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Trindade Island, Brazil, is a small, remote volcanic island located 1140 km off the coast of southeastern Brazil. The green turtle (Chelonia mydas) nesting aggregation on Trindade is genetically distinct, the largest in the southwest Atlantic, and represents the southern limit of green turtle nesting in the Atlantic. Projeto TAMAR (a Brazilian conservation program) has monitored the nesting aggregation discontinuously since 1982. In 2009, a standardized protocol was established for the two beaches (Andradas and Tartarugas) with the highest nest abundance. Data from December 2009 through April 2017 (except 2013) were used in this study. Annual numbers of tracks left by females that emerged onto the beach vary between 558 and 3317 tracks for Andradas and between 760 and 3559 tracks for Tartarugas. Mean nesting probabilities (probability that an emerging female deposits eggs) for all years were 0.22 (95% HDI (highest posterior density interval) = 0.14–0.30) for Andradas and 0.45 (95% HDI = 0.37–0.53) for Tartarugas. Nesting probabilities varied among and within years and had a negative relationship with daily track counts. During our study, annual estimates of nests were stable on both Andradas (range 38–2001) and Tartarugas (range 248–2769). Nest abundance estimates between 1991 and 2008 from an earlier study indicated a stable population, extending the duration of apparent stability to 26 years with the caveat that the studies used different estimation methods. This stability is in contrast with the increasing trends for most green turtle nesting aggregations in the Atlantic. [ABSTRACT FROM AUTHOR]

Fisheries can profoundly affect bycatch species with 'slow' life history traits. Managing bait type offers one tool to control species selectivity. Different species and sizes of marine predators have different prey, and hence bait, preferences. This preference is a function of a bait's chemical, visual, acoustic and textural characteristics and size, and for seabirds the effect on hook sink rate is also important. We conducted a global meta-analysis of existing estimates of the relative risk of capture on different pelagic longline baits. We applied a Bayesian random effects meta-analytic regression modelling approach to estimate overall expected bait-specific catch rates. For blue shark and marine turtles, there were 34% (95% HDI: 4–59%) and 60% (95% HDI: 44–76%) significantly lower relative risks of capture on forage fish bait than squid bait, respectively. Overall estimates of bait-specific relative risk were not significantly different for seven other assessed taxa. The lack of a significant overall estimate of relative capture risk for pelagic shark species combined but significant effect for blue sharks suggests there is species-specific variability in bait-specific catch risk within this group. A qualitative literature review suggests that tunas and istiophorid billfishes may have higher catch rates on squid than fish bait, which conflicts with reducing marine turtle and blue shark catch rates. The findings from this synthesis of quantitative and qualitative evidence support identifying economically viable bycatch management measures with acceptable tradeoffs when multispecies conflicts are unavoidable, and highlight research priorities for global pelagic longline fisheries. [ABSTRACT FROM AUTHOR]

Project prioritization protocols are an important tool for allocating conservation resources efficiently, and have been applied to a range of species and ecosystems. Current approaches are inadequate when applied to species with distinct threats impacting different and/or multiple life history stages, such as sea turtles. We develop a model that integrates the benefit of any management project on a population by way of its expected population growth rate, including projects targeting different and/or multiple life history stages. To illustrate its utility, we prioritize projects for investment relevant to Australia's eastern population of Flatback turtle ( Natator depressus). We rely upon expert-elicitation to estimate individual benefit parameters, feasibility, and cost, and calculate the cost-effectiveness of each project. The most cost-effective project was not the most feasible, cheapest, or most beneficial. Our approach will help managers make efficient decisions that account for the full range of threats operating on a population. [ABSTRACT FROM AUTHOR]

Abstract: Sea turtles have iteroparous reproduction, migrating periodically from foraging habitat to nesting grounds where they generally lay several clutches at regular intervals throughout a nesting season. The total length of the nesting season depends ultimately on environmental conditions that are conducive to the production of viable hatchlings, and varies from 3 to 4months to year-round nesting. As with many migratory marine species, the ease of monitoring marine turtles on their nesting beaches opposed to on their foraging grounds, has resulted in a focus of research on breeding females for population studies and provides a useful albeit limited population index. To explore the precision of monitoring regimes to sample nesting turtle populations, we developed theoretical models for 3 1/2-month and 9-month nesting populations. We used individual-based models for tagged animals and parametric and non-parametric models to estimate annual nest abundance for track count data. These simulation models show that seasonality substantially influenced both the length and temporal position of optimal sampling regimes, showing a five to sevenfold greater effort in monitoring required for longer nesting seasons in order to encounter between 83 and 90% of the annual population. The implications for trend detection and inter-annual and inter-species variations are discussed. [Copyright &y& Elsevier]

Where conservation resources are limited and conservation targets are diverse, robust yet flexible priority-setting frameworks are vital. Priority-setting is especially important for geographically widespread species with distinct populations subject to multiple threats that operate on different spatial and temporal scales. Marine turtles are widely distributed and exhibit intra-specific variations in population sizes and trends, as well as reproduction and morphology. However, current global extinction risk assessment frameworks do not assess conservation status of spatially and biologically distinct marine turtle Regional Management Units (RMUs), and thus do not capture variations in population trends, impacts of threats, or necessary conservation actions across individual populations. To address this issue, we developed a new assessment framework that allowed us to evaluate, compare and organize marine turtle RMUs according to status and threats criteria. Because conservation priorities can vary widely (i.e. from avoiding imminent extinction to maintaining long-term monitoring efforts) we developed a "conservation priorities portfolio" system using categories of paired risk and threats scores for all RMUs (n=58). We performed these assessments and rankings globally, by species, by ocean basin, and by recognized geopolitical bodies to identify patterns in risk, threats, and data gaps at different scales. This process resulted in characterization of risk and threats to all marine turtle RMUs, including identification of the world's 11 most endangered marine turtle RMUs based on highest risk and threats scores. This system also highlighted important gaps in available information that is crucial for accurate conservation assessments. Overall, this priority-setting framework can provide guidance for research and conservation priorities at multiple relevant scales, and should serve as a model for conservation status assessments and prioritysetting for widespread, long-lived taxa. [ABSTRACT FROM AUTHOR]

Background: Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques - including site-based monitoring, genetic analyses, mark-recapture studies and telemetry - can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. Methodology/Principal Findings: To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine- to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. Conclusions/Significance: The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework - including maps and supporting metadata - will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis. [ABSTRACT FROM AUTHOR]

There is growing evidence that small-scale, coastal, passive net fisheries may be the largest single threat to some sea turtle populations. We review assessments of turtle interactions in these fisheries, and experiments on gear-technology approaches (modifying gear designs, materials and fishing methods) to mitigate turtle by-catch, available from a small number of studies and fisheries. Additional assessments are needed to improve the limited understanding of the relative degree of risk coastal net fisheries pose to turtle populations, to prioritize limited conservation resources and identify suitable mitigation opportunities. Whether gear technology provides effective and commercially viable solutions, alone or in combination with other approaches, is not well-understood. Fishery-specific assessments and trials are needed, as differences between fisheries, including in gear designs; turtle and target species, sizes and abundance; socioeconomic context; and practicality affect efficacy and suitability of by-catch mitigation methods. Promising gear-technology approaches for gillnets and trammel nets include: increasing gear visibility to turtles but not target species, through illumination and line materials; reducing net vertical height; increasing tiedown length or eliminating tiedowns; incorporating shark-shaped silhouettes; and modifying float characteristics, the number of floats or eliminating floats. Promising gear-technology approaches for pound nets and other trap gear include: replacing mesh with ropes in the upper portion of leaders; incorporating a turtle releasing device into traps; modifying the shape of the trap roof to direct turtles towards the location of an escapement device; using an open trap; and incorporating a device to prevent sea turtle entrance into traps. [ABSTRACT FROM AUTHOR]

Overexploitation is currently the main cause of marine defaunation. Vulnerability to overexploitation varies across populations. Determining which populations are of highest ecological risk from fishing mortality guides management. Because no single approach is optimal across taxonomic groups, a multi-model ensemble of relative risk estimates for a data-poor Pacific Ocean tuna longline fishery was obtained from two semi-quantitative Productivity-Susceptibility Analyses (PSAs) and from a quantitative approach that estimates instantaneous fishing mortality to compare to reference points of yield-per-recruit models. Individual estimates were combined to produce a pooled mean relative risk rank order. The study identified stocks below biological limits for which the contribution from this fishery to cumulative anthropogenic mortality may warrant intervention. Relative risks in descending order were for populations of albatrosses, cetaceans, mesopelagic sharks, rays, marine turtles, epipelagic sharks and teleosts. The fishery's contribution to cumulative fishing mortality of western central north Pacific Ocean striped marlin warrants a more rigorous assessment to determine absolute risks. The study identified the disparate factors explaining relative risk from an individual fishery versus absolute risk from cumulative anthropogenic mortality sources. Improved risk assessments are possible by addressing identified deficits with PSAs, obtaining information on variables that explain catch and post-capture survival risks that was unavailable for this assessment, improving electronic monitoring data quality and filling gaps in life history traits. Findings support stakeholders to design integrated bycatch management frameworks that mitigate fishing mortality of the most vulnerable taxa and account for multispecies conflicts that result from some bycatch mitigation methods. • A risk assessment identified most vulnerable taxa caught in a tuna longline fishery. • An ensemble of assessment approaches accounted for differences between taxa. • Relative risks were highest for albatrosses, mesopelagic sharks and cetaceans. • Mortality of a striped marlin stock warrants determining absolute risks. • Addressing assessment method deficits and filling information gaps are priorities. [ABSTRACT FROM AUTHOR]

We investigated cause-specific temporal and spatial trends in sea turtle strandings in the Hawaiian Archipelago. Five species of sea turtle were recorded in 3,861 strandings over a 22-year period (1982–2003). Green turtles comprised 97% of these strandings with size and gender composition reflecting the demographic structure of the resident green turtle population and relative green turtle abundance in Hawaiian waters. The cause of strandings was determined by necropsy based on a complete gross external and internal examination. Totally 75% of the 3,732 green turtle strandings were from Oahu where strandings occur year-round. The most common known cause of the green turtle strandings was the tumour-forming disease, fibropapillomatosis (28%) followed by hook-and-line fishing gear-induced trauma (7%), gillnet fishing gear-induced trauma (5%), boat strike (2.5%), and shark attack (2.7%). Miscellaneous causes comprised 5.4% of strandings whereas 49% of green turtle strandings could not be attributed to any known cause. Green turtle strandings attributable to boat strike were more likely from Kauai and Oahu while fibropapilloma strandings were more likely from Oahu and Maui. Hook-and-line gear strandings were more likely from Oahu due to higher per capita inshore fishing effort. The specific mortality rate (conditional probability) for fibropapillomatosis was 88%, 69% for gillnet gear and 52% for hook-and-line gear. The probability of a dead green turtle stranding increased from 1982 but levelled off by the mid-1990s. The declining mortality risk was because the prevalence and severity of fibropapillomatosis has decreased recently and so has the mortality risk attributable to gillnet gear. Despite exposure to disease and inshore fishing gears, the Hawaiian green turtle stock continues to recover following protection since the late 1970s. Nevertheless, measures to reduce incidental capture of sea turtles in coastal Hawaiian fisheries would be prudent, especially since strandings attributable to hook-and-line fishing gear have increased steadily since 1982. [ABSTRACT FROM AUTHOR]

Abstract: The loggerhead sea turtle is an endangered species exposed to many anthropogenic hazards in the Pacific. It is widely held that pelagic longline fisheries pose the major risk for Pacific loggerheads but the effects of other risk factors such as human-induced global climate change have rarely been considered. So we used generalised additive regression modelling and autoregressive-prewhitened cross-correlation analysis to explore whether regional ocean temperatures affect the long-term nesting population dynamics for the 2 Pacific loggerhead genetic stocks (Japan, Australia). We found that both Pacific stocks have been exposed to slowly increasing trends in mean annual sea surface temperature in their respective core regional foraging habitats over the past 50 years. We show that irrespective of whether a population was decreasing or increasing that there was an inverse correlation between nesting abundance and mean annual sea surface temperature in the core foraging region during the year prior to the summer nesting season. Cooler foraging habitat ocean temperatures are presumably associated with increased ocean productivity and prey abundance and consequently increased loggerhead breeding capacity. So warming regional ocean temperatures could lead to long-term decreased food supply and reduced nesting and recruitment unless Pacific loggerheads adapt by shifting their foraging habitat to cooler regions. So the gradual warming of the Pacific Ocean over the past 50 years is a major risk factor that must be considered in any meaningful diagnosis of the long-term declines apparent for some Pacific loggerhead nesting populations. [Copyright &y& Elsevier]

We analyzed a large dataset to quantify adult annual survival probability and remigration intervals for the Tortuguero, Costa Rica green turtle population. Annual survival probability was estimated at 0.85 (95% CI 0.75–0.92) using a recovery model and at 0.85 (95% CI 0.83–0.87) using an open robust design model. The two most common modes of remigration are 2 and 3 years. Annual survival probability is lower and remigration intervals are shorter than for other green turtle populations. Explanations for short remigration intervals include reproductive compensation due to historic population declines, availability of better quality food items, favorable environmental conditions, and short distance to the main foraging grounds. Variation in survival and remigration intervals have profound consequences for management and life history evolution. The short remigration intervals of Tortuguero green turtles partly offset mortality caused by turtle fishing in Nicaragua and mean that low juvenile survival represents a more urgent threat to the population than low adult survival. Low adult survival probability could result in selective pressure for earlier age at maturity. [ABSTRACT FROM AUTHOR]

The olive ridley is the most abundant seaturtle species in the world but little is known of the demography of this species. We used skeletochronological data on humerus diameter growth changes to estimate the age of North Pacific olive ridley seaturtles caught incidentally by pelagic longline fisheries operating near Hawaii and from dead turtles washed ashore on the main Hawaiian Islands. Two age estimation methods [ranking, correction factor (CF)] were used and yielded age estimates ranging from 5 to 38 and 7 to 24 years, respectively. Rank age-estimates are highly correlated ( r = 0.93) with straight carapace length (SCL), CF age estimates are not ( r = 0.62). We consider the CF age-estimates as biologically more plausible because of the disassociation of age and size. Using the CF age-estimates, we then estimate the median age at sexual maturity to be around 13 years old (mean carapace size c. 60 cm SCL) and found that somatic growth was negligible by 15 years of age. The expected age-specific growth rate function derived using numerical differentiation suggests at least one juvenile growth spurt at about 10–12 years of age when maximum age-specific growth rates, c. 5 cm SCL year−1, are apparent. [ABSTRACT FROM AUTHOR]