Marine Megafauna Sea Turtles, Seabirds and Marine Mammals

Author(s):  
Rocío Mariano Jelicich ◽  
Paula Berón ◽  
Sofia Copello ◽  
Natalia A. Dellabianca ◽  
Germán García ◽  
...  
Phytotaxa ◽  
2015 ◽  
Vol 233 (3) ◽  
pp. 236 ◽  
Author(s):  
Roksana Majewska ◽  
J. P. Kociolek ◽  
Evan W. Thomas ◽  
Mario De Stefano ◽  
Mario Santoro ◽  
...  

Marine mammals such as whales and dolphins have been known for a long time to host a very specific epizoic community on their skin. Less known however is the presence of a similar community on the carapaces of sea turtles. The present study is the first describing new taxa inhabiting sea turtle carapaces. Samples, collected from nesting olive ridley sea turtles (Lepidochelys olivacea) on Ostional Beach (Costa Rica), were studied using light and scanning electron microscopy. Two unknown small-celled gomphonemoid taxa were analysed in more detail and are described as two new genera, closely related to other gomphonemoid genera with septate girdle bands, such as Tripterion, Cuneolus and Gomphoseptatum. Chelonicola Majewska, De Stefano & Van de Vijver gen. nov. has a flat valve face, uniseriate striae composed of more than three areolae, simple external raphe endings, internally a siliceous flap over the proximal raphe endings and lives on mucilaginous stalks. Poulinea Majewska, De Stefano & Van de Vijver gen. nov. has at least one concave valve, uniseriate striae composed of only two elongated areolae, external distal raphe endings covered by thickened siliceous flaps and lives attached to the substrate by a mucilaginous pad. Chelonicola costaricensis Majewska, De Stefano & Van de Vijver sp. nov. and Poulinea lepidochelicola Majewska, De Stefano & Van de Vijver sp. nov. can be separated based on stria structure, girdle structure composed of more than 10 copulae, raphe structure and general valve outline. A cladistics analysis of putative members of the Rhoicospheniaceae indicates that the family is polyphyletic. Chelonicola and Poulinea are sister taxa, and form a monophyletic group with Cuneolus and Tripterion, but are not closely related to Rhoicosphenia, or other genera previously assigned to this family. Features used to help diagnose the family such as symmetry and presence of septa and pseudosepta are homoplastic across the raphid diatom tree of life.


2021 ◽  
Author(s):  
Leslie Roberson ◽  
Chris Wilcox

Abstract Fisheries bycatch continues to drive the decline of many threatened marine species such as seabirds, sharks, marine mammals, and sea turtles. Management frameworks typically address bycatch with fleet-level controls on fishing. Yet, individual operators differ in their fishing practices and efficiency at catching fish. If operators have differing abilities to target species, they should also have differing abilities to anti-target bycatch species. We analyse variations in threatened species bycatch among individual operators from five industrial fisheries representing different geographic areas, gear types, and target species. The individual vessel is a significant predictor of bycatch for 15 of the 16 species-fishery interactions, including species that represent high or low costs to fishers, or have economic value as potentially targeted byproducts. Encouragingly, we found high performance operators in all five fishing sectors, including gears known for high bycatch mortality globally. These results show the potential to reduce negative environmental impacts of fisheries with incentive-based interventions targeting specific performance groups of individuals. Management of threatened species bycatch Incidental catch of marine animals in fishing gear ("bycatch") has been recognized as a serious problem for several decades. Despite widespread efforts to address it, bycatch remains one of the most pressing issues in fisheries management today, especially for threatened or protected species such as sea turtles, seabirds, elasmobranchs, and marine mammals1,2. The most common approaches to reducing bycatch have been command-and-control measures implemented across the entire fleet or industry, such as technology requirements or total allowable catch for particular bycatch species3,4. These conventional approaches have been far from universally successful, and have often performed worse in practice than models and trials suggested, even when the same approach is translated to a similar fishery5. The Skipper Effect Managing bycatch is a problem of fishing efficiency. Although management frameworks typically treat fishing fleets as a unit, several studies suggest that the skill of individual operators (the "skipper effect") could be a driver of important and unexplained variations in fishing efficiency. A skipper's skill is some combination of managerial ability, experience and knowledge of the environment, ability to respond to rapidly changing information and conditions at sea, and numerous other factors that are difficult to describe or record6. There is ongoing debate about the key components of operator skill and its importance in different contexts, such as different gears or technical advancement of fisheries7–10. Yet, numerous studies show consistent variation in target catch rates among anglers, skippers, or fishing vessels that is not explained by environmental variables or economic inputs7,11−13. This includes technically advanced and homogeneous fleets where a skipper's skill would seemingly be less important14. Previously, the skipper effect has been explored in relation to fishing efficiency and profitability (effort and target catch). However, if fishers have differing abilities to catch species they want, it follows that they would also have variable skill at avoiding unwanted species. Untangling the skipper effect is difficult without very detailed data, which are often not available for target catch and are extremely rare for bycatch. We capitalize on a rare opportunity to compare multiple high-resolution fisheries datasets that have information about both target and bycatch. We use fisheries observer data from five Australian Commonwealth fisheries sectors to answer three key questions: 1) Is there significant and predictable variation among operators in their target to bycatch ratios? We hypothesize that there are characteristics at the operator level that lead some vessels to perform worse than others on a consistent basis, and that operator skill is an important factor driving variations in bycatch across fishing fleets; 2) Does the pattern hold across species, gear types, and fisheries? We predict that, irrespective of the bycatch context, there are high performing operators that are able to avoid bycatch while maintaining high target catch; and 3) Does skipper skill transfer across species?” We posit that certain types of bycatch are inherently more difficult to avoid but expect to find correlations between bycatch rates, indicating that a skipper's ability to avoid one species extends to other types of bycatch. If these hypotheses hold true, then there exists untapped potential to reduce bycatch without imposing additional controls on fishing effort and gear. This would support an alternative approach to framing management questions such as those around threatened species bycatch. It may be that it is not a random event across a fishery, but in fact is an issue of particular low performance operators. In this case, measures aimed directly at those individual operators could be an opportunity to make considerable progress towards reducing threatened species bycatch, at potentially much lower cost than common whole-of-fishery solutions.


Drones ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 142
Author(s):  
Liam C. Dickson ◽  
Kostas A. Katselidis ◽  
Christophe Eizaguirre ◽  
Gail Schofield

Temperature is often used to infer how climate influences wildlife distributions; yet, other parameters also contribute, separately and combined, with effects varying across geographical scales. Here, we used an unoccupied aircraft system to explore how environmental parameters affect the regional distribution of the terrestrial and marine breeding habitats of threatened loggerhead sea turtles (Caretta caretta). Surveys spanned four years and ~620 km coastline of western Greece, encompassing low (<10 nests/km) to high (100–500 nests/km) density nesting areas. We recorded 2395 tracks left by turtles on beaches and 1928 turtles occupying waters adjacent to these beaches. Variation in beach track and inwater turtle densities was explained by temperature, offshore prevailing wind, and physical marine and terrestrial factors combined. The highest beach-track densities (400 tracks/km) occurred on beaches with steep slopes and higher sand temperatures, sheltered from prevailing offshore winds. The highest inwater turtle densities (270 turtles/km) occurred over submerged sandbanks, with warmer sea temperatures associated with offshore wind. Most turtles (90%) occurred over nearshore submerged sandbanks within 10 km of beaches supporting the highest track densities, showing the strong linkage between optimal marine and terrestrial environments for breeding. Our findings demonstrate the utility of UASs in surveying marine megafauna and environmental data at large scales and the importance of integrating multiple factors in climate change models to predict species distributions.


2021 ◽  
Vol 8 ◽  
Author(s):  
Janie L. Reavis ◽  
H. Seckin Demir ◽  
Blair E. Witherington ◽  
Michael J. Bresette ◽  
Jennifer Blain Christen ◽  
...  

Incidental capture, or bycatch, of marine species is a global conservation concern. Interactions with fishing gear can cause mortality in air-breathing marine megafauna, including sea turtles. Despite this, interactions between sea turtles and fishing gear—from a behavior standpoint—are not sufficiently documented or described in the literature. Understanding sea turtle behavior in relation to fishing gear is key to discovering how they become entangled or entrapped in gear. This information can also be used to reduce fisheries interactions. However, recording and analyzing these behaviors is difficult and time intensive. In this study, we present a machine learning-based sea turtle behavior recognition scheme. The proposed method utilizes visual object tracking and orientation estimation tasks to extract important features that are used for recognizing behaviors of interest with green turtles (Chelonia mydas) as the study subject. Then, these features are combined in a color-coded feature image that represents the turtle behaviors occurring in a limited time frame. These spatiotemporal feature images are used along a deep convolutional neural network model to recognize the desired behaviors, specifically evasive behaviors which we have labeled “reversal” and “U-turn.” Experimental results show that the proposed method achieves an average F1 score of 85% in recognizing the target behavior patterns. This method is intended to be a tool for discovering why sea turtles become entangled in gillnet fishing gear.


2018 ◽  
Author(s):  
Abel Valdivia ◽  
Shaye Wolf ◽  
Kieran Suckling

AbstractThe U.S. Endangered Species Act (ESA) is the world’s strongest environmental law protecting imperiled plants and animals, and a growing number of marine species have been protected under this law as extinction risk in the oceans has increased. Marine mammals and sea turtles comprise 36% of the 161 ESA-listed marine species, yet analyses of recovery trends after listing are lacking. Here we gather the best available annual population estimates for all marine mammals (n=33) and sea turtles (n=29) listed under the ESA as species. Of these, we quantitatively analyze population trends, magnitude of population change, and recovery status for representative populations of 23 marine mammals and 9 sea turtles, which were listed for more than five years, occur in U.S. waters, and have data of sufficient quality and span of time for trend analyses. Using generalized linear and non-linear models, we found that 78% of marine mammals (n=18) and 78% of sea turtles (n=7) significantly increased after listing; 13% of marine mammals (n=3) and 22% of sea turtles (n=2) showed non-significant changes; while 9% of marine mammals (n=2), but no sea turtles declined after ESA protection. Overall, species with populations that increased in abundance were listed for 20 years or more (e.g., large whales, manatees, and sea turtles). Conservation measures triggered by ESA listing such as ending exploitation, tailored species management, and fishery regulations, among others, appear to have been largely successful in promoting species recovery, leading to the delisting of some species and to increases in most. These findings underscore the capacity of marine mammals and sea turtles to recover from substantial population declines when conservation actions under the ESA are implemented in a timely and effective manner.


2019 ◽  
Author(s):  
Elena Valsecchi ◽  
Jonas Bylemans ◽  
Simon J. Goodman ◽  
Roberto Lombardi ◽  
Ian Carr ◽  
...  

ABSTRACTMetabarcoding studies using environmental DNA (eDNA) and high throughput sequencing (HTS) are rapidly becoming an important tool for assessing and monitoring marine biodiversity, detecting invasive species, and supporting basic ecological research. Several barcode loci targeting teleost fish and elasmobranchs have previously been developed, but to date primer sets focusing on other marine megafauna, such as marine mammals have received less attention. Similarly, there have been few attempts to identify potentially ‘universal’ barcode loci which may be informative across multiple marine vertebrate Orders. Here we describe the design and validation of four new sets of primers targeting hypervariable regions of the vertebrate mitochondrial 12S and 16S rRNA genes, which have conserved priming sites across virtually all cetaceans, pinnipeds, elasmobranchs, boney fish, sea turtles and birds, and amplify fragments with consistently high levels of taxonomically diagnostic sequence variation. ‘In silico’ validation using the OBITOOLS software showed our new barcode loci outperformed most existing vertebrate barcode loci for taxon detection and resolution. We also evaluated sequence diversity and taxonomic resolution of the new barcode loci in 680 complete marine mammal mitochondrial genomes demonstrating that they are effective at resolving amplicons for most taxa to the species level. Finally, we evaluated the performance of the primer sets with eDNA samples from aquarium communities with known species composition. These new primers will potentially allow surveys of complete marine vertebrate communities in single HTS metabarcoding assessments, simplifying workflows, reducing costs, and increasing accessibility to a wider range of investigators.


2021 ◽  
Vol 224 (4) ◽  
pp. jeb236216
Author(s):  
Chihiro Kinoshita ◽  
Takuya Fukuoka ◽  
Tomoko Narazaki ◽  
Yasuaki Niizuma ◽  
Katsufumi Sato

ABSTRACTAnimals with high resting metabolic rates and low drag coefficients typically have fast optimal swim speeds in order to minimise energy costs per unit travel distance. The cruising swim speeds of sea turtles (0.5–0.6 m s−1) are slower than those of seabirds and marine mammals (1–2 m s−1). This study measured the resting metabolic rates and drag coefficients of sea turtles to answer two questions: (1) do turtles swim at the optimal swim speed?; and (2) what factors control the optimal swim speed of turtles? The resting metabolic rates of 13 loggerhead and 12 green turtles were measured; then, the cruising swim speeds of 15 loggerhead and 9 green turtles were measured and their drag coefficients were estimated under natural conditions. The measured cruising swim speeds (0.27–0.50 m s−1) agreed with predicted optimal swim speeds (0.19–0.32 m s−1). The resting metabolic rates of turtles were approximately one-twentieth those of penguins, and the products of the drag coefficient and frontal area of turtles were 8.6 times higher than those of penguins. Therefore, our results suggest that both low resting metabolic rate and high drag coefficient of turtles determine their slow cruising speed.


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