Growth rate and projected age at sexual maturity for immature hawksbill turtles and green turtles foraging in the remote marine protected area of Aldabra Atoll

doi:10.21203/rs.3.rs-2214027/v1

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Research Article

Growth rate and projected age at sexual maturity for immature hawksbill turtles and green turtles foraging in the remote marine protected area of Aldabra Atoll

https://doi.org/10.21203/rs.3.rs-2214027/v1

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published 20 Mar, 2023

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Changes in marine ecosystems from human stressors, and concerns over how species will respond to these changes have emphasized the importance of understanding and monitoring crucial demographic parameters for population models. Long-lived, migratory, marine vertebrates such as sea turtles are particularly vulnerable to changes. Life-history parameters like growth in body size can be largely influenced by environmental processes which can impact population growth. We analyzed a 40-year (1981–2021) capture-mark-recapture dataset from the protected UNESCO World Heritage Site, Aldabra Atoll, Seychelles, to estimate key population parameters, including body growth, for immature green turtles (Chelonia mydas) and hawksbill turtles (Eretmochelys imbricata). Curved carapace length (CCL) ranged from 34.3–110.9 cm (mean ± SD: 51.0 ± 11.4 cm, n = 1191) for green turtles and 28.7–89.4 cm (47.7 ± 14.4 cm, n = 538) for hawksbill turtles. Recapture events, with an 11-month minimum period, revealed a mean annual growth rate of 3.2 ± 1.5 cm year-1 for green turtles (n = 75) and 2.8 ± 1.4 cm year-1 for hawksbill turtles (n = 110). Hawksbill turtles exhibited a non-monotonic growth rate while no significant growth-size relationship was detected for green turtles. Green turtle mean annual growth per 10-cm size class was highest in the larger size classes. Hawksbill turtle growth rate was highest in the larger size classes (50‒69.9 cm) then declined in the largest size class (80‒79.9 cm). Per the growth functions, green turtles and hawksbill turtles may spend > 8 and 18 years, respectively, using Aldabra as a foraging ground.

capture-mark-recapture

Chelonia mydas

Eretmochelys imbricata

Western Indian Ocean

developmental habitat

Demographic models for population viability analyses, often used for endangered species management, are only reliable if the underlying data for the relevant parameters (e.g. body growth, age structure, mortality and dispersal) are available and accurate (Beissinger and Westphal 1998). With significant changes currently taking place in marine ecosystems (e.g., Waycott et al. 2009; Pacoureau et al. 2021), including increasing temperatures and changes to climate systems (IPCC 2021); species long-term monitoring data are necessary for gauging and potentially mitigating changes in their populations (Magurran et al. 2010).

Population growth in long-lived species can be sensitive to changes in demographic parameters, such as survival and growth (Heppell 1998). Slow-growing, late-maturing marine vertebrates, like sea turtles, are of high conservation concern due to slow population recovery potential and high vulnerability to anthropogenic stressors (Hamann et al. 2010; Rees et al. 2016). Sea turtle growth rates have been described for various species and compared across regions (Balazs and Chaloupka 2004; Chaloupka et al. 2004; Avens et al. 2021), synthesized globally into meta-analytic frameworks (Ramirez et al. 2020a) and explored in relation to environmental changes (Bjorndal et al. 2013a, 2016, 2017). Several growth rate studies have shown site and regional variation (e.g., Chaloupka et al. 2004; Hawkes et al. 2014; Bjorndal et al. 2016, 2017).

Once sexual maturity is reached in sea turtles, energy allocated to growth shifts towards reproductive output (Green 1993; Bjorndal et al. 2013b) and can slow growth to negligible levels after several years (Omeyer et al. 2017, 2018). Understanding differences in growth rates and age at sexual maturity is essential to derive robust population models needed for management purposes, including assessing possible conservation actions (Casale and Heppell 2016; Piacenza et al. 2019).

The environment has a strong influence on growth and reproduction of ectothermic turtles. Variation between individual turtles and sites contributes to growth rates (e.g., Chaloupka et al. 2004; Bjorndal, Parsons et al. 2013), emphasizing the importance of collating demographics from various sites and regions. Additionally, population growth rates can be influenced by human modified environments such as power plants (Eguchi et al. 2012), though there is a lack of comparative life history parameters from sites with limited direct human impacts (Bellini et al. 2019). The South-West Indian Ocean (Wallace et al. 2010) Regional Management Units (RMU) host internationally important populations for both hawksbill turtles (Eretmochelys imbricata; Mortimer and Donnelly 2008) and green turtles (Chelonia mydas; Seminoff et al. 2015). While many populations are increasing in the South-West Indian Ocean (Allen et al. 2010; Mortimer et al. 2011, 2020; Pritchard et al. 2022), there is limited understanding of the relationship between growth rates and age at sexual maturity in the region besides glimpses into reencountered individuals (Mortimer et al. 2010; Sanchez et al. 2020). These life history parameters of in-water and immature populations have been flagged as a priority and are important for informing conservation management decisions (Wallace et al. 2010; Rees et al. 2016; Wildermann et al. 2018).

The Seychelles Aldabra Atoll in the South-West Indian Ocean, hosts one of the two largest nesting populations of green turtles in the region (Pritchard et al. 2022) and provides foraging habitat for immature hawksbill turtles and green turtles (Frazier 1971; Mortimer 1984). The aggregations of immature green turtles comprise mixed genetic stocks including those from the central South-West Indian Ocean (Tromelin, northern islands in the Mozambique Channel, and coastal Kenya and Mozambique) (Jensen et al. 2020; Sanchez et al. 2020). The hawksbill turtle foraging aggregations show migratory connections between the inner Seychelles/Amirantes and Chagos (Mortimer and Broderick 1999; Hamann et al. 2010; Mortimer et al. 2010; Phillips et al. 2014; Arantes et al. 2020); we use a large capture-mark-recapture dataset spanning 40 years from Aldabra to provide some of the first estimates of growth rates and age at sexual maturity for green turtles and hawksbill turtles in the South-West Indian Regional Management Unit. Specifically, we aim to investigate: (1) annual growth rates; (2) whether growth rates have changed over time; (3) how long turtles use Aldabra as a foraging ground; and (4) whether age at sexual maturity can be estimated for green turtles and hawksbill turtles with the long-term dataset.

Study Site

Aldabra Atoll is one of the remote outer island complexes of the Seychelles and is 470 km from Madagascar and 1120 km from Mahé island, the human population center of Seychelles. The atoll includes four main islands surrounding a protected shallow lagoon which covers 196 km² and is generally less than 8 m in depth with a tidal range of 2–3 m (Farrow and Brander 1971). The atoll exterior has fringing reefs with steep, seaward slopes. There are two trade wind seasons: the wetter and warmer northwest monsoon (Nov/ Dec–Mar) and the drier and cooler southeast (Apr–Nov). The atoll was inscribed as a UNESCO World Heritage Site in 1982, and only a small team of 10 to 20 staff managed by the Seychelles Islands Foundation currently live at the research station on Picard Island. Aldabra’s remoteness, harsh terrain, lack of freshwater, and large tidal changes, along with strict management have kept its marine ecosystems and processes significantly less disturbed than many other atolls worldwide (Friedlander et al. 2015). Green turtles have been protected from exploitation at Aldabra since 1969. Hawksbill turtles have been protected since 1979 for when it became illegal to take any turtles within protected areas (Mortimer 1984).

Data collection

In the present study, turtle captures from 1981 to 2022 occurred mostly in the lagoon and near the channels of Aldabra (Fig. 1), but tended to be concentrated on the western part of the atoll, near the research station. Sampling sessions were opportunistic and not standardized spatially or temporally. Turtles were either hand-captured by walking through tidal pools and partially exposed seagrass and macroalgae mats at low tide, or by jumping onto or next to individuals from a boat during high tide (i.e., ‘rodeo’ technique) (Eckert et al. 1999). For logistical reasons, captures by boat occurred in sandy areas of the lagoon near the research station, with several focal capture sites within this area (Fig. 1).

Sampling locations were determined by sea conditions and tide height. The first turtle sighted at the location was pursued until caught, or a new turtle followed if the first escaped capture. Once captured, turtles were tagged on the trailing edges of both front flippers (or existing tags recorded), following standard procedures (Balazs 1999). Monel (National Band & Tag Co. styles 681, 49) and plastic yellow Roto-tags (Dalton Supplies Ltd.) were used from the 1980s through mid-1990s, followed by Inconel tags (National Band & Tag Co. style 681) from the mid-1990s to present, with larger Titanium tags (Aust. ‘Turtle’/ Titanium Stockbrands) applied to larger turtles (> 15 kg before 2020, > 10 kg since 2020). Carapace measurements were recorded including minimum (CCLmin) and notch-to-tip (CCLn-t) (as defined by Bolten 1999), and both straight carapace (SCL) and curved carapace lengths (CCL) were taken.

In cases where CCLn-t measurements were not taken and CCLmin measurements existed for an individual, a CCLmin conversion factor was used to obtain the CCLn-t (cm), to maximize capture measurements (Table S1). All length measurement comparisons are reported in CCLn-t. Since measurements were taken by several observers across the decades, measurement error was calculated by comparing the consistency in repeat measurements on the same individuals that were collected within two weeks of each other (Braun-McNeill et al. 2008); mean measurement absolute error was calculated by taking the difference between measurements and calculating absolute mean. It was estimated as 0.52 ± 1.4 cm SD (-4.7–0.8 cm; n = 15).

Data analysis

Analyses were performed in RStudio Version 1.4.1106 and R 4.0.4 (R Core Team 2021). Generalized Additive Models (GAMs) were implemented with package ‘mgcv’ (Wood 2011). Thin plate regression splines and smoothness parameters were estimated by restricted maximum likelihood, REML (Wood 2011; Pedersen et al. 2019). To assess the K (the number of knots used in the fitted splines), the functions Gam.check and k.check were used in the mgcv package (Pedersen et al. 2019). GAMs and confidence intervals were plotted with LOESS smooths using R package ‘ggplot2’ (Wickham 2016). All data were inspected for normality with a Shapiro-Wilk test and non-parametric analyses were used when normality was not met.

Size distributions were estimated for first time captures only. Study day for each capture was defined as the number of days since the beginning of the growth dataset. Measurements resulting in negative growth, due to either measurement error or carapace damage, were included to avoid bias (Bjorndal et al. 2016, 2017).

To mute seasonal peaks or troughs related to condition and minimize growth measurement errors, a recapture dataset was created using a minimum interval of 11 months between captures (Bjorndal et al. 2017). If the period between recaptures was less than 11 months, the next chronological recapture was used. When available, multiple recapture intervals of the same individual were used. Annual growth rate was calculated as the change in CCL during the growth interval, divided by the number of years in the growth interval (Casale et al. 2009; Colman et al. 2015; Bjorndal et al. 2017; Bellini et al. 2019).

To assess if growth rate has changed over time, the 30–40 cm and 40–50 cm CCL size classes, for which sufficient samples sizes were available for a meaningful temporal comparison, were analyzed with year. Growth rate was investigated as a function of year (mean year was binned into years) and turtle ID was used as a random, independent variable to account for repeated measurements of the same individual and for individual-specific heterogeneity: gam(GR ~ s(year), random = list(id ~ 1), method = “REML”, family = gaussian) turning it into a generalized additive mixed model (GAMM). A Kruskal Wallis test with pairwise comparisons was used if the GAMM was significant.

We explored the relationship between age and size in three steps. First, the time spent by turtles at Aldabra was estimated. This was done by investigating growth rate through a GAMM as a function of the following continuous covariates: mean size, mean sampling year, and recapture interval (RI; in years). ID was used as a random, independent variable, as done when assessing growth rate over time (above). The equation was: gam(GR ~ s(CCL) + s(year) + s(RI), random = list(id ~ 1), method = “REML”, family = Gaussian; see also Casale et al. 2009; Colman et al. 2015; Bellini et al. 2019). GAMMs were run separately for the two species. Size specific predictions of the growth rate function were extracted (with 95% confidence intervals) for each capture-mark-recapture (CMR) record, ordered by ascending CCL values. (i.e., the first and last records are the smaller and larger turtles, respectively).

Since it is unknown how old turtles were before recruiting to Aldabra as a foraging ground, we estimated the age of turtles, since recruitment, with year 0 associated with the smallest median size for each species in the data. The integration equation, y(CCL_i) = y(CCL_i−1) + (CCL_i – CCL_i−1)/ r(CCL_i), was used, where: y(CCL_i) represents the age at the initial mean size, y(CCL_i−1) is the age of the previous recorded mean size, and r(CCL_i) is the individual annual growth rate (Colman et al. 2015; Bellini et al. 2019). The integration was also performed to obtain confidence intervals from the GAMMs. The smallest median size for each species was used as the starting CCL_i−1. The last predicted value represented the time spent at Aldabra.

Second, the age of turtles at Aldabra was estimated by adding the estimated time spent at Aldabra (calculated above) to the age of recruitment, which was unknown. To estimate the age of turtles when they first recruit to Aldabra, we compiled figures from the literature. For green turtles, recruitment to neritic habitat has been considered 2–7 years for 30–40 cm CCL (Brazil; Lenz et al. 2017) or 6–9 years for 35–47 cm CCL (south Great Barrier Reef; Limpus and Chaloupka 1997). Using skeletochronology and straight carapace length (SCL), it was estimated as 5–6 years in Hawaii (Zug et al. 2002), 3–6 years in Florida (Zug and Glor 1998) and 1–7 years on the US east coast (Goshe et al. 2010). For hawksbill turtles, recruitment was estimated at 4.5–5.5 years for 33.5 cm SCL in Ascension (Putman et al. 2014; Weber et al. 2017), 1–3 years for 20–25 cm SCL in the Virgin Islands (Boulon Jr 1994), or 2–4 years with SCL by skeletochronology in Hawaii (Snover et al. 2013). Ranges of 2–8 years and 2–5 years were used as the age of recruitment (to be associated with the smallest captured sizes per species) to Aldabra for green turtles and hawksbill turtles, respectively, in this study.

To attempt an age at sexual maturity, we estimated the time needed to grow from the largest observed size class in our dataset to the mean adult nesting size. Published adult growth rates in peer-reviewed literature from Aldabra (for green turtles) and rookeries in the Seychelles (for hawksbill turtles) were used in the model to estimate age at sexual maturity. For green turtles, we used the mean nesting size (108.9 cm CCLn-t) on Aldabra from 1995–2016 (n = 4635; SIF unpubl. data, same dataset from Mortimer et al. 2022, and a female adult growth rate of 0.14 cm year-1 from Aldabra nesters (Mortimer et al. 2022) in the model. For hawksbill turtles, we used the mean nesting size (86.4 cm CCLn-t) from Cousine Island, Seychelles (Gane et al. 2020), and an adult growth rate of 0.17 cm year-1 for females > 80 cm CCL (Coral Sea, Queensland, Australia; Bell and Pike 2012).

A size-specific growth rate function for Aldabra with the addition of the adult growth rate was derived through GAMMs with the model: gam(GR ~ s(CCL), random = list(id ~ 1), method = “REML”, family = gaussian). The GAMM-predicted growth rates were then run through an integration equation (Colman et al. 2015, Bellini et al. 2019) from the largest size observed per species to the mean adult nesting size. Due to a gap in body length measurements between the largest immature captures in the Aldabra dataset and the mean nesting size, the equation was modified; growth rates from the GAMM were predicted at intervals of 1-cm CCL instead of by the mean CCL. The integration equation was applied to a size range of 67–109 cm CCL for green turtles and 73–87 cm CCL for hawksbill turtles. The adult growth rate (as above) was conservatively assumed to be the minimum growth and any estimated growth rates with values lower than the adult growth rate (only applicable for hawksbill turtles in the 84–86 cm CCL range) were substituted with the adult growth rate. An estimate of age of sexual maturity was calculated by adding this time (from the largest size in the dataset to the mean nesting size) to the estimated age at the largest size in the dataset.

Capture frequency, size distribution and annual growth

From July 1981 to March 2021, there were 494 capture sessions and 2287 turtle captures (Fig. S1). For first time captures, curved carapace length notch-to-tip (CCLn-t) for green turtles ranged 34.3–110.9 cm (mean ± SD: 51.0 ± 11.4 cm, median 46.8 cm, n = 1191), and hawksbill turtles ranged 28.7–89.4 cm (mean ± SD: 47.7 ± 14.4 cm, median 43.6 cm, n = 538) (Fig. 2; Table S2, Fig. S2). The ratio of overall recaptures to total captures was 16.8% (242/1439) and 35.6% (302/848) for green turtles and hawksbill turtles, respectively. Recaptured individuals were caught 2–10 times; 91% and 80% of recaptured individual green turtles and hawksbill turtles (not including individuals only captured once) were caught two or three times (Table S3).

There were 544 total recapture events, including multiple recaptures of the same individual. The growth dataset consisted of 411 green turtle and 451 hawksbill turtle recapture events from 174 and 167 individual green turtles and hawksbill turtles, respectively. However, applying the 11-month minimum interval between recaptures, this dataset decreased to 185 recapture events (Table 1), with recapture interval ranges of 0.9–5.6 years for green turtles (n = 75) and 0.9–10.4 years for hawksbill turtles (n = 110). Mean overall annual growth rate was 3.2 ± 1.5 cm year-1 for green turtles and 2.8 ± 1.4 cm year-1 for hawksbill turtles (Table 1). When split into 10-cm size classes, higher growth rates were seen in the larger (40–70 cm CCL) size classes in both species, but decreased in the largest hawksbill turtle size class (Table 1).

Table 1

Number of recapture growth intervals per 10 cm CCLn-t (curved carapace length notch-to-tip) size class based off the mean CCL. There can be multiple growth rates from the same individual. RI = recapture interval. Figures in brackets represent the median and range, except in the column of n, where it represents the count of individual turtles.
	Green turtles			Hawksbill turtles
Year range	1996–2019			1987–2018
RI (years)	1.9 ± 1.2 (1.5; 0.9–5.6)			2.0 ± 1.5 (1.5; 0.9–10.4)
Size class (cm)	n	CCLn-t (cm) mean ± SD	Growth rate (cm year-1) mean ± SD	n	CCLn-t (cm) mean ± SD	Growth rate (cm year-1) mean ± SD
30–39.9	4	38.6 ± 1.0	2.1 ± 1.3	25	37 ± 2.2	1.6 ± 1.1
40–49.9	48	45.2 ± 2.6	3.0 ± 2.0	48	44.6 ± 2.5	2.9 ± 1.1
50–59.9	19	53.2 ± 2.5	3.7 ± 1.1	29	54.4 ± 3.0	3.6 ± 1.5
60–69.9	4	65 ± 3.3	3.6 ± 0.5	5	64.1 ± 3.4	3.5 ± 1.0
70–79.9	-	-	-	3	71.8 ± 1.6	0.7 ± 1.1
All size classes	75 (68)	48.0 ± 6.3 (46.6; 37.2–68.0)	3.2 ± 1.5 (3.2; 0.4–9.8)	110 (83)	47.1 ± 8.7 (45.5; 32.3–73.2)	2.8 ± 1.4 (2.8; -0.5–5.9)

Growth rate change with time and size

No significant difference was found in mean growth rate between the two size classes (30–40 cm and 40–50 cm CCL) for green turtles (Wilcoxon rank sum exact test, W = 334, N1 = 48, N2 = 19, P = 0.091) therefore both size classes were combined to estimate the growth rate over time. The GAM results suggested no significant change in growth rate over time (F = 0.46, edf = 1.5, p = 0.64, n = 67; Fig. S3).

A significant difference in growth rate was found between the 30–40 cm (1.6 ± 1.1 cm year-1, n = 25) and 40–50 cm CCL (2.9 ± 1.1 cm year-1, n = 48; Table 1) size classes for hawksbill turtles (Wilcoxon rank sum exact test, W = 471, p = 0.018). Therefore, only the 40–50 cm size class was used to assess changes in growth rate over time. The GAMM results for hawksbill turtle growth rates suggested a significant year effect (F = 2.86, edf = 3.3, p = 0.046, n = 48; Fig. S3) but no significance for year was found in the pairwise comparison.

Size-at-age

For green turtles, mean size, mean sampling year, and recapture interval did not significantly affect growth estimates (Fig. 3). These variables, however, only captured 7.0% of the variance in the GAMM model, which suggests a substantial amount of growth variability is not being explained by the covariates (Table S4, Fig. S4, S5). For hawksbill turtles, mean size (F = 11.28, edf = 3.66, p < 2e-16) and mean year significantly influenced growth (F = 5.55, edf = 4.1, p < 1.37e-4; Fig. 3). In this case, these predictor variables captured 48.2% of the variance in the model, suggesting that nearly half the variance in growth data is attributed to mean size and mean year (Table S5; Fig. S6, S7). Hawksbill turtles showed non-monotonic growth (growth rates increased while size increased, then decreased at a larger size) (Fig. 3).

Using minimum and maximum turtle sizes within the dataset to estimate the amount of time turtles are using Aldabra as a foraging ground (Table 1), the size-at-age growth function for green turtles estimated a 37.2 cm CCL turtle (size since recruitment) to take 8.9 years (6.9–13.1, 95% CI) to reach 67.0 cm (Fig. 3). Adding the estimated interval between hatching from its egg and recruiting from pelagic to benthic foraging habitat for green turtles (2–8 years), a 67 cm green turtle would be 10.9–16.9 years old. The size-age growth function for hawksbill turtles estimated that a 32.3 cm CCL turtle (typical size at recruitment to benthic foraging habitat) to take 18.8 years (95% CI: 13.2–30.2) to reach 73 cm. Adding the estimated recruitment interval for hawksbill turtles (2–5 years), a 73 cm hawksbill turtle would be 20.8–23.8 years old. The CCL range for captured hawksbill turtles included the smallest nesting female on Cousine, Seychelles (67 cm CCL; Gane et al. 2020).

Age at sexual maturity

For green turtles, the function derived from the GAMM (F = 2.0, edf = 2.1, p = 0.1, n = 76 ; Fig. S8) using the modified integration equation predicted 19 years to grow from 67 to 108 cm CCL (Fig. S9). For hawksbill turtles, the function derived from the GAMM (F = 9.9, edf = 3.7, p < 2.6e-7, n = 111; Fig. S10) using the modified integration equation predicted 28.9 years to grow from 73 to 86 cm CCL, respectively (Fig. S11). Adding the time to reach the largest size in the dataset calculated in the previous section, including the recruitment intervals, a 108 cm CCL green turtle would be 29.9–35.9 years old. Using our non-monotonic growth curve, a sexually mature 86 cm hawksbill turtle would be 49.7‒52.7 years old, if it had spent its entire post-pelagic growth period at Aldabra.

Our study provides the first growth rates of immature turtles and estimated age at sexual maturity for green turtles and hawksbill turtles in the Western Indian Ocean based on a long-term mark-recapture data set and using modern statistical techniques of growth rate analysis. This information improves current regional knowledge about these species, which can contribute towards improved population models to inform their conservation decisions.

Growth rates

Green turtle non-monotonic growth has been reported for the Pacific (Limpus and Chaloupka 1997; Seminoff et al. 2002; Balazs and Chaloupka 2004; Eguchi et al. 2012; Bell et al. 2019) and a few sites in the Atlantic (Kubis et al. 2009; Colman et al. 2015); decreasing, monotonic growth has been more characteristic of the Caribbean (Bjorndal et al. 2000; Patrício et al. 2014). The green turtle growth spurts in this study, occurring in the larger size classes, were similar to those in the Pacific: growth spurt ca. 60–75 cm CCL with differences between the populations and sexes (south Great Barrier Reef; Limpus and Chaloupka 1997; Balazs and Chaloupka 2004); growth spurts ca. 65 cm SCL at Midway Atoll and in the south-eastern Hawaiian archipelago ca. 50–53 cm SCL (Balazs and Chaloupka 2004); ca. 50–55 cm SCL in south California (Eguchi et al. 2012). There are also a few aggregations in the Atlantic with a similar growth spurt (50–60 cm CCL, Brazil; Colman et al. 2015; ca. 60 cm SCL, Florida; Kubis et al. 2009) (Table S7).

Monotonic (Bjorndal and Bolten 2010; Hawkes et al. 2014) and non-monotonic growth (Chaloupka and Limpus 1997; Krueger et al. 2011; Snover et al. 2013) has been recorded for hawksbill turtles. The non-monotonic growth of hawksbill turtles in this study had growth spurts in the larger size classes (50–59 and 60–69 cm). Similar growth spurts at 60 cm CCL have been recorded in the south Great Barrier Reef (Chaloupka and Limpus 1997) (Table S8).

There are several possible ecological factors that can affect growth rates and can explain the observed patterns. The smallest size classes are possibly new recruits shifting from pelagic to neritic foraging habitat; sea turtles are likely encountering lower, oceanic nutrition during their pelagic phase (Bolten 2003). The spike in growth rates seen in the smaller size classes elsewhere for these species is proposed to be a period of compensatory growth, after adjusting to the neritic habitat, thereby causing a spike in growth in the smaller size classes (Bjorndal and Bolten 2010; Bjorndal et al. 2016). Conversely, a growth spurt is being seen in the larger size classes on Aldabra.

Quality and abundance of food can also contribute to growth rate differences. Green turtles grow faster when foraging on seagrass compared to those foraging on mixed diets (seagrass, algae and omnivorous diets) (Bjorndal et al. 2017) and diet can vary greatly between regions and foraging aggregations, to which temperature has recently been linked (Esteban et al. 2020). Differences in growth rates between three ecologically different juvenile green turtle foraging grounds along the central Florida coast were attributed mostly to habitat type and turtle density (Kubis et al. 2009). Similar conclusions were made for differences seen in hawksbill turtle aggregations in Puerto Rico (Diez and Van Dam 2002). There may also be species-specific differences (Colman et al. 2015; Bellini et al. 2019) as a result of food availability for mostly herbivorous versus mostly spongivorous species (Krueger et al. 2011). The growth spurt pattern for hawksbill turtles and green turtles seen at Aldabra was similar to the pattern seen in the same two species in the south Great Barrier Reef (Chaloupka and Limpus 1997; Limpus and Chaloupka 1997; Chaloupka et al. 2004). The foraging habits of both species at Aldabra have not been studied; for an atoll whose ecosystems experience significantly less direct human impact than many other places, and with the turtle nesting population not yet thought to be at carrying capacity nor near historic levels (e.g., green turtles see Pritchard et al. 2022). Further conclusions cannot be made until the ecology of each species is better understood at the atoll.

Climatic events have been tied to growth, where ecological regime shifts occurring after 1997 have been suggested as a driver for sea turtle growth declines in the West Atlantic (Bjorndal et al. 2013a, 2016, 2017). These trends were not seen in Australia and Hawaii for green turtles (Balazs and Chaloupka 2004; Chaloupka et al. 2004) or in the North Atlantic for Kemp’s ridley turtles (Avens et al. 2020; Ramirez et al. 2020b). Year was a significant covariate on hawksbill turtle growth rate for the current study, when looking at only the 40–50 cm size class with 1997 and 2001 nearly significant (slight increase in growth rate those years). The Aldabra growth rate dataset is small and should be cautiously interpreted, but these years are around the same time (yet opposite direction) that growth rates were seen decreasing in the Atlantic basin (Bjorndal et al. 2013a, 2016, 2017). The Indian Ocean is not exempt from extreme weather and regime shifts. In the 1997/98 global reef bleaching event, Seychelles’ reefs were negatively affected (Spencer et al. 2000), which was an effect of the same El Niño-Southern Oscillation that is negatively associated with Atlantic hawksbill turtle and green turtle growth rates (Bjorndal et al. 2016, 2017).

The global bleaching event in 1998 caused up to 66% hard coral mortality at Aldabra (Spencer et al. 2000). The 2015/16 global bleaching event also caused high coral mortalities on Aldabra, shifting sections of reef to an algae dominated benthic community (Cerutti et al. 2020). Aldabra reefs showed high recovery, with the lagoon having the highest resilience (Koester et al. 2020). There is a predicted and expected increase in bleaching events in the future (Van Hooidonk et al. 2014). The predicted intervals in between these bleaching events may become too short for even Aldabra’s reef to recover (Koester et al. 2020), which will have an effect on sea turtle habitats and food item availability. This is not specific to Aldabra but will be globally felt. This emphasizes a need to understand how the current habitats are able to support these sea turtle species and how they may change with predicted climate changes.

There are other factors that potentially contribute to growth variation that were not assessed in this study, including not being able to take into account differences between the sexes (e.g., Chaloupka et al. 2004; Goshe et al. 2010) and density effects (Bjorndal et al. 2000; Kubis et al. 2009). Long recapture intervals can affect the assumption of linear growth between captures (Casale et al. 2009; Bjorndal et al. 2017; Bellini et al. 2019), which was not accounted for with maximum intervals. There was also a lack of or small sample size of the larger and smallest size classes which can influence the results if not representative. The measurements were taken by multiple people over the years, possibly introducing larger measurement bias. Although the sample size (n = 15) was small, the measurement error (0.52 cm) was also small and not expected to have significantly influenced the growth rates.

Age at sexual maturity

Our predicted green turtle age at maturity of > 30 years, when considering the large confidence intervals, is similar to that of other regions (Table 2), including different areas in the Pacific (Limpus and Chaloupka 1997; Balazs and Chaloupka 2004; Van Houtan et al. 2014) and the northwest Atlantic (Goshe et al. 2010). The Caribbean stands out with lower estimates, generally with predictions of < 25 years (Frazer and Ladner 1986; Bell et al. 2005; Patrício et al. 2014).

Our predicted hawksbill age to sexual maturity (~ 50 years) at Aldabra should be regarded with caution because of the limited data available in the larger size classes (resulting in large confidence intervals). Moreover, it assumes that hawksbills spend their entire post-pelagic growth period residing at Aldabra, when in fact, there is evidence that immature turtles may actually reside at a succession of geographically separated developmental habitats as they grow from post-pelagic to adult size (Carr et al. 1978; Meylan et al. 2011). Empirical evidence for that theory can be found in two recapture events within the Western Indian Ocean indicating faster growth in the larger subadult size classes of the animals involved than what we have documented on the foraging habitat at Aldabra.

One is a hawksbill first intercepted in the Aldabra lagoon at 57.2 cm CCL in 1996, that was found 13 years later nesting at Desroches (Seychelles) at 86.2 cm CCL, having grown at a minimum rate of 2.2 cm year-1 between the two interceptions. (Mortimer et al. 2010). The other is a 67.8 cm CCL hawksbill turtle first intercepted at Cocos Keeling (South-East Indian Ocean) in 2005 and found 12 years later nesting at Fregate Island (Seychelles) at 94 cm CCL. It also grew at a minimum rate of 2.2 cm year-1 between the two interceptions (van de Crommenacker et al. 2022).

Satellite tracking of post-nesting adult female hawksbills from both Cousin Island, Seychelles (Mortimer and Balazs 2000) and Diego Garcia, Chagos (Hays et al. 2022b) demonstrated their adult foraging habitat to comprise relatively deep-water sites located far from shallow coastal habitats. More data are needed to know both the locations of subadult hawksbill foraging grounds to see if they also occur in these deep-water sites away from coastal habitats, and also characteristics of the forage available to larger turtles at such sites.

In contrast, approximately 40% of post-nesting adult female green turtles satellite tracked from Diego Garcia, Chagos (Hays et al. 2014, 2022b) in the Western Indian Ocean, travelled to adult foraging sites in Seychelles, including near-shore, shallow-water seagrass habitats (Stokes et al. 2019). These data complement the findings of the present study that shallow-water seagrass habitats similar to those at Aldabra provide adequate forage to support aggregations of larger sized green turtles.

Table 2

Age at sexual maturity (ASM) estimates, in years, from published literature. Studies differ in sample sizes, methods, and measurements used. CMR = capture mark recapture, Sk = skeletochronology, sGBR = southern Great Barrier Reef, nGBR = northern Great Barrier Reef, WIO = Western Indian Ocean.
ASM predictions (years)	Ocean basin	Location	Method	Reference
Green turtles
12–26	Caribbean	Costa Rica	CMR	Frazer and Ladner 1986
14–22	Caribbean	Puerto Rico	CMR	Patrício et al. 2014
15–19	Caribbean	Grand Cayman	CMR	Bell et al. 2005
17–33	Atlantic	Ascension Is	CMR	Frazer and Ladner 1986
23	Pacific	Hawaii	CMR	Van Houtan et al. 2014
24–36	Atlantic	Suriname	CMR	Frazer and Ladner 1986
25–35	Atlantic	Florida	CMR	Mendonça 1981; Frazer and Ehrhart 1985
25–50	Pacific	sGBR	CMR	Chaloupka et al. 2004
> 30	Atlantic	Brazil	CMR	Colman et al. 2015
> 30	WIO	Aldabra	CMR	This study
35–40, > 50	Pacific	Hawaii	CMR	Balazs and Chaloupka 2004
> 40	Atlantic	Florida, Costa Rica, Mexico	Sk	Goshe et al. 2010
> 40	Pacific	sGBR	CMR	Limpus and Chaloupka 1997
> 40	Pacific	Hawaii	Sk	Van Houtan et al. 2014
> 90	Pacific	Galapagos	CMR	Green 1993; Zárate et al. 2015
Hawksbill turtles
< 10	Caribbean	Anegada	CMR	Hawkes et al. 2014
14–24	Caribbean	Antigua	Genetics/ CMR	Levasseur et al. 2021
14–18	Atlantic	Brazil	CMR	Bellini et al. 2019
15–25	W Atlantic	W Atlantic	Sk	Avens et al. 2021
17–22	Pacific	Hawaii	Sk	Snover et al. 2013
> 20	Caribbean	St. Thomas	CMR	Boulon Jr 1994
20–40	Pacific	nGBR	CMR	Bell and Pike 2012
> 30	Pacific	sGBR	CMR	Chaloupka and Limpus 1997
> 50	WIO	Aldabra	CMR	This study

In wild populations, older age at maturity may impact intrinsic population growth which has implications for population trend analyses (Congdon et al. 1993). Other factors, however, also influence fecundity. Post-maturity growth rates appear to be minimal, but turtles continue to reproduce for decades thereafter (e.g., Omeyer et al. 2017; 2018). Larger females produce more eggs in a clutch (Bjorndal and Carr 1989), and larger females in captivity are known to have shorter inter-breeding intervals (Bjorndal et al. 2013b). In wild populations, a younger age at sexual maturity could be beneficial (i.e., potentially enabling quicker population recovery) but prove difficult to interpret since age at sexual maturity estimates are not yet refined enough for high confidence, and additionally many turtle populations do not have estimates. Moreover, turtles reaching sexual maturity at a smaller size may not necessarily also be reaching maturity at a younger age if they are growing more slowly. Rather they may simply be growing slower and reaching adulthood at the same age, but at a smaller size. Aldabra nesting green turtles have seen a significant decline in mean carapace length from 1996 to 2016 (Mortimer et al. 2022), possibly due to an increase in relative numbers of new nesters (Hays et al. 2022a) leading to an age structure shift (Piacenza et al. 2016) at the same time that nesting numbers have increased (Pritchard et al. 2022). Mortimer et al. (2022) do not rule out that Aldabra females may also be attaining maturity at relatively smaller sizes. Assessing growth rates in immature turtles and whether they change over time (Bjorndal et al. 2013a, 2016, 2017) will give a better understanding of whether shifts in growth are occurring and whether they are driven by changes in immature growth rates.

The large increases in Aldabra nesting green turtles and Seychelles nesting hawksbill turtle populations (Allen et al. 2010; Gane et al. 2020; Pritchard et al. 2022) indicate that populations of both species at protected sites in the Seychelles are having a strong recovery. Green turtles were protected at Aldabra in the late 1960s, therefore according to our models, the first protected cohort would have begun breeding around 2000, and reproductive output on Aldabra has increased 173% in number of clutches (using 5-season averages from 1980‒1985 to 2014‒2019) with an overall nesting population growth rate of 2.6% per year (Pritchard et al. 2022). Prior to 1994 when national legislation was implemented that protected all hawksbill turtles in Seychelles, they were only protected in nature reserves such as Cousin Island which showed an 8-fold increase in nesting females between 1970 and 2009 (Allen et al. 2010).

Results of this study contribute towards a better understanding of growth rates and age at sexual maturity for turtles in the Western Indian Ocean Regional Management Unit (Wallace et al. 2010). There is a great need for growth rate information to strengthen population models, particularly in Regional Management Units that are data deficient (Wildermann et al. 2018; Ramirez et al. 2020a).

Recommendations

The growth patterns and age at sexual maturity estimates in Aldabra and the wider South-West Indian Ocean (SWIO) could be improved through further investigations and improved datasets. We recommend to (i) increase the sample size on all size classes, with a focus on increasing measurements at the smallest and largest size classes; (ii) reduce measurement errors by taking multiple measurements at the same encounter (e.g., Hawkes et al. 2014); (iii) obtain further information on fine-scale movement and habitat use (by tracking individuals) including use of the lagoon and surrounding reefs; (iv) improve models by investigating foraging ecology and resource availability with increasing body size; (v) determine the locations of foraging grounds of sub-adult and adult hawksbill turtles, and assess their foraging habitat and prey availability at those sites, to determine how food availability may differ from that at habitat utilized predominantly by immature hawksbill turtles < 65 cm CCL; (vi) investigate density dependence and carrying capacity through population estimates and habitat availability; (vii) improve understanding of when and where (and at what size) animals are recruiting in and out of the foraging population, together with improved knowledge of genetic connectivity; (viii) assess long term growth trends of adult green turtles nesting at the atoll.

There is a need for comparative growth datasets in the SWIO to determine if non-monotonic growth is common to the region or if it is unique to Aldabra and to pool the data together to improve the models. The attempts to estimate age at sexual maturity in this study should be improved through further growth measurements, by addressing the limitations identified in the growth rate dataset, as well as by exploring age at sexual maturity at other sites in the region. Comparisons among studies are challenged by different methods for relating growth and size (e.g., using initial size verses mean size, straight carapace length verses CCL; minimum and maximum recapture interval requirements; capture mark recapture, skeletochronology, von Bertalanffy, etc.) and dataset sizes can pose a limitation.

Aldabra, and the growth rates estimated there, may represent a valuable benchmark for measuring climate change effects. Effective on-site protection there along with its remote location has kept the marine ecosystems free of commercial fishing pressure for > 40 years and limited the inputs of human nutrients and most other pollutants. These marine ecosystems contain high biodiversity, including predatory sharks (Friedlander et al. 2015), and could provide a reference with which to compare areas that experience greater direct human impacts that could affect sea turtle growth (e.g., Eguchi et al. 2012; Long et al. 2021). We recommend continued and expanded monitoring efforts of the recovering turtle population at this valuable reference site.

ETHICAL STANDARDS

All data collection was undertaken by or through the Seychelles Islands Foundation, the managing body of Aldabra Atoll UNESCO World Heritage Site with standardized protocols based on international best practice. No turtles were killed or injured during data collection for this study.

ACKNOWLEDGMENTS

We are extremely grateful to all the Seychelles Islands Foundation staff for maintaining this long-term monitoring program on the logistically challenging Aldabra Atoll. We are especially thankful for the numerous people who assisted in collecting the data, including the conservation managers/ research officers, island managers/wardens, researchers and the very skillful skippers over the last 40 years.

Funding

Seychelles Islands Foundation has collected and provided all data for the study and provided logistical support for CLS.

Competing interests

There are no known conflicts of interest.

Authors contributions

CLS: Conceptualization, Data Curation, Methodology, Investigation, Formal analysis, Writing- Original Draft. JAM: Design of field study and project supervision between 1981-2008. PC: Conceptualization, Methodology, Supervision, Writing- Review & Editing. NB: Administration, Conceptualization, Supervision, Writing- Review & Editing. FFD: Administration, Supervision, Writing- Review & Editing. JAM, LA, MB, RvB, AJB, LC, JvdC, JCC, ND, EM, BM: Investigation, Data Curation, Writing: Review & Editing.

Data availability

The datasets analyzed from the current study are available from the corresponding author upon reasonable request.

Allen Z, Shah N, Grant A, Derand G, Bell D (2010) Hawksbill turtle monitoring in Cousin Island Special Reserve, Seychelles: an eight-fold increase in annual nesting numbers. Endanger Species Res 11:195–200. https://doi.org/10.3354/esr00281
Arantes LS, Vargas SM, Santos FR (2020) Global phylogeography of the critically endangered hawksbill turtle (Eretmochelys imbricata). Genet Mol Biol 43:1–12. https://doi.org/10.1590/1678-4685-GMB-2019-0264
Avens L, Ramirez MD, Hall AG, Snover ML, Haas HL, Godfrey MH, Goshe LR, Cook M, Heppell SS (2020) Regional differences in Kemp’s ridley sea turtle growth trajectories and expected age at maturation. Mar Ecol Prog Ser 654:143–161. https://doi.org/10.3354/meps13507
Avens L, Ramirez M, Goshe L, Clark J, Meylan A, Teas W, Shaver D, Godfrey M, Howell L (2021) Hawksbill sea turtle life-stage durations, somatic growth patterns, and age at maturation. Endanger Species Res 45:127–145. https://doi.org/10.3354/esr01123
Balazs GH (1999) Factors to consider in the tagging of sea turtles. In: Eckert KL, Bjorndal KA, Abreu-Grobois A, Donnelly M (eds) Research and management techniques for the conservation of sea turtles. IUCN/SSC Marine Turtle Specialist Group, Washington, pp 101–109
Balazs GH, Chaloupka M (2004) Spatial and temporal variability in somatic growth of green sea turtles (Chelonia mydas) resident in the Hawaiian Archipelago. Mar Biol 145:1043–1059. https://doi.org/10.1007/s00227-004-1387-6
Beissinger SR, Westphal MI (1998) On the use of demographic models of population viability in endangered species management. J Wildl Manage 62:821. https://doi.org/10.2307/3802534
Bell CDL, Parsons J, Austin TJ, Broderick AC, Ebanks-Petrie G, Godley BJ (2005) Some of them came home: the Cayman turtle farm headstarting project for the green turtle Chelonia mydas. Oryx 39:137–148. https://doi.org/10.1017/S0030605305000372
Bell I, Pike D (2012) Somatic growth rates of hawksbill turtles Eretmochelys imbricata in a northern Great Barrier Reef foraging area. Mar Ecol Prog Ser 446:275–283. https://doi.org/10.3354/meps09481
Bell IP, Meager J, van de Merwe JP, Madden Hof CA (2019) Green turtle (Chelonia mydas) population demographics at three chemically distinct foraging areas in the northern Great Barrier Reef. Sci Total Environ 652:1040–1050. https://doi.org/10.1016/j.scitotenv.2018.10.150
Bellini C, Santos A, Patrício A, Bortolon L, Godley B, Marcovaldi M, Tilley D, Colman L (2019) Distribution and growth rates of immature hawksbill turtles Eretmochelys imbricata in Fernando de Noronha, Brazil. Endanger Species Res 40:41–52. https://doi.org/10.3354/esr00979
Bjorndal KA, Bolten AB (2010) Hawksbill sea turtles in seagrass pastures: success in a peripheral habitat. Mar Biol 157:135–145. https://doi.org/10.1007/s00227-009-1304-0
Bjorndal KA, Carr A (1989) Variation in clutch size and egg size in the green turtle nesting population at Tortuguero, Costa Rica. Herpetologica 45:181–189
Bjorndal KA, Bolten AB, Chaloupka MY (2000) Green turtle somatic growth model: evidence for density dependence. Ecol Appl 10:269–282. https://doi.org/10.1890/1051-0761(2000)010[0269:GTSGME]2.0.CO;2
Bjorndal KA, Schroeder BA, Foley AM, Witherington BE, Bresette M, Clark D, Herren RM, Arendt MD, Schmid JR, Meylan AB, Meylan PA, Provancha JA, Hart KM, Lamont MM, Carthy RR, Bolten AB (2013a) Temporal, spatial, and body size effects on growth rates of loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic. Mar Biol 160:2711–2721. https://doi.org/10.1007/s00227-013-2264-y
Bjorndal KA, Parsons J, Mustin W, Bolten AB (2013b) Threshold to maturity in a long-lived reptile: interactions of age, size, and growth. Mar Biol 160:607–616. https://doi.org/10.1007/s00227-012-2116-1
Bjorndal KA, Chaloupka M, Saba VS, Diez CE, van Dam RP, Krueger BH, Horrocks JA, Santos AJB, Bellini C, Marcovaldi MAG, Nava M, Willis S, Godley BJ, Gore S, Hawkes LA, McGowan A, Witt MJ, Stringell TB, Sanghera A, Richardson PB, Broderick AC, Phillips Q, Calosso MC, Claydon JAB, Blumenthal J, Moncada F, Nodarse G, Medina Y, Dunbar SG, Wood LD, Lagueux CJ, Campbell CL, Meylan AB, Meylan PA, Perez VRB, Coleman RA, Strindberg S, Guzmán-H V, Hart KM, Cherkiss MS, Hillis-Starr Z, Lundgren IF, Boulon RH Jr, Connett S, Outerbridge ME, Bolten AB (2016) Somatic growth dynamics of West Atlantic hawksbill sea turtles: a spatio-temporal perspective. Ecosphere 7:1–14. https://doi.org/10.1002/ecs2.1279
Bjorndal KA, Bolten AB, Chaloupka M, Saba VS, Bellini C, Marcovaldi MAG, Santos AJB, Bortolon LFW, Meylan AB, Meylan PA, Gray J, Hardy R, Brost B, Bresette M, Gorham JC, Connett S, Crouchley BVS, Dawson M, Hayes D, Diez CE, van Dam RP, Willis S, Nava M, Hart KM, Cherkiss MS, Crowder AG, Pollock C, Hillis-Starr Z, Muñoz Tenería FA, Herrera-Pavón R, Labrada-Martagón V, Lorences A, Negrete-Philippe A, Lamont MM, Foley AM, Bailey R, Carthy RR, Scarpino R, McMichael E, Provancha JA, Brooks A, Jardim A, Lopez-Mendilaharsu M, González-Paredes D, Estrades A, Fallabrino A, Martinez-Souza G, Velez-Rubio GM, Boulon RH Jr, Collazo JA, Wershoven R, Guzmán Hernández V, Stringell TB, Sanghera A, Richardson PB, Broderick AC, Phillips Q, Calosso M, Claydon JAB, Metz TL, Gordon AL, Landry AM Jr, Shaver DJ, Blumenthal J, Collyer L, Godley BJ, McGowan A, Witt MJ, Campbell CL, Lagueux CJ, Bethel TL, Kenyon L (2017) Ecological regime shift drives declining growth rates of sea turtles throughout the West Atlantic. Glob Chang Biol 23:4556–4568. https://doi.org/10.1111/gcb.13712
Bolten AB, Eckert KL, Bjorndal KA, Abreu-Grobois FA (1999) M Donnelly Res Manag Tech Conserv Sea Turtles IUCN/SSC Mar Turt Spec Gr Publ No 4 1–5
Bolten AB (2003) Life history patterns of sea turtles: consequences of an oceanic juvenile stage. In: Lutz PL, Musick J, Wyneken J (eds) The biology of sea turtles. CRC Press, Boca Raton, FL, pp 243–257
Boulon RH (1994) Growth rates of wild juvenile hawksbill turtles, Eretmochelys imbricata, in St. Thomas, United States Virgin Islands. Copeia 1994:811–814. https://doi.org/10.2307/1447200
Braun-McNeill J, Epperly S, Avens L, Snover M, Taylor J (2008) Growth rates of loggerhead sea turtles (Caretta caretta) from the western North Atlantic. Herpetol Conserv Biol 3:273–281
Carr A, Carr MH, Meylan AB(1978) The ecology and migrations of sea turtles. 7, The West Caribbean green turtle colony.Bull. Am. Museum Nat. Hist.162
Casale P, Heppell SS (2016) How much sea turtle bycatch is too much? A stationary age distribution model for simulating population abundance and potential biological removal in the Mediterranean. Endanger Species Res 29:239–254. https://doi.org/10.3354/esr00714
Casale P, Mazaris AD, Freggi D, Vallini C, Argano R (2009) Growth rates and age at adult size of loggerhead sea turtles (Caretta caretta) in the Mediterranean Sea, estimated through capture-mark-recapture records. Sci Mar 73:589–595. https://doi.org/10.3989/scimar.2009.73n3589
Cerutti JMB, Burt AJ, Haupt P, Bunbury N, Mumby PJ, Schaepman-Strub G (2020) Impacts of the 2014–2017 global bleaching event on a protected remote atoll in the Western Indian Ocean. Coral Reefs 39:15–26. https://doi.org/10.1007/s00338-019-01853-1
Chaloupka M, Limpus C (1997) Robust statistical modelling of hawksbill sea turtle growth rates (southern Great Barrier Reef). Mar Ecol Prog Ser 146:1–8. https://doi.org/10.3354/meps146001
Chaloupka M, Limpus C, Miller J (2004) Green turtle somatic growth dynamics in a spatially disjunct Great Barrier Reef metapopulation. Coral Reefs 23:325–335. https://doi.org/10.1007/s00338-004-0387-9
Colman LP, Patrício ARC, McGowan A, Santos AJB, Marcovaldi M, Bellini C, Godley BJ (2015) Long-term growth and survival dynamics of green turtles (Chelonia mydas) at an isolated tropical archipelago in Brazil. Mar Biol 162:111–122. https://doi.org/10.1007/s00227-014-2585-5
Congdon JD, Dunham AE, Van Loben Sels RC (1993) Delayed sexual maturity and demographics of Blanding’s turtles (Emydoidea blandingii): implications for conservation and management of long-lived organisms. Conserv Biol 7:826–833. https://doi.org/10.1046/j.1523-1739.1993.740826.x
Diez CE, Van Dam RP (2002) Habitat effect on hawksbill turtle growth rates on feeding grounds at Mona and Monito Islands, Puerto Rico. Mar Ecol Prog Ser 234:301–309. https://doi.org/10.3354/meps234301
Eckert KL, Bjorndal KA, Abreu-Grobois FA, Donnelly M (1999) Research and management techniques for the conservation of sea turtles
Eguchi T, Seminoff JA, LeRoux RA, Prosperi D, Dutton DL, Dutton PH (2012) Morphology and growth rates of the green sea turtle (Chelonia mydas) in a northern-most temperate foraging ground. Herpetologica 68:76–87. https://doi.org/10.1655/HERPETOLOGICA-D-11-00050.1
Esteban N, Mortimer JA, Stokes HJ, Olivier J, Richard L, Hays GC (2020) A global review of green turtle diet: sea surface temperature as a potential driver of omnivory levels. Mar Biol 1–17. https://doi.org/10.1007/s00227-020-03786-8
Farrow GE, Brander KM (1971) Tidal studies on Aldabra. Philos Trans R Soc London B Biol Sci 260:91–121
Flanders Marine Institute (2022) The intersect of the Exclusive Economic Zones and IHO sea areas, version 4
Frazer NB, Ehrhart LM(1985) Preliminary growth models for green, Chelonia mydas, and loggerhead, Caretta caretta, turtles in the wild. Copeia 1985:73. https://doi.org/10.2307/1444792
Frazer NB, Ladner RC(1986) A growth curve for green sea turtles, Chelonia mydas, in the U.S. Virgin Islands, 1913-14. Copeia 1986:798–802
Frazier J (1971) Observations on sea turtles at Aldabra Atoll. Philos Trans R Soc London B Biol Sci 260:373–410. https://doi.org/10.1098/rstb.1971.0019
Friedlander A, Ballesteros E, Beets J, Brown E, Fay J, Haupt P, Henning B, Rose P, Sala E(2015) Biodiversity and ecosystem health of the Aldabra Group, southern Seychelles- scientific report to the government of Seychelles
Gane J, Downs CT, Olivier I, Brown M (2020) Nesting ecology and hatching success of the hawksbill turtle (2004–2014) on Cousine Island, Seychelles. Afr J Mar Sci 42:53–65. https://doi.org/10.2989/1814232X.2020.1727952
Goshe LR, Avens L, Scharf FS, Southwood AL (2010) Estimation of age at maturation and growth of Atlantic green turtles (Chelonia mydas) using skeletochronology. Mar Biol 157:1725–1740. https://doi.org/10.1007/s00227-010-1446-0
Green D (1993) Growth rates of wild immature green turtles in the Galápagos Islands, Ecuador. J Herpetol 27:338–341
Hamann M, Godfrey MH, Seminoff JA, Arthur K, Barata PCR, Bjorndal KA, Bolten AB, Broderick AC, Campbell LM, Carreras C, Casale P, Chaloupka M, Chan SKF, Coyne MS, Crowder LB, Diez CE, Dutton PH, Epperly SP, Fitz Simmons NN, Formia A, Girondot M, Hays GC, Cheng IJ, Kaska Y, Lewison R, Mortimer JA, Nichols WJ, Reina RD, Shanker K, Spotila JR, Tomás J, Wallace BP, Work TM, Zbinden J, Godley BJ (2010) Global research priorities for sea turtles: Informing management and conservation in the 21st century. Endanger Species Res 11:245–269. https://doi.org/10.3354/esr00279
Hawkes LA, Mcgowan A, Broderick AC, Gore S, Wheatley D, White J, Witt MJ, Godley BJ (2014) High rates of growth recorded for hawksbill sea turtles in Anegada, British Virgin Islands. Ecol Evol 4:1255–1266. https://doi.org/10.1002/ece3.1018
Hays GC, Mortimer JA, Ierodiaconou D, Esteban N (2014) Use of Long-Distance Migration Patterns of an Endangered Species to Inform Conservation Planning for the World’s Largest Marine Protected Area. Conserv Biol 28:1636–1644. https://doi.org/10.1111/cobi.12325
Hays GC, Taxonera A, Renom B, Fairweather K, Lopes A, Cozens J, Laloë J, Hays GC(2022a) Changes in mean body size in an expanding population of a threatened species
Hays GC, Atchison-Balmond N, Cerritelli G, Lalo JO, Luschi P, Mortimer JA, Rattray A, Esteban N (2022b) Travel routes to remote ocean targets reveal the map sense resolution for a marine migrant. J R Soc Interface. doi: 10.1098/rsif.2021.0859
Heppell SS(1998) Application of life-history theory and population model analysis to turtle conservation. Copeia 1998:367–375
IPCC (2021) Summary for policymakers. In: Climate change 2021: the physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. In: V. M-D, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (eds) Energy and Environment. Cambridge University Press. In Press.
Jensen MP, Dalleau M, Gaspar P, Lalire M, Jean C, Ciccione S, Mortimer JA, Quillard M, Taquet C, Wamukota A, Leroux G, Bourjea J (2020) Seascape genetics and the spatial ecology of juvenile green turtles. Genes (Basel) 11:278. https://doi.org/10.3390/genes11030278
Koester A, Migani V, Bunbury N, Ford A, Sanchez C, Wild C (2020) Early trajectories of benthic coral reef communities following the 2015/16 coral bleaching event at remote Aldabra Atoll. Seychelles Sci Rep 10:1–15. https://doi.org/10.1038/s41598-020-74077-x
Krueger BH, Chaloupka MY, Leighton PA, Dunn JA, Horrocks JA (2011) Somatic growth rates for a hawksbill turtle population in coral reef habitat around Barbados. Mar Ecol Prog Ser 432:269–276. https://doi.org/10.3354/meps09125
Kubis S, Chaloupka M, Ehrhart L, Bresette M (2009) Growth rates of juvenile green turtles Chelonia mydas from three ecologically distinct foraging habitats along the east central coast of Florida, USA. Mar Ecol Prog Ser 389:257–269. https://doi.org/10.3354/meps08206
Lenz AJ, Avens L, Borges-Martins M (2017) Age and growth of juvenile green turtles Chelonia mydas in the western South Atlantic Ocean. Mar Ecol Prog Ser 568:191–201. https://doi.org/10.3354/meps12056
Levasseur KE, Stapleton SP, Quattro JM (2021) Precise natal homing and an estimate of age at sexual maturity in hawksbill turtles. Anim Conserv 45:127–145. https://doi.org/10.1111/acv.12657
Limpus C, Chaloupka M (1997) Nonparametric regression modelling green sea turtle growth rates (southern Great Barrier Reef). Mar Ecol Prog Ser 149:23–34. https://doi.org/10.3354/meps149023
Long CA, Chabot RM, El-Khazen MN, Kelley JR, Mollet‐Saint Benoît C, Mansfield KL (2021) Incongruent long‐term trends of a marine consumer and primary producers in a habitat affected by nutrient pollution. Ecosphere 12:e03553. https://doi.org/10.1002/ecs2.3553
Magurran AE, Baillie SR, Buckland ST, Dick JMP, Elston DA, Scott EM, Smith RI, Somerfield PJ, Watt AD (2010) Long-term datasets in biodiversity research and monitoring: assessing change in ecological communities through time. Trends Ecol Evol 25:574–582. https://doi.org/10.1016/j.tree.2010.06.016
Mendonça MT (1981) Comparative growth rates of wild immature Chelonia mydas and Caretta caretta in Florida. J Herpetol 15:447–451
Meylan PA, Meylan AB, Gray JA (2011) The ecology and migrations of sea turtles 8. Tests of the developmental habitat hypothesis. Bull Am Museum Nat Hist 2011:1–70. https://doi.org/10.1206/357.1
Mortimer J, Balazs GH(2000) Post-nesting migrations of hawksbill turtles in the granitic Seychelles and implications for conservation. Proc Ninet Int Sea Turt Symp US Dep Commer NOAA Tech Memo NOAA-TM-NMFS-SEFSC-44322–25
Mortimer J, Gerlach J, Summerton P (2010) Long distance migrations of hawksbills tagged at Aldabra Atoll. Mar Turt Newsl 11:9–11
Mortimer JA (1984) Marine turtles in the Republic of the Seychelles: status and management. IUCN Conservation Library, Gland, Switzerland
Mortimer JA, Broderick D(1999) Population genetic structure and developmental migrations of sea turtles in the Chagos Archipelago and adjacent regions inferred from mtDNA sequence variation. In: Sheppard C, Seaward M (eds) Ecology of the Chagos Archipelago. Westbury for the Linnean Society of London, pp 185–194
Mortimer JA, Donnelly M(2008) Eretmochelys imbricata. The IUCN Red List of Threatened Species: e.T8005A12881238
Mortimer JA, Von Brandis RG, Liljevik A, Chapman R, Collie J (2011) Fall and rise of nesting green turtles (Chelonia mydas) at Aldabra Atoll, Seychelles: positive response to four decades of protection (1968–2008). Chelonian Conserv Biol 10:165–176. https://doi.org/10.2744/CCB-0872.1
Mortimer JA, Esteban N, Guzman AN, Hays GC (2020) Estimates of marine turtle nesting populations in the south-west Indian Ocean indicate the importance of the Chagos Archipelago. Oryx 54:332–343
Mortimer JA, Appoo J, Bautil B, Betts M, Burt AJ, Chapman R, Currie JC, Doak N, Esteban N, Liljevik A, Mahoune JT, Onezia C, Pistorius P, Richards H, Samedi U, Sanchez CL, Seabrook W, Underwood A, van de Crommenacker J, von Brandis R, Hays GC (2022) Long-term changes in adult size of green turtles at Aldabra Atoll and implications for clutch size, sexual dimorphism and growth rates. Mar Biol 169–123. https://doi.org/10.1007/s00227-022-04111-1
Omeyer LCM, Godley BJ, Broderick AC (2017) Growth rates of adult sea turtles. Endanger Species Res 34:357–371. https://doi.org/10.3354/esr00862
Omeyer LCM, Fuller WJ, Godley BJ, Snape RTE, Broderick AC (2018) Determinate or indeterminate growth? Revisiting the growth strategy of sea turtles. Mar Ecol Prog Ser 596:199–211. https://doi.org/10.3354/meps12570
Pacoureau N, Rigby CL, Kyne PM, Sherley RB, Winker H, Carlson JK, Fordham SV, Barreto R, Fernando D, Francis MP, Jabado RW, Herman KB, Liu K-M, Marshall AD, Pollom RA, Romanov EV, Simpfendorfer CA, Yin JS, Kindsvater HK, Dulvy NK (2021) Half a century of global decline in oceanic sharks and rays. Nature 589:567–571. https://doi.org/10.1038/s41586-020-03173-9
Patrício R, Diez CE, van Dam RP (2014) Spatial and temporal variability of immature green turtle abundance and somatic growth in Puerto Rico. Endanger Species Res 23:51–62. https://doi.org/10.3354/esr00554
Pedersen EJ, Miller DL, Simpson GL, Ross N (2019) Hierarchical generalized additive models in ecology: an introduction with mgcv. PeerJ. doi: 10.7717/peerj.6876
Phillips KP, Mortimer JA, Jolliffe KG, Jorgensen TH, Richardson DS (2014) Molecular techniques reveal cryptic life history and demographic processes of a critically endangered marine turtle. J Exp Mar Bio Ecol 455:29–37. https://doi.org/10.1016/j.jembe.2014.02.012
Piacenza SE, Balazs GH, Hargrove SK, Richards PM, Heppell SS (2016) Trends and variability in demographic indicators of a recovering population of green sea turtles Chelonia mydas. Endanger Species Res 31:103–117. https://doi.org/10.3354/esr00753
Piacenza SE, Richards PM, Heppell SS (2019) Fathoming sea turtles: monitoring strategy evaluation to improve conservation status assessments. Ecol Appl 29:1300–1315. https://doi.org/10.1002/eap.1942
Pritchard A, Sanchez C, Bunbury N, Burt A, Currie J, Doak N, Fleischer-Dogley F, Metcalfe K, Mortimer J, Richards H, van de Crommenacker J, Godley B (2022) Green turtle population recovery at Aldabra Atoll continues after 50 year of protection. Endanger Species Res 47:205–215. https://doi.org/10.3354/esr01174
Putman NF, Abreu-Grobois FA, Broderick AC, Ciofi C, Formia A, Godley BJ, Stroud S, Pelembe T, Verley P, Williams N (2014) Numerical dispersal simulations and genetics help explain the origin of hawksbill sea turtles in Ascension Island. J Exp Mar Bio Ecol 450:98–108. https://doi.org/10.1016/j.jembe.2013.10.026
QGIS Development Team (2022) QGIS Geographic Information System. Open Source Geospatial Foundation Project. Version 3.12.1
R Core Team (2021) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
Ramirez M, Popovska T, Babcock E (2020a) Global synthesis of sea turtle von Bertalanffy growth parameters through Bayesian hierarchical modeling. Mar Ecol Prog Ser 657:191–207. https://doi.org/10.3354/meps13544
Ramirez MD, Avens L, Goshe LR, Snover ML, Cook M, Haas HL, Heppell SS (2020b) Regional environmental drivers of Kemp’s ridley sea turtle somatic growth variation. Mar Biol 167:1–20. https://doi.org/10.1007/s00227-020-03754-2
Rees AF, Alfaro-Shigueto J, Barata PCR, Bjorndal KA, Bolten AB, Bourjea J, Broderick AC, Campbell LM, Cardona L, Carreras C, Casale P, Ceriani SA, Dutton PH, Eguchi T, Formia A, Fuentes MMPB, Fuller WJ, Girondot M, Godfrey MH, Hamann M, Hart KM, Hays GC, Hochscheid S, Kaska Y, Jensen MP, Mangel JC, Mortimer JA, Naro-Maciel E, Ng CKY, Nichols WJ, Phillott AD, Reina RD, Revuelta O, Schofield G, Seminoff JA, Shanker K, Tomás J, van de Merwe JP, Van Houtan KS, Vander Zanden HB, Wallace BP, Wedemeyer-Strombel KR, Work TM, Godley BJ (2016) Are we working towards global research priorities for management and conservation of sea turtles? Endanger Species Res 31:337–382. https://doi.org/10.3354/esr00801
Sanchez C, Lucas C, Odhiambo O, Beswick J, van de Geer C (2020) A juvenile green turtle long distance migration in the Western Indian Ocean. Mar Turt Newsl 160:5–7
Seminoff JA, Resendiz A, Nichols WJ (2002) Home range of green turtles Chelonia mydas at a coastal foraging area in the Gulf of California, Mexico. Mar Ecol Prog Ser 242:253–265. https://doi.org/10.3354/meps242253
Seminoff JA, Camryn AD, Balazs GH, Dutton PH, Eguchi T, Haas HL, Hargrove SA, Jensen M, Klemm DL, Lauritsen AM, MacPherson SL, Opay P, Possardt EE, Pultz S, Seney E, Van Houtan KS, Waples RS (2015) Status review of the green turtle (Chelonia mydas). under the U.S. Endangered Species Act
Snover ML, Balazs GH, Murakawa SKK, Hargrove SK, Rice MR, Seitz WA (2013) Age and growth rates of Hawaiian hawksbill turtles (Eretmochelys imbricata) using skeletochronology. Mar Biol 160:37–46. https://doi.org/10.1007/s00227-012-2058-7
Spencer T, Teleki KA, Bradshaw C, Spalding MD (2000) Coral bleaching in the southern Seychelles during the 1997–1998 Indian Ocean warm event. Mar Pollut Bull 40:569–586. https://doi.org/10.1016/S0025-326X(00)00026-6
Stokes HJ, Mortimer JA, Hays GC, Unsworth RKF, Laloë JO, Esteban N (2019) Green turtle diet is dominated by seagrass in the Western Indian Ocean except amongst gravid females. Mar Biol. doi: 10.1007/s00227-019-3584-3
van de Crommenacker J, Mortimer JA, Whiting A, Macrae I, Flores T, Whiting S (2022) Linkage between Cocos (Keeling) developmental habitat and hawksbill nesting beaches of Seychelles. Mar Turt Newsl July 2022:25–27. https://doi.org/seaturtle.org/mtn/
Van Hooidonk R, Maynard JA, Manzello D, Planes S (2014) Opposite latitudinal gradients in projected ocean acidification and bleaching impacts on coral reefs. Glob Chang Biol 20:103–112. https://doi.org/10.1111/gcb.12394
Van Houtan KS, Hargrove SK, Balazs GH (2014) Modeling sea turtle maturity age from partial life history records. Pac Sci 68:465–477. https://doi.org/10.2984/68.4.2
Wallace BP, DiMatteo AD, Hurley BJ, Finkbeiner EM, Bolten AB, Chaloupka MY, Hutchinson BJ, Alberto Abreu-Grobois F, Amorocho D, Bjorndal KA, Bourjea J, Bowen BW, Dueñas RB, Casale P, Choudhury BC, Costa A, Dutton PH, Fallabrino A, Girard A, Girondot M, Godfrey MH, Hamann M, López-Mendilaharsu M, Marcovaldi MA, Mortimer JA, Musick JA, Nel R, Pilcher NJ, Seminoff JA, Troëng S, Witherington B, Mast RB (2010) Regional Management Units for marine turtles: a novel framework for prioritizing conservation and research across multiple scales. PLoS ONE 5:1–11. https://doi.org/10.1371/journal.pone.0015465
Waycott M, Duarte CM, Carruthers TJB, Orth RJ, Dennison WC, Olyarnik S, Calladine A, Fourqurean JW, Heck KL, Hughes AR, Kendrick GA, Kenworthy WJ, Short FT, Williams SL (2009) Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc Natl Acad Sci U S A 106:12377–12381. https://doi.org/10.1073/pnas.0905620106
Weber SB, Weber N, Godley BJ, Pelembe T, Stroud S, Williams N, Broderick AC (2017) Ascension Island as a mid-Atlantic developmental habitat for juvenile hawksbill turtles. J Mar Biol Assoc United Kingdom 97:813–820. https://doi.org/10.1017/S0025315414001258
Wickham H(2016) ggplot2: elegant graphics for data analysis. In: Springer-Verlag New York. ISBN 978-3-319-24277-4. https://ggplot2.tidyverse.org
Wildermann NE, Gredzens C, Avens L, Barrios-Garrido HA, Bell I, Blumenthal J, Bolten AB, McNeill JB, Casale P, Di Domenico M, Domit C, Epperly SP, Godfrey MH, Godley BJ, González-Carman V, Hamann M, Hart KM, Ishihara T, Mansfield KL, Metz TL, Miller JD, Pilcher NJ, Read MA, Sasso C, Seminoff JA, Seney EE, Williard AS, Tomás J, Vélez-Rubio GM, Ware M, Williams JL, Wyneken J, Fuentes MMPB (2018) Informing research priorities for immature sea turtles through expert elicitation. Endanger Species Res 37:55–76. https://doi.org/10.3354/esr00916
Wood SN (2011) Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J R Stat Soc Ser B Stat Methodol 73:3–36. https://doi.org/10.1111/j.1467-9868.2010.00749.x
Zárate PM, Bjorndal KA, Seminoff JA, Dutton PH, Bolten AB (2015) Somatic growth rates of green turtles (Chelonia mydas) and hawksbills (Eretmochelys imbricata) in the Galápagos Islands. J Herpetol 49:641–648. https://doi.org/10.1670/14-078
Zug GR, Glor RE (1998) Estimates of age and growth in a population of green sea turtles (Chelonia mydas) from the Indian River lagoon system, Florida: a skeletochronological analysis. Can J Zool 76:1497–1506. https://doi.org/10.1139/z98-090
Zug GR, Balazs GH, Wetherall JA, Parker DM, Murakawa SKK (2002) Age and growth of Hawaiian green sea turtles (Chelonia mydas): an analysis based on skeletochronology. Fish Bull 100:117–127

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Growth rate and projected age at sexual maturity for immature hawksbill turtles and green turtles foraging in the remote marine protected area of Aldabra Atoll

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Abstract

Figures

Introduction

Materials And Methods

Study Site

Data collection

Data analysis

Results

Capture frequency, size distribution and annual growth

Growth rate change with time and size

Size-at-age

Age at sexual maturity

Discussion

Growth rates

Age at sexual maturity

Recommendations

Declarations

References

Supplementary Files

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Version 1