Enhancing the TurtleWatch product for leatherback sea turtles,a dynamic habitat model for ecosystem‐based management

Fishery management measures to reduce interactions between fisheries and endangered or threatened species have typically relied on static time‐area closures. While these efforts have reduced interactions, they can be costly and inefficient for managing highly migratory species such as sea turtles. The NOAA TurtleWatch product was created in 2006 as a tool to reduce the rates of interactions of loggerhead sea turtles with shallow‐set longline gear deployed by the Hawaii‐based pelagic longline fishery targeting swordfish. TurtleWatch provides information on loggerhead habitat and can be used by managers and industry to make dynamic management decisions to potentially reduce incidentally capturing turtles during fishing operations. TurtleWatch is expanded here to include information on endangered leatherback turtles to help reduce incidental capture rates in the central North Pacific. Fishery‐dependent data were combined with fishing effort, bycatch and satellite tracking data of leatherbacks to characterize sea surface temperature (SST) relationships that identify habitat or interaction ‘hotspots’. Analysis of SST identified two zones, centered at 17.2° and 22.9°C, occupied by leatherbacks on fishing grounds of the Hawaii‐based swordfish fishery. This new information was used to expand the TurtleWatch product to provide managers and industry near real‐time habitat information for both loggerheads and leatherbacks. The updated TurtleWatch product provides a tool for dynamic management of the Hawaii‐based shallow‐set fishery to aid in the bycatch reduction of both species. Updating the management strategy to dynamically adapt to shifts in multi‐species habitat use through time is a step towards an ecosystem‐based approach to fisheries management in pelagic ecosystems.     

Incidental capture of leatherback sea turtles in fixed fishing gear off Atlantic Canada

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Use of remote sensing tools to predict focal areas for sea turtle conservation in the south-western Atlantic

1. Fisheries bycatch of non-target species in the commercial fleet is a major source of anthropogenic injury and mortality for sea turtles and marine megafauna.
2. The Río de la Plata maritime front (RLPMF) and its adjacent international waters – comprising part of the Argentine and Uruguayan exclusive economic zones, is a highly important fishing ground in the south-western Atlantic Ocean as well as feeding and development grounds for sea turtles.
3. This paper analyses the distribution of the bottom and pelagic trawling fishery within the RLPMF using information from Vessel Satellite Monitoring System. With this information, areas of highest trawling intensity were defined and further evaluated their overlap with sea turtle habitat-use areas from available sea turtle satellite tracking information.
4. Results besides identifying high-susceptibility areas for sea turtle bycatch by the commercial trawler fleet along the RLPMF, provide predictive tools to identify vulnerable areas to interaction of sea turtles and the commercial fishing fleet.
5. Implementation of bycatch mitigation measures, such as reduced fishing effort areas by the Argentine and Uruguayan fisheries management agencies has the potential to benefit the fisheries as well as marine megafauna. Furthermore, there is a need for additional research on the impact that this fleet can have on sea turtles present in the area.

     

A comparison of methods to spatially represent pelagic longline fishing effort in catch and bycatch studies

Bycatch in fisheries has been recognized as a threat to many endangered populations of sea turtles, sea birds and marine mammals. Interactions between pelagic longline fisheries and critically endangered populations of leatherback sea turtles (Dermochelys coriacea) have led to temporary closures of the Hawaiian pelagic longline swordfish fishery and severe bycatch quotas. The negative impact of these events on both the populations of certain endangered species and the economic livelihood of the fishermen has resulted in a strong push from all sides to better understand bycatch events. Typically, analyses of longline catch and bycatch have examined fishing effort summarized over large areas (≥1°). Although aggregation of effort to this level may be necessary to account for uncertainty, confidentiality concerns, or to make comparisons across regions, it specifically limits the researcher's ability to characterize the local oceanographic factors that may drive individual bycatch events. Higher resolution analyses must be undertaken to identify such features. However, for these higher resolution analyses, the methods currently used to spatially represent pelagic longline fishing effort may significantly affect researcher's results. Here, we look at different methods to represent this fishing effort (i.e., points, centroids, polylines and polygons) at various resolutions (2 km to 5°) to better understand which method and spatial resolution are most appropriate. Our results validate the use of point features to represent fishing effort in previous low resolution studies of the Hawaiian pelagic longline fishery by showing that the set point method is suitable for studies with resolutions lower than 15 km. However, at higher resolutions (≤15 km) and in areas with more sparsely distributed fishing, aggregated effort values differed significantly between spatial representation methods. We demonstrate that the use of polygons to describe pelagic longline fishing effort is more representative and necessary for such high resolution analyses.     

中东太平洋公海金枪鱼延绳钓误捕海龟的观察和分析

根据2006年2－11月科学观察员对热带东太平洋公海海域(05°N～10°S,134° W~173°W)金枪鱼延绳钓渔业的调查,期间共投钩223次(天),误捕到绿海龟、蠵龟、丽龟、玳瑁和棱皮龟5种共22尾,死亡海龟13尾。从海龟误捕率看,平均每次尾数为0.098 65。平均每千钩尾数0.037 40。从海龟的钩获部位看,喙(嘴)上钩占41.0%,躯干部位上钩占13.6%,喉部上钩占13.6%,前肢上钩占18.2%,主绳缠绕被捕获占13.6%。海龟的误捕区域位于04°S以北海域,几乎可全年捕获。此外分析了不同钩位误捕海龟的数量,探讨了影响误捕率和死亡率的因素,提出保护对策。     

The relationship between the skipjack tuna (Katsuwonus pelamis) fishery and seasonal temperature variability in the south-western Atlantic

The spatio‐temporal distribution of tuna fishing effort has been related to oceanographic circulation and features in several seas of the world. Understanding the relationship between environmental variables and fishery resource dynamics is important for management decisions and to improve fishery yields. The relationship between sea temperature variability and the pole‐and‐line skipjack tuna (Katsuwonus pelamis) fishery in the south‐western Atlantic Ocean was investigated in this work. Data from logbooks, satellite images (sea surface temperature), and oceanographic surveys were used in the analyses. Skipjack are caught in warm tropical waters of the Brazil Current (BC). The north–south displacement of fishing effort was strongly associated to seasonal variation of the surface temperature, which was coupled to the tropical BC flow. Oceanographic fronts from autumn to spring and a shallow thermocline in summer probably induces the aggregation of skipjack schools over the shelfbreak, favouring fishing operations. Hypotheses are proposed to explain the relationship between peaks of fishing events and the presence of topographic peculiarities of the shelfbreak.     

Incidental capture and mortality of sea turtles in the industrial double‐rig‐bottom trawl fishery in south‐eastern Brazil

1. Incidental capture by fisheries is one of the principal threats to sea turtles. This study analysed spatial and temporal patterns of sea turtle bycatch, and estimated the direct initial mortality rate of these animals, in the industrial double‐rig‐bottom trawl fishery in south‐eastern Brazil. This is also the first attempt to relate bycatch/at‐sea mortality in bottom trawling to stranded turtles found along the adjacent coast.
2. The fishery was monitored from October 2015 to April 2018 through data collected voluntarily by the captains of eight industrial double‐rig trawlers. Two hundred and one sea turtles were captured during 9362 tows (43,657.52 trawling hours), resulting in a catch per unit effort (CPUE) of 0.0025 ± 0.0032 turtles h^?1 with a standard net of 30.5 m headrope, with no significant difference between the estimated CPUEs for licensed shrimp and demersal fish trawlers.
3. Caretta caretta (52.24%) and Lepidochelys olivacea (38.81%) were the most frequently captured species. According to Generalized Linear Models, C. caretta bycatch was significantly higher during winter, at lower latitudes (?24° to ?23°) and higher longitudes (?42° to ?40°), while the L. olivacea bycatch was significantly higher at higher latitudes (?23° to ?21°). The direct initial mortality rate of sea turtles in the shrimp trawlers was 7.65 ± 3.85%. However, none of the dead individuals subsequently released with plastic tags (n = 10) were found stranded on the coast. Mortality was not significantly related to the depth or duration of the trawling.
4. The results of this study suggest the need for improvements to the current management of the bottom trawl fishery in Brazil, moving from a species‐based to a spatial and seasonal‐based approach. There is also a need to develop turtle excluder devices adapted to local fishing conditions.

     

Bycatch mortality can cause extirpation in four freshwater turtle species

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Citizen science helps assessing spatio‐temporal distribution of sea turtles in foraging areas

1. Spatio‐temporal distribution is fundamental information for species of conservation concern, like sea turtles, that are threatened by anthropogenic activities at sea such as fishing. While coarse‐scale distribution information is available for several sea turtle populations, fine‐scale distribution informing on hot‐spot areas for spatial management is more difficult to obtain.
2. Here a citizen science approach involving tourism boats was undertaken to investigate the spatio‐temporal distribution of the loggerhead sea turtle (Caretta caretta) in the Pelagie Archipelago, located in a major foraging area for this species in the Mediterranean and where high fishing‐induced mortality occurs. The study was designed to provide data of absence and total sampling effort, commonly under‐reported in citizen science studies, allowing comparison among zones and periods. This was complemented by reports from fishing vessels.
3. Tourism boats reported 584 loggerhead turtle sightings during 1718 daily trips and fishing vessels reported 280 loggerhead turtles captured during 1040 fishing days. The results indicate a strong heterogeneous distribution in the Archipelago, with a low turtle occurrence around the main island, Lampedusa, where the highest human presence and activity occur. This may represent rare evidence of displacement behaviour of turtles that is worth further investigation. This also suggests that the current small marine protected area around Lampedusa has a low conservation impact. Zones with higher loggerhead turtle occurrence appear to be in the south and the west parts of the Archipelago, suggesting that spatial management would be possible when relatively small hot‐spots have been identified through specific surveys.
4. This study shows the potential of citizen science for providing preliminary information to guide more demanding and specific investigations. Such an approach may tremendously and rapidly improve the current knowledge on fine‐scale sea turtle distribution in regions with a great extension of coastlines and intensive tourist activities, such as the Mediterranean.

     

Sea turtle by‐catch in the Mediterranean

Sea turtle by‐catch data in the Mediterranean were reviewed and analysed with fishing effort. The results indicate over 132 000 captures per year, with probably over 44 000 incidental deaths per year, while many others are killed intentionally. Small vessels using set net, demersal longline or pelagic longline represent most of the Mediterranean fleet and likely cause more incidental or intentional deaths than large vessels typically using bottom trawl or pelagic longline. When interactions, mortality, intentional killing, size (a proxy for reproductive value) and turtle populations are considered, results indicate that Mediterranean green (Chelonia mydas) and loggerhead turtles (Caretta caretta) are more affected (i) by fishing gears such as bottom trawlers, demersal longlines and set nets, (ii) by small‐scale fisheries, and (iii) by fishing in the eastern basin. Although small‐scale fisheries should be the priority target, available measures are easier to implement on the fewer large vessels. Moreover, these measures are few, and they are not implemented yet, while others should still be tested for the Mediterranean fisheries. Thus, measures for reducing captures or mortality through changing gear‐specific characteristics may help, but probably a more holistic conservation strategy aimed to an ecosystem‐based fishery management for a sustainable fishing would be the only solution for the long‐term survival of Mediterranean Sea turtle populations and their habitats. Small‐scale fisheries should manage marine resources, including turtles, in a responsible and sustainable way. Turtles may not only benefit from but can also help this process if their non‐consumptive value is fully recognized.     

Sea turtles bycatch in the Adriatic Sea set net fisheries and possible hot‐spot identification

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Characterizing environmental and spatial variables associated with the incidental catch of olive ridley (Lepidochelys olivacea) in the Eastern Tropical Pacific purse‐seine fishery

In the Eastern Tropical Pacific (ETP), a region of high fishing activity, olive ridley (Lepidochelis olivacea) and other sea turtles are accidentally caught in fishing nets with tuna and other animals. To date, the interaction between fishing activity, ocean conditions and sea turtle incidental catch in the ETP has been described and quantified, but the factors leading to the interaction of olive ridleys and fishing activity are not well understood. This information is essential for the development of future management strategies that avoid bycatch and incidental captures of sea turtles. We used Generalized additive models (GAM) to analyze the relationship between olive ridley incidental catch per unit effort (iCPUE) in the ETP purse‐seine fisheries and environmental conditions, geographic extent and fishing set type (associated with dolphins, floating objects or in free‐swimming tuna schools). Our results suggest that water temperature, set type and geographic location (latitude, longitude and distance to nesting beaches) are the most important predictor variables to describe the probability of a capture event, with the highest iCPUE observed in sets made over floating objects. With the environmental predictors used, sea surface temperatures (SST) of 26–30°C and chlorophyll‐a (chl‐a) concentrations <0.36 mg m^?3 were associated with the highest probability of an incidental catch. Temporally, the highest probability of an incidental catch was observed in the second half of the year (June to December). Four regions were observed as high incidental catch hotspots: North and south of the equator between 0–10°N; 0–10°S and from 120 to 140°W; and along the Colombian coast and surrounding regions.     

Harvest models and stock co‐occurrence: probabilistic methods for estimating bycatch

A primary goal of ecosystem‐based fishery management is to reduce non‐target stock impacts, such as incidental harvest, during targeted fisheries. Quantifying incidental harvest has generally incorporated fishery‐dependent catch data, yet such data may be biased by gear non‐retention, observation difficulties, and non‐random harvest patterns that collectively lead to an impartial understanding of non‐target stock capture. To account for such issues and explicitly recognize the combined influence of ecological and harvest factors contributing to incidental capture within targeted fisheries, we demonstrate a probabilistic modelling framework that incorporates: (i) background rates of target and non‐target stock co‐occurrence as the primary ecological basis for incidental harvest; (ii) the probability of harvesting at localities exhibiting co‐occurrences; (iii) the probability of selecting for non‐target species with fishery gear; and, (iv) as a function of harvest effort, the overall probability of incidental capture for any non‐target stock contained in the species pool available for harvest. To illustrate application of the framework, simulation models were based on fishery‐independent data from a freshwater fishery in Ontario, Canada. Harvest simulations of empirical stock data indicated that greatest species‐specific capture values were over 4000 times more likely than for species with lowest values, indicating highly variable capture probabilities because of the combined influence of stock heterogeneity and harvest dynamics. Estimated bycatch–effort relationships will allow forecasting incidental harvest on the basis of effort to evaluate future shifts in fishing activity against specific ecosystem‐based fishery management objectives, such as reducing the overall probability of bycatch while maintaining target landings.     

Effects of 17/0 circle hooks and bait on sea turtles bycatch in a Southern Atlantic swordfish longline fishery

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Overview of loggerhead turtles coastal nets interactions in the Mediterranean Sea

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Seasonal encounter rate,life stages and main threats to the loggerhead sea turtle (Caretta caretta) in the Aeolian Archipelago (southern Thyrrenian Sea)

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Standardized catch and survival rates,and effect of a ban on shark retention,Palau pelagic longline fishery

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Incidental catch of marine turtles by Spanish bottom trawlers in the western Mediterranean

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Movements and behaviors of swordfish Xiphias gladius in the United States Pacific Leatherback Conservation Area

This study reports on the movements of swordfish tagged within the Pacific Leatherback Conservation Area (PLCA), an expansive region (>500,000 km²) off the U.S. West Coast that has been seasonally restricted to drift‐gillnet fishing since 2001 to reduce leatherback sea turtle (Dermochelys coricea) interactions. Thirteen swordfish were outfitted with satellite‐linked archival tags scheduled for short (2–20 days, n = 11) and longer‐term (150 days, n = 2) data collection. All tags were deployed on basking swordfish using traditional harpoon‐based methods during the fall of 2012–2013, near offshore seamounts (35.6°N/122.9°W to 37.4°N/123.5°W). Depth and temperature data from 11 swordfish (~90 to 150 kg) resulted in <251 days of movement information from the PLCA region. All tagged individuals exhibited surface‐oriented nocturnal movements, spending >99% of the night above the average thermocline depth (37.5 m), with an average night depth of 8.3 ± 1.6 m. Daytime depth distribution was greater and more variable (mean 107.1 ± 21.2 m), with fish primarily displaying three behavioral patterns: (i) basking activity, 16.7% of the day, (ii) a mixed‐layer distribution between 3 m and the thermocline (26.8% of the day), and (iii) prolonged dives below the thermocline, 56.5% of the day. For seven of the tracks, daytime basking rates increased when thermocline depth was <37 m. As fish moved offshore, there was less variability in vertical movements with a reduction in both basking activity and mixed layer occupancy, as well as an increase in average daytime depth. These data are discussed with respect to the potential development of alternative fishery options for the PLCA.     

Are bycatch rates sufficient as the principal fishery performance measure and method of assessment for seabirds?

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