“…On the other hand, for leatherbacks it would be 0.85 (95% prediction interval: 0.45–0.97). Figure 1 Random-effects forest plot of the inverse-variance weighted annual survival estimates for the 59 marine turtle studies (letters after reference year indicate different estimates from the same reference) 37 , 40 – 42 , 51 – 88 . The species-specific pooled or random-effect survival rate estimates (RE diamonds) are shown in addition to the prediction intervals (horizontal bar through each RE diamond).…”
Comparative syntheses of key demographic parameters are critical not only for identifying data gaps, but also for evaluating sources of heterogeneity among estimates. Because demographic studies frequently exhibit heterogeneity, evaluating sources of heterogeneity among estimates can inform biological patterns and conservation actions more broadly. To better understand adult survival in marine turtles and avoid drawing inaccurate conclusions from current estimates, we conducted a comprehensive meta-analysis to test how heterogeneity among estimates was partitioned among phylogenetic, biogeographic and methodological factors. Fifty-nine studies from five marine turtle species met the minimum selection criteria for inclusion in our meta-analysis. Heterogeneity among survival estimates was first partitioned between differences in ocean basin (Indo-Pacific versus Atlantic), then by differences among family/tribe within the Indo-Pacific (Chelonini versus Carettini and Dermochelidae). However, apparent differences attributed to biogeography (ocean basin effect) and phylogeny (family/tribe effect) were highly correlated with methodological differences in tag type, model type, habitat type and study duration, thereby confounding biological interpretations and complicating efforts to use many current survival estimates in population assessments. Our results highlight the importance of evaluating sources of heterogeneity when interpreting patterns among similar demographic studies and directly inform efforts to identify research priorities for marine turtles globally.
“…On the other hand, for leatherbacks it would be 0.85 (95% prediction interval: 0.45–0.97). Figure 1 Random-effects forest plot of the inverse-variance weighted annual survival estimates for the 59 marine turtle studies (letters after reference year indicate different estimates from the same reference) 37 , 40 – 42 , 51 – 88 . The species-specific pooled or random-effect survival rate estimates (RE diamonds) are shown in addition to the prediction intervals (horizontal bar through each RE diamond).…”
Comparative syntheses of key demographic parameters are critical not only for identifying data gaps, but also for evaluating sources of heterogeneity among estimates. Because demographic studies frequently exhibit heterogeneity, evaluating sources of heterogeneity among estimates can inform biological patterns and conservation actions more broadly. To better understand adult survival in marine turtles and avoid drawing inaccurate conclusions from current estimates, we conducted a comprehensive meta-analysis to test how heterogeneity among estimates was partitioned among phylogenetic, biogeographic and methodological factors. Fifty-nine studies from five marine turtle species met the minimum selection criteria for inclusion in our meta-analysis. Heterogeneity among survival estimates was first partitioned between differences in ocean basin (Indo-Pacific versus Atlantic), then by differences among family/tribe within the Indo-Pacific (Chelonini versus Carettini and Dermochelidae). However, apparent differences attributed to biogeography (ocean basin effect) and phylogeny (family/tribe effect) were highly correlated with methodological differences in tag type, model type, habitat type and study duration, thereby confounding biological interpretations and complicating efforts to use many current survival estimates in population assessments. Our results highlight the importance of evaluating sources of heterogeneity when interpreting patterns among similar demographic studies and directly inform efforts to identify research priorities for marine turtles globally.
“…We also applaud all the efforts of sea turtle conservation biologists to report the outcomes of their monitoring [for example, the previous studies ( 9 , 13 , 24 , 35 ) but also see tables S2 and S3 for a full listing of published articles]. An important development in helping this reporting of monitoring data has also been the emergence of new conservation journals [for example, the studies of Groom et al ( 27 ) and Piacenza et al ( 36 )]. However, it is important to be aware of the data gaps that remain.…”
Section: Discussionmentioning
confidence: 99%
“…However, we note that available time series in the public domain may often not capture information that has been collected on trends in abundance at some nesting sites. Encouragingly, data sets that are helping to fill these data gaps are continually being published [for example, the study of Groom et al ( 27 )], so an improved assessment of the conservation status of flatback turtles may soon be possible. This same issue of data availability also likely applies to other species, with the likelihood that often abundance time series will not be in the public domain.…”
“…Ectotherms, for instance, are particularly susceptible to the surrounding environment for their individual productivity (i.e. somatic growth and reproduction; Bjorndal et al 2016), and long-term monitoring during different life stages is needed to assess population status and changes in abundance (Groom et al 2017).…”
Knowledge of life history parameters is essential for the effective management of species of conservation concern. For migratory marine vertebrates such as hawksbill sea turtles Eretmochelys imbricata, feeding aggregations are important developmental habitats, allowing the study of population dynamics. Here, we used data from a 31 yr mark-recapture study of juvenile hawksbill sea turtles in the Fernando de Noronha Archipelago, Brazil, to estimate key demographic parameters. Turtles recruit to the neritic habitat at similar sizes to those of other Atlantic hawksbill aggregations. The curved carapace length (CCL) at the first capture ranged from 28 to 84 cm (mean ± SD: 44.6 ± 9.8 cm). Median minimum residence time of turtles captured at least twice was 3.2 yr, whilst long-term minimum residence of up to 14 yr was also observed, with turtles showing site fidelity within the archipelago. The mean size of turtles captured was constant throughout time. Turtles grew on average 3.4 ± 2.2 cm yr-1 , with a monotonic expected growth rate function generally decreasing with increasing size. At these rates, hawksbill turtles in Fernando de Noronha would need to spend ca. 14−18 yr to reach minimum adult breeding size (~74 cm CCL). This mark-recapture study has been essential to understanding the ecology and demographic parameters of this regional hawksbill turtle neritic foraging ground.
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