“…A rapid search of the literature confirms the presence of stranded or bycaught leatherbacks in all main hotspots identified in the active dispersal simulation: in the Azores area [50], off Mauritania [51, 52], along the Portuguese coast [47], in the Gulf of Cadiz [53] and along the Tunisian coast [54]. Stranded or bycaught leatherbacks are also reported in the Bay of Biscay [55], along the Galician coast [56], the Moroccan coast [57], and in the Mediterranean sea [58].…”
Section: Resultsmentioning
confidence: 96%
“…They typically extend 150 km off the coastal areas where strandings are reported. The arrival area off Mauritania [20–30°W; 11–22°N] corresponds to the zone where leatherback bycatches were reported [51] although the vast majority of bycatches actually occurred west of 25°W.Fig. 6Lower (red dots) and upper (blue dots) age estimates for the smallest individuals observed in different areas, compared with the ages of the simulated active turtles (green dots) first entering these areas.…”
Background
The Northwest Atlantic (NWA) leatherback turtle (
Dermochelys coriacea
) subpopulation is one of the last healthy ones on Earth. Its conservation is thus of major importance for the conservation of the species itself. While adults are relatively well monitored, pelagic juveniles remain largely unobserved. In an attempt to reduce this knowledge gap, this paper presents the first detailed simulation of the open ocean dispersal of juveniles born on the main nesting beaches of French Guiana and Suriname (FGS).
Methods
Dispersal is simulated using STAMM, an Individual Based Model in which juveniles actively disperse under the combined effects of oceanic currents and habitat-driven movements. For comparison purposes, passive dispersal under the sole effect of oceanic currents is also simulated.
Results
Simulation results show that oceanic currents lead juveniles to cross the Atlantic at mid-latitudes. Unlike passive individuals, active juveniles undertake important north-south seasonal migrations while crossing the North Atlantic. They finally reach the European or North African coast and enter the Mediterranean Sea. Less than 4-year-old active turtles first arrive off Mauritania. Other productive areas on the eastern side of the Atlantic (the coast of Galicia and Portugal, the Gulf of Cadiz, the Bay of Biscay) and in the Mediterranean Sea are first reached by 6 to 9-year-old individuals. This active dispersal scheme, and its timing, appear to be consistent with all available stranding and bycatch data gathered on the Atlantic and Mediterranean coasts of Europe and North Africa. Simulation results also suggest that the timing of the dispersal and the quality of the habitats encountered by juveniles can, at least partly, explain why the NWA leatherback subpopulation is doing much better than the West Pacific one.
Conclusion
This paper provides the first detailed simulation of the spatial and temporal distribution of juvenile leatherback turtles dispersing from their FGS nesting beaches into the North Atlantic Ocean and Mediterranean Sea. Simulation results, corroborated by stranding and bycatch data, pinpoint several important developmental areas on the eastern side of the Atlantic Ocean and in the Mediterranean Sea. These results shall help focus observation and conservation efforts in these critical areas.
Electronic supplementary material
The online version of this article (10.1186/s40462-019-0149-5) contains supplementary material, which is available to authorized users.
“…A rapid search of the literature confirms the presence of stranded or bycaught leatherbacks in all main hotspots identified in the active dispersal simulation: in the Azores area [50], off Mauritania [51, 52], along the Portuguese coast [47], in the Gulf of Cadiz [53] and along the Tunisian coast [54]. Stranded or bycaught leatherbacks are also reported in the Bay of Biscay [55], along the Galician coast [56], the Moroccan coast [57], and in the Mediterranean sea [58].…”
Section: Resultsmentioning
confidence: 96%
“…They typically extend 150 km off the coastal areas where strandings are reported. The arrival area off Mauritania [20–30°W; 11–22°N] corresponds to the zone where leatherback bycatches were reported [51] although the vast majority of bycatches actually occurred west of 25°W.Fig. 6Lower (red dots) and upper (blue dots) age estimates for the smallest individuals observed in different areas, compared with the ages of the simulated active turtles (green dots) first entering these areas.…”
Background
The Northwest Atlantic (NWA) leatherback turtle (
Dermochelys coriacea
) subpopulation is one of the last healthy ones on Earth. Its conservation is thus of major importance for the conservation of the species itself. While adults are relatively well monitored, pelagic juveniles remain largely unobserved. In an attempt to reduce this knowledge gap, this paper presents the first detailed simulation of the open ocean dispersal of juveniles born on the main nesting beaches of French Guiana and Suriname (FGS).
Methods
Dispersal is simulated using STAMM, an Individual Based Model in which juveniles actively disperse under the combined effects of oceanic currents and habitat-driven movements. For comparison purposes, passive dispersal under the sole effect of oceanic currents is also simulated.
Results
Simulation results show that oceanic currents lead juveniles to cross the Atlantic at mid-latitudes. Unlike passive individuals, active juveniles undertake important north-south seasonal migrations while crossing the North Atlantic. They finally reach the European or North African coast and enter the Mediterranean Sea. Less than 4-year-old active turtles first arrive off Mauritania. Other productive areas on the eastern side of the Atlantic (the coast of Galicia and Portugal, the Gulf of Cadiz, the Bay of Biscay) and in the Mediterranean Sea are first reached by 6 to 9-year-old individuals. This active dispersal scheme, and its timing, appear to be consistent with all available stranding and bycatch data gathered on the Atlantic and Mediterranean coasts of Europe and North Africa. Simulation results also suggest that the timing of the dispersal and the quality of the habitats encountered by juveniles can, at least partly, explain why the NWA leatherback subpopulation is doing much better than the West Pacific one.
Conclusion
This paper provides the first detailed simulation of the spatial and temporal distribution of juvenile leatherback turtles dispersing from their FGS nesting beaches into the North Atlantic Ocean and Mediterranean Sea. Simulation results, corroborated by stranding and bycatch data, pinpoint several important developmental areas on the eastern side of the Atlantic Ocean and in the Mediterranean Sea. These results shall help focus observation and conservation efforts in these critical areas.
Electronic supplementary material
The online version of this article (10.1186/s40462-019-0149-5) contains supplementary material, which is available to authorized users.
“…The relative magnitude of the effect of the single factor hook shape on catch rates is likely substantially larger for leatherback sea turtles (ca. 63% lower catch rate on circle vs. J-shaped hook when bait type was not variable, Watson et al 2005;Sales et al 2010;Foster et al 2012, Coelho et al 2015Santos et al 2012Santos et al , 2013 than for sharks (ca. 20% higher relative risk of capture on circle vs. J-shaped hook, Gilman et al 2016b).…”
Section: Pelagic Longline Hook Shapementioning
confidence: 98%
“…Leatherback sea turtles (Dermochelys coriacea), the only extant sea turtle species to not have a hard shell, are most frequently caught in pelagic longline gear by becoming foul-hooked and entangled. They have lower catch rates on circle than J-shaped hooks (Watson et al 2005;Sales et al 2010;Pacheco et al 2011;Foster et al 2012;Coelho et al 2015;Santos et al 2012Santos et al , 2013Gilman and Huang 2017). For hardshelled and leatherback turtles that ingest a hook, circle hooks result in a lower proportion of turtles swallowing the hook deeply relative to J-shaped hooks (Andraka et al 2013;Gilman and Huang 2017).…”
Bycatch in fisheries can have profound effects on the abundance of species with relatively low resilience to increased mortality, can alter the evolutionary characteristics and concomitant fitness of affected populations through heritable trait-based selective removals, and can alter ecosystem functions, structure and services through food web trophic links. We challenge current piecemeal bycatch management paradigms, which reduce the mortality of one taxon of conservation concern at the unintended expense of others. Bycatch mitigation measures may also reduce intraspecific genetic diversity. We drew examples of broadly prescribed 'best practice' methods to mitigate bycatch that result in unintended cross-taxa conflicts from pelagic longline, tuna purse seine, gillnet and trawl fisheries. We identified priority improvements in data quality and in understanding ecological effects of bycatch fishing mortality to support holistic ecological risk assessments of the effects of bycatch removals conducted through semi-quantitative and model-based ().,-volV) ( 01234567 89().,-volV) approaches. A transition to integrated bycatch assessment and management that comprehensively consider biodiversity across its hierarchical manifestations is needed, where relative risks and conflicts from alternative bycatch management measures are evaluated and accounted for in fisheries decision-making processes. This would enable managers to select measures with intentional and acceptable tradeoffs to best meet objectives, when conflicts are unavoidable.
“…Polygon = density of the posterior draws, horizontal line = 95% credible interval of the posterior draws, solid dot = mean of the posterior draws shrunk towards the Random Effect estimate that is the pooled or overall log risk ratio for all 13 studies, dashed vertical line indicates no baitspecific effect with shrinkage estimates to the left of this line reflecting a lower blue shark catch rate on pelagic forage fish bait than on squid bait. Heterogeneity (tau) = 0.74 (95% HDI: 0.41-1.19) Javitech (2003), Watson et al (2005), Ariz et al (2006), Rueda et al (2006), Kim et al (2007Kim et al ( , 2008, Mejuto et al (2008), García-Cortés et al (2009), Yokota et al (2006Yokota et al ( , 2009, Stokes et al (2011), Foster et al (2012), Baez et al (2013), Santos et al (2012Santos et al ( , 2013, Coelho et al (2015) and Gilman et al (2007Gilman et al ( , 2012Gilman et al ( , 2014aGilman et al ( , 2016a b Abbes et al (1996), ECOTAP (1998), Bach et al (2000, Watson et al (2005), Mejuto et al (2008), Petersen et al (2008), Galeana-Villasenor et al (2009), Yokota et al (2009), Foster et al (2012), Amorim et al (2014) and Gilman et al (2007Gilman et al ( , 2012Gilman et al ( , 2014aGilman et al ( , 2016a Watson et al (2005), Coelho et al (2012), Foster et al (2012) and Amorim et al…”
Section: Bait Type Underlying Mechanisms For Effect On Catch Riskmentioning
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 Electronic supplementary material The online version of this article (
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