Ocean-wide tracking of pelagic sharks reveals extent of overlap with longline fishing hotspots

Overfishing is arguably the greatest ecological threat facing the oceans, yet catches of many highly migratory fishes including oceanic sharks remain largely unregulated with poor monitoring and data reporting. Oceanic shark conservation is hampered by basic knowledge gaps about where sharks aggregate across population ranges and precisely where they overlap with fishers. Using satellite tracking data from six shark species across the North Atlantic, we show that pelagic sharks occupy predictable habitat hotspots of high space use. Movement modeling showed sharks preferred habitats characterized by strong sea surface-temperature gradients (fronts) over other available habitats. However, simultaneous Global Positioning System (GPS) tracking of the entire Spanish and Portuguese longline-vessel fishing fleets show an 80% overlap of fished areas with hotspots, potentially increasing shark susceptibility to fishing exploitation. Regions of high overlap between oceanic tagged sharks and longliners included the North Atlantic Current/Labrador Current convergence zone and the Mid-Atlantic Ridge southwest of the Azores. In these main regions, and subareas within them, shark/vessel co-occurrence was spatially and temporally persistent between years, highlighting how broadly the fishing exploitation efficiently “tracks” oceanic sharks within their space-use hotspots year-round. Given this intense focus of longliners on shark hotspots, our study argues the need for international catch limits for pelagic sharks and identifies a future role of combining fine-scale fish and vessel telemetry to inform the ocean-scale management of fisheries.Oceanic pelagic sharks are iconic top predators with relatively low resilience to exploitation (1–3), yet many tens of millions of individuals are caught each year by high-seas fisheries (2) with significant reductions in catch rates documented for many species (4–6). This level of exploitation is especially problematic because the harvest of oceanic sharks remains largely unregulated (2, 7). For the majority of shark species that make up more than 95% of oceanic shark catches, no international or bilateral harvest limits have been imposed (2, 7). Consequently, analysis indicates that extinction risk in oceanic and coastal sharks and rays is higher than for most other vertebrates (3). Accordingly, there is a critical need and concern for improved management and conservation of oceanic sharks.Management action for oceanic sharks such as catch quotas, size limits, and/or area closures (i.e., marine protected areas, MPAs) is hampered by a paucity of high-quality data on total catches, landings, species identification, catch locations, and the susceptibility of sharks to fisheries (2, 4, 7). In addition, poor recordkeeping, a lack of reporting or deliberate underreporting of pelagic shark catches by the high seas longlining fleet and/or fishing nations (7), contributes to poor data quality that can lead to increased uncertainty in scientific stock assessments of population trends (8–10). Furthermore, it is particularly difficult to accurately quantify population trends of pelagic sharks and the efficacy of different management tools because these sharks are highly migratory, moving long distances over whole ocean basins (11, 12), which can further complicate conservation strategies (13). Information is urgently needed on the habitat preferences, movements, and migrations of oceanic sharks and the extent of overlap with commercial fisheries (4, 11, 14). For instance, stable or increasing catch per unit effort (CPUE) trends might be linked to changes in areas fished, potentially altering overlap with important habitats of sharks that could mask real population declines already occurring. However, a significant limitation affecting management of oceanic sharks is little knowledge of where, when, and how fish and fishing vessels overlap across their entire ranges (4, 15). There have been recent technological advances in surveillance of the ocean environment (16), fisheries’ activities (17), and tracking fish movements and migrations (11, 12). However, high-resolution monitoring (18) of environment–fish–fishery interactions across whole population ranges is lacking, despite the potential of this approach to inform conservation.In this study, we examine in unprecedented detail, to our knowledge, the spatial dynamics of multiple pelagic shark species and two complete fishing fleets in the North Atlantic Ocean over multiple years by using remote telemetry of animals and longline vessels to quantify the overlap between fishing exploitation and shark habitat use. The Atlantic is one of the most heavily fished ocean ecosystems where surface longline deployments can be up to eightfold higher than in the Pacific (14). Pelagic sharks account for approximately 30% of the total elasmobranch catch within the Atlantic Ocean with ∼70% of this total comprising a single species, the blue shark Prionace glauca (7). The shortfin mako Isurus oxyrinchus is the second most frequently caught species on Atlantic longlines, making up approximately 20% of pelagic shark catches (7). The tiger shark Galeocerdo cuvier is also known to migrate seasonally into oceanic habitats (19) that are exploited by high seas longliners, whereas coastal/pelagic hammerhead sharks (Sphyrna mokkaran and Sphyrna lewini) probably overlap with fishers exploiting the continental shelf (20).To investigate how oceanic and coastal pelagic sharks use distributional ranges with distinct environmental heterogeneity, we satellite-tracked >100 individuals over ∼8,000 d by using electronic tags that give a fishery-independent spatial distribution over time (Fig. 1A, Materials and Methods, and SI Appendix, SI Materials and Methods and Tables S1 and S2). Sharks were tagged at seven main locations (coastal and oceanic) spanning the North Atlantic: from southwest England (United Kingdom) to Florida (United States) that included oceanic pelagic species (blue shark, n = 38; shortfin mako, n = 14; longfin mako, n = 1) in addition to coastal/oceanic pelagic species (tiger, n = 32; great hammerhead, n = 12; scalloped hammerhead, n = 2) (SI Appendix, Fig. S1 and Table S1). We analyzed these data with simultaneous Vessel Monitoring System (VMS) Global Positioning System (GPS) positions of 186 Spanish and Portuguese longliners (>15 m length) over a 9-y period. These longline fleets are two of the most important in the North Atlantic capturing pelagic sharks (7, 14) (SI Appendix, SI Materials and Methods). Our analyses aimed (i) to determine the movements and habitat preferences of pelagic sharks and longline vessels, and (ii) to identify the areas where sharks and commercial vessels overlapped the most and the temporal persistence of these areas.Open in a separate windowFig. 1.Spatial distributions of satellite-tracked pelagic sharks. (A) Fishery-independent satellite track geolocations of oceanic and coastal/pelagic sharks in the North Atlantic Ocean, 2006–2012. Space use shift between spring-summer (March–August) (B) and autumn-winter (September–February) (C) determined from tag geolocations. (D) Map of the calculated high (hotspot; red) and low (coldspot; blue) use habitats of tracked sharks. SS, Sargasso Sea.     

The battle between harvest and natural selection creates small and shy fish

Harvest of fish and wildlife, both commercial and recreational, is a selective force that can induce evolutionary changes to life history and behavior. Naturally selective forces may create countering selection pressures. Assessing natural fitness represents a considerable challenge in broadcast spawners. Thus, our understanding about the relative strength of natural and fisheries selection is slim. In the field, we compared the strength and shape of harvest selection to natural selection on body size over four years and behavior over one year in a natural population of a freshwater top predator, the northern pike (Esox lucius). Natural selection was approximated by relative reproductive success via parent–offspring genetic assignments over four years. Harvest selection was measured by comparing individuals susceptible to recreational angling with individuals never captured by this gear type. Individual behavior was measured by high-resolution acoustic telemetry. Harvest and natural size selection operated with equal strength but opposing directions, and harvest size selection was consistently negative in all study years. Harvest selection also had a substantial behavioral component independent of body length, while natural behavioral selection was not documented, suggesting the potential for directional harvest selection favoring inactive, timid fish. Simulations of the outcomes of different fishing regulations showed that traditional minimum size-based harvest limits are unlikely to counteract harvest selection without being completely restrictive. Our study suggests harvest selection may be inevitable and recreational fisheries may thus favor small, inactive, shy, and difficult-to-capture fish. Increasing fractions of shy fish in angling-exploited stocks would have consequences for stock assessment and all fisheries operating with hook and line.

Anticipating and preparing for future evolutionary changes within harvested populations whether by fishing or hunting is critical for sustainable natural resource management and successful conservation of ecosystems (1–6). Harvest-induced evolution is a concern for both commercial and recreational fisheries, and harvest from recreational fisheries now frequently exceeds harvest from commercial fisheries in some marine fish and most inland fish populations (7). Harvesting, firstly, elevates adult mortality which favors the evolution of life history adaptations that maximize current as opposed to future reproduction [i.e., a fast life history characterized by early reproduction at a small size and elevated reproductive effort (1, 2)]. Additionally, harvesting is trait selective. Most individuals in harvested populations are not captured or hunted randomly (8). Instead, a suite of traits elevates the probability of harvest (8–13). In fisheries, vulnerability to harvest and fish body size are positively related across most fishing gears, and the relationship is exacerbated by the widespread use of minimum landing sizes (14, 15). Consequently, the average body size of individuals within fish stocks is commonly observed to decrease (15, 16).Decreasing average body size in fish stocks first results from demographic truncation by direct removal of large individuals within a generation but may also result from evolutionary adaptation to a new fitness landscape (17). Positively size-selective harvesting alters the fitness landscape by favoring early reproduction at smaller sizes, in turn slowing down postmaturation growth due to altered allocation of energy from soma to gonads (2, 18). Additionally, reduced postmaturation growth may arise from evolutionary adaptations in energy acquisition–related behaviors [e.g., evolution of risk-sensitive foraging in response to the selective removal of bold, active, or aggressive behavioral phenotypes (19, 20)]. There is considerable debate whether any observed phenotypic changes, derived from monitoring data from wild fisheries, in life history traits such as maturation timing or growth rate are indeed evolutionary (i.e., genetic) or an effect of phenotypic plasticity (21), and a recent review concluded that no conclusive example for fisheries-induced evolution exists at the scale of wild fisheries (21).Most research on fisheries-induced selection and evolution has been focused on life history traits (2). However, fisheries can also induce adaptive changes in behavior through at least two mechanisms. First, by creating selection pressures that favor fast life histories, fisheries may indirectly alter correlated behavioral traits like aggressive and bold behaviors (22–24). Second, passive gear types such as gill nets, traps, or hooks heavily rely on a behavioral response by individual fish for successful capture (25). Fish that are able to forage more, at the expense of taking more risks, are able to grow faster and may produce more offspring (26–28), but they may also be more vulnerable to capture (10, 27) and mortality by predation (29). Accordingly, models comparing life history outcomes emerging from either purely behavioral to purely size-dependent vulnerability to capture demonstrate that behavioral selection can create the same pressures and ultimately evolutionary outcomes as size-selective capture and, depending on context, either favor bold or shy fish (30, 31). As personality traits are known to have a heritable component (32, 33) and vary consistently among individuals (34, 35), the selective capture of active, aggressive, and bold fish may ultimately promote the emergence of timid populations (10, 19, 27). Independent of life history adaptations, these changes may also disrupt the “pace-of-life” syndrome and the correlation of behavior and life history (24, 36, 37). A widespread increase in timidity implies that fish will become harder to catch (10). If this is the case, challenges in stock assessments will arise as they are built on assumptions of consistent fish availability to sampling gear over time to serve as indices of abundance (19, 38, 39).Our understanding of selective harvest’s impact on phenotypic change has not yet been able to fully explain empirical observations from fisheries in the wild (40, 41). Indeed, the rate and impacts of harvest-induced evolution continues to attract controversy despite more than 20 y of research (2, 21, 41). Models of harvest-induced life history evolution consistently underestimate rates of phenotypic change observed in empirical studies from the wild, while experimental studies in the laboratory tend to overestimate empirical rates of evolution (40–42). The discrepancy between models or laboratory studies and empirical data in the wild may partly result from plastic, rather than evolutionary, impacts on phenotypes collected in the wild (43), from inappropriate assumptions of fitness trade-offs in models (30, 31), from exaggerated fishing mortality induced in selection line experiments (44), or from inadvertent selection on other traits correlated with growth, such as behavioral traits, rather than direct selection on size (30, 31). To understand the potential for harvest-induced evolution, a key first step is to understand the selection pressures induced by exploitation in the wild (42, 45). This is because following the breeder’s equation from quantitative genetics, the selection response in any trait is a product of the selection differentials acting on a trait and the trait’s heritability (46). We focus here on estimating selection acting on adaptive traits in a wild fish population and compare the selection to natural selective forces on the same traits.In particular, the counteracting forces of natural selection must be considered to understand the total selective forces acting on a phenotype (47, 48). However, natural selection has rarely been empirically measured in the context of harvest selection in wild fisheries (45, 47–49). Meta-analyses on selection in the wild indicate that fishing is one of the few anthropogenic selective forces consistently stronger than natural selection (49). Yet, natural selection compared to size-selective fisheries has, so far, only been quantified by fitness proxies such as survival (45), growth rate, or female body size (47, 48), assumed to be positively correlated with lifetime reproductive success (RS) (50). As the RS of fish is challenging to measure in the wild, it is unclear how body size and fitness actually scale (50), and consequently it is largely unclear what natural selection on body size or other traits looks like in exploited stocks. Further, the fitness landscape of behavioral traits has rarely been assessed in the wild, although behavior commonly relates to growth (51), survival (52, 53), and RS (26, 27).Our aim was to quantify the strength and direction of harvest and natural selection in the wild using an experimentally exploited top predatory fish and to improve our understanding of whether a portion of harvest size selection is actually the result of undetected behavioral selection (54, 55). To that end, we investigated the strength and direction of harvest selection on body size and activity in northern pike, Esox lucius, measuring fitness in the context of natural selection as relative reproductive success (RRS) over four years and classification of movement behavior over one year using high-resolution acoustic telemetry (56) covering an entire natural ecosystem. We used hook and line fishing as an example of a widespread fishing gear used by both recreational and commercial fisheries. We predicted that harvest and natural size selection act in opposition in which larger fish would have higher RRS (50) but would also be more likely to be captured by angling (57, 58). Furthermore, we expected that fishing selection on size would be much stronger than natural selection (49). However, we also predicted additional harvest selection on behavior (55) because recreational fishing gear is known to be related to behavioral phenotypes (10, 55, 59–61). Finally, through simulations, we investigated how regulations could alter the relationship between harvest and natural selection and potentially counteract fishing selection considering minimum length limits and harvest slots based on established models (42).     

Evaluation of pacemaker telemetry as a diagnostic feature for detecting atrial tachyarrhythmias in patients with sick sinus syndrome.

AIM: The aim of the present study was to validate pacemaker telemetry as a diagnostic feature for detecting atrial tachyarrhythmias (AT) during pacemaker treatment in patients with sick sinus syndrome (SSS). METHODS AND RESULTS: Patients with SSS and bradytachy syndrome (n = 28, 20 women), mean age 71 +/- 10.3 years, were included. The patients were treated with AAIR (n = 14) or DDDR pacing. At a routine follow-up visit pacemaker telemetry was reset and the patients underwent Holter recording for at least 24 h. Episodes of atrial fibrillation (AF) during Holter recording were compared with episodes of AT detected by the pacemaker. Only episodes of AF lasting for at least 1 min during Holter recording were registered. AT detected by the pacemaker telemetry was defined as: an atrial high rate episode with a rate of > or = 220 bpm for > or = 5 min, atrial sensing with a rate of > or = 170 bpm in > or = 5% of total counted beats, mode-switching in > or = 5% of total time recorded or a mode-switching episode of > or = 5 min. Twenty-eight Holter recordings (mean duration 31.5 h, range 20-72 h) were used for evaluation. Ten patients had one or more episodes of AF lasting at least 1 min on their Holter recordings. Nine of these patients had AT detected by their pacemaker telemetry according to our criteria. None of the patients had AT detected by the pacemaker telemetry and not by the Holter recording. The specificity and sensitivity for detection of AT recorded by the pacemaker telemetry in this study was 100% and 90%, respectively. The false-positive rate was 0%. CONCLUSION: Pacemaker telemetry was found to be a reliable tool for detecting AT in patients with SSS.     

Comparison of Simultaneous Measurements of Blood Pressure by Tail-Cuff and Carotid Arterial Methods in Conscious Spontaneously Hypertensive and Wistar-Kyoto Rats

We determined the validity of systolic blood pressure (SBP) measured by tail-cuff blood pressure (TCBP) with direct intra-arterial measurements. In conscious, restrained Wistar-Kyoto (WKY) and spontaneously hypertensive rats (SHR), carotid artery (CA) BP and TCBP were simultaneously measured. In both WKY and SHR strains, highly significant correlations between CABP and TCBP were found and Bland-Altman analyses showed no bias when the two methods were compared. The limits of agreement between CABP and TCBP in WKY and SHR were wide and reproducibility of pressure measurements by either technique was poor, with some evidence for strain-dependent differences. Pressure measurements made over short time frames, however, showed close agreement between CABP and TCBP. Acetylcholine-induced reductions in pressure were equivalently detected by tail-cuff and direct arterial measurement in both strains but angiotensin II-induced pressure elevations were over-estimated by tail-cuff in SHR. Telemetered SBP measurements in conscious rats were highly variable in a strain-dependent manner.     

清开灵和葛根素注射液对清醒犬血压的影响

目的:清醒Beagle犬静脉滴注给予清开灵注射液或葛根素注射液,观察药物是否引起类过敏反应及其对血压的影响.方法:经手术在Beagle犬体内埋植植入子,手术恢复后用文献报道的类过敏阳性药compound 48/80和聚氧乙烯山梨糖醇酐单油酸酯(吐温-80)来验证该动物检测模型的可行性,然后分别经静脉滴注给予清开灵注射液或葛根素注射液,采用DataquestA.R.T.4.3系统连续监测给药过程中及给药后Beagle犬血压的变化并观察犬的体征变化.结果:类过敏阳性药compound 48/80和吐温-80给药后犬出现骚动、皮肤潮红、巩膜充血等类过敏症状,且血压出现不同程度的下降,证明清醒Beagle犬遥测系统检测类过敏反应模型成立.清开灵注射液1.2,2.3,11.5 mL·kg-1对犬血压均未见明显影响;0.24 mL·kg-1葛根素注射液组的血压变化不明显,而0.47 mL·kg-1葛根素注射液引起犬血压明显降低,平均动脉压在药后30 min时从药前的(115.35 ±7.73) mmHg降低到(91.74± 10.18) mmHg (P ＜0.01),收缩压从药前的(147.33±14.65) mmHg降低到(112.88 ±6.51) mmHg(P ＜0.01),但未见明显的体征变化.结论:清开灵注射液对清醒Beagle犬血压没有明显影响,葛根素注射液可引起清醒Beagle犬血压下降,且与剂量相关,可能是由其自身的药理作用引起的,初步判断清开灵注射液和葛根素注射液没有引起清醒Beagle犬发生类过敏反应.     

Evaluation of terfenadine and ketoconazole-induced QT prolongation in conscious telemetered guinea pigs

Terfenadine and ketoconazole are the most widely used positive reference agents in non-clinical cardiac repolarization safety studies. The aim of the present study was to evaluate the effects of terfenadine, ketoconazole and their combination on QT prolongation using conscious guinea pigs. Conscious telemetered guinea pigs were orally administered terfenadine (50 mg/kg), ketoconazole (200 mg/kg) or a combination of the two, and effects on QT were recorded using a telemetry system. The QT correction was carried out with Bazett's formula to eliminate confounding effect of HR. Neither terfenadine nor ketoconazole produced any effect on the RR and QT intervals, QRS complex or heart rate (HR). However, a combination of terfenadine and ketoconazole significantly prolonged the RR and QT intervals and decreased HR in a time-dependent manner. This study demonstrated that the combination of terfenadine and ketoconazole produces QT prolongation in conscious telemetered guinea pigs.     

Chronic central administration of apelin-13 over 10 days increases food intake, body weight, locomotor activity and body temperature in C57BL/6 mice

The peptide apelin has been located in a wide range of tissues, including the gastrointestinal tract, stomach and adipose tissue. Apelin and its receptor has also been detected in the arcuate and paraventricular nuclei of the hypothalamus, which are involved in the control of feeding behaviour and energy expenditure. This distribution suggests apelin may play a role in energy homeostasis, but previous attempts to discern the effects of apelin by acute injection into the brain have yielded conflicting results. We examined the effect of a chronic 10-day intracerebroventricular (i.c.v.) infusion of apelin-13 into the third ventricle on food intake, body temperature and locomotor activity in C57BL/6 mice. Apelin-13 (1 microg/day) increased food intake significantly on days 3-7 of infusion; thereafter, food intake of treated and control individuals converged. This convergence was potentially because of progressive conversion of apelin-13 to [Pyr(1)]apelin-13 which has a four-fold lower receptor binding affinity at the orphan G protein-coupled receptor, APJ. Locomotor activity was also higher in the apelin-treated mice, especially during the nocturnal peak, when most feeding occurs, and the first hours of the light phase. Body temperature was also elevated during this increased period of activity, but was otherwise unaffected. Apelin-13-infused animals gained more weight than the saline-infused controls, suggesting the elevated locomotor activity did not offset the increased food intake. Elevated locomotion and the consequent increases in body temperature were probably secondary effects to the increased food intake. These results suggest that apelin-13 may play a central role in the control of feeding behaviour and is one of only two peripheral ligands known to stimulate rather than inhibit intake. As apelin production is elevated during obesity, this may provide an important feed-forward mechanism exacerbating the problem. Antagonists of the apelin receptor may therefore be useful pharmaceuticals in the treatment of obesity.     

Does access to bed‐chair pressure sensors reduce physical restraint use in the rehabilitative care setting?

Background. The common use of physical restraints in older people in hospitals and nursing homes has been associated with injurious falls, decreased mobility and disorientation. By offering access to bed‐chair pressure sensors in hospitalized patients with perceived fall risk, nurses may be less inclined to resort to physical restraints, thereby improving clinical outcomes. Aims and objectives. To investigate whether the access of bed‐chair pressure sensors reduces physical restraint use in geriatric rehabilitation wards. Design. Randomized controlled trial. Methods. Consecutively, patients admitted to two geriatric wards specialized in stroke rehabilitation in a convalescent hospital in Hong Kong, and who were perceived by nurses to be at risk of falls were randomly assigned to intervention and control groups. For the intervention group subjects, nurses were given access to bed‐chair pressure sensors. These sensors were not available to control group subjects, as in usual practice. The trial continued until discharge. The primary outcomes were the proportion of subjects restrained by trunk restraint, bedrails or chair‐board and the proportion of trial days in which each type of physical restraint was applied. The secondary outcomes were the proportions of those who improved in the mobility and transfer domains of modified Barthel index on discharge and of those who fell. Results. One hundred and eighty subjects were randomized. Fifty (55·6%) out of the 90 intervention group subjects received the intervention. There was no significant difference between the intervention and control groups in the proportions and duration of having the three types of physical restraints. There was also no group difference in the chance of improving in mobility and transfer ability, and of having a fall. Conclusion. Access to bed‐chair pressure sensor device neither reduced the use of physical restraints nor improved the clinical outcomes of older patients with perceived fall risk. Relevance to clinical practice. The provision of bed‐chair pressure sensors may only be effective in reducing physical restraints when it is combined with an organized physical restraint reduction programme.     

“Patient reported outcomes” following experimental surgery—using telemetry to assess movement in experimental ovine models

Many potential treatments for orthopedic disease fail at the animal to human translational hurdle. One reason for this failure is that the majority of pre‐clinical outcome measurements emphasize structural changes, such as gross morphology and histology, and do not address pain or its alleviation, which is a key component of treatment success in man. With increasing emphasis on “patient reported outcome measurements (PROM)” in clinical practice, in this study we have used two different telemetric methods (geolocation and Fitbark activity trackers, Kansas City, MO) to measure movement behavior, i.e., an indirect PROM, in an ovine osteoarthritis induction and an osteochondral defect model performed in adult female Welsh Mountain sheep. This study demonstrates that both systems can be used to track movement and activity of experimental sheep before and after surgery and that the Geolocator system recorded a decrease in distance moved and activity at the end of the experimental period in both models. The Fitbark activity tracker also recorded significant alterations in movement behavior at the end of these studies and this method of recording showed a correlation between Fitbark data and radiography, macroscopic and histological scoring (well recognized outcome measurements), particularly in animals with large (10 mm) defects, i.e., more severe pathology. These results suggest that telemetry is able to track movement behavior in experimental sheep and that the methodology should be considered for inclusion in outcome measures in preclinical orthopedic research. © 2017 The Authors. Journal of Orthopaedic Research® Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 36:1498–1507, 2018.