Govinden Rodney
email: rgovinden@sfa.sc

Capello Manuela

Dagorn Laurent

Behavior of skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacares), and bigeye (T. obsesus) tunas associated with drifting fish aggregating devices (dFADs) in the Indian Ocean, assessed through acoustic telemetry

Keywords: acoustic telemetry, associative behavior, bigeye tuna, fish aggregating devices, Indian Ocean, skipjack tuna, yellowfin tuna

We investigated the associative behavior of skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacares), and bigeye (T. obsesus) tuna within multi-species aggregations associated with drifting fish aggregating devices (dFADs) in two different regions of the western Indian Ocean: the Mozambique Channel and the Seychelles, using acoustic telemetry. We documented the residence and absence times of tunas at two temporal scales (coarse and fine scale) and made comparisons between regions. A total of 56 tunas were tagged and released at 7 different dFADs (4 in the Mozambique Channel and 3 in the Seychelles) during four research cruises. We recorded the first observations of skipjack tuna making excursions of more than 24 hours away from dFADs before returning and confirmed findings of other studies showing that yellowfin tuna can make long excursions (4.07 days) before returning to their home dFADs. Combining both studied regions, average residence times were 7.59 days (min 0.03; max 16.49), 6.64 days (min 0.01; max 26.72), and 4.58 days (min 0.09; max 18.33) for bigeye, yellowfin, and skipjack tuna, respectively. Exponential models best fitted the residence times for all three tuna species, indicating time-independent probabilities of departure from dFADs. For yellowfin tuna, at a coarse temporal scale, no regional differences were observed in the residence times. However, at a fine temporal scale, regional differences were apparent in both residence and absence times. This study provides new information on the associative behavior of tunas at dFADs in the Indian Ocean which is key to improving the sciencebased management of dFADs.

Introduction

For centuries fishers have made use of floating objects to enhance the capture of fish [START_REF] Freon | Review of fish associative behavior: toward a generalization of the meeting point hypothesis[END_REF][START_REF] Dempster | Fish aggregation device (FAD) research: gaps in current knowledge and future directions for ecological studies[END_REF]. While floating objects have always been an important component of the strategy of purse seine fleets targeting tropical tunas (skipjack Katsuwonus pelamis, yellowfin Thunnus albacares and bigeye Thunnus obesus), fish aggregating devices (FADs) have become the main fishing mode for these fleets in the last three decades. Each year FAD fishing by purse seiners contributes nearly 2.5 million tons of the global tropical tuna catch [START_REF] Dagorn | Is it good or bad to fish with FADs? What are the real impacts of the use of drifting FADs on pelagic marine ecosystems[END_REF][START_REF] Fonteneau | Global spatio-temporal patterns in tropical tuna purse seine fisheries on drifting fish aggregating devices (DFADs): Taking a historical perspective to inform current challenges[END_REF]ISSF, 2018). The increase in the deployment of large numbers of drifting FADs (dFADs) in the ocean has impacts in terms of catchability, but also on the habitat [START_REF] Dagorn | Is it good or bad to fish with FADs? What are the real impacts of the use of drifting FADs on pelagic marine ecosystems[END_REF][START_REF] Maufroy | Large-Scale Examination of Spatio-Temporal Patterns of Drifting Fish Aggregating Devices (dFADs) from Tropical Tuna Fisheries of the Indian and Atlantic Oceans[END_REF] and potentially on the ecology of the species that associate with such objects, by possibly acting as ecological traps [START_REF] Marsac | Drifting FADs used in tuna fisheries: an ecological trap?[END_REF][START_REF] Hallier | Drifting fish aggregation devices could act as an ecological trap for tropical tuna species[END_REF][START_REF] Dagorn | Is it good or bad to fish with FADs? What are the real impacts of the use of drifting FADs on pelagic marine ecosystems[END_REF]. Although FADs have played a key role in the strategy of purse seiner fleets, monitoring and controlling their numbers has only recently occurred on the agenda of tuna Regional Fisheries Management Organizations (RFMO). FAD management plans are now a priority for all RFMO, but the lack of knowledge on the role of floating objects in the ecology of tunas complicates the work of policy makers. Knowing the amount of time tunas spend in association with dFADs and in unassociated free-swimming schools, and whether such variables change with local densities of dFADs, represents one of the key pieces of knowledge required to improve the science-based management of FADs.

The majority of studies investigating the behavior of tunas at FADs, primarily using acoustic telemetry, have been conducted on anchored FADs (e.g. [START_REF] Holland | Horizontal and vertical movements of yellowfin and bigeye tuna associated with fish aggregating devices[END_REF][START_REF] Cayré | Behaviour of yellowfin tuna (Thunnus albacares) and skipjack tuna (Katsuwonus pelamis) around fish aggregating devices (FADs) in the Comoros Islands as determined by ultrasonic tagging[END_REF][START_REF] Ohta | Periodic behavior and residence time of yellowfin and bigeye tuna associated with fish aggregating devices around Okinawa Islands, as identified with automated listening stations[END_REF][START_REF] Schaefer | Behavior of bigeye (Thunnus obesus) and skipjack (Katsuwonus pelamis) tunas within aggregations associated with floating objects in the equatorial eastern Pacific[END_REF]Dagorn et al., 2007a;[START_REF] Robert | Intraindividual behavioral variability displayed by tuna at fish aggregating devices (FADs)[END_REF][START_REF] Govinden | Movement behaviour of skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares) tuna at anchored fish aggregating devices (FADs) in the Maldives, investigated by acoustic telemetry[END_REF][START_REF] Rodriguez-Tress | Associative behavior of yellowfin Thunnus albacores, skipjack Katsuwonus pelamis, and bigeye tuna T. obesus at anchored fish aggregating devices (FADs) off the coast of Mauritius[END_REF]. Despite the rapid expansion in the use of dFADs across the world's oceans and the recognition that dFADs may impact the behavior of tunas, there have been very few studies examining the behavioral ecology of tuna species that aggregate around such drifting floating objects. The majority of these have been carried out in the Pacific Ocean [START_REF] Matsumoto | Behavioral study of small bigeye and yellowfin tunas aggregated with floating object using ultrasonic coded transmitter[END_REF][START_REF] Schaefer | Behavior of bigeye (Thunnus obesus) and skipjack (Katsuwonus pelamis) tunas within aggregations associated with floating objects in the equatorial eastern Pacific[END_REF][START_REF] Muir | Behavior of target and non-target species on drifting FADs and when encircled by purse seine gear[END_REF][START_REF] Schaefer | Simultaneous behavior of skipjack (Katsuwonus pelamis), bigeye (Thunnus obsesus), and yellowfin (T. albacares) tunas, within large multi-species aggregations associated with drifting fish aggregating devices (FADs) in the equatorial eastern Pacific Ocean[END_REF][START_REF] Matsumoto | Behavior of skipjack tuna (Katsuwonus pelamis) associated with a drifting FAD monitored with ultrasonic transmitters in the equatorial central Pacific Ocean[END_REF][START_REF] Matsumoto | Comparison of the behavior of skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacores) and bigeye (T. obesus) tuna associated with drifting FADs in the equatorial central Pacific Ocean[END_REF], while only two have been conducted in the Indian Ocean [START_REF] Dagorn | Satelite-linked acoustic receivers to observe behaviour of fish in remote areas[END_REF][START_REF] Forget | Behaviour and vulnerability of target and non-target species at drifting fish aggregating devices (FADs) in the tropical tuna purse seine fishery determined by acoustic telemetry[END_REF] and one in the Atlantic Ocean [START_REF] Tolotti | Association dynamics of tuna and purse seine bycatch species with drifting fish aggregating devices (FADs) in the tropical eastern Atlantic Ocean[END_REF].

Knowledge on the associative patterns of tunas at FADs are necessary to develop models and assess the potential effects of changing densities of FADs and other habitat variables on their behavior (primarily through comparisons of associative patterns in different oceanic regions).

Furthermore, such information is needed to improve our understanding of the catchability and the catch per unit effort (CPUE) of purse seiners fishing with dFADs [START_REF] Katara | Standardization of catch rates for the Eastern tropical Atlantic bigeye tuna caught by the French purse seine FAD fishery[END_REF][START_REF] Capello | Population assessment of tropical tuna based on their associative behavior around floating objects[END_REF][START_REF] Gaertner | Results achieved within the framework of the EU research project: Catch, Effort, and eCOsystem impacts of FAD-fishing (CECOFAD). Working paper presented at the Indian Ocean Tuna Commission working party on Tropical Tunas[END_REF]. In this study, we used acoustic telemetry to investigate the associative behavior of skipjack, yellowfin and bigeye tuna within multi-species aggregations associated with dFADs in two regions of the western Indian Ocean: the Mozambique Channel and the Seychelles. Specifically, we aimed to document the residence and absence times of three species of tunas at a coarse and fine temporal scale, and compare their associative patterns between species and regions.

Materials and methods

Acoustic telemetry experiment

Four research cruises were carried out between March 2010 and April 2012 in the Mozambique Channel and the Seychelles area (Fig. 1; Table 1). During the cruises, dFADs were located through collaboration with European purse seine vessels. Once a dFAD was located and if there were enough tunas aggregated under the FAD, fishing operations were carried out to catch and tag fish.

Tunas were caught using hand-line gear or rod and reel. Captured tunas were carefully brought onboard and placed in a V-shaped tagging cradle where a hose supplying sea water was inserted into the mouth to oxygenate the fish's gills. The fork length of the tunas was measured to the nearest centimeter using calipers.

Tunas were fitted with either a V13, V13P (pressure-sensitive) or V13TP (temperature and pressure-sensitive) (90s nominal delay, 69kHz, 1H) coded acoustic tag following standard internal tagging procedures as described in [START_REF] Dagorn | Satelite-linked acoustic receivers to observe behaviour of fish in remote areas[END_REF]. All tagged tunas were released within close proximity of the dFAD where captured. Tagging took place around seven dFAD and passive monitoring of fish was carried out using Vemco VR4-Global satellite-linked acoustic receivers (VEMCO, a division of Innovasea, Canada) attached to the dFAD (Table 1). These receivers remotely relay the acoustic detection logs on a daily basis using the Iridium satellite system. Due to the threat of piracy, range testing could not be carried out to determine the exact detection range of the receivers. We have therefore assumed a similar detection range of 460 -686 m as [START_REF] Schaefer | Simultaneous behavior of skipjack (Katsuwonus pelamis), bigeye (Thunnus obsesus), and yellowfin (T. albacares) tunas, within large multi-species aggregations associated with drifting fish aggregating devices (FADs) in the equatorial eastern Pacific Ocean[END_REF] who carried out range tests in the equatorial eastern Pacific Ocean using similar tags, in similar environmental conditions.

Data analysis

Residence and absence times

The amount of time tunas spent associated with a dFAD was investigated at two temporal scales. Firstly, the continuous residence time (CRT), defined by [START_REF] Ohta | Periodic behavior and residence time of yellowfin and bigeye tuna associated with fish aggregating devices around Okinawa Islands, as identified with automated listening stations[END_REF] as "the duration in which a tagged tuna was continuously monitored without day-scale (>24 h) absences" was calculated. The continuous absence time (CAT), which is the time between two consecutive CRT, also known as an excursion, was calculated [START_REF] Capello | A methodological framework to estimate the site fidelity of tagged animals using passive acoustic telemetry[END_REF]. Secondly, the fine-scale residence time (FCRT), defined by [START_REF] Govinden | Movement behaviour of skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares) tuna at anchored fish aggregating devices (FADs) in the Maldives, investigated by acoustic telemetry[END_REF] as "the duration over which a tagged tuna was monitored without a one-hour absence" was calculated. Using the FCRT, the fine-scale continuous absence time (FCAT) was calculated.

Similar to the study conducted by [START_REF] Robert | Intraindividual behavioral variability displayed by tuna at fish aggregating devices (FADs)[END_REF], survival curves of CRT data were fitted using three different models (single exponential, double exponential and power law). The single and double exponential models imply that the probability of a fish joining/leaving a dFAD is independent of the time spent away from or at the dFAD. In contrast, the power law model indicates a functional dependence between the probability of a fish joining/leaving a dFAD and the time the fish spends away from or at the dFAD. The best-fit model was identified using the Akaike Information Criterion (AIC) [START_REF] Akaike | Information theory and an extension of the maximum likelihood principle[END_REF] and by examining the quantile-quantile plots.

The models were fitted for each species by grouping the two regions to represent the Indian Ocean (IO) and by separate regions for species where there were enough data points in each region. Table 2 provides a summary of the models fitted in this study.

Survival curves of CRTs were compared using the logrank statistical test, using the 'survival' package in R [START_REF] Therneau | A Package for Survival Analysis in S. version 2.38[END_REF][START_REF] Core | R: A language and environment for statistical computing[END_REF] to examine whether differences exist between species in the IO and between the two regions. The significance threshold was set at p<0.05.

Comparisons were carried out for species where the sample size (number of data points) was larger than five. Consequently, comparisons between regions could only be carried out for yellowfin tuna. Similarly, the logrank statistical test was used to compare the different survival curves of FCRT and FCAT and regional comparisons were conducted for bigeye and yellowfin tuna. The average FCRT and FCAT were calculated for each species in each region.

Index of residence

The degree of association with dFAD displayed by each species was investigated by calculating an index of residence (IR). For each tagged individual j, the index of residence (IR) was defined as follows:

𝐼𝑅 𝑗 = ∑ 𝐹𝐶𝑅𝑇 𝑖𝑗 𝑁 𝑗 𝑖=1 𝑇𝑅𝑇 𝑗
where FCRTij is the i th fine-scale continuous residence time recorded for individual j,  denotes the sum running over all the Nj FCRT recorded, and TRTj is the total residence time calculated as the elapsed time between the first and last detection recorded for individual j. For each species, the above index was averaged for all individuals and the standard error was calculated.

Diel periodicity

To examine the diel periodicity in the presence of tunas in each region, the daily acoustic detection data was compiled in hourly bins and a fast fourier transformation (FFT) was carried out using the 'stats' package in R (R Core Team, 2016). Only tunas with TRTs of over five days were included in this analysis.

To elucidate any pattern in the arrival and departure time of tunas at dFAD between the two regions, we used the FCRT data to calculate the percentage number of arrival and departure events in each hour bin for all dFAD combined for each region. Rao's spacing tests were carried out to determine whether arrival and departure events were uniformly distributed throughout the day [START_REF] Batschelet | Circular statistics in biology[END_REF]. The analysis was carried out using the 'circular' package in R [START_REF] Agostinelli | R package 'circular[END_REF][START_REF] Core | R: A language and environment for statistical computing[END_REF]. The arrival and departure events were separated into daytime and nighttime. Nighttime was the period from 6 pm to 6 am. Day-night differences in the arrival and departure events were investigated for each species in the two different region using Kruskal-Wallis tests ('stats' R package; [START_REF] Core | R: A language and environment for statistical computing[END_REF]. All statistical analysis was carried out using software package R (R version 3.3.1) (R Core Team, 2016).

Results

The acoustic tagging experiment was performed at 7 different dFADs (4 in the Mozambique Channel and 3 in the Seychelles), see Table 2. A total of 56 tunas were tagged and released at the dFADs, of which 46 individuals were detected and monitored with the VR4-Global acoustic receivers. The numbers of tunas tagged and detected from each species at each dFAD is provided in Table 2. All fish were monitored until they left the dFAD except at dFAD MOZ31 where the experiment was interrupted after 12 days due to a fishing event. The sizes of bigeye tuna tagged in the Mozambique Channel and Seychelles ranged from 54 to 56 cm FL (mean ± SD: 55 ± 1, n=4)

and 43 to 59 cm FL (mean ± SD: 52 ± 8, n=4) respectively. Tagged skipjack tuna ranged in size from 47 to 57 cm FL (mean ± SD: 50 ± 3, n=13) and 42 to 56 cm FL (mean ± SD: 48 ± 6, n=4) respectively, whilst yellowfin tuna ranged from 29 to 111 cm FL (mean ± SD: 65 ± 22, n=16) and 42 to 66 cm FL (mean ± SD: 59 ± 9, n=15) respectively.

Residence times

Continuous residence times (CRT) and continuous absence times (CAT)

Of the 46 tunas detected at the dFADs, a total of 8 yellowfin and 3 skipjack tunas made excursions away from the dFAD which lasted more than 24 hours (Fig. 2). However, the majority of the excursions occurred approximately 2 hours after the fish were released, which may reflect an effect of capture and tagging. Only two skipjack and one yellowfin tuna in the Mozambique Channel made excursions 3 to 18 days after being released. The average duration of these excursions was 1.56 days for skipjack tuna and ranged from 1.10 days to 2.27 days (n=3). In contrast, the duration of the only excursion observed for yellowfin tuna was 4.07 days.

In the Mozambique Channel, the average CRT of yellowfin tuna (7.56 days) was longer than the two other species, whereas in the Seychelles, bigeye tuna had a longer average CRT of 8.77 days.

However, a wide degree of inter-individual variability was observed in both areas (Table 3, Fig. 2). Moreover, only two skipjack and two bigeye tuna were detected in the Seychelles and in the Mozambique Channel, respectively, rendering any interspecific comparisons between regions of limited use. For both areas combined, the average CRT was 7.59 d for bigeye, 6.64 days for yellowfin and 4.58 d for skipjack (Table 3).

The survival curves of CRTs obtained for the three tuna species for the IO region are shown in Figure 3. The logrank statistical test showed that there were no significant differences among species (p=0.44). Based on the AIC values, the double exponential model provided the best fit for the survival curve of CRTs of yellowfin and skipjack tuna (Table 4). Using the optimized parameters from the model (a and b in Table 4), for yellowfin tuna, the short associations were characterized by mean stays (1/a) of 4.73 hours, whilst the mean duration of the long periods (1/b) of CRT was 16.67 days. For skipjack tuna, the mean duration of the short associations was 3.42 hours whilst the average duration of the long associations was 7.14 days. However, for both species, the p-value of the parameters associated to the shorter timescale was not significant. In contrast, for bigeye tuna the double exponential model did not converge and the single exponential model provided the best AIC, with a mean CRT duration of 11.11 days.

Yellowfin tuna was the only species for which a comparison between survival curves of CRTs recorded in the two regions could be conducted. The logrank test of comparison run between survival curves of CRTs recorded in the Mozambique Channel and in the Seychelles area showed no significant differences between the two regions (p=0.58), see Figure 1S in the Supplementary Material.

Fine scale continuous residence time (FCRT) and fine-scale continuous absence time (FCAT)

The survival curves of FCRTs and FCATs for the three tuna species in the Mozambique Channel and Seychelles area are shown in Figure 4. For yellowfin tuna, a significant difference was observed in the survival curves of FCRT between the two regions (logrank test, p<0.01). The average FCRT in the Mozambique Channel (16.6 hours) was nearly three times longer than in Seychelles (5.8 hours) (Table 5). In contrast, no difference was observed in the FCRT of bigeye tuna between the two regions (logrank test, p=0.15). The average FCRT was 10.1 hours and 17.6 hours in the Mozambique Channel and the Seychelles respectively (Table 5). For skipjack tuna, only the data recorded in the Mozambique Channel could be analyzed, since the two individuals tagged in the Seychelles area remained associated for a short period of time. The average duration FCRT for skipjack tuna in the Mozambique Channel was 6.5 hours.

Regional comparisons of survival curves of FCATs showed that there was a significant difference in the FCAT of yellowfin tuna between the Mozambique Channel and Seychelles (logrank test, p=0.01), whilst no significant difference was observed for bigeye tuna between the two areas (logrank test, p=0.97). The average FCAT showed little variability between species and regions and ranged between 3.1 and 4.1 hours (Table 5).

Index of Residence

The index of residence indicates that all tuna were strongly associated with the dFADs (Fig. 5).

All indices were comparable, indicating a certain homogeneity of associative behavior among species and regions. Yellowfin tuna in the Mozambique Channel exhibited stronger associations, spending in average 90% of their time within the reception range of the receiver, while the same species in the Seychelles area, as well as other species in the Mozambique Channel or the Seychelles area, showed average indices of residence between 69 and 76% (Fig. 5).

Diel patterns in detection

The FFT results showed clear 24-hour peaks in the detection for the majority of tunas (Fig. 2S in Supplement 1). However, the amplitude of the peaks varied between individuals of the same species and between regions with some fish showing a stronger diel pattern than others.

Arrival and departure events

The percentage number of arrival and departure events was not uniform over 24 hours (Rao's spacing test; p<0.05) for all three species in both regions (Fig. 6). In the Mozambique Channel, arrival events were significantly more common at night than during the day for all three species (Kruskal-Wallis test; p<0.05) with a percentage of nighttime arrivals of 77%, 83%, and 90% for skipjack, bigeye and yellowfin tuna respectively. Similarly, nighttime departure events were significantly higher for bigeye and yellowfin tuna (Kruskal-Wallis test; p<0.05) and corresponded to 100% and 81%, respectively, of all departures. In contrast, there was no significant difference between the nighttime and daytime departure events of skipjack tuna (Kruskal-Wallis test; p>0.05), where departures started at noon and only 63% of departures occurred at night (Fig. 6).

In Seychelles, the diel pattern of arrivals and departures was less clear. For bigeye tuna departures and arrivals were spread between noon and early night and there were no significant differences between the nighttime and daytime arrival and departure events (Kruskal-Wallis test; p>0.05).

Indeed, only 62% of arrivals and 41% of departures occurred at night (Fig. 6). In contrast, for yellowfin tuna, the frequency of nighttime arrival events was significantly higher than in the day (Kruskal-Wallis test; p<0.05). Sixty-nine percent of arrival events took place at night compared to 31% during daytime. However, departure events were distributed throughout the whole day and there was no significant daytime (47%) or nighttime (53%) difference (Kruskal-Wallis test; p>0.05) (Fig. 6).

Discussion

Following upon the first measures of residence times of tunas at dFAD in the Indian Ocean [START_REF] Dagorn | Satelite-linked acoustic receivers to observe behaviour of fish in remote areas[END_REF], this study provides a more comprehensive insight into the associative behavior of the three major tuna species at dFAD in this ocean.

Large-scale dynamics

The Mozambique Channel is a region rich in meso-scale features [START_REF] De Ruijter | Observations of the flow in the Mozambique Channel[END_REF] and an area where natural logs form a large proportion of the available floating object habitats (Dagorn et al., 2013). In contrast, the Seychelles area is considered to be oceanographically more uniform and the majority of floating objects are artificial dFADs. Remarkably, despite these potential differences in the environment, we found that yellowfin tuna (the only species where a comparison between areas was possible) manifested the same continuous residence times across both areas.

This result justifies the combined analysis of CRTs recorded in different areas for yellowfin tuna.

It is important to note that sample size could potentially affect the statistical power of the test, therefore a much larger sample size would be required to potentially detect any geographical differences. The smaller sample size available for bigeye and skipjack tuna constrained the comparative analysis of CRT for these species at the level of the Indian Ocean.

The fit of the survival curves of CRTs demonstrated that exponential models best fitted the residence times for the three tuna species, indicating time-independent probabilities of departure from dFADs [START_REF] Robert | Intraindividual behavioral variability displayed by tuna at fish aggregating devices (FADs)[END_REF]. The double exponential model was the best fit for yellowfin and skipjack tuna, revealing two behavioral modes characterized by either very short (of the order of a few hours) or long residence times (about two weeks). However, the p-value associated with the short timescales were not significant, indicating that the short residence times were not significantly different from zero. Similar short residence times for tunas at FADs were previously observed (e.g. [START_REF] Dagorn | Satelite-linked acoustic receivers to observe behaviour of fish in remote areas[END_REF]at drifting FADs, Robert et al., 2013[START_REF] Govinden | Movement behaviour of skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares) tuna at anchored fish aggregating devices (FADs) in the Maldives, investigated by acoustic telemetry[END_REF] at anchored FADs). The authors interpreted these short residence times as a result of local environmental conditions, which can still be valid in our study. However, as these very short residence times were mainly recorded immediately after tagging, occurring for nearly half of the tagged individuals, it could also be attributed to a tagging induced stress response [START_REF] Scutt Phillips | Revisiting the vulnerability of juvenile bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna caught by purse-seine fisheries while associating with surface waters and floating objects[END_REF]. In a similar experiment on silky sharks, [START_REF] Filmalter | Global comparison of post release survival of silky sharks caught by tropical purse seine vessels[END_REF] observed that 90% of tagged silky sharks (Carcharhinus falciformis) left the monitored dFAD after they were released.

The authors attributed this behavior to stress associated with capture, handling and tagging.

Without further information on the local conditions, it is not possible to explain whether these short residence times are natural or due to stress caused by the catching and tagging events. For bigeye tuna, the single exponential model provided the best fit indicating a single behavioral mode.

However, bigeye tuna was also the species with the smallest number of individuals tagged, therefore the absence of very short residence times may be an artefact of the small sample size.

In a similar study conducted on yellowfin tuna at anchored FADs in Hawaii, [START_REF] Robert | Intraindividual behavioral variability displayed by tuna at fish aggregating devices (FADs)[END_REF] found that only exponential models fitted the survival curves of CRTs. Similarly, in the Atlantic Ocean, single exponential models provided the best fit for skipjack tuna, whilst the double exponential model provided the best fit for bigeye and yellowfin tuna [START_REF] Tolotti | Association dynamics of tuna and purse seine bycatch species with drifting fish aggregating devices (FADs) in the tropical eastern Atlantic Ocean[END_REF].

Similarly, [START_REF] Rodriguez-Tress | Associative behavior of yellowfin Thunnus albacores, skipjack Katsuwonus pelamis, and bigeye tuna T. obesus at anchored fish aggregating devices (FADs) off the coast of Mauritius[END_REF] observed that the skipjack and bigeye tuna CRTs at anchored FADs were best fitted by single exponential model. In contrast, the CRTs for yellowfin tuna were best fitted by a power law model, however, they argued that the single exponential model provided a good alternative fit to the data based on the significance of the model parameter and the behavior of the quantile-quantile plot. Our observations therefore support the findings of the previous studies that the three tuna species exhibit similar mechanisms that describe their behavioral dynamics i.e, the behavioral processes are time independent.

For both regions combined we observed mean CRTs of 7.59 days for bigeye, 6.64 days for yellowfin and 4.58 days for skipjack. In comparison to other studies carried out in the Indian Ocean, [START_REF] Dagorn | Satelite-linked acoustic receivers to observe behaviour of fish in remote areas[END_REF] observed much shorter mean residence times of 1.43, 1.04 and 0.91 days for bigeye, yellowfin and skipjack tuna respectively. These data, however, were collected with classic acoustic receivers (which need to be recovered to download the data) or with new specified in that study. In the Atlantic Ocean, [START_REF] Tolotti | Association dynamics of tuna and purse seine bycatch species with drifting fish aggregating devices (FADs) in the tropical eastern Atlantic Ocean[END_REF] observed a single bigeye tuna that made an excursion lasting 1.01 days. Studies on anchored FADs did show long scale CATs.

Returns to the same FAD and visits to other FADs were both observed (Dagorn et al., 2007a[START_REF] Robert | Size-dependent behavior of tuna in an array of fish aggregating devices (FADs)[END_REF], 2013). The latter type of CATs was possible because several FADs in the same array were instrumented with acoustic receivers, a protocol that is quite difficult to replicate for dFAD as the array is constantly changing. Observing long-scale returns to the same dFAD, could in theory, depend on the local densities of floating objects, e.g. the distance between floating objects. Data reported in [START_REF] Fauvel | Comparative study of the distribution of natural versus artificial drifting Fish Aggreating Devices (FADs) in the Western Indian Ocean[END_REF] showed that FADs contributed to a greater increase in the number of floating objects in the Seychelles area compared to the Mozambique Channel and found that FADs contributes to decreasing the average distance between two floating objects. In areas where floating objects are close to each other, it is logic to consider that tunas could find another FAD during their excursions. In contrast, in areas where floating objects are further apart, encountering another floating object might take longer, and therefore the probability of returning to the same FAD could be higher. Of the 8 yellowfin tuna which were observed returning to the same FAD, 6 were tagged in the Seychelles and 2 in the Mozambique Channel, while the 3 skipjack exhibiting a return movement to the same FAD were all tagged in the Mozambique Channel. The behavior of these few tagged tunas can only be interpreted in regards to the actual local floating object environment where these fish were swimming, which is not known. Monitoring the local densities of floating objects during tagging experiments would considerably help interpreting the data. Our study provides the first observation of long scale excursions (> 24 h) for skipjack tuna and highlights the importance of long-term monitoring of tunas associated with dFADs in order to obtain a comprehensive understanding of their associative behavior.

Fine-scale dynamics

When inspecting the associative behavior of tuna at a fine scale, we showed that there were regional and species-specific differences. The analysis of FCRT revealed that the residence times of yellowfin tuna were about three times higher in the Mozambique Channel compared to the Seychelles region. The index of residence shows that all tuna are strongly associated with FADs, with fish spending in average between 69 and 90% of their time in the vicinity of FADs. It is noteworthy that the highest values were measured for yellowfin tuna in the Mozambique Channel.

This could be due to a particular behavior of this species under the specific oceanographic dynamics of the Mozambique Channel, where drifting objects could frequently encounter features such as eddies and fronts, which are known for their increased productivity. As a result, foraging excursions away from a floating object could be shorter, but understanding why skipjack tuna did not also show higher indices of residence in this region deserves more behavioral investigations, in particular better characterization of possible different foraging strategies of these species under these conditions.

For bigeye tuna, the comparison of FCRT between regions did not reveal significant differences, nor did the index of residence. However, the patterns of arrivals and departures were different between regions, with a higher activity at nighttime in the Mozambique Channel than in the Seychelles for both bigeye and yellowfin tuna. The small-scale behavior of skipjack tuna in the Mozambique showed an index of residence similar to that of bigeye tuna, but a less marked diel pattern in the activity.

In the equatorial central Pacific Ocean, [START_REF] Matsumoto | Comparison of the behavior of skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacores) and bigeye (T. obesus) tuna associated with drifting FADs in the equatorial central Pacific Ocean[END_REF] observed significantly higher detection rates during the daytime compared to nighttime. In contrast, in the eastern equatorial Pacific Ocean, [START_REF] Schaefer | Simultaneous behavior of skipjack (Katsuwonus pelamis), bigeye (Thunnus obsesus), and yellowfin (T. albacares) tunas, within large multi-species aggregations associated with drifting fish aggregating devices (FADs) in the equatorial eastern Pacific Ocean[END_REF] found that there were no significant differences between the day and night percentages of time that the three tuna species spent within the detection range of the receiver at the FAD. However, they observed that skipjack tuna spent more time during the day and less time at night in close proximity of FADs compared to bigeye and yellowfin tuna.

Around anchored FADs near Okinawa Islands, [START_REF] Ohta | Periodic behavior and residence time of yellowfin and bigeye tuna associated with fish aggregating devices around Okinawa Islands, as identified with automated listening stations[END_REF] found that 72 % of the CRT logs of yellowfin and 100 % of those of bigeye tuna showed a periodicity of approximately 24 h. Moreover, they classified the fluctuations in detection rates into five simple patterns. One of the patterns was characterized by a detection rate that was significantly higher in the nighttime than in the daytime. This was the most common pattern observed for yellowfin tuna. In addition, in Hawaii, [START_REF] Holland | Horizontal and vertical movements of yellowfin and bigeye tuna associated with fish aggregating devices[END_REF] observed yellowfin and bigeye tunas making diurnal movements on and off FADs. The tunas stayed close to the FADs during daytime and left between late afternoon and nighttime to make extensive nighttime excursions.

We observed some differences in the nighttime and daytime activity of tunas associated with dFADs in the two regions. In the Mozambique Channel, for all three species, the nighttime arrival events were significantly higher compared to the daytime. In addition, the nighttime departure events of yellowfin and bigeye tuna were significantly higher, whilst for skipjack there was no difference between daytime and nighttime. This suggests that all three species are more mobile and active during nighttime. This is coherent with the current knowledge which considers that nighttime excursions could correspond to foraging behavior [START_REF] Jaquemet | Do drifting and anchored Fish Aggregating Devices (FADs) similarly influence tuna feeding habits? A case study from the western Indian Ocean[END_REF][START_REF] Schaefer | Vertical movements, behavior, and habitat of bigeye tuna (Thunnus obesus) in the equatorial eastern Pacific Ocean, ascertained from archival tag data[END_REF] (see below). However, during the day, skipjack tuna is more active than yellowfin and bigeye tuna, which tends to show that this species also have considerable foraging activity during daylight hours. In Seychelles, the arrival events of yellowfin tuna were significantly higher during nighttime compared to during the day. However, there was no difference between the nighttime and daytime departure events. In contrast, for bigeye tuna there was no difference between the nighttime and daytime arrival and departure events. This indicates that both species were more active throughout the day and night in Seychelles compared to the Mozambique Channel. It could be hypothesized that these differences between regions correspond to different foraging strategy or different prey availability at night and day in these regions (see below). As a consequence, in Seychelles, the daily residence times for yellowfin tuna were much lower compared to the Mozambique Channel.

The exact causes for the differences in fine-scale association patterns are still poorly understood.

Movements away from FADs can possibly be associated with feeding habits. In the equatorial eastern Pacific Ocean, Alatorre-Ramirez et al. (2017) observed that although both yellowfin and skipjack tuna employed similar predation strategy, their diet composition was significantly different indicating that they occupy different trophic levels and that there is no competition for food between the two species. [START_REF] Jaquemet | Do drifting and anchored Fish Aggregating Devices (FADs) similarly influence tuna feeding habits? A case study from the western Indian Ocean[END_REF] deduced that patterns in the dietary habits of tunas around dFADs are complex and related to the prey availability in their vicinity and the productivity of the pelagic waters where the dFADs and tunas drift to. Moreover, [START_REF] Schaefer | Vertical movements, behavior, and habitat of bigeye tuna (Thunnus obesus) in the equatorial eastern Pacific Ocean, ascertained from archival tag data[END_REF] suggested that the nighttime occurrence or absence of deep scattering layer (DSL) prey organisms may influence the behavior of tunas, therefore influencing their associative patterns with dFADs. The presence of predators can potentially influence the associative patterns of tunas around FADs. [START_REF] Ohta | Periodic behavior and residence time of yellowfin and bigeye tuna associated with fish aggregating devices around Okinawa Islands, as identified with automated listening stations[END_REF] observed cases where the presence of predators coincided with the short-term absences of monitored tuna.

Comparison between regions at different temporal scales for yellowfin

Our results for yellowfin tuna showed that assessing the regional variability of the associative behavior of tuna at dFAD is a matter of timescales. While the large-scale residence times appeared to be zone-independent, the small-scale behavior appeared to vary between Seychelles and the Mozambique Channel. Even if the link between these short and long timescales remains unclear, we can advance some hypotheses on how this observation could be possible. One hypothesis may be that the two timescales are independent, i.e., the fine-scale behavior and the factors affecting it (e.g. local environment, prey availability, presence of predators and densities of floating objects)

are not influencing the long-term residence of yellowfin tuna at dFAD, which would depend on other factors operating over longer timescales.

Conclusion

This study contributes towards a better understanding of the associative behavior of tropical tunas with dFAD in the Indian Ocean through the characterization of residence and absence times at two different temporal scales. In general, we observed that the CRT of yellowfin and bigeye tuna were longer than those of skipjack tuna. We recorded the first observations of skipjack tuna making excursions of more than 24 hours away from dFAD before returning, and confirmed findings of other studies showing that yellowfin tuna can make long excursions and return to the same dFAD.

In addition, we show that, in the case of yellowfin tuna, regional comparisons of the associative behavior is dependent on time scale. Understanding the behavioral patterns of tunas around dFADs remains a complex issue. In order to get a comprehensive understanding of the associative patterns, there is clearly a need to carry out additional field experiments whereby potential factors driving the associative patterns are characterized or measured. This may include the collection of in situ data on environmental conditions, including densities of floating objects, tuna abundance, prey availability and predator presence in conjunction with passive acoustic tracking of tunas. In order to assess the links between the behavior at small and large timescales, there is a need to combine long-term passive tracking studies with short-term active tracking experiments to get a better understanding of the short-term movement of tunas both at and away from dFAD.

Eventually, collecting residence and absence times at different dFADs under different conditions (abundance of tunas, prey, predators and densities of floating objects) will allow us to better understand the drivers of the associative behavior. These are key parameters needed for modelling

FiguresFig. 1

 1 Figures

Fig. 2

 2 Fig. 2 Residence times for tagged tunas in the Mozambique Channel and Seychelles. Black bars correspond to the CRTs and white bars represent absences of 24 hours or more (CATs). The symbol ‡ marks CRTs which were interrupted due to fishing.

Fig. 3

 3 Fig. 3 Survival curves of CRTs for tunas tagged in the Indian Ocean. Dashed lines represents the best model fit.

Fig. 4

 4 Fig. 4 Survival curves of FCATs (a) and FCRTs (b) for tunas tagged in the Mozambique Channel and Seychelles.

Fig. 5

 5 Fig. 5 Average index of residence for tunas tagged in the Mozambique Channel and Seychelles. Error bars indicate standard errors.

Table 3

 3 Summary statistics for the continuous residence time (CRT) for tunas in the Mozambique Channel, Seychelles and for both areas combined (Indian Ocean). N= number of tunas, n= number of CRTs

Table 4

 4 Comparison of the goodness of fit between models. The parameter estimates and values of Akaike Information Criterion (AIC) are given for the three models tested on the survival curves of continuous residence time (CRT) obtained for each tuna species.

Table 5

 5 Summary statistics for FCRT and FCAT in days (in hours) recorded for different species and regions. Last column is the p value of the logrank test of comparison.

Acknowledgments

This study was carried out with financial support from the Commission of the European Communities, specifically the RTD programme of Framework Programme 7, "Theme 2-Food, Agriculture, Fisheries and Biotechnology", through the research project MADE (Mitigating adverse ecological impacts of open ocean fisheries) and the research project QUAESITUM (Quantifying environmental and social interactions for tuna fisheries management), Marie Curie Actions IEF, FP7. This work does not necessarily reflect the Commission's views and in no way anticipates its future policy in this area. This work was funded by the International Seafood Sustainability Foundation (ISSF). The research was conducted independently by the authors and its results, professional opinions and conclusions are solely the work of the authors. There are no contractual obligations between ISSF and the authors that might influence the results, professional opinions and conclusions. R. Govinden received financial support from the observatory of exploited tropical pelagic ecosystems (Ob7) from the Mixed Unit of Research MARBEC to travel to France. No conflict of interest has been declared by the authors.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

prototypes of satellite-linked acoustic receivers, which did not allow for long observations. Most of these data were therefore interrupted. In the equatorial central Pacific Ocean, [START_REF] Matsumoto | Behavior of skipjack tuna (Katsuwonus pelamis) associated with a drifting FAD monitored with ultrasonic transmitters in the equatorial central Pacific Ocean[END_REF] observed short mean CRT of 2.3 days for skipjack tuna, whilst [START_REF] Matsumoto | Comparison of the behavior of skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacores) and bigeye (T. obesus) tuna associated with drifting FADs in the equatorial central Pacific Ocean[END_REF] recorded mean CRTs of 2.2 and 5.1 days for bigeye, 2.2 and 6.1 days for yellowfin and 0.2 and 2.4 days for skipjack tuna at two different dFADs. In contrast, in the Atlantic Ocean, [START_REF] Tolotti | Association dynamics of tuna and purse seine bycatch species with drifting fish aggregating devices (FADs) in the tropical eastern Atlantic Ocean[END_REF] observed much longer mean CRTs of 25.31, 19.15 and 9.19 days for bigeye, yellowfin nd skipjack tuna respectively. At anchored FADs in the Maldives, [START_REF] Govinden | Movement behaviour of skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares) tuna at anchored fish aggregating devices (FADs) in the Maldives, investigated by acoustic telemetry[END_REF] recorded shorter mean CRTs of 0.2 and 3.5 days for skipjack and 0.66 days for yellowfin tuna. In contrast, [START_REF] Ohta | Periodic behavior and residence time of yellowfin and bigeye tuna associated with fish aggregating devices around Okinawa Islands, as identified with automated listening stations[END_REF] reported median CRTs of 7.0 and 7.9 days for bigeye and yellowfin tuna, respectively, around anchored FADs near Okinawa Island, whilst [START_REF] Dagorn | Satelite-linked acoustic receivers to observe behaviour of fish in remote areas[END_REF] reported that mean CRTs for bigeye and yellowfin tuna around anchored FADs near Hawaii was 4.8 and 8.0 days, respectively. From these comparisons, it appears that CRTs are of the same order of magnitude, independent of FAD type and region. However, it can be observed that the CRT of yellowfin and bigeye tuna are generally longer than that of skipjack tuna. Several authors have also noted this observation from previous studies (e.g. [START_REF] Schaefer | Simultaneous behavior of skipjack (Katsuwonus pelamis), bigeye (Thunnus obsesus), and yellowfin (T. albacares) tunas, within large multi-species aggregations associated with drifting fish aggregating devices (FADs) in the equatorial eastern Pacific Ocean[END_REF][START_REF] Matsumoto | Behavior of skipjack tuna (Katsuwonus pelamis) associated with a drifting FAD monitored with ultrasonic transmitters in the equatorial central Pacific Ocean[END_REF][START_REF] Matsumoto | Comparison of the behavior of skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacores) and bigeye (T. obesus) tuna associated with drifting FADs in the equatorial central Pacific Ocean[END_REF][START_REF] Rodriguez-Tress | Associative behavior of yellowfin Thunnus albacores, skipjack Katsuwonus pelamis, and bigeye tuna T. obesus at anchored fish aggregating devices (FADs) off the coast of Mauritius[END_REF][START_REF] Tolotti | Association dynamics of tuna and purse seine bycatch species with drifting fish aggregating devices (FADs) in the tropical eastern Atlantic Ocean[END_REF]. Variability in the residence times of tunas at FADs is likely to be species specific and related to different factors that influence the local conditions around the FAD, such as food availability, the environmental conditions, presence of predators or the proximity of other floating objects in the vicinity [START_REF] Ohta | Periodic behavior and residence time of yellowfin and bigeye tuna associated with fish aggregating devices around Okinawa Islands, as identified with automated listening stations[END_REF][START_REF] Robert | Intraindividual behavioral variability displayed by tuna at fish aggregating devices (FADs)[END_REF].

We observed a total of eight yellowfin and three skipjack tuna that returned to the dFADs after making prolonged excursions lasting more than 24 hours. However, of these 11 tunas, seven yellowfin and one skipjack made these excursions within 2 hours after being released, similarly to the excursions observed for silky sharks [START_REF] Filmalter | Global comparison of post release survival of silky sharks caught by tropical purse seine vessels[END_REF], and could be interpreted as a reaction to the stress of capture and tagging. In contrast, one yellowfin tuna made an excursion lasting 4.07 days, 12 days after it was tagged. Moreover, two skipjack tuna undertook excursions lasting more than a day (1.10 and 2.27 days) after prolonged CRTs (4 and 18 days respectively).

Similar observations of tuna returning to a dFAD after a long excursion (> 24 h) comes from [START_REF] Matsumoto | Comparison of the behavior of skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacores) and bigeye (T. obesus) tuna associated with drifting FADs in the equatorial central Pacific Ocean[END_REF] who observed one yellowfin and one bigeye tuna returning to the dFAD after an absence of more than 24 hours. However, the duration of the absence time was not the behavior of tuna in order to assess the effects of densities of floating objects on their movement patterns, a key priority to develop science-based management of the number of dFAD.

Conflict of interests

The authors declare to have no conflict of interest.

Author contributions

LD, FF, JDF designed the study, LD, FF, JDF, RG performed the experiments, RG and MC carried out the data analysis, RG took the lead in writing the manuscript, RG, LD and MC contributed to the interpretation of the results. All authors provided critical feedback and helped shape the manuscript.

Tables Table 1 Tagging


Marc Soria
email: marc.soria@ird.fr

Yann Tremblay

A Blaison

F Forget

Estelle Crochelet

Soria Marc

Tremblay Yann

Blaison

Forget Fabien

Dagorn Laurent

Large-scale movements and site fidelity of two bull sharks Carcharhinus leucas estimated from a double-tagging experiment at Réunion Island (southwest Indian Ocean)

Keywords: philopatry, pop-up satellite archival tags, residence time, shark-bite management, telemetry, western Indian Ocean

HAL is

Introduction

The bull shark Carcharhinus leucas occurs in warm tropical and subtropical waters, primarily on continental shelves [START_REF] Daly | Residency patterns and migration dynamics of adult bull sharks (Carcharhinus leucas) on the east coast of Southern Africa[END_REF][START_REF] Heupel | Conservation challenges of sharks with continental scale migrations[END_REF]. Bull sharks are reported to be largely philopatric, with some seasonal migrations along the coast [START_REF] Carlson | Habitat use and movement patterns of bull sharks Carcharhinus leucas determined using pop-up satellite archival tags[END_REF][START_REF] Espinoza | Evidence of partial migration in a large coastal predator: opportunistic foraging and reproduction as key drivers?[END_REF].

Like other apex predators, bull sharks play a key role in the proper functioning of coastal tropical and subtropical ecosystems [START_REF] Ferretti | Patterns and ecosystem consequences of shark declines in the ocean[END_REF]. Globally, many shark populations have been under intense fishing pressure throughout their ranges [START_REF] Queiroz | Global spatial risk assessment of sharks under the footprint of fisheries[END_REF]), resulting in substantial population declines. According to the International Union for Conservation of Nature, C. leucas is regarded as Near Threatened. However, bull sharks have also been considered to be responsible for attacks on humans, particularly during the last decade at Reunion Island [START_REF] Lagabrielle | Environmental and anthropogenic factors affecting the increasing occurrence of shark-human interactions around a fast-developing Indian Ocean island[END_REF].

Since 2011, the mean number of shark bites per year has increased markedly from 1.1 to 3 for the periods 1980-2010and 2011-2019, respectively (Taglioni et al. 2018). Between 2011and 2019, 27 attacks (of which 11 were fatal) occurred, which is considerable given the population of Reunion Island (863 000 inhabitants in 2016).

To date, little is known about the large-scale movements of bull sharks, particularly around small oceanic islands [START_REF] Brunnschweiler | Oceans apart? Short-term movements and behaviour of adult bull sharks Carcharhinus leucas in Atlantic and Pacific Oceans determined from pop-off satellite archival tagging[END_REF]. Therefore, there is a critical need to improve our understanding of the habitat use of bull sharks, particularly their site fidelity and movements, to mitigate the negative interactions between humans and sharks [START_REF] Ferretti | Reconciling predator conservation with public safety[END_REF][START_REF] Meyer | Habitat geography around Hawaii's oceanic islands influences tiger shark (Galeocerdo cuvier) spatial behaviour and shark bite risk at ocean recreation sites[END_REF]).

However, classic tracking technologies used on terrestrial animals, such as GPS and radio, cannot be used to track aquatic animals as radio waves and GPS signals cannot travel efficiently through water [START_REF] Grothues | A Review of Acoustic Telemetry Technology and a Perspective on its Diversification Relative to Coastal Tracking Arrays[END_REF]. For fishes that do not regularly surface, a good alternative is to use archival tags or pop-up satellite archival tags (PSAT) that can provide geolocation estimates through the measurement of light. However, raw geolocations derived from light-based algorithms have a large uncertainty, often hundreds of kilometers, and may have limited potential for addressing specific questions in fine-scale spatial ecology. To improve the precision of geolocation estimates, different environmental data, such as sea surface temperature [START_REF] Teo | Validation of geolocation estimates based on light level and sea surface temperature from electronic tags[END_REF], have been used to restrict geolocation uncertainty [START_REF] Nielsen | Improving light-based geolocation by including sea surface temperature[END_REF]). However, these methods are limited to estimates that occur more than once or a few times a day [START_REF] Patterson | Using GPS data to evaluate the accuracy of state-space methods for correction of Argos satellite telemetry error[END_REF]. In this study, we utilised a doubletagging method consisting of two independent tracking technologies used simultaneously on the same individual: PSAT and acoustic telemetry [START_REF] Cochran | Multi-method assessment of whale shark (Rhincodon typus) residency, distribution, and dispersal behavior at an aggregation site in the Red Sea[END_REF]. Acoustic telemetry uses a combination of transmitters deployed on tagged individuals with a network of fixed acoustic receivers that provide presence/absence data with a relatively good level of precision (site dependent: 100-800 m). PSAT tags are not spatially restricted to stationary acoustic-monitoring receivers for location estimates, and provide time-series data on ambient light (used for geolocation), temperature and depth of the tagged individual. By using these two biologging tools, we investigated the degree of site fidelity and the extent of movements of bull sharks when they leave the coastal waters of Reunion Island.

Materials and methods

In March 2013 two adult bull sharks were each equipped with two electronic tags: a pop-up archival transmitting tag (MiniPAT-247A PSAT tag, Wildlife Computers, Chicago, USA ) and a coded acoustic transmitter (V16TP-4x; delay range: 40-80 s, power output 158 dB, battery life of 845 days, Vemco, INNOVA SEA, Nova Scotia, Canada).

Each acoustic transmitter was implanted into the peritoneal cavity through a mid-ventral incision. The acoustic network consisted of 44 receivers deployed around Reunion Island (Figure 1). Each time an acoustic tag enters the detection radius (maximum range ~400 m) of a receiver, its ID and a time stamp are recorded [START_REF] Blaison | Seasonal variability of bull and tiger shark presence on the west coast of Reunion Island, western Indian Ocean[END_REF]. The acoustic telemetry dataset was used to assert the locations of the sharks in the coastal waters of the island throughout the study duration. Each PSAT tag was rigged with a heat-shrink-covered 20-cm monofilament tether and was attached externally using a mono-filament line punctured through the first dorsal fin. Each PSAT tag was programmed to detach itself after 192 days, float to the surface and transmit the archived data via the Argos satellite constellation. The software WC-DAP Global Position Estimator 2.00.0027 (Wildlife Computers) was used to process the raw light data [START_REF] Wilson | Estimation of location : global coverage using light intensity[END_REF]) and generated two location estimates per day. We used the particle-filtering modelling approach described by [START_REF] Tremblay | A Parsimonious Approach to Modeling Animal Movement Data[END_REF], which is similar to the WC-GPE3 program of Wildlife Computers, to estimate the probable locations of the sharks every eight hours. Constraints such as sea surface temperature and maximum diving depth were not used to refine the position estimates due to the lack of a horizontal thermal gradient and the relatively shallow occurrence of the sharks in the water column, which did not provide useful information on the bathymetry of the area. The maximum swimming speed of 4.55 km h -1 was used in the model and was based on the literature [START_REF] Daly | Residency patterns and migration dynamics of adult bull sharks (Carcharhinus leucas) on the east coast of Southern Africa[END_REF][START_REF] Lea | To Madagascar and back: long-distance, return migration across open ocean by a pregnant female bull shark Carcharhinus leucas[END_REF] and on speeds estimated from movements between acoustic receivers. The known locations from acoustic detections within the receiver array were used to refine the tracks generated by the geolocation model.

To reduce false acoustic detections, a shark was considered as present at a receiver when at least two detections were recorded during one hour. The geolocation model was set to avoid the landmass by using Dijkstra's algorithm [START_REF] Singal | Dijkstra Shortest Path Algorithm using Global Positioning System[END_REF]) to find the path of least resistance (i.e. shorter distance). Finally, given the limited accuracy of the geolocation estimates, we defined 'coastal waters' as the waters within 20 km of the coast. As such, an 'excursion' was termed as a trip of at least two days' duration outside coastal waters (i.e. >20 km from the coast).

Results

The details of the tagging and tracking data are summarised in Table 1. The tag on the male detached prematurely. Using a backward-drift model (P Sabarros, IRD, pers. comm.), the pop-up location was estimated to be southeast of the island, approximately 10 km offshore (21°30' S, 55°45' E). For the tag on the female, the pressure sensor indicated a fixed depth of 100 meters from 9 August 2013 until the tag surfaced on the 192nd day. Consequently, we used only the data collected prior to that date.

The pop-up location was 36 km south of the tagging site and 2 km offshore (21°19' S, 55°23' E).

The proportion of time spent in coastal waters (<20 km) was 58.1% and 89.9% for the male and female, respectively. It appears that the female undertook a limited number of large-scale movements and for most of the time remained in the coastal waters southwest of Reunion Island. This individual performed only three excursions off the coast of the island, each lasting a few days (less than a week), with a maximum distance from the island of about 60 km (Figures 2,3, Table 2).

The male exhibited a broader spatial pattern all around the island (Figures 2,3) and performed a single long excursion south of the island to the vicinity of a submarine ridge that culminated at a seamount situated 210 km from Reunion Island (23°.17' S, 55°.30' E). This excursion was performed in April over 20 d and covered approximately 1 260 km (Table 2). This large-scale movement was followed by six other short excursions of between 40 and 90 km from the coast.

Discussion

Using a double-tagging approach with acoustic telemetry and pop-up archival tags, we were able to substantially improve the accuracy of the tracks by adding more-precise locations. This approach is particularly useful for marine animals that rarely surface, like the bullshark, and which cannot be tracked using GPS technology [START_REF] Winship | Statespace framework for estimating measurement error from double-tagging telemetry experiments: State-space model for double-tagging data[END_REF].

The results showed that both bull sharks were regularly found inshore, suggesting a possible fidelity to the west coast of Reunion Island. This insular fidelity is similar to that described in previous studies on adult bull sharks [START_REF] Brunnschweiler | Oceans apart? Short-term movements and behaviour of adult bull sharks Carcharhinus leucas in Atlantic and Pacific Oceans determined from pop-off satellite archival tagging[END_REF][START_REF] Werry | Sex-based spatial segregation of adult bull sharks, Carcharhinus leucas, in the New Caledonian great lagoon[END_REF]. At Reunion Island, coastal fidelity of adult female bull sharks could be related to the mating activities thought to occur between May and August [START_REF] Pirog | Reproductive biology, multiple paternity and polyandry of the bull shark Carcharhinus leucas[END_REF]. The observed offshore excursions, particularly those undertaken by the male, differed from the large-scale movements of several months and thousands of kilometers previously reported for this species [START_REF] Lea | To Madagascar and back: long-distance, return migration across open ocean by a pregnant female bull shark Carcharhinus leucas[END_REF][START_REF] Espinoza | Evidence of partial migration in a large coastal predator: opportunistic foraging and reproduction as key drivers?[END_REF] or for other shark species [START_REF] Chapman | There and back again: a review of residency and return migrations in sharks, with implications for population structure and management[END_REF][START_REF] Meyer | Habitat geography around Hawaii's oceanic islands influences tiger shark (Galeocerdo cuvier) spatial behaviour and shark bite risk at ocean recreation sites[END_REF]. It seems unlikely that these offshore movements resemble large scale, seasonal and philopatric migrations as previously recorded for this species. Extensive movements punctuated by repeated offshore excursions have already been observed in sharks. This behaviour was observed in great white sharks (Jorgensen et al. 2010) where several individuals simultaneously occurred in an offshore area, and it was hypothesised that these potential meeting points, or 'cafés', were motivated by feeding or mating. The offshore excursion of the male bull shark observed in our study was oriented toward a ridge situated more than 250 km from the island. Such oceanic features are known to increase productivity via water enrichment associated with localised upwelling [START_REF] Morato | Seamounts are hotspots of pelagic biodiversity in the open ocean[END_REF]; hence it can be hypothesised that this seamount serves as an offshore feeding area.

Considering the limitations of the PSAT technology [START_REF] Hays | Why do Argos satellite tags deployed on marine animals stop transmitting?[END_REF], the small sample size (two individuals) and the limited study duration, great care has to be taken when trying to generalise the observed patterns of movement behaviour and residency to the entire bull shark population frequenting Reunion Island. However, the offshore excursions observed in our study confirm the ability of bull sharks to leave coastal waters for the open ocean and potentially highlight the important role of the oceanic habitat in the ecology of this species. The motive driving these repetitive offshore excursions displayed by bull sharks remains unclear and should be examined in future studies.

Figure 1 :

 1 Figure 1: Positions of 44 acoustic receivers around Reunion Island and tagging locations of the male (M) and the female (F) bull sharks Carcharhinus leucas

Figure 2 :

 2 Figure 2: Horizontal movements of (a) the tagged male bull shark from March to September 2013 and (b) the tagged female bull shark from March to August 2013. The intensity of the yellow pixels indicates the probability of occurrence. The pink circle indicates 20 km from the coast.

Figure 3 :

 3 Figure 3: Timeline displaying estimations of the distance from the coast (solid line) and acoustic detections in the coastal waters (red triangles) of (a) a male and (b) a female bull shark tagged off Reunion Island. The pink line indicates excursions of over 20 km and a minimum of two days duration. Pale grey line represents the error (standard deviation) of a location estimated from the positions generated by the model using a combination of speeds drawn at random below the maximum speed threshold set.

Acknowledgements -We are grateful to all the members of the institutions and associations involved in the CHARC program (Connaissance de l'HAbitat des Requins Côtiers de la Réunion) and to IRD, CRPMEM, University of Reunion Island, Globice, Kélonia, ARVAM, Squal'Idées, RNMR and Ifremer, as well as the fishers and volunteers who assisted with the shark tagging and made our work possible. This study received financial support from the European Union (convention FEDER ref. 2012-dossier Presage n°33021), the French government (BOP 113 n°2012/03) and the Regional Council of Reunion Island (POLENV n°20120257).