TurtleWatch: a tool to aid in the bycatch reduction of loggerhead turtles Caretta caretta in the Hawaii-based pelagic longline fishery

Howell, Evan A.; Kobayashi, Donald R.; Parker, Denise M.; Balazs, George H.; Polovina, Jeffrey J.

doi:10.3354/esr00096

Cited by 219 publications

(265 citation statements)

References 23 publications

(36 reference statements)

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“…This information can have a profound influence on traditional hypotheses of oceanic transport and basin-scale connectivity. The time that it takes to traverse the open ocean and the fact that these highly migratory animals spend years to decades in this pelagic habitat leaves sea turtles vulnerable to anthropogenic threats, in particular bycatch in fisheries [39]. Knowledge of dispersal patterns, the areas highly frequented by vulnerable sea turtles and the corridors of movement between life stages is a priority for sea turtle conservation [40,46].…”

Section: Discussionmentioning

confidence: 99%

“…From an ecological perspective, much can still be learned as to how physical forcing from ocean circulation influences the dispersal pathways and spatio-temporal dispersal of young juveniles from this population. From a conservation standpoint, current United States fisheries management strategies in the central North Pacific Ocean are specifically geared towards the interaction with at-sea loggerheads [39] Here, we combine high-resolution ocean circulation models with long-term, previously unpublished 20-36 month old loggerhead sea turtle tracks from the North Pacific Ocean basin. The trajectories of passively drifting particles are compared with those of observed turtles released from the same date and nesting location in the western North Pacific, thereby testing the passive migration hypothesis for juvenile loggerhead sea turtles in the North Pacific Ocean.…”

Section: Introductionmentioning

confidence: 99%

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Active dispersal in loggerhead sea turtles ( Caretta caretta ) during the ‘lost years’

et al. 2016

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Highly migratory marine species can travel long distances and across entire ocean basins to reach foraging and breeding grounds, yet gaps persist in our knowledge of oceanic dispersal and habitat use. This is especially true for sea turtles, whose complex life history and lengthy pelagic stage present unique conservation challenges. Few studies have explored how these young at-sea turtles navigate their environment, but advancements in satellite technology and numerical models have shown that active and passive movements are used in relation to open ocean features. Here, we provide the first study, to the best of our knowledge, to simultaneously combine a high-resolution physical forcing ocean circulation model with long-term multi-year tracking data of young, trans-oceanic North Pacific loggerhead sea turtles during their 'lost years' at sea. From 2010 to 2014, we compare simulated trajectories of passive transport with empirical data of 1-3 year old turtles released off Japan (29.7-37.5 straight carapace length cm). After several years, the at-sea distribution of simulated current-driven trajectories significantly differed from that of the observed turtle tracks. These results underscore current theories on active dispersal by young oceanic-stage sea turtles and give further weight to hypotheses of juvenile foraging strategies for this species. Such information can also provide critical geographical information for spatially explicit conservation approaches to this endangered population.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Active dispersal in loggerhead sea turtles ( Caretta caretta ) during the ‘lost years’

et al. 2016

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“…For example, several RMUs that interact with longline gear in the Northwest Atlantic Ocean and North Pacific Ocean fell into this category, which could reflect the substantial efforts in these regions to monitor and reduce turtle bycatch through on-board observer programs and the implementation and compliance of several mitigation measures, including changes to hooks, bait, and spatiotemporal distribution of fishing effort , Gilman et al 2006, Howell et al 2008. Regionally focused analyses of bycatch patterns over time in response to mitigation efforts would shed light on this possibility, although the ''snapshot'' nature of the bycatch studies makes such analyses challenging.…”

Section: Identifying Conservation and Monitoring Priorities Among Rmumentioning

confidence: 99%

Impacts of fisheries bycatch on marine turtle populations worldwide: toward conservation and research priorities

et al. 2013

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Abstract. Fisheries bycatch is considered the most serious threat globally to long-lived marine megafauna (e.g., mammals, birds, turtles, elasmobranchs). However, bycatch assessments to date have not evaluated population-level bycatch impacts across fishing gears. Here, we provide the first global, multigear evaluation of population-level fisheries bycatch impacts for marine turtles. To compare bycatch impacts of multiple gears within and among marine turtle populations (or regional management units, RMUs), we compiled more than 1,800 records from over 230 sources of reported marine turtle bycatch in longline, net, and trawl fisheries worldwide that were published between 1990-2011. The highest bycatch rates and levels of observed effort for each gear category occurred in the East Pacific, Northwest and Southwest Atlantic, and Mediterranean regions, which were also the regions of highest data availability. Overall, available data were dominated by longline records (nearly 60% of all records), and were nonuniformly distributed, with significant data gaps around Africa, in the Indian Ocean, and Southeast Asia. We found that bycatch impact scores-which integrate information on bycatch rates, fishing effort, mortality rates, and body sizes (i.e., proxies for reproductive values) of turtles taken as bycatch-as well as mortality rates in particular, were significantly lower in longline fishing gear than in net and trawl fishing gears. Based on bycatch impact scores and RMU-specific population metrics, we identified the RMUs most and least threatened by bycatch globally, and found wide variation among species, regions, and gears within these classifications. The lack of regional or species-specific patterns in bycatch impacts across fishing gears suggests that gear types and RMUs in which bycatch has the highest impact depend on spatially-explicit overlaps of fisheries (e.g., gear characteristics, fishing practices, target species), marine turtle populations (e.g., conservation status, aggregation areas), and underlying habitat features (e.g., oceanographic conditions). Our study provides a blueprint both for prioritizing limited conservation resources toward managing fishing gears and practices with the highest population impacts on sea turtles and for enhancing data collection and reporting efforts.

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“…Move-on rules have been widely implemented with real-time closures lasting days to weeks over distances as short as 2-10 km in radius (5,10,13,14), with the potential to be implemented on temporal scales of days or hours if higher-resolution catch data are incorporated. Oceanographic closures are areas defined by environmental conditions (e.g., sea surface temperature) and have been implemented on a daily (15) and biweekly (16,17) basis. In the only compulsory example, the Eastern Australia pelagic longline fishery employs a habitat model to inform a dynamic oceanographic closure to reduce bycatch of southern bluefin tuna (Thunnus maccoyii) based on 5-km resolution temperature data, but the oceanographic closure is implemented at a much coarser scale (17).…”

Section: Scale In Fisheries Managementmentioning

confidence: 99%

Dynamic ocean management increases the efficiency and efficacy of fisheries management

Dunn

Maxwell

Boustany

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

170

123

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In response to the inherent dynamic nature of the oceans and continuing difficulty in managing ecosystem impacts of fisheries, interest in the concept of dynamic ocean management, or realtime management of ocean resources, has accelerated in the last several years. However, scientists have yet to quantitatively assess the efficiency of dynamic management over static management. Of particular interest is how scale influences effectiveness, both in terms of how it reflects underlying ecological processes and how this relates to potential efficiency gains. Here, we address the empirical evidence gap and further the ecological theory underpinning dynamic management. We illustrate, through the simulation of closures across a range of spatiotemporal scales, that dynamic ocean management can address previously intractable problems at scales associated with coactive and social patterns (e.g., competition, predation, niche partitioning, parasitism, and social aggregations). Furthermore, it can significantly improve the efficiency of management: as the resolution of the closures used increases (i.e., as the closures become more targeted), the percentage of target catch forgone or displaced decreases, the reduction ratio (bycatch/catch) increases, and the total time-area required to achieve the desired bycatch reduction decreases. In the scenario examined, coarser scale management measures (annual time-area closures and monthly full-fishery closures) would displace up to four to five times the target catch and require 100-200 times more square kilometer-days of closure than dynamic measures (gridbased closures and move-on rules). To achieve similar reductions in juvenile bycatch, the fishery would forgo or displace between USD 15-52 million in landings using a static approach over a dynamic management approach.dynamic ocean management | real-time management | ecosystem-based fisheries management | spatiotemporal | bycatch A lthough traditional fisheries management has focused on assessing the health of individual fish stocks, there has been a strong trend over the past two decades toward the incorporation of ecosystem components into fisheries management (1, 2). Ecosystem-based fisheries management (EBFM) seeks to meet multiple, potentially conflicting goals across ecological, economic, and social objectives (3, 4). Meeting these goals is made more complex in marine ecosystems due to the inherent dynamic nature of the oceans. In response to continuing difficulty in managing the ecosystem impacts of fisheries in a highly dynamic environment, including bycatch (i.e., the accidental interaction of fishing gear with nontarget species), interest in the concept of dynamic ocean management (DOM) has accelerated (5-10). Maxwell et al. (8) define dynamic management as "management that changes in space and time in response to the shifting nature of the ocean and its users based on the integration of new biological, oceanographic, social and/or economic data in near real-time" (8). Dynamic management reflects advancement in our abi...

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TurtleWatch: a tool to aid in the bycatch reduction of loggerhead turtles Caretta caretta in the Hawaii-based pelagic longline fishery

Cited by 219 publications

References 23 publications

Active dispersal in loggerhead sea turtles ( Caretta caretta ) during the ‘lost years’

Active dispersal in loggerhead sea turtles ( Caretta caretta ) during the ‘lost years’

Impacts of fisheries bycatch on marine turtle populations worldwide: toward conservation and research priorities

Dynamic ocean management increases the efficiency and efficacy of fisheries management

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