sampling design was used to survey the study area, following the same design and protocols as data collection under MUCRU’s broader inshore dolphin research projects. These methods have been effectively employed in the southwest of WA since 2007 (Smith et al., 2013). Data were collected over a five- week period from 04 October to 05 November 2013. This period was selected to avoid the weather and logistical complications of the wet season and to complement the schedule of our other data collection on the Dampier Peninsula.

Using a 5.6 m research vessel with 100 hp four-stroke outboard motor, the study area was surveyed by following two pre-determined transect routes, designed as offset zig-zag lines of approximately 60 km in length, to provide relatively even coverage of the area and sample a range of water depths (Figure 1). The

two transect routes were completed alternately to a total of seven repeats during the study period (four × A, three × B). The inshore extent of survey effort varied according to the state of the tide. We continued inshore on route to a water depth of 0.8 m, or a distance of approximately 200 m from shore (whichever was reached first), before changing course and heading parallel to shore or offshore to the next transect turn. The vessel’s position was automatically recorded at 10-second intervals throughout survey activities by a GPS. Transects were always followed in an east to west direction, to minimize the influence of sun glare on our ability to visually detect dolphins.

Figure 1: Study area and transect design. Depth contours are Lowest Astronomical Tide.

To reduce bias in our ability to detect dolphins, survey effort was only conducted in sea states ≤ three and wave height ≤ 0.5 m, with the vast majority occurring in sea state ≤ two and wave height ≤ 0.3 m. As such, survey effort was largely restricted to the hours of 06:00 - 12:00, due to the seasonal pattern of increasing wind throughout the day. Sea state and wave height were recorded continuously while on transect effort. Transects were completed in the shortest possible time, given the aforementioned constraints on sea conditions, at a survey speed of 10-12 km/h.

When following transect effort, a crew of 4 or 5 observers searched for dolphins off the front half of the vessel between 90° left and right of the vessel’s heading. Observers scanned for dolphins using the naked eye with occasional assistance from handheld 8×42 binoculars. Upon sighting dolphins, the vessel departed from the survey transect route and attempted to approach the dolphin group to a suitable distance (typically 10-30 m) to identify species, group size, behaviour and composition (i.e. adults, juveniles and calves), in addition to obtaining photographs of individual animals for identification purposes. We defined a ‘group’ as one or more dolphins exhibiting relatively close spatial cohesion, where each member was within 100 m of any other member and involved in the same or similar behavioural activity (as per Parra et al., 2006). At the location of each group, a series of environmental parameters were also collected (water depth, secchi depth, sea surface temperature, wind speed and direction).

Two observers, each equipped with a Canon digital SLR camera and Canon 100-400 mm f/4.5-5.6L lens, attempted to photograph all dolphins present (Figure 2). Efforts were focused on obtaining good-quality photographs of dorsal fins. Group surveys lasted a minimum of five minutes and ended once observers were confident that the best possible photographs had been obtained of all animals present (typically < 30 minutes), or the dolphins were lost.

Figure 2. Research vessel and observers surveying a group of dolphins within Roebuck Bay.

Distribution of sightings, group sizes and encounter rates

Mapping was performed using ESRI’s ArcGIS v10.0 with the XTools Pro v10.1 extension. Maps illustrating the locations of dolphin sightings were produced, with graduated symbols corresponding to group size. For sightings in which the number of dolphins present was estimated as a range, the minimum group size was taken. As such, metrics of group sizes and encounter rates are minimum estimates.

Daily vessel track-points were downloaded and merged with time-specific sea state, wave height and on/off effort data. Track-points were then interpolated to lines of effort to calculate the total length of each transect. For encounter rates, a default buffer of 250 m was applied to all transect lines to represent the approximate area surveyed, resulting in a 500 m wide ‘survey strip’ around the vessel. This value was selected as an estimate of the average distance to which dolphins could be reliably observed from the vessel under a variety of sea conditions (modified from Sargeant et al., 2007, Smith et al., 2013). A universal value of 250 m is a simplification of the highly variable nature of dolphin detection probability, but is considered a representative value for the analyses presented here.

The total number of dolphins (including dependent calves) encountered on a given transect was then divided by the total survey area of the corresponding transect to give an encounter rate of dolphins per km 2 of survey effort. Individual dolphins resighted within one hour of the original sighting were not counted a second time. Encounter rates were calculated for each individual transect and, also, for the total survey effort over the study period.

A regular grid of cell size 1 km × 1 km was then generated to overlay the study area. Spatial joins were made between the grid cells, transect survey strips and locations of dolphin groups to determine relative abundance of each dolphin species, expressed as number of dolphins per km 2 of survey effort within each grid cell.

Grading and scoring of photographic-identification images

Individual dolphins were identified from photographs based on patterns of nicks and notches on the leading and trailing edges of the dorsal fin which were visible from both sides, resulting in a database of individuals (Urian et al., 1999). In capture-recapture analyses, two potential sources of bias are misidentification of individuals and heterogeneity in capture probability (Friday et al., 2000, Gowans and Whitehead, 2001, Nicholson et al., 2012). When using photographic-identification as a method of ‘capture’, these sources of bias can be addressed through grading of photographs and scoring of individuals for quality and distinctiveness, respectively.

All individuals were scored according to the distinctiveness of their dorsal fin. Three different observers independently scored each individual according to the criteria outlined by Urian et al. (1999) as D1 (highly distinctive), D2 (distinctive) or D3 (indistinctive) (Figure 3). Each individual was assigned the score given by ≥ two of the three observers. Only D1 and D2 individuals were considered further in the analyses (Nicholson et al., 2012, Tyne et al., 2014). Dependent calves were excluded from the analyses.

All photographs were qualitatively analysed and a selection of the best images of each individual were retained. Each of these retained images was then subject to a quality assessment based on published protocols (Urian et al., 1999, Rosel et al., 2011, Nicholson et al., 2012). Quality criteria considered were clarity and focus, degree of contrast, angle of the dorsal fin to the camera, proportion of the dorsal fin visible, and the proportion of the frame filled by the fin (Figure 3). The underlying assumption was that the least distinctive individual should be readily identifiable from the lowest quality image used in the analyses; images not meeting this criterion were excluded from the analyses.

Figure 3. Plate 1 (left): examples of distinctive individuals (1-A, 1-B) compared to indistinctive individuals (1- C, 1-D). Plate 2 (right): examples of acceptable quality images (2-A, 2-C) and unacceptable images (2-B, 2-D) of two individuals. Image 2-B is unacceptable due to the angle of the dorsal fin relative to the camera; image 2-D is unacceptable as part of the dorsal fin is obscured.

Proportion of distinctly marked individuals in the population

To account for the proportion of indistinctive (D3) dolphins in abundance estimation, group surveys were selected in which all individuals present were photographed to the quality standard described above. From these, the number of distinctive (D1 and D2) individuals encountered was divided by the total number of individuals (D1, D2 and D3) encountered during the whole study period (Nicholson et al., 2012).

Identification and resight rates

Following image grading, capture histories were compiled for all individuals as a record of whether or not an individual was captured within each group sighting. These were then summarized at two levels of sampling event: (1) per day of effort, and (2) per completed transect. The cumulative number of individuals identified was calculated per day of effort and plotted as a discovery curve. We also calculated the number of times each distinctive individual was encountered throughout the study period, with each individual restricted to one encounter per day.

Abundance estimates

The capture histories of distinctive individuals were used in program MARK (White and Burnham, 1999) to run capture-recapture models estimating abundance. In accordance with our sampling design and procedures at other study sites, we initially fitted a simple closed model. Due to the heterogeneity in sea conditions between different sampling occasions (and, therefore, the probability of detecting dolphins), the model allowed capture probabilities to vary with time for each sampling occasion. This was compared to a model which specified a constant capture probability. Recapture probability ( c) was set equal to first capture probability (p), as capture should not affect recapture (i.e. no ‘trap response’) when using photo- identification methods. Closed models provided an estimated abundance of distinctive animals ( Nd ) and the capture probability ( p) of an individual available for capture during the sampling period.

The assumptions of our closed model (Pollock, 1982, Pollock et al., 1990, Williams et al., 2002) were that (1) all individuals have equal probability of being captured within a sampling occasion (single transect), (2) capture and recapture probabilities are equal (no ‘trap response’), (3) marks are unique, permanent and identified correctly, (4) the sampling occasion (single transect) is instantaneous, (5) the population is closed to immigration and emigration during the sampling period, (6) each individual’s probability of capture is independent of all others, and (7) all individuals have equal probability of survival between sampling occasions.

There is a high likelihood that assumption (5) (the population is closed to immigration and emigration during the sampling period) was violated, for reasons discussed below. To account for this, we also fitted POPAN open models to the data, which account for the movement of individual animals in/out of the area during the sampling period. Open models are subject to the same assumptions as those listed above for closed models, with the exception of (5). Open models provided an estimated abundance of distinctive animals ( Nd ) and the parameters: capture probability ( p), apparent survival probability ( phi ) from one sampling occasion to the next, and the probability of entry ( pent ) of an individual into the population from one sampling occasion to the next. The apparent survival probability is the product of true survival times the probability that the animal does not emigrate. Different combinations of constant or time-varying parameters were tested in the models.

The Akaike’s Information Criterion (AICc) was used as a measure of relative goodness of fit of each closed model. The model with the lowest AICc was selected as the best fitting, with consideration also given to models within two AICc units where applicable (Burnham and Anderson, 2002). For POPAN open models, the

program RELEASE was used in MARK to determine goodness-of-fit (Lebreton et al., 1992). Over-dispersion in the models was accounted for by estimating the over-dispersion measure ĉ using the chi-square statistic divided by its degrees of freedom. QAIC values were used for model selection, with the lowest QAIC value an indication of the most parsimonious model (Anderson et al., 1994).

The total population size was calculated by dividing the size of the distinctive population by the proportion of distinctive animals (as described above). Standard errors and confidence intervals were corrected as per Williams et al. (2002) and Burnham et al. (1987), respectively.

Heterogeneity of capture probabilities between individuals has been widely acknowledged in capture- recapture studies, leading to a violation of assumption (1) and potential downward-bias of abundance estimates (Pollock et al. 1990; Williams et al. 2002). To investigate this potential bias, we ran several alternative simple closed models which allow for heterogeneity of capture probabilities among individuals.

Potential movements of animals between study sites

The catalogue of identification images for individuals encountered within Roebuck Bay was methodically cross-referenced with those available from research over the period 2012-2013 at other study sites on the Dampier Peninsula (Beagle Bay and Cygnet Bay). This was conducted for all three dolphin species.

Results

Effort Over a total period of 32 days 2, seven transect repeats were completed. Each transect took two to three days (or part thereof) of effort to complete, totaling 19 days on which transect effort occurred. The majority was completed in two or three consecutive days. A total of 418.5 km of transect was surveyed. Individual transects varied in length from 50 km to 65 km according to the state of the tide, with a mean length of 60 km.

Extrapolating from the 500 m survey strip (see Methods), each transect surveyed approximately 30% of the total study area. When transferred to the 1 × 1 km grid, survey effort took place in 133 grid cells, with the effort in each ranging from < 0.01 km 2 to 3.8 km 2 (Figure 4). Almost complete coverage of the study area was achieved, with only a few small near-shore grid cells not falling within the survey strip on any transects. Effort was relatively even across the study area, with some expected peaks at transect turns and intersections.

2 An additional six days (or part thereof) of survey took place in which conditions were unsuitable for transect effort to occur. Owing to the non-systematic nature of this effort, these data were excluded from the analyses.

Figure 4. Effort map showing transects and total survey effort during the study period.

Distribution of dolphin sightings and group sizes

A total of 79 dolphin group sightings were recorded across the seven transects. With a total of 74 group sightings, snubfin dolphins were by far the most frequently encountered species. Four groups of bottlenose dolphins and one of humpback dolphins constituted the remainder of sightings. Two of the snubfin groups also included a single bottlenose dolphin. No other mixed-species groups were observed.

Snubfin dolphins were frequently encountered in the Inner Anchorage area - a distinct channel of deeper water (typically 10-20 m water depth) extending ca. 10 km east from the port (Figure 5). Snubfin dolphins were encountered less frequently in the shallow waters over the intertidal foreshore flats to the north of the Inner Anchorage, and very rarely to the south of Middle Ground. Two off-transect forays up Dampier Creek at high tide and one up Crab Creek did not yield any dolphin sightings, although snubfins were observed close to the mouths of these tidal creeks. Snubfin dolphins were frequently encountered throughout the study area to the east and southeast of the Inner Anchorage, where intertidal and shallow subtidal flats extend several kilometers offshore of the mangrove-fringed west-facing shore (Figure 5). The majority of groups encountered in this area were in < 5 m water depth, with many as shallow as < 2 m. The majority of bottlenose dolphin sightings occurred within the Inner Anchorage. The single sighting of humpback dolphins was in the southeast of the study area, at a water depth of 8 m.

Figure 5. Dolphin sightings and transect lines throughout the entire study period, illustrating group sizes for snubfin (yellow circles), bottlenose (blue circles) and humpback (red circles) dolphins. Depth contours are Lowest Astronomical Tide.

Group sizes of snubfin dolphins ranged from one to 16, with a mean of 4.4 (+/- SE 0.44). Group sizes of one to three were the most frequently observed; when combined, they accounted for approximately half of all observations (Figure 6). Larger groups, in excess of five, were less common, although several groups of 12 or more animals were observed. Dependent calves were recorded in 20 (27%) of the total 74 sightings of snubfin dolphin groups; all but three of these included a single calf. Due to the difficulty in distinguishing between age classes of independent individuals (i.e. fully-grown adults vs sub-adults/juveniles) in the field, no attempts are made to estimate the proportion of sub-adults/juveniles here.

Bottlenose dolphin group size ranged from one to 8, with a mean of 3.3 (+/- SE 1.1). The majority of bottlenose groups were of females with dependent calves. The single humpback dolphin sighting was a group of 18, including at least three dependent calves.

18 16 14 12 10 8

Frequency 6 4 2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Group size Figure 6. Frequency distribution of snubfin dolphin group sizes.

Encounter rates

Encounter rates varied considerably between transects for all three species (Table 1). Snubfin dolphins were by far the most frequently encountered species, with encounter rates typically ranging between ca. 1.4 and 2.0 dolphins per km 2 of survey effort. Transect number four had an exceptionally low encounter rate, corresponding to just two sightings of small groups of snubfin dolphins. Transect number seven had an exceptionally high encounter rate, including several larger groups of snubfin dolphins.

When mapped, encounter rates of snubfin dolphins (Figure 7) illustrate a similar picture to those of sightings alone (Figure 5).

Encounter rate Transect length Survey area 2 Transect Route (number of dolphins per km survey effort) (km) (km 2) Snubfin Bottlenose Humpback 1 A 67.5 32.6 1.96 0.25 0.55 2 B 50.7 25.3 1.62 0.24 0.00 3 A 59.1 28.9 1.73 0.00 0.00 4 B 63.6 31.4 0.19 0.03 0.00 5 A 59.8 29.6 1.39 0.14 0.00 6 B 53.3 26.8 1.72 0.00 0.00 7 A 64.5 32.0 2.69 0.03 0.00 Total 418.5 206.5 1.62 0.10 0.09 (mean) (59.8) (29.5) (1.61) (0.10) (0.08) Table 1. Total and per transect encounter rate for snubfin, bottlenose and humpback dolphins.

Figure 7. Encounter rates of snubfin dolphins per 1 km × 1 km grid cell across the entire study period. Depth contours are Lowest Astronomical Tide.

Identification and resight rates

Following photo-grading, a total of 100 distinctive (D1 and D2) snubfin individuals (excluding calves) were observed across the study period. The distinctive proportion of the population was calculated as 0.905. When plotted as the cumulative number of individuals identified vs days of transect effort (Figure 8), there was no evidence of a plateau in the rate of discovery of new individuals over time. This suggests that only a subset of the total number of animals which may use the study area were observed during the study period. Nine of the distinctive snubfin individuals were identified as females with dependent calves.

A total of six bottlenose individuals (excluding calves) were identified over the study period. These were all assessed as distinctive and all six individuals were identified by the fifth day of effort. Four of these individuals were females with dependent calves.

The single group of humpback dolphins encountered yielded 15 individuals (excluding calves), all of which were distinctive and three of which had dependent calves. This sighting of humpback dolphins was on the second day of effort; no further sightings of this species occurred during the study period.

The majority of distinctive snubfin individuals were only encountered on one or two of the total seven transects (Figure 9). The number of ‘per transect resights’ then dropped sharply to just two individuals encountered on five transects. No individuals were encountered on all transects.

110 100 90 80 70 60 50 40 30

Cumulative individuals identified individuals Cumulative 20 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Days of effort Figure 8. Cumulative number of distinctive snubfin individuals (excluding calves) identified for each day of effort during the study period.

40 35 30 25 20 15 Number of individuals of Number 10 5 0 1 2 3 4 5 6 7 Number of transects on which each individual encountered

Figure 9. The total number of transects on which each snubfin dolphin individual was encountered.

Abundance estimates

Data for bottlenose and humpback dolphins were too few to derive abundance estimates. Both closed and open (POPAN) models were successfully fitted to data for snubfin dolphins (Table 2). Data from all seven transects repeats were used. Tests of the open model indicated a small degree of over-dispersion, which was corrected for specifying a ĉ value of 1.36. This caused a small increase in the standard error (SE) and widening of the 95% confidence interval (CI), but did not alter the estimate of N. Abundance estimates from both closed and open models were similar, with largely over-lapping confidence intervals.

For the best-fitting open model, apparent survival and probability of entry parameters were constant across sampling occasions, while capture probability varied with time. Apparent survival was 0.999 (± 0.003 SE) and probability of entry was 0.086 (± 0.024 SE) (see Appendix 2). Capture probabilities typically varied from 0.27 to 0.60, with a notably lower value of 0.02 for transect 4 (upon which very few animals were observed). Mean capture probability was 0.32.

Distinctive population Total population Model n Nd SE 95% CI N SE 95% CI Closed p(t)c(t)p=c 100 113 4.8 106-126 125 6.7 112-138 Open (POPAN) phi(.)p(t)pent(.) 100 124 9.7 105-144 137 11.6 117-162 Table 2. Abundance estimates of snubfin dolphins, showing results for the distinctive population, and those extrapolated to the total population (proportion distinctive = 0.905). n = total number of individuals captured; Nd = estimated size of distinctive population; N = estimated size of total population. Within models, p = probability of capture; c = probability of recapture; phi = survival rate; pent = probability of entry; (t) = time-varying; (.) = constant with time.

A closed model allowing for heterogeneity in capture probabilities of individuals (Chao model) produced a very similar abundance estimate (< 5% difference) to that produced by the closed model which did not account for this heterogeneity.

Potential movements of animals between study sites

Detailed examination of photographically identified individuals did not reveal any matches of individuals between Roebuck Bay and either Beagle Bay or Cygnet Bay for any species.

Local and indigenous engagement and data dissemination

The Yawuru Traditional Owners of the area, represented by Nyamba Buru Yawuru Pty Ltd (NBY), were consulted by WWF-Australia at an early stage of the proposed research activities. A research proposal was circulated and informal approval was granted, conditional upon active participation in the project and appropriate dissemination of the research outcomes.

Prior to commencing data collection, a meeting was held between MUCRU fieldwork leader, Alex Brown, and representatives of WWF-Australia, NBY, the WA Department of Parks and Wildlife (DPaW) and the DPaW Yawuru Rangers. An overview of the project background, relevance, outputs and proposed activities were provided by MUCRU and WWF-Australia. Feedback was received on the proposed study area and transect lines were modified accordingly. A schedule for NBY and DPaW Yawuru Ranger participation in data collection was agreed.

NBY representative Phillip Tamwoy participated in data collection on a total of 12 days over the study period. Phillip quickly became a capable and valued member of the team, taking an even share in all duties, including observation, boat driving, camera operation and data recording. Unfortunately, a mismatch between appropriate sea conditions and ranger availability prevented DPaW Yawuru Ranger participation in the data collection.

Discussion

Abundance of dolphins in Roebuck Bay

We estimated an abundance of 137 (SE 10.2, 95% CI 119-159) snubfin dolphins (excluding calves) using an area of approximately 100 km 2 within Roebuck Bay during the month of October 2013. The identification and resight rates of individual animals suggest that this estimate represents a subset of the animals which use the study area at temporal scales > one month.

Our abundance estimate for snubfin dolphins is significant at an Australia-wide scale, as it is larger than any of the published abundance estimates of snubfin dolphins off the east coast of Queensland and the Northern Territory. Over six years of data collection, Cagnazzi et al. (2013) revealed a small, geographically isolated population in the Fitzroy River region of central Queensland, with around 70-80 snubfin dolphins using the area on a yearly basis. While the total study area was large, the representative range of the population was ca. 350 km 2. Further north, off Townsville, Parra et al. (2006) collected data from 1999 to 2002 and estimated the abundance of snubfin dolphins at ca. 70 in a study area of ca. 310 km 2 within Cleveland Bay. Surveys of a large area of approximately 1,000 km 2 in the Darwin region (incorporating Darwin and Bynoe Harbours, and Shoal Bay), Northern Territory, from 2012-2013 yielded an abundance estimate of 17-29 snubfin dolphins using the area during three different three-week sampling periods (Brooks and Pollock, 2013). It was suggested that the surveyed area represents only a proportion of the range of a much larger population of 70 or more.

In Western Australian waters, recent research by MUCRU at Cygnet Bay over the period 2012-2013 has revealed a small, resident population of ca. 50 snubfin dolphins within an area of approximately 130 km 2 (Brown et al., 2013). Occurring roughly 250 km to the north on the eastern tip of the Dampier Peninsula, this is the geographically closest documented population of snubfin dolphins to Roebuck Bay. Similar research in the Beagle Bay area (ca. 130 km north of Roebuck Bay) recorded just two encounters of two snubfin individuals from a total of two months of survey effort, also within an area of approximately 130 km 2.

Our data showed no plateau in the number of snubfin dolphin individuals identified over time (Figure 8), a high proportion of animals observed on just one or two transects (Figure 9), high variability in encounter rates per transect (Table 1), and no reduction in sightings towards the boundary of the study area. All of these characteristics suggest the movement of individuals in and out of the study area over the study period. This was supported by the probability of entry > 0. While the apparent survival rate was close to 1, suggesting no mortality or permanent emigration during the study period, this is very common in studies of marine mammals and an open model may still be the most appropriate (e.g. Tyne et al., 2014). Of the two abundance estimates provided, we therefore consider the estimate derived from an open model to be the most biologically representative and informative to management agencies.

An assumption of the models used in this study is that movement of animals in/out of the study area (temporary emigration) is random i.e. equal in both directions. Abundance estimates may be biased if non- random (‘Markovian’) temporary emigration is occurring, where a net movement of animals in/out of the study area occurs over the course of the sampling period. An example of this may be a migration or local shift in distribution associated with seasonal behaviour (e.g. Smith et al., 2013). While little is known of seasonality in the behaviour or distribution of snubfin dolphins, we have no reason to suspect the presence of non-random temporary emigration within our data and, therefore, consider our abundance estimates to be unbiased in this respect. Our analyses also suggested that any downward bias caused by heterogeneity of capture probabilities among individuals is small; our strict image quality and distinctiveness criteria will have gone some way to minimizing this potential bias (Nicholson et al., 2012).

The distribution of snubfin sightings suggests that, for many animals, the study area represents only a subset of their range; many individuals identified within the study area may be encountered outside of the study area, particularly over the extensive shallow area to the southeast. This is supported by sightings of snubfin dolphins to the south of the study area towards Thangoo Station (Thiele, 2010; DPaW Yawuru Rangers, pers. comm. October 2013). Within our survey period, the Inner Anchorage and shallow area to the east and southeast of the Inner Anchorage supported higher densities of animals than some other areas. However, the relative importance of these areas should be interpreted with caution, given the single month of survey effort. Greater spatial and temporal coverage would be required to examine the distribution of animals and reliably identify areas of greater or lesser importance. Our results suggest that snubfin dolphins could be encountered anywhere within the study area, and the density of animals in the area as a whole is among the highest recorded in Australian waters to date.

It is important to note the limited temporal coverage of these results and the potential for seasonality in the abundance of dolphins within Roebuck Bay. While studies off the east coast of Queensland have not recorded any seasonality in abundance of snubfin or humpback dolphins (Parra, 2005, Cagnazzi, 2011), seasonal and inter-annual variation in local abundance has been observed in inshore populations of bottlenose dolphins (Balmer et al., 2008, Smith et al., 2013). Repeating the survey effort presented here across different seasons and years is required to investigate any temporal variation in abundance.

No individuals identified at Roebuck Bay of any species had been previously observed during surveys at Beagle Bay or Cygnet Bay. The maximum reported movements of individual snubfin and humpback dolphins off the east coast of Queensland are 70 km and 130 km, respectively (Cagnazzi, 2011). It is therefore unsurprising that our relatively limited survey effort did not reveal movements of animals over the 130 km and 250 km distances to Beagle and Cygnet Bays, respectively. Additionally, patterns of site fidelity and population genetic structure suggest that movements of individuals over these distances are uncommon (Parra et al., 2006, Cagnazzi et al., 2011 & 2013, Brown et al., in prep.).

The low number of bottlenose dolphins encountered suggests that very few bottlenose dolphins use the study area, at least at the time of year at which this study took place. Limited inferences can be made from the single sighting of humpback dolphins, but these data suggest that humpback dolphins do not frequently occur within the study area, at least at the time of year at which the study took place.

Conservation and management implications

While based on a single month of survey effort, our data suggest that Roebuck Bay supports the highest density and largest population of snubfin dolphins recorded in the published literature to date. Despite this, our estimated abundance of ca. 130 individuals is small and warrants conservation concern. Under the IUCN Red List Criteria (IUCN, 2012b), populations of fewer than 250 mature individuals are classified as ‘endangered’. While the criteria are typically applied to the global population size (i.e. throughout the species’ range), these criteria may be applied to regional populations where they meet the definition of a subpopulation (IUCN, 2012a). This regional classification was recently applied to the geographically and genetically isolated population of < 100 individual snubfin dolphins in the Fitzroy River region, Queensland, by Cagnazzi et al. (2013), who concluded that the subpopulation could be classified as ‘endangered’ (Cagnazzi et al., 2013).

The information on abundance presented here is not sufficient alone to define snubfin dolphins in Roebuck Bay as a subpopulation and assess them under regional IUCN Red List Criteria. However, preliminary results of genetic analyses suggest that they are differentiated from the geographically closest documented population of snubfin dolphins at Cygnet Bay, and should be managed as independent units (Brown et al., in prep.). Given the abundance estimate presented here (of which only a subset could be considered reproductively mature), preliminary genetic results and our current understanding of snubfin dolphin

distribution in the region (Parra et al., 2002, Allen et al., 2012, Brown et al., unpublished data), decision makers and resource management agencies should be prioritising measures to minimise anthropogenic threats to this population in the current planning of a marine protected area.

Inshore dolphins are vulnerable to a variety of anthropogenic pressures, including habitat degradation and loss through coastal zone development and increasing boat traffic, as well as injury and mortality through interactions with fisheries (e.g. Read, 2008, Jefferson et al., 2009, Thiele, 2010, Parra et al., 2012). It is beyond the scope of the current study to assess the range and significance of potential threats to inshore dolphins in Roebuck Bay. However, we recommend that decision-makers consider the likely importance of Roebuck Bay to snubfin dolphins when developing management plans to address the various ecological values and anthropogenic activities taking place in the area. This has previously been recognised within Interim Management Guidelines prepared by the Roebuck Bay Working Group (2009).

Our results provide limited, but critical baseline data on the community of inshore dolphins within Roebuck Bay. This represents an important step towards determining the importance of this area to inshore dolphins and will contribute towards our limited understanding of these species throughout their range.

We have presented an example of structured, scientifically rigorous baseline data collection. This level of data collection, reproduced across months and years, should be considered an essential pre-requisite to assessing the potential impacts of coastal zone development on inshore dolphins, along with other potentially threatening activities (Allen et al., 2012, Bejder et al., 2012).

Recommendations for future research

Our results present a ‘snapshot’ estimate of the abundance of snubfin and other inshore dolphins within a subsection of Roebuck Bay over a five-week period in 2013. Our primary recommendation for future research is to repeat this survey effort at different times of the year to investigate temporal variability in the abundance, along with demographic parameters associated with residency of individuals. Plans are already underway to repeat this survey effort in April 2014; this will go some way to providing greater temporal coverage and some limited information on residency. However, consideration should be given to the development of an ongoing, temporally structured survey effort, which may enable detection of longer-term trends in abundance.

A program of regular monitoring at a lower-intensity survey effort, using local resources and personnel, could also be of value. This could provide information on encounter rates and group composition at regular intervals on an annual scale, and may reveal information on the degree of residency of individuals within the area.

Consideration should also be given to applying a structured survey design across a broader area, which encompasses the entire embayment of Roebuck Bay and some adjacent areas. While this spatial scale is unlikely to be logistically feasible for capture-recapture estimates of abundance, it may delineate the geographic range of the population and provide information on the relative importance of areas within this range.

Acknowledgements

This research was jointly funded by WWF-Australia, the Australian Marine Mammal Centre (Project 11/23) and Murdoch University. Valuable input to the study design and logistical advice was provided by representatives of Nyamba Buru Yawuru Pty Ltd. and the DPaW Yawuru Rangers. The data collection would not have been possible without research assistants Marine Quintin, Felix Smith, Christy Harrington and

Tomás Kavanagh, who volunteered many weeks of hard work. The authors are grateful to Tanya Vernes of WWF-Australia for her efforts towards facilitating this research, in addition to the efficiency of the Murdoch University grants team. We are grateful to Deb Thiele for comments on an earlier draft. Thanks also go to Arrow Pearls Pty Ltd for providing the research team with subsidised accommodation within Broome.

Literature cited

ALLEN, S. J., CAGNAZZI, D. D., HODGSON, A. J., LONERAGAN, N. R. & BEJDER, L. 2012. Tropical inshore dolphins of north-western Australia: Unknown populations in a rapidly changing region. Pacific Conservation Biology, 18 , 56-63. ANDERSON, D. R., BURNHAM, K. P. & WHITE, G. C. 1994. AIC model selection in overdispersed capture- recapture data. Ecology, 75 , 1780-1793. BALMER, B. C., WELLS, R. S., NOWACEK, S. M., NOWACEK, D. P., SCHWACKE, L. H., MCLELLAN, W. A., SCHARF, F. S., ROWLES, T. K., HANSEN, L. J., SPRADLIN, T. R. & PABST, D. A. 2008. Seasonal abundance and distribution patterns of common bottlenose dolphins (Tursiops truncatus) near St. Joseph Bay, Florida, USA. Journal of Cetacean Research and Management, 10 , 157-167. BEJDER, L., HODGSON, A., LONERAGAN, N. & ALLEN, S. 2012. Coastal dolphins in north-western Australia: The need for re-evaluation of species listings and short-comings in the Environmental Impact Assessment process. Pacific Conservation Biology, 18 , 22-25. BROOKS, L. & POLLOCK, K. 2013. Abundance, movements and habitat use of coastal dolphins in the Darwin Region: Analysis of the first four primary samples (October 2011 to April 2013). Draft report for the Nothern Territory Government Department of Land Resource Management. BROWN, A., KOPPS, A. M., ALLEN, S. J., BEJDER, L., LITTLEFORD-COLQUHOUN, B., PARRA, G. J., CAGNAZZI, D., THIELE, D., PALMER, C. & FRÈRE, C. in prep. Population differentiation and hybridisation of Australian snubfin and Indo-Pacific humpback dolphins in north-western Australia. BROWN, A., POLLOCK, K. H., BEJDER, L. & ALLEN, S. J. 2013. Distribution and abundance of tropical inshore dolphins in Cygnet Bay, Western Australia. Oral presentation. 20th Biennial Conference on the Biology of Marine Mammals. University of Otago, Dunedin, New Zealand. BURNHAM, K. P. & ANDERSON, D. R. 2002. Model selection and multi-model inference: a practical information-theoretic approach, Second edition., New York, Springer-Verlag. BURNHAM, K. P., ANDERSON, D. R., WHITE, G. C., BROWNIE, C. & POLLOCK, K. H. 1987. Design and analysis methods for fish survival experiments based on release-recapture, Bethesda, MD. CAGNAZZI, D. 2011. Conservation Status of Australian snubfin dolphin, Orcaella heinsohni, and Indo-Pacific humpback dolphin, Sousa chinensis, in the Capricorn Coast, Central Queensland, Australia. PhD PhD, Southern Cross University. CAGNAZZI, D., PARRA, G. J., WESTLEY, S. & HARRISON, P. L. 2013. At the Heart of the Industrial Boom: Australian Snubfin Dolphins in the Capricorn Coast, Queensland, Need Urgent Conservation Action. PLoS ONE, 8. CAGNAZZI, D. D. B., HARRISON, P. L., ROSS, G. J. B. & LYNCH, P. 2011. Abundance and site fidelity of Indo- Pacific Humpback dolphins in the Great Sandy Strait, Queensland, Australia. Marine Mammal Science, 27 , 255-281. FRIDAY, N., SMITH, T. D., STEVICK, P. T. & ALLEN, J. 2000. Measurement of photographic quality and individual distinctiveness for the photographic identification of humpback whales, Megaptera novaeangliae. Marine Mammal Science, 16 , 355-374. GOWANS, S. & WHITEHEAD, H. 2001. Photographic identification of northern bottlenose whales (Hyperoodon ampullatus): Sources of heterogeneity from natural marks. Marine Mammal Science, 17 , 76-93. GROUP, R. B. W. 2009. Roebuck Bay Interim Management Guidelines: A step towards a community based management plan.

IUCN 2012a. Guidelines for Application of IUCN Red List Criteria at Regional and National Levels: Version 4.0. Gland, Switzerland and Cambridge, UK.: IUCN. IUCN 2012b. IUCN Red List Categories and Criteria: Version 3.1. Second edition. Gland, Switzerland and Cambridge, UK.: IUCN. JEFFERSON, T. A., HUNG, S. K. & WÜRSIG, B. 2009. Protecting small cetaceans from coastal development: Impact assessment and mitigation experience in Hong Kong. Marine Policy, 33 , 305-311. LEBRETON, J. D., BURNHAM, K. P., CLOBERT, J. & ANDERSON, D. R. 1992. Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecological Monographs, 62 , 67-118. NICHOLSON, K., BEJDER, L., ALLEN, S. J., KRÜTZEN, M. & POLLOCK, K. H. 2012. Abundance, survival and temporary emigration of bottlenose dolphins (Tursiops sp.) off Useless Loop in the western gulf of Shark Bay, Western Australia. Marine and Freshwater Research, 63 , 1059-1068. PARRA, G. J. 2005. Behavioural ecology of Irrawaddy, Orcaella brevirostris (Owen in Gray, 1866), and Indo- Pacific humpback dolphins, Sousa chinensis (Osbeck, 1765), in northeast Queensland, Australia: a comparative study. PhD PhD, James Cook University. PARRA, G. J. 2006. Resource partitioning in sympatric delphinids: Space use and habitat preferences of Australian snubfin and Indo-Pacific humpback dolphins. Journal of Animal Ecology, 75 , 862-874. PARRA, G. J., AZUMA, C., PREEN, A. R., CORKERON, P. J. & MARSH, H. 2002. Distribution of Irrawaddy dolphins, Orcaella brevirostris , in Australian waters. Raffles Bulletin of Zoology , 141-154. PARRA, G. J., BEASLEY, I., ALLEN, S., BROOKS, L. & POLLOCK, K. H. 2012. Draft coordinated research strategy to collect information required to assess the national conservation status of Australian tropical inshore dolphins. Final Report to the Department of Sustainability, Environment, Water, Population and Communities. PARRA, G. J., CORKERON, P. J. & MARSH, H. 2006. Population sizes, site fidelity and residence patterns of Australian snubfin and Indo-Pacific humpback dolphins: Implications for conservation. Biological Conservation, 129 , 167-180. POLLOCK, K. H. 1982. A capture-recapture design robust to unequal probability of capture. Journal of Wildlife Management, 46 , 752-757. POLLOCK, K. H., NICHOLS, J. D., BROWNIE, C. & HINES, J. E. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs, 107. READ, A. J. 2008. The looming crisis: Interactions between marine mammals and fisheries. Journal of Mammalogy, 89 , 541-548. REEVES, R. R., DALEBOUT, M. L., JEFFERSON, T. A., KARCZMARSKI, L., LAIDRE, K., O’CORRY-CROWE, G., ROJAS-BRACHO, L., SECCHI, E. R., SLOOTEN, E., SMITH, B. D., WANG, J. Y. & ZHOU, K. 2008a. Sousa chinensis . IUCN Red List of Threatened Species Version 2013-1. IUCN. REEVES, R. R., JEFFERSON, T. A., KARCZMARSKI, L., LAIDRE, K., O’CORRY-CROWE, G., ROJAS-BRACHO, L., SECCHI, E. R., SLOOTEN, E., SMITH, B. D., WANG, J. Y. & ZHOU, K. 2008b. Orcaella heinsohni . IUCN Red List of Threatened Species Version 2013-1. IUCN. ROSEL, P. E., MULLIN, K. D., GARRISON, L., SCHWACKE, L., ADAMS, J., BALMER, B., CONN, P., CONROY, M. J., EGUCHI, T., GORGONE, A., HOHN, A., MAZZOIL, M., SCHWARZ, C., SINCLAIR, C., SPEAKMAN, T., URIAN, K. W., VOLLMER, N., WADE, P., WELLS, R. & ZOLMAN, E. 2011. Photo-identification campture-mark-recapture techniques for estimating abundance of bay, sound and estuary populations of bottlenose dolphins along the U.S. east coast and Gulf of Mexico: a workshop report. NOAA Technical Memorandum. SARGEANT, B. L., WIRSING, A. J., HEITHAUS, M. R. & MANN, J. 2007. Can environmental heterogeneity explain individual foraging variation in wild bottlenose dolphins ( Tursiops sp.)? Behavioral Ecology and Sociobiology, 61 , 679-688. SMITH, H. C., POLLOCK, K., WAPLES, K., BRADLEY, S. & BEJDER, L. 2013. Use of the robust design to estimate seasonal abundance and demographic parameters of a coastal bottlenose dolphin (Tursiops aduncus) population. PLoS One, 8, e76574. THIELE, D. 2010. Collision course: snubfin dolphin injuries in Roebuck Bay. Report to WWF-Australia.

TYNE, J. A., POLLOCK, K. H., JOHNSTON, D. W. & BEJDER, L. 2014. Abundance and Survival Rates of the Hawai'i Island Associated Spinner Dolphin (Stenella longirostris) Stock. PLoS One, 9, e86132. URIAN, K. W., HOHN, A. A. & HANSEN, L. J. 1999. Status of the photo-identification catalog of coastal bottlenose dolphins of the western North Atlantic: report of a workshop of catalog contributors. NOAA Administrative Report. WHITE, G. C. & BURNHAM, K. P. 1999. Program MARK: Survival estimation from populations of marked animals. Bird Study, 46 , S120-S139. WILLIAMS, B. K., NICHOLS, J. D. & CONROY, M. J. 2002. Analysis and Management of Animal Populations, San Diego, CA, Academic Press.

Appendix 1 - Encounter rate maps of all species

Snubfin dolphins

Figure A1-1. Encounter rates of snubfin dolphins per 1 km × 1 km grid cell across the entire study period. Depth contours are Lowest Astronomical Tide.

Bottlenose dolphins

Figure A1-2. Encounter rates of bottlenose dolphins per 1 km × 1 km grid cell across the entire study period. Depth contours are Lowest Astronomical Tide.

Humpback dolphins

Figure A1-3. Encounter rates of humpback dolphins per 1 km × 1 km grid cell across the entire study period. Depth contours are Lowest Astronomical Tide.

Appendix 2 - Abundance estimate model outputs

POPAN open models

Model QAICc Delta QAICc AICc Weights Model Likelihood Num. Par QDeviance {p(t)phi(.)pent(.)} 328.1651 0 0.63289 1 9 0 {p(t)phi(.)pent(t)} 330.4055 2.2404 0.20646 0.3262 12 0 {p(t)phi(t)pent(t)} 330.9072 2.7421 0.16065 0.2538 10 0 {p(t)phi(.)pent(t)} 360.4447 32.2796 0 0 4 0 {p(.)phi(t)pent(t)} 361.5273 33.3622 0 0 7 0 {p(t)phi(t)pent(.)} 37596.19 37268.0298 0 0 8 37108.87 {p(t)phi(.)pent(t)} 37665.16 37336.9979 0 0 3 37188.47 {p(.)phi(.)pent(.)} 37797.77 37469.6031 0 0 3 37321.08 Table A2-1. Results of POPAN open models, each incorporating either constant (.) or time-varying (t) parameters of phi = apparent survival; p = capture probability; pent = probability of entry (into study area). Shaded model is the best fitting.

Parameter Estimate SE Lower 95% CI Upper 95% CI phi 0.999998 0.0032094 0.0008581 1 p - transect 1 0.600113 0.1633624 0.2832664 0.8507108 p - transect 2 0.381742 0.090036 0.2262046 0.5659999 p - transect 3 0.34106 0.0703203 0.2189396 0.4886789 p - transect 4 0.021326 0.0174698 0.0042066 0.1010432 p - transect 5 0.265699 0.0529443 0.1753128 0.3811482 p - transect 6 0.260281 0.0512023 0.1728239 0.3720882 p - transect 7 0.401847 0.0615521 0.2891148 0.5260099 pent 0.086314 0.0243916 0.0490001 0.1476326 Nd 124.4285 9.7328325 105.3521183 143.5048217 Table A2-2. Parameter estimates from the selected POPAN open model {p(t)phi(.)pent(.)}. phi = apparent survival; p = capture probability (per transect); pent = probability of entry (into study area during study period); Nd = estimated abundance of distinctive animals; SE = standard error.

Closed models

Model AICc Delta AICc AICc Weights Model Likelihood Num. Par Deviance {p(t)c(t)p=c} 37.1668 0 1 1 8 108.4615 {p(.)c(.)p=c} 96.7068 59.54 0 0 2 180.1927 Table A2-3. Results of closed models, each incorporating either constant (.) or time-varying (t) parameters of p = probability of initial capture; p = probability of recapture (p=c specified as no trap-response). Shaded model is the best fitting.

Parameter Estimate SE Lower 95% CI Upper 95% CI p - transect 1 0.319106 0.045956 0.236415 0.415001 p - transect 2 0.23933 0.041453 0.167612 0.329583 p - transect 3 0.248194 0.04203 0.175122 0.339217 p - transect 4 0.017728 0.012447 0.004427 0.068259 p - transect 5 0.248194 0.04203 0.175122 0.339217 p - transect 6 0.265922 0.043122 0.190251 0.35837 p - transect 7 0.443203 0.05046 0.347749 0.543044 Nd 112.8152 4.821317 106.2809 126.1475 Table A2-4. Parameter estimates from the selected closed model {p(t)c(t)p=c}. p = capture probability (per transect); Nd = estimated abundance of distinctive animals; SE = standard error.

Appendix 3 - Dugong sightings

Dugong were frequently observed throughout the majority of the study area (Figure A-4). Each time they were observed, the date, time, water depth, estimated group size and location were recorded. However, groups were not approached for detailed survey, so locations, group sizes and water depths are approximate only. The definition of a group was fairly loose i.e. individuals within 100-200 m of each other. A total of 44 dugong sightings were recorded over the study period, including those observed during survey effort and opportunistically when not on effort. Without the ability to identify individuals, some of these observations may represent resights.

Figure A3-1. Dugong sightings recorded throughout the study period. Transect lines are shown in grey. Depth contours are in Lowest Astronomical Tide.