Seasonal Variation in the Behavior of Sea Turtles at a Brazilian Foraging Area
Abstract
This study was conducted in São Sebastião Channel, along the Southern Brazil Platform, and describes the occurrence of 3 species of sea turtles in the area, their main behavioral patterns, and the anthropogenic-related threats. Green turtles (Chelonia mydas) showed a preference for a site covered by Halodule spp. seagrass and hawksbill turtles (Eretmochelys imbricata) showed a preference for a sheltered bay with little wave action and the presence of rocks covered with Palythoa caribaeorum. These sites exhibited different characteristics due to the presence of ocean currents and variable habitat types in the Channel. This study enabled the description of the São Sebastião Channel as a foraging and resting area for sea turtles. We also suggest changing the category of the local marine protected area to enable better protection of turtles.
Sea turtles have complex life cycles, carrying out extensive migrations between foraging and breeding habitats that are located from hundreds to thousands of kilometers apart (Lutz and Musick 1997; Plotkin 2003). After the oceanic juvenile phase, which lasts 3–5 yrs after their birth (Reich et al. 2007), juvenile turtles recruit to inshore areas for development. At this stage, as is the case with green turtles (Chelonia mydas), they often reside in or near coastal bays, reefs, and estuaries rich in algae, seagrass, and/or invertebrates (Musick and Limpus 1997). When approaching maturity, pubescent turtles often move into adult foraging habitats (Musick and Limpus 1997). In some populations, adult habitats are geographically distinct from juvenile developmental habitats, whereas in other populations these two life stages may overlap or coincide (Musick and Limpus 1997). Upon reaching sexual maturity, these turtles begin large migratory cycles between foraging grounds and breeding areas, with migrations often extending into oceanic areas (Luschi et al. 2003).
In Brazil, sea turtle nesting occurs between the states of Sergipe and Rio de Janeiro and on three oceanic islands: Fernando de Noronha, Atol das Rocas, and Trindade (Marcovaldi and Marcovaldi 1999); scant nesting may occur elsewhere. In contrast, the entire coast of Brazil provides foraging habitat for sea turtles, although different species occur at varying densities along the coast (Gallo et al. 2006). Currently, the main threats in foraging areas in Brazil are incidental bycatch in fishing gear, especially with coastal fishing activities (Gallo et al. 2006), and the ingestion of anthropogenic debris (Bugoni et al. 2001; Mascarenhas et al. 2004).
Sea turtle foraging grounds in Brazil and worldwide are usually characterized by environments with sandy and rocky substrates that host a diversity of coral, sponge, algae, and seagrass species (Bondioli et al. 2005; Gallo et al. 2006; Makowski et al. 2006; Bjorndal and Bolten 2010; Berube et al. 2012). Compared with research on turtles in the breeding areas, relatively few studies have been conducted on juvenile turtles in developmental and foraging areas. However, these studies have important implications for the conservation of turtles and marine ecosystems (Crouse et al. 1987).
Development of reliable techniques for population estimation in foraging areas, either relative or absolute, should be a high priority because they allow us to monitor the effects of human activities on sea turtle populations and the success or failure of management policies (Bjorndal 1999). Furthermore, when these efforts are combined with ecological studies, we can better understand what habitats and ecosystems are more or less susceptible to human impacts. For example, knowledge about sea turtle home ranges and the oceanographic and biological parameters within these areas of activity can help define how the space is used and what defines an “optimum” foraging habitat, both in terms of their biological value and their importance for population viability (Hamann et al. 2010).
The north coast of São Paulo is an important feeding area for green turtles (Gallo et al. 2006), but few studies have been conducted in the region. The São Sebastião Channel (SSC) hosts a Marine Protected Area (MPA) called the Marine Ecological Sanctuary of Ilhabela. However, this kind of protection area does not fit into any category defined by the National System of Nature Conservation Units (Federal Law 9.985/2000; Brazil 2000); therefore, this area lacks the political and financial support required for the implementation of protective measures and, consequently, has experienced losses in its local biodiversity. It is necessary that more studies be developed in the Marine Ecological Sanctuary of Ilhabela in order to provide data to assist in the readjustment of the MPA and the conservation of endangered animals therein.
Transect sampling is the primary method of estimating animal abundance in wildlife studies. Transects may be as simple as swimming over a reef looking for turtles or as sophisticated as a spatially stratified, aerial line-transect survey (Gerrodette 2000). This methodology relies on visual identification, thus minimizing disturbance to animals and reducing times and costs compared with other techniques such as capture–mark–recapture and catch-per-unit-effort analyses (Mancini et al. 2015). Whereas visual count techniques have been commonly used to determine population abundance in fish communities (Sale 2002), such techniques have been sparingly applied to study marine turtles (Gerrodette 2000; Houghton et al. 2003; Roos et al. 2005; Schofield et al. 2006; Mancini et al. 2015). In these cases, visual surveys usually involve line transects via snorkeling. This type of survey allows for simultaneous evaluation of turtle abundance along with characteristics such as species, life stage, sex, and size (Roos et al. 2005). As noted by Mancini et al. (2015), this type of survey can produce accurate estimates of relative abundance and density of marine turtles in their feeding grounds.
This study focuses on 3 species of sea turtles (Caretta caretta, Chelonia mydas, and Eretmochelys imbricata) that occur in the Southern Brazil Platform Large Marine Ecosystem and describes resting and feeding behavior of C. mydas and E. imbricata. Knowledge of behavioral patterns will assist the development of proper conservation plans for sea turtles in their foraging habitats and will help with determining the adequacy of the existing protected marine area.
METHODS
Study Area
The São Sebastião Channel (23°46″S, 45°21″W) is located on the northern coast of São Paulo in southeastern Brazil. Four different bodies of water occupy the São Sebastião Channel (SSC) throughout the year (Table 1). The biodiversity associated with each body of water increases the total biodiversity of the Channel, adding complexity to the local food chain (Oliveira and Marques 2007). Surveys conducted in the SSC revealed the presence of more than 120 species of sponges (Hajdu et al. 1996, 1999; Pinheiro and Hajdu 2001), which could also attract hawksbill turtles, as sea sponges are considered one of their main food items (van Dam and Diez 1998; León and Bjorndal 2002). The benthic communities of the southern and northern portions of the SSC present high species diversity that contrasts with the unbalanced communities found at the central area (Pires-Vanin et al. 2013). The community structure and ecological relationships are shaped by the complexity and heterogeneity of the substratum and the marine current circulation, although anthropogenic activities may have negative impacts, particularly in the central area (Pires-Vanin et al. 2013). The southern area of the Channel is characterized by rocky bottom, most of which is covered by the species Palythoa caribaeorum (Chimetto et al. 2011). The sediments in this region are composed of fine sand with a high degree of selection due to wave action (Barcellos and Furtado 1999). The sea floor in the central region is mainly composed of fine sediments and covered by sea grass Halodule spp., which has been described as one of the main green turtle food items (Bjorndal 1997; Limpus et al. 2005; Arthur et al. 2009). Site 4 (in this region) is the only one among the sampling areas that presented these characteristics. The northern area of the Channel presents deposition of coarser sediments due to lower wave action (Barcellos and Furtado 1999).
Field Surveys
Two methodologies were adopted for the surveys: fixed-point monitoring and direct underwater observations (Houghton et al. 2003; Roos et al. 2005; Schofield et al. 2006). The latter method was conducted by divers during 52 d in the austral summer (January, February, March, and April) and 46 d in the austral winter (June, July, August, and September).
There were 6 survey sites distributed throughout the SSC. The sampling sites were selected to represent the southern, central, and northern regions of the SSC owing to their diversity in habitat type. Thus, the sampling areas were distributed with 2 sites in the south, 2 in the central region, and 2 in the north of the SSC along the insular margin (Fig. 1). The points of underwater observations are ∼ 5 km apart from each other, with the exception of Site 2, which is located only 1.5 km from Site 3. However, Site 2 was included in the sampling because it belongs to a Marine Protected Area managed by the city of Ilhabela.
Citation: Chelonian Conservation and Biology 16, 1; 10.2744/CCB-1200.1
Observations were conducted through snorkeling along predetermined transects. Prior to each dive, the following data were recorded: date, time, water temperature (using a mercury column thermometer), sampling location, and visibility (in meters). Visibility was measured using the following procedure: a diver held the tip of the flexible end of a 30-m measuring tape while a second diver moved away to the point until he could not see his partner, and at this point, the distance between them was recorded (Reisser 2006). Visibility was categorized as bad if diver–diver visibility was lost between 0 and 2 m, regular if lost at 2–4 m, and good if lost at > 4 m. The snorkeling surveys were performed on the surface, and the depth of sampled habitats ranged from 2 to 5 m. Visibility influenced divers' ability to see the seafloor (i.e., seafloor not viewable during bad visibility periods). Censuses were conducted along transects 300 m in length, with a visual count being carried out by 2 divers, who slowly (about 0.125 m/sec) swam parallel at the same speed in the same direction and along the transect (Roos et al. 2005; Rincon-Diaz et al. 2011). During this trajectory, divers were connected by a string with a length that varied according to the minimum visibility of the water on every dive, thus ensuring that all turtles present in the central track of the transect (between the divers) were sighted and that the parallel trajectory between the divers was maintained. While each diver monitored one side of the track, both monitored the central strip (Roos et al. 2005) (Fig. 2). The dive time in each transect was standardized to 40 min so that no difference existed between the actual search time for each survey. One of the divers (A.F.) participated in all surveys; the second diver position was filled from among 3 other trained snorkelers. At all times, snorkelers tried to maintain a distance of at least 4 m from the sighted animal (when it was possible owing to visibility) so as not to interfere with the turtle's behavior (Houghton et al. 2003; Taquet et al. 2006). After every survey transect, the total number of turtles was calculated as the sum of the individuals sighted in the 2 external strips and the maximum number of individuals recorded in the central strip. As per Roos et al. (2005), sightings recorded in the central strip were also used to estimate the differences among observers. Considering that both observers monitored the central strip, it is assumed that they sighted the same, or very close, number of individuals. Statistically, the difference between observer sighting performance was analyzed with a Wilcoxon test.
Citation: Chelonian Conservation and Biology 16, 1; 10.2744/CCB-1200.1
During each transect, observed turtles were counted and their activities recorded (Houghton et al. 2003; Taquet et al. 2006). The straight carapace length (SCL) of the animals was estimated according to 3 size ranges: juvenile (≤ 60 cm), subadult (60–90 cm), or adult (> 95 cm for green turtle and > 80 cm for hawksbill turtle; Chaloupka and Limpus 1997; Limpus and Chaloupka 1997; Proietti et al. 2014). The length class was estimated according to 10-cm size ranges to minimize possible errors in this type of estimation (Reisser 2006). Houghton et al. (2003) revealed that through calibration, the curved carapace length (CCL) of marine turtles can be consistently estimated to within 10 cm of their actual size. Although rudimentary, this has advantages for assessing the presence or absence of specific life history stages from particular environments.
The behavior of turtles observed by snorkelers was classified as foraging (i.e., ingestion of prey whilst resting on the seabed or whilst maintaining position in the water column), swimming (i.e., swimming in water column), resting (i.e., remaining stationary on the seabed without foraging), or aided resting (i.e., remaining stationary at the seabed while using an external structure; adapted from Houghton et al. 2003). Divers classified behaviors only when they were clearly observed. Photographic records were obtained during observations to recognize individuals (photo-identification) and to record any unusual behavior such as the use of cleaning stations or inclined resting (when turtles were observed resting at an angle of 45°, using rocks as support). For each dive site (Sites 1, 2, 3, 4, 5, and 6) where transects were conducted, a fixed point of observation along the shore was also established where the observations were made by adapting the scan sampling method described by Altmann (1974). Each survey period lasted 70 min, divided into five, 10-min observation periods with a space of 5 min rest between each. Two observations (morning and afternoon) were conducted with the objective of estimating the peak activity periods of these animals at each site. The number of times an animal rose to the surface to breathe was noted, and at the end of the 10-min observation period an estimate of how many turtles were sighted in that time was calculated. The number of sighted turtles was estimated by visual monitoring (when possible) where the observer followed the turtle and recorded its external characteristics (e.g., as size, color, presence of fibropapillomas) to help differentiate the individual and avoid pseudoreplication. Prior to each survey we recorded air temperature, Beaufort sea state, and tidal state (low tide, ebb and flood tide, and high tide according to the tide table). Relevant observations, such as the passing of boats or fishermen and weather events in the previous days, among other factors, were also recorded; thus, any connection could be inferred between these factors and the presence of the animals.
Data Analysis
Data analysis was performed using the R Statistics Program (R Core Team 2014). By applying generalized linear models (GLM; McCullagh and Nelder 1989; Zeleis et al. 2008), the influence of the environmental variables on the number of observed turtles and the behavior displayed by these animals were evaluated. The general model for the observed behavior analysis was composed of a response variable (observed behaviors) and 5 predictor variables (water temperature, location, size classes, type of sea floor, and season), with the last 4 variables being categorical. We also used a GLM analysis of the data from the fixed-point observations to check the influence of predictor variables (water temperature, location, Beaufort sea state, tidal range, season, and number of vessels) on the number of spotted turtles (response variable).
The general model of GLM applied to the data from the underwater surveys incorporated environmental variables (water visibility, location, water temperature, and season; i.e., predictor variables) to check their influence on the number of spotted turtles.
During the winter months, underwater observations were not possible at Site 4 because of poor visibility at the site during the season (< 0.5 m); this was accounted for in the analysis through the offset function. When the visibility was poor, the bottom was not viewable by observers, and this may have interfered in sighting of turtles. So this variable was also accounted for in analyses through the offset function.
Because the direct observation of turtles through diving is limited by some environmental variables such as visibility, Beaufort sea state, and even the behavior of the sea turtles, the animal counts showed a high number of zeros. Some models (for example, the inflated zeros model and the Hurdle model; Mullahy 1986; Lambert 1992) take into account an excess of zero counts, which recur in ecological work (Zeleis et al. 2008). After verisimilitude testing of the possible models within the GLM analysis (Zeleis et al. 2008), the Hurdle model was determined to best fit the data. To analyze the behavior of the sea turtles we chose the model using the lower value of the Akaike Information Criterion (AIC; Akaike 1974).
RESULTS
Samples were collected from January to September 2014, totaling 378 hrs of sampling effort between the fixed-point and underwater observations, which were distributed across 196 hrs in the summer and 182 hrs in the winter. Of the 119 turtles sighted during the underwater observations, 84% were C. mydas, 16% were E. imbricata (Table 2), and a single individual was C. caretta (Site 2) (Table 2). Unidentified turtles were not counted in the survey. Chelonia mydas and E. imbricata were recorded in the summer and winter. Registered turtle counts in the center strip showed no significant differences among divers (V = 447 Wilcox; p > 0.05). Of the dives, 70% had poor visibility, 20% had regular visibility, and 10% had good visibility.
Data regarding the presence of vessels were incorporated into the general GLM model, but the test did not find that the presence of vessels changed the number of turtles. That is, while the presence of a boat may impact a turtle's surfacing frequency, it is not expected to cause turtles to leave the study area.
Of the 101 green turtles sighted during the underwater observations, 7% were classified as subadults and the rest were classified as juveniles. The size classes of turtles observed at the different sites were heterogeneous (Pearson's chi-square test, χ2 = 19.5779, p = 0.0014). Regarding the influence of environmental variables on the underwater observations, the Hurdle model indicated that only visibility and water temperature influenced the predicted number of animals observed in each dive. During the winter months underwater observations were not possible at Site 4 owing to poor visibility (< 0.5 m).
Regarding the hawksbill turtles sighted, 8 turtles were classified as subadults, 7 as juveniles, and 3 as adults. These numbers did not differ significantly (Pearson's chi-square test, χ2 = 3.6471, p = 0.1615), and no difference was observed among the sampling sites regarding turtle size classes (Pearson's chi-square test, χ2 = 3.5366, p = 0.4723). The distribution of the hawksbill turtles in the observation sites are shown in Table 2.
During 157 hrs of fixed-point observations (Table 3), 2132 surfacing events were counted and a significant relationship was observed between the frequency of these events and the Beaufort sea state (Kruskal-Wallis: χ2 = 12.75, df = 3, p = 0.005). There was a significant difference in the number of surfacing events observed during summer versus winter, but only at Site 3 (Kruskal-Wallis: χ2 = 17.7068, p < 0.001) and Site 6 (Kruskal-Wallis: χ2 = 8.5974, p = 0.003366). The Hurdle model found that only local sampling sites (p < 0.001) and the Beaufort sea state (p = 0.004) influenced the observation of sea turtles.
To analyze the sea turtle behavior, the model chosen based on low AIC (Akaike 1974) indicates that only the location and type of sea floor were influential on the behaviors observed. The behaviors of the 2 species (C. mydas and E. imbricata) were analyzed together from the predefined categories and different behaviors were recorded separately. Of the 4 behaviors observed, turtles were most frequently seen while swimming (58%) followed by resting (18%), foraging (14%), and aided resting (12%); no foraging behavior was observed during winter months (Table 4). In addition to the 4 primary behaviors, sergeant major fish (Abudefduf saxatilis) were observed cleaning hawksbills on 4 occasions while the individuals were exhibiting aided rest behavior. Hawksbill turtles were also frequently observed lying prone on the rocks with their front flippers placed under their bodies. During the observations of green turtle feeding behavior we identified 3 food items: green algae (Ulva lactuca), seagrass (Halodule spp.), and the zoanthid P. caribaeorum. Hawksbill turtles were observed foraging on the zoanthid P. caribaeorum at Sites 2 and 3. For underwater observations, the Hurdle model found that only visibility and water temperature influenced the number of animals observed during each survey. Although the Hurdle model indicated that the temperature of the water influenced the number of animals seen, the same did not occur for the behaviors sighted.
During this research, 2 green turtle carcasses were found close to Site 4, one with a carapace length of 85 cm and the other with a carapace length of 50 cm; both had large lesions in their shells indicative of damage from boat propellers. In addition, one 35-cm green turtle was encountered stranded alive on the beach; the turtle was missing a front flipper and had several injuries consistent with boat strikes. Apparent boat collision injuries were also observed on the carapaces of 3 green turtles and 1 hawksbill turtle observed during the underwater surveys.
DISCUSSION
The methodological approach adopted in this study allowed us to identify aspects of the green turtle and hawksbill turtle behaviors that were unknown in the region so far. The sampling methods used during our research were considered appropriate, and this was supported by the fact that we found no significant difference in the frequency of sightings among divers. During the underwater observations, when it was not possible to see the animals by diving due to poor visibility, their presence was verified through the observations during fixed-point surveys, thus making the methodologies complementary.
Underwater Observation
During periods of low temperatures, when environmental conditions are known to be suboptimal, sea turtles can decrease their metabolism (Southwood et al. 2003), possibly presenting lethargic behavior, resting on the marine substrate (Felger et al. 1976), and performing more lengthy and deeper dives (Southwood et al. 2003). Sea turtles in Ilhabela are believed to exhibit these behaviors without the need to move to higher latitudes in search of warmer waters during winter months. Although the number of sighted turtles was influenced by water temperature, no significant change in the number of observations between summer and winter was observed, thus indicating that turtles are present throughout the year in SSC, possibly due to the influence of the Coastal Waters entering through the northern part of the channel.
Although some authors cite the inactivity threshold as 15°C (Felger et al. 1976; Seminoff 2000), the green turtle population seemed to respond differently when faced with temperature changes. In the SSC, there were no significant changes in behavior in relation to changes in water temperature (which decreased from ∼ 25°C in the summer to ∼ 18°C in the winter). This contrasts with the results of Seminoff (2000), which showed that although green turtles were present throughout the year at foraging grounds of the Gulf of California, they became inactive at waters below 15°C.
The “visibility” variable proved to be limiting to the research, with fewer turtles being observed when the visibility was classified as bad. Roos et al. (2005) and Salmon et al. (2010) also found limitations in the research due to the restriction caused by visibility in studies undertaken in Mackay, Australia, and Mayotte Island in the Indian Ocean, respectively. These results indicate the importance of considering this variable in surveys conducted by divers because the low visibility may not indicate the absence of the animal but rather the diver's inability to see them. As the observations made at a fixed site were not influenced by visibility, this methodology allows for recording the presence of turtles even when they are not sightable during underwater surveys. This underscores the value of using these 2 complementary approaches in our survey efforts.
Green Turtles
Regarding green turtle size, the smallest turtles observed in this study were in the 20–30-cm size class whereas the largest turtles were in the 60–70-cm size class. Based on this size range, green turtles observed in this study included both juvenile and subadults (Chaloupka and Limpus 1997; Limpus and Chaloupka 1997). The largest green turtles observed in this study also were of a size similar to that described by Pilcher (2010); approximately 60–70 cm.
Some studies have described the average size of newly recruited individuals to foraging areas (Balazs et al. 2000; Balazs and Chaloupka 2004; Pilcher 2010; Colman et al. 2014) (Table 5). Among the sighted animals, 32% had a carapace length of 30–40 cm, which may indicate that the region is a recruitment area for green turtles after their pelagic phase and provides food and shelter.
The occurrence of a higher number of subadult green turtles at Site 4 may have been due to the characteristics of the sea floor, which consisted of fine sediment and was covered by Halodule spp. seagrass, which has elsewhere been described as one of the main green turtle food items (Bjorndal 1997; Limpus et al. 2005; Arthur et al. 2009). This site is the only one among the sampling areas that presented these characteristics.
The current and tide hydrodynamics within the SSC influence the types of substrate on each beach (Netto et al. 2005) and may also influence the distribution and concentration of sea turtles due to differences in food availability and resting conditions. Site 2 has a sheltered bay with little wave action and offers the presence of rocks (Netto et al. 2005) that can serve as a refuge for sea turtles. This fact may explain the higher incidence of juvenile green turtles and the greater frequency of observed foraging behavior compared with other sites. Site 2 also featured an extensive coverage of P. caribaeorum in the rocky areas (Chimetto et al. 2011); this species was observed as a food item at Ilha dos Arvoredos, Santa Catarina, Brazil (Reisser et al. 2013).
The prevalence and greater number of juvenile green turtles at the sites located in the southern region of the São Sebastião Channel (Sites 1 and 2) can also be connected to the dynamics of the ocean currents in the channel. The South Atlantic Central Water mass (SACW) is rich in nutrients and is important for marine productivity throughout this area (Oliveira and Marques 2005). The SACW increases the number of sea turtles mainly in the southern region, where this mass enters the channel by gradient pressure force (Silva et al. 2005). Although the northern region has lesser nutrients than does the southern region, we observed more turtles in this northern region. Perhaps the higher temperatures of the northern region (due to the Coastal Waters mass) are the primary factor attracting sea turtles to this area, as this would optimize metabolism and allow for year-round residence.
This research indicated that green turtles remain in the channel throughout the year, even when food resources seem to decrease. Makowski et al. (2006) reported that when resources are sufficiently available, individuals might develop affinities to specific areas, both for food and for resting habitat. Similarly, Ilhabela appears to offer juvenile green turtles the necessary resources to remain year-round.
Hawksbill Turtles
Unlike the green turtle, the hawksbill turtles observed in this study were predominantly subadult individuals, and this species was most prevalent in the southern Channel region. The occurrence of this species only in the central and southern regions of the Channel is linked to a greater occurrence of the species P. caribaeorum.
The presence of the adult hawksbills at Site 2 throughout the year indicates that this is a significant foraging and resting area for this species. Juvenile hawksbill turtles are known to exhibit sedentary behavior when they find a suitable foraging area (Pritchard and Trebbau 1984), remaining in such places for long periods. Two of the 3 individuals found at Site 2 and classified as adults during this study were in the 90–100-cm size range, and the third individual, also classified as an adult based on size, had a carapace length of 70–80 cm (Fernandes et al. 2015). The residence of adult hawksbill turtles in foraging areas in Brazil was recorded by Marcovaldi et al. (2012) in northeastern Brazil, but no records exist of these adult animals residing in the south and southeastern portions of Brazil. Fishermen and local residents of Ilhabela report the permanence of adult hawksbills at this area for at least 5 yrs (pers. comm. with local fisherman, January 2014). Meylan et al. (2011) reported on the growth rate of hawksbill turtles in Bermuda, citing that upon recruitment these turtles may remain residents for upwards of 30 yrs. Gaos et al. (2016) recorded that hawksbill habitat use in eastern Pacific was strongly associated with mangrove saltwater forests and shrimp ponds.
Fixed-Point Observations
The sightings from the fixed points showed significant differences among the sampling areas, with only Sites 2 and 4 showing a significant increase in the number of surfacing events in comparison to other sites.
The proximity to vessels has not been indicated by the GLM as a limiting factor to the presence of turtles; this finding indicates that turtles may therefore be more susceptible to collisions. Hazel et al. (2007) concluded that higher vessel speeds in Moreton Bay, Australia, increased the likelihood of turtles being unable to escape collision and, therefore, resulted in a greater risk of boat strikes. The vessels observed during this study often traveled at high speeds and at a distance of less than 100 m from the coast. The sound of the boats' engines offer small benefit to the submerged sea turtles in allowing them to identify a threat, and these animals may be unable to identify the sound's origin, or perhaps turtles become habituated to the sound such that boat noise elicits no avoidance response (Hazel et al. 2007). Because sea turtles tend to develop long-term fidelity to coastal foraging areas, for each individual turtle that resides in areas with vessel traffic the risk of collision may persist over decades. For turtles, this cumulative risk of collision is high, and the likely consequence of collision is severe injury or death (Hazel et al. 2007). With vessel numbers likely to increase over time, the risk of boat strikes will progressively increase unless the permitted speed of the boats is reduced considerably, navigation away from the coast is required, or both.
Conservation Implications
This study provides relevant information about sea turtles of the São Sebastião Channel and highlights the importance of continued research on sea turtle populations in the region. Our results also contribute to a better understanding of sea turtle dynamics and may help inform conservation practices in the region of Site 2, which is within the limits of the Marine Protected Area (MPA). Whereas some areas are currently protected only in theory, conservation goals are often not achieved owing to the lack of an adequate management plan. Therefore, verification of the effectiveness of conservation strategies within this MPA is necessary to ensure the conservation or protection of biodiversity (Schiavetti et al. 2013). Furthermore, we recommend the establishment of standards regarding speed and distance from the coast in places with the highest concentrations of sea turtles so as to minimize the risk of boat strikes. We also encourage the formation and expansion of the MPA, which seeks to preserve important habitats for the species being studied.
Sampling areas along the São Sebastião Channel and Marine Protected Area (MPA).
Methodology scheme for the turtle census (adapted from Roos et al. 2005).
Contributor Notes
Handling Editor: Jeffrey A. Seminoff
