Combined data from nesting beach monitoring and satellite telemetry allowed us to provide robust estimates of average clutch frequency for hawksbills turtles nesting in Rio Grande do Norte state, Brazil, with estimates ranging from 3.3 when using observed data from beach monitoring to 4.7 when combining the beach monitoring data with satellite telemetry. Larger clutch frequency estimations when using satellite telemetry and data from nesting turtles opposed to only using data from nesting beach is reflective of previous studies (Rees et al. 2010; Tucker 2010; Weber et al. 2013; Esteban et al. 2017; Tucker et al. 2018). Larger clutch frequency numbers, when estimating number of nesting females, results in a lower estimate of nesting female numbers, as the total number of clutches is divided by a larger denominator (Mazaris et al. 2008). That is why clutch frequency is considered a key demographic parameter to marine turtles and when not accurately estimated may lead to inflated estimation of nesting females. Despite the importance of clutch frequency estimates, this parameter has been rarely estimated for Atlantic hawksbill turtles, with disparities in estimations, based on beach monitoring, between continental rookeries (less than three clutches per females) and island rookeries (4 to 5 clutches per female) (Garduño-Andrade et al. 1999; Xavier et al. 2006; Beggs et al. 2007; Kamel and Delcroix 2009; Kendall et al. 2019). This disparity is likely due to nests being missed, since it is typically easier to encounter all nesting females at smaller, geographically isolated beaches, which is usually the case at islands. As turtles nesting at continental beaches may nest within a region, there is the possibility that they may be nesting at adjacent beaches to those surveyed. Nevertheless, although evidence exists that hawksbill turtles nesting in islands exhibit strong site fidelity (Levasseur et al. 2019), evading from the original site to other near islands can also occur (Iverson et al. 2016), making challenging to obtain unbiased clutch frequency estimates with beach monitoring data solely. Clutch frequency using satellite telemetry has been calculated for nesting hawksbill turtles in the Dominican Republic (between 2–4 clutches); however, the selection of individuals for these estimations may have included females that nested previously in the season, underestimating clutch frequencies (Revuelta et al. 2015).
The temporal scale of monitoring, and consequently data inclusion into estimates, affects clutch frequency estimates; thus, care should be taken to ensure that the whole nesting season is incorporated into such estimations. Bio-logging tools such as radio or satellite telemetry are very helpful to keep track of internesting returns (Rees et al. 2010; Tucker 2010; Weber et al. 2013; Esteban et al. 2017; Tucker et al. 2018); however, it is important that device deployment occurs during the first nesting event of the breeding season or prior. Indeed, disparities in clutch frequency estimations can be observed between studies that use different sampling designs. For example, in our study we only considered individuals nesting in the first portion of the nesting season to avoid including turtles that had nested previously within the season, with an estimated 3.9 clutches for ECFb. However a ECFb of 2.6 was estimated by Santos et al. (2013) at the same study sites when considering all individuals nesting over the course of the entire nesting season. This difference may be driven by the inclusion of turtles that may have nested previously within the nesting season. Acknowledging that the first nesting event might not have been accounted for clutch estimations, Rivalan et al. (2006) estimated clutch frequency in leatherback turtles using an approach that considers that the turtle may have nested but not been observed prior to their first and after the last recorded nesting event. This approach was first designed to estimate stopover duration on birds (Schaub et al. 2001; Efford 2005) and further adapted to improve estimation of clutch frequency in leatherback turtles (Dermochelys coriacea) using beach monitoring data (Rivalan et al. 2006). Despite the fact that we cannot ensure that the selected turtles for the present study have not nested previously, our approach of selecting individuals from the first portion of the nesting season reduces biases associated with individuals potentially nesting previously (see Esteban et al., 2017; Tucker, 2010; Tucker et al., 2018). Futures studies can use different approaches (e.g., ultrasonography, the amount of fat in a turtles neck) to confirm the stage of nesting (Blanco et al. 2012; Walcott et al. 2012, 2013).
Residence length, a parameter that might be used to calculate clutch frequency (Esteban et al. 2017; Kendall et al. 2019) also requires knowledge of the first and last nesting event for individual nesting turtles. Residence length at a site is a result of the cumulative sum of each turtle internesting interval, from first to last nesting event (Esteban et al. 2017). Several factors may influence the internesting and residence length of turtles and should be considered. First, disturbances during nesting, such as lights, coastal construction, predators, human activities, anthropogenic debris, sand compaction or even other turtles may prevent the turtle to conclude/start nesting causing unsuccessful attempts (Witherington 1992; Fuentes et al. 2016; Fujisaki and Lamont 2016; Drobes et al. 2019; Garrison and Fuentes 2019; Sella and Fuentes 2019). In these cases the turtle returns to the sea and waits for the next opportunity to nest; this could be in the same night, but often in the following night(s) (see Hamann et al., 2002). If false crawls occur repeatedly, the extended internesting intervals will increase residence length. Second, temperature influences physiology, with warmer waters causing internesting intervals to decrease (Sato et al. 1998; Hays et al. 2002). Behavior may also influence temperature, i.e. the turtles may select shallow warmer waters for breeding residence (see Fossette et al., 2012; Schofield et al., 2009). Also linked to physiology, the water limitation hypothesis has been suggested to influence the length of internesting interval (Price et al. 2019). Indeed, rehydration was theoretically suggested as responsible for mass recovery during the internesting interval (Santos et al. 2010) when gravid hawksbill turtles are fasting (Goldberg et al. 2013). Lastly, the process of PTT attachment may influence nesting turtle behavior, in particular if the turtle is displaced to another area for the instrumentation and further release, which was not the case for this study (see Luschi et al., 2003, 1996).
Our estimates for residence length that incorporated data from satellite telemetry were close to each other IRLs of 55.9 ± 11.8 days (range 31–76 days; N = 18) and the PRL of 52.6. It is interesting to note that this single number (PRL) was estimated based on the difference between average date for first nesting event from beach monitoring (N = 210), which includes turtles seen only once (transients), and the average date from departure from satellite telemetry (N = 35) (Fig. S4). The longest residence length (85 days) at a breeding site recorded for hawksbill turtle using satellite telemetry was observed in the US Virgin Islands (N = 30; Hart et al., 2019). Because most satellite telemetry studies with nesting hawksbill turtles focus on migration and delineating foraging grounds (Cuevas et al. 2008; Van Dam et al. 2008; Hawkes et al. 2012; Moncada et al. 2012), those that included internesting intervals in their analyses have not typically been designed to track individuals since their first nesting event, and as a result their residence length at the breeding site are likely to be underestimated (Troëng et al. 2005; Gaos et al. 2012; Marcovaldi et al. 2012; Pilcher et al. 2014; Nivière et al. 2018; Hart et al. 2019). Cases in which the female hawksbill turtle was tracked from the foraging site towards the breeding site are scarces in the literature (Hawkes et al. 2012; Iverson et al. 2016), and residence length at the breeding site has been provided for only one individual (Iverson et al. 2016). Even though, with recent technological advancement satellite tags have the ability to last longer and store more data, problems with tag retention are still one of the biggest challenges to satellite telemetry studies (see Pilcher et al., 2020). Studies aiming to improve tag retention should be prioritized to gain more benefit from satellite tracking studies.
Our IRLb comparison for turtles from the first portion of the nesting season was higher than that for turtles starting the season from February onwards, suggesting that early nesters may have higher clutch frequency. For other species such as many birds the timing of arrival for the nesting season influences breeding success (Verhulst and Nilsson 2008; De Forest and Gaston 2010). Walcott et al. (2012) found that hawksbill turtles that arrive earlier in the nesting season occupy shallower waters, which may be associated with higher quality breeding residence habitats. In this sense, the arrival time for the breeding season may also influence residence selection, which possibly affects its length and therefore clutch frequency estimates. One way to investigate the possible influence of arrival timing during the nesting season on clutch frequency would be to deploy satellite transmitters before the females arrive at the breeding site. This would require the device to function for more than two years, as the remigration interval for hawksbill turtles is typically two years (Santos et al. 2013) or to attach the equipment in the foraging ground prior to migration (see Pilcher et al., 2020). However, selecting turtles at foraging grounds that will likely start migration to breeding areas is challenging since it would require the identification of individuals that are reproductively ready to leave, this could be determined with laparoscopy or ultrasound (Pilcher et al. 2020). It is speculated that the longer the distance from the foraging ground to the breeding site the more energy turtles will spend on migration (Enstipp et al. 2016) and therefore less energy may be allocated to reproduction, resulting in smaller clutch frequency or clutch sizes (Patel et al. 2015). On the other hand, resident turtles that do not need to allocate energy to large migrations may nest more times during the season or exhibit smaller remigration interval (Ceriani et al., 2015; Vander Zanden et al., 2014). In addition, the quality of foraging grounds also plays a determinant role on energy accumulation and fecundity (Broderick et al. 2001; Vander Zanden et al. 2014; Ceriani et al. 2015); however, possible impacts on clutch frequency remain unknown. Thus, if environmental changes are likely to influence the quality of foraging habitats over time (Hays 2000), there is the need to revisit demographic parameters such as clutch frequency and remigration interval from time to time.
The spatial extent of sampling, and data inclusion, also needs to be considered for clutch frequency estimation. It is very common for projects to report their nest count for their specific study site (Mascarenhas et al. 2004; Marcovaldi et al. 2007; Camillo et al. 2009; Moura et al. 2012; Santos et al. 2013). However, our study highlights that the use of clutch frequency data to estimate abundance of nesting females based on nest counts should only be used when the whole population is considered, in a more comprehensive way (see Ceriani et al., 2019). For instance, if we use our ECFs = 4.7 to infer number of nesting females within our study sites for the year with highest number of nests (18/19 = 138 nests), the result would be 29 females. However, in that season 48 individual females were encountered, with 33% of transient turtles (16 females; Table S2) that also used adjacent beaches to nest (Santos et al. 2013). There are studies with hawksbill turtles that exclude transient turtles for the calculation of clutch frequency (Beggs et al. 2007). Using this approach for the previous example, the estimation would result in 3.9 clutches per female, which is the same ECFb that we obtained; however, if we just divide the total number of clutches by the number of individual females observed, it would result in 2.9 clutches per female. Therefore, sampling a fraction of the population will always require dealing with biases from transient turtles. Sometimes turtles are wrongly considered transient as a reflection of low detectability by beach monitoring (Pfaller et al. 2013). For example, in our study even with an intensive monitoring effort, nests were missed, as was evidenced by the haul-out from female ID 4* (see Tables S5 and S6). Tidal regime may play an important role on detectability, especially during high spring tides, as turtle tracks can be erased by waves. Indeed, the missed record A7 (Table S6) occurred during spring tide. In our study site, hawksbill turtles often (48%) nest below the highest spring tide line, as they crawl up the maximum possible path and come across a sand slope that is exposed to high spring tides (Santos et al. 2016). Thus, tidal regime is an important factor to consider when designing monitoring surveys and interpreting nesting information. Additionally, despite the fact that most hawksbills turtles nest at night, a few nests occur during the day (A. J. B. S. personal communication), hindering the individual’s detection, especially during spring tide periods. Strong winds and rain may also influence the detectability of marine turtle nests (Metcalfe et al. 2015).
Our results indicate that beach monitoring data combined with satellite telemetry information may fine tune clutch frequency estimation for marine turtles. However, it is important to consider that if the internesting habitat for hawksbill turtles is very close to the shoreline (e.g. less than 1 km), detecting nesting events through satellite telemetry will require tags with fine scale resolution, which are usually costly (Esteban et al. 2017). Thus it is suggested that residence length should be used as indicator of clutch frequency, such approach would allow for sample sizes to be higher through the use of lower resolution cheaper satellite tags. Our approach and suggestions although applied to hawksbill turtles nesting in Rio Grande do Norte, should be considered for other nesting locations in Brazil (e.g., Bahia, Piauí, Paraiba, Pernambuco, Alagoas and Sergipe states), which would allow for nesting numbers to be estimated for this endangered genetically discrete population.