About

The SeaQL Lab at Virginia Tech is an interdisciplinary group working on different aspects of Fisheries Science, Marine Ecology and Conservation. With a special interest in sharks and rays, we look to characterize the structure and function of natural ecosystems and develop solutions for sustainable ocean use. Taking advantage of unorthodox data sources, we attempt to fill knowledge gaps that inform important ecological systems.

Research topics

• Geography
• Ecology
• Fishery
• Computer Science
• Biology
• Environmental resource management
• Business
• Geology
• Geodesy
• Environmental science
• Oceanography

Selected publications

• Underwater UHF RFID Tag for Tracking of Pebbles or Similar Things

  2025-09-08

  article1st authorCorresponding

  RFID tag have gained interest in tracking of pebbles for monitoring the morphodinamics of coasts, bancks and landslides. Generally, Low Frequency (LF) tag are used for that application. In this work we explore the possibility to use UHF tags instead. Appropriate link-budget equations show that this kind of tag can be profitably used in fresh water. We designed a small-sized tag that can be embedded in a pebble and evaluated its ability to be detected from a variable distance when placed in water. The numerical results obtained with a full-wave method are in agreement with those predicted by the link buget equation. The maximum reading distance in fresh water is about 50 cm which is comparable with that of LF tags.

  PublisherDOI

• Density-dependent network structuring within and across wild animal systems

  Nature Ecology & Evolution · 2025-09-04 · 4 citations

  articleOpen access
  PublisherOA PDFDOI

• Trophic niche partitioning between the white shark (Carcharodon carcharias) and the shortfin mako (Isurus oxyrinchus) in the central Mediterranean Sea

  Wildlife Research · 2025-09-22 · 2 citations

  articleOpen accessSenior author

  Context Large predatory sharks such as the white shark (WS) and shortfin mako (SMK) have been historically depleted to Critically Endangered levels in the Mediterranean Sea. Despite their low abundance, the Tunisian Plateau seemingly plays a crucial ecological role as a potential nursery and feeding ground, supporting the early life stages of these species. Aims Here we investigated the trophic ecology of WS and SMK, which co-exist in the Tunisian Plateau, focusing on juveniles and young-of-the-year (YOY). Methods We conducted stable isotope analysis of carbon (δ13C) and nitrogen (δ15N) from muscle samples to assess the trophic niche breadth and overlap between the two species. We estimated the possible prey contribution with Bayesian mixing models under two prey-grouping schemes, namely, functional prey categories (cephalopods, small pelagics, large pelagics, demersal fishes, dolphins) and habitat-based categories (coastal-pelagic, oceanic-pelagic, coastal-demersal, bathyal-demersal). Key results White sharks had significantly higher δ15N values than did shortfin makos, but no differences in age classes or sexes were detected, and no inter- or intraspecific variation in δ13C values were observed. Corrected standard ellipse areas were similar, with only ~12% core-area overlap between species, providing evidence for niche partitioning. The mixing model results were consistent across prey grouping schemes; WS seemingly display a generalist diet both in functional preys and foraging habitat, whereas SMK rely more on small pelagic fishes largely derived from coastal-pelagic habitats. Conclusions Trophic segregation between WS and SMK supports their co-existence on the Tunisian Plateau. Such differential resource use is likely to minimize interspecific competition and promote stable sympatry in this productive area. Implications Our results constitute the first isotopic and mixing-model-based dietary assessment of early life stage WS and SMK in the central Mediterranean. Their sightings may reflect both a higher population abundance in the region and intense fishing pressure. Given their trophic roles and the potential ecological consequences of their decline, incorporating trophic information with complementary methods (e.g. telemetry) could be useful to track feeding-ground utilization. Such integrated approach could inform timing and placement of mitigation measures (e.g. gear modifications) tailored to each species’ trophic habits, helping sustain their survival in the Mediterranean Sea.

  PublisherOA PDFDOI

• Digital Conservation Can Fill Data Gaps in Data‐Poor Regions: Case of Elasmobranchs in India

  Aquatic Conservation Marine and Freshwater Ecosystems · 2025-11-01

  articleOpen access

  ABSTRACT Internet and social media use have increased significantly over the past decade, resulting in huge volumes of biodiversity data that are potentially cost‐effective means to better inform biodiversity conservation and resource management. We examine the role of digital conservation in a data‐poor context of the Global South, using sharks and rays in India as a case study. India is a top shark fishing nation characterised by few, disconnected species‐specific research and conservation projects but lacks nation‐scale conservation insights. We analysed 1293 elasmobranch‐related posts and recorded 83 species from six social media and citizen science platforms. We identified two key dimensions of data—ecological and social (including politics and governance)—and tested the effectiveness of these data in mirroring or complementing scientific research. We found that digital platforms were (i) spatio‐temporally better representative than scientific research, because they included 96 underrepresented regions and spanned 18 years, despite some biases; (ii) useful to detect the presence of data‐poor and rare species; and (iii) effective to detect human–elasmobranch interactions and public perceptions towards sharks and rays, topics which are poorly represented in the scientific literature. We find that digital conservation can therefore be utilised to generate national‐scale insights in regions with limited resources and site‐specific data. It is also useful to fill socioecological data gaps to drive better management and increased public participation/awareness for conservation. The multidisciplinary nature of data emerging from digital conservation has high relevance for current and future conservation of species.

  PublisherOA PDFDOI

• From Data Deficient to Big Data in Shark Conservation

  Fish and Fisheries · 2025-08-11 · 1 citations

  articleOpen access1st authorCorresponding

  ABSTRACT Citizen science is increasingly harnessed worldwide to gather data otherwise requiring a prohibitive investment of funding and time. Meanwhile, the revolution in digital communication offers opportunities from crowdsourcing, big data approaches and social network mining to quickly and cost‐effectively fill major gaps in knowledge necessary to protect endangered populations. Sharks are among the most endangered and data‐poor vertebrates in the ocean. Mainly due to overfishing, many shark populations are declining worldwide, while most species lack basic abundance, distribution and life‐history data. Hence, filling knowledge gaps across taxa, ecosystems, and regions is urgently needed to increase our understanding of their ecology, develop effective conservation actions and reverse their loss. Here, we introduce a novel citizen science and crowdsourcing approach for conservation through sharkPulse, a new platform automating data ingestion and organisation to build the largest database of shark occurrence records to date. Designed to complement and extend similar biodiversity monitoring tools relying heavily on user submissions, sharkPulse aims to source large streams of online shark images and transform them into occurrence records, filling knowledge gaps in shark ecology and biology. This platform offers a blueprint to leverage AI and big data approaches, social network data mining and participatory science to efficiently and continuously source visual media materials and transform the monitoring of data‐limited marine and terrestrial animal populations.

  PublisherOA PDFDOI

• Recovery of Delaware Bay horseshoe crabs following harvest reductions

  Marine and Coastal Fisheries · 2025-09-01

  articleOpen access

  ABSTRACT Objective Horseshoe crabs Limulus polyphemus play a vital role in the Delaware Bay ecosystem. The migratory stopover of several shorebird species occurs during the horseshoe crab spawning season, and the eggs of horseshoe crabs provide an essential food source to fuel their northward migration to breeding areas. High commercial fishery use of horseshoe crabs as bait during the 1990s coincided with a decline in crabs and shorebirds, particularly the red knot Calidris canutus rufa, which has been listed as threatened under the U.S. Endangered Species Act since 2015. In response to the population decline of shorebirds, the Atlantic States Marine Fisheries Commission began reducing the harvest of horseshoe crabs in 2000 with a goal of rebuilding the population of horseshoe crabs and shorebirds that depend upon them. The objective of this analysis was to determine whether horseshoe crab harvest management in the Delaware Bay region has increased the abundance of the species in recent years. Methods We analyzed data from fisheries-independent trawl surveys of horseshoe crab relative abundance using a Bayesian hierarchical model to determine whether harvest management has resulted in the rebuilding of the horseshoe crab population to levels seen in 1990—a period before the overuse of horseshoe crabs and the decline in the population of red knots. Results Data from multiple surveys showed that the horseshoe crab population in Delaware Bay declined from the 1990s through approximately 2005, was relatively low and stable until 2010, and then increased through 2023, with a 0.38 probability of exceeding the 1990 level. Conclusions The results of this analysis support the effectiveness of management decisions related to horseshoe crabs in the Delaware Bay region. In response to harvest restrictions, the abundance of horseshoe crabs has neared levels observed in the early 1990s—a period prior to high commercial use and a decline in both horseshoe crabs and shorebirds that depend on them for food during annual migrations.

  PublisherDOI

• Estimating the spatial distribution of the white shark in the Mediterranean Sea via an integrated species distribution model accounting for physical barriers

  Environmetrics · 2024-07-08 · 12 citations

  articleOpen access

  Abstract Conserving oceanic apex predators, such as sharks, is of utmost importance. However, scant abundance and distribution data often challenge understanding the population status of many threatened species. Occurrence records are often scarce and opportunistic, and fieldwork aimed to retrieve additional data is expensive and prone to failure. Integrating various data sources becomes crucial to developing species distribution models for informed sampling and conservation purposes. The white shark, for example, is a rare but persistent inhabitant of the Mediterranean Sea. Here, it is considered Critically Endangered by the IUCN, while population abundance, distribution patterns, and habitat use are still poorly known. This study uses available occurrence records from 1985 to 2021 from diverse sources to construct a spatial log‐Gaussian Cox process, with data‐source specific detection functions and thinning, and accounting for physical barriers. This model estimates white shark presence intensity alongside uncertainty through a Bayesian approach with Integrated Nested Laplace Approximation (INLA) and the inlabru R package. For the first time, we projected species occurrence hot spots and landscapes of relative abundance (continuous measure of animal density in space) throughout the Mediterranean Sea. This approach can be used with other rare species for which presence‐only data from different sources are available.

  PublisherOA PDFDOI

• First satellite track of a juvenile shortfin mako shark (Isurus oxyrinchus) in the Mediterranean Sea

  Frontiers in Marine Science · 2024-12-09 · 2 citations

  articleOpen accessSenior author

  The shortfin mako shark (Isurus oxyrinchus) is a highly mobile, coastal littoral, and epipelagic oceanic species broadly distributed in tropical, subtropical, and temperate seas worldwide (Rigby et al., 2019). In recent years, there has been growing recognition of the impacts of overfishing on shortfin mako populations, and the species is now listed as Endangered by the International Union for the Conservation of Nature (IUCN) (Rigby et al., 2019). The species is listed as Critically Endangered in the Mediterranean Sea due to long-term and continuing exploitation coupled with inadequate management (Walls and Soldo, 2016). Of particular concern is the ongoing capture of juvenile mako sharks in the Central Mediterranean and the Strait of Sicily, which have been identified as potential nursery areas (Walls and Soldo, 2016;Cattano et al., 2023;Mancusi et al., 2023).Even with significant declines in pelagic sharks regionally (Ferretti et al., 2008), sharks continue to be occasionally targeted in the Mediterranean Sea, though the most critical risk to shark populations in the region is bycatch in other fisheries (Bradai et al., 2018;Carpentieri et al., 2021). In the Mediterranean, most fishers typically retain their shark bycatch, with some estimates of shark discard rates as low as 1% (Megalofonou et al., 2005) even for protected species, though discard rates are likely to vary by season and gear (Carpentieri et al., 2021). Despite their imperiled status, shortfin mako sharks remain one of the region's commonly encountered sharks for fishers, especially for longlines (Carpentieri et al., 2021), and sharks are typically retained despite falling under regional protections such as the Bern Convention, Bonn Convention, and Barcelona Convention (Serena et al., 2014). Of additional concern is the relatively unmonitored recreational fishery, which may additionally encounter high numbers of shortfin mako sharks, many of which are retained, but the scale of this fishery is not well known (Udovičić et al., 2019;Panayiotou et al., 2020). Concerningly, young-of-the-year (YOY) and juvenile specimens comprise the bulk of captured individuals reported in the Mediterranean (Saidi et al., 2019;Udovičić et al., 2019;Panayiotou et al., 2020;Cattano et al., 2023;Mancusi et al., 2023;Scacco et al., 2023). Given the life history of shortfin mako sharks, particularly their advanced age at maturity (Natanson et al., 2020), this frequent and ongoing capture of juvenile sharks represents a severe threat to regional populations, as many sharks will never reach maturity, let alone successfully reproduce. These losses highlight the need for more detailed information regarding the movement patterns and space use of juvenile shortfin mako sharks, for which little is known in the Mediterranean.In recent years, a proliferation of telemetry studies has drastically improved our understanding of the movements and space use of large marine predators like shortfin mako sharks around the globe (Queiroz et al., 2019); however, virtually no study has focused on Mediterranean populations, especially sharks. Here, we report the satellite track from a pop-off archival tag (PAT) deployed on a juvenile shortfin mako shark in the Mediterranean Sea in May 2023. To our knowledge, this track represents the first satellite tag deployed on a shortfin mako shark in the Mediterranean Sea. We describe the horizontal and vertical movements the study shark performed over 54 days at liberty (DAL), discussing potential drivers for the observed movements and the implications of the track for the conservation of shortfin mako sharks regionally.We opportunistically tagged a juvenile female shortfin mako shark (estimated size = ~120 cm total length; estimated age: 1-4 years) while observing longline fishing operations on the Tunisian plateau (Figure 1). The shark was tagged on the 17 th of May 2023, in the early morning, after being captured at approximately 40 meters (m) depth. The shark was captured via bottom longline in an area of the plateau characterized by seagrass meadows. The longline was deployed over a 3-hour period from 19:30-22:30 on the night of the 16 th of May 2023, and was left to soak for 90 minutes before longline retrieval commenced at midnight. The shark was observed on the line and brought to the boat at approximately 03:15 in the morning, roughly halfway through the longline retrieval. The shark was quickly brought on board and tagged with a PAT (Model: MiniPAT, Wildlife Computers, Redmond, WA, USA), which was attached to the shark using a monofilament tether wrapped in heat shrink tubing and a stainless-steel dart anchor that was implanted in the dorsal musculature (Jorgensen et al., 2010). The PAT tag was programmed to sample light, depth, and temperature every 3 seconds for 180 days and was deployed with the auto-detect mortality and depth threshold release (DTR) settings activated. Immediately after tagging, the hook was removed, and the shark was quickly released. All research was conducted under Virginia Tech Institutional Animal Care and Use Committee Protocol 22-094.We reconstructed the animal's most probable movements via two frequently used models for interpreting light-level position estimates from PATs. We did not omit any tag days immediately after tagging due to the limited track length. We first estimated the animal's movements using GPE3, a location processing framework using a Hidden Markov model (HMM) provided by the tag manufacturer using published methods (Pedersen et al., 2011). Initial position estimates are derived algorithmically using light curves generated during twilight events to create estimates of latitude and longitude, which are further constrained by comparing tag-derived sea surface temperatures (SSTs) with remotely sensed SSTs (obtained from NOAA Optimum Interpolation SST V2 High Resolution Dataset) at the estimated location. These position estimates are then processed within the HMM to estimate the hidden state (i.e., the animal's true location) by incorporating observation error, estimated animal speed, and the application of a bathymetric mask (from NOAA ETOPO1 1 Arc-Minute Global Relief Model) to further constrain estimated locations daily. A posterior probability distribution is generated for the most likely animal position at every time step, consisting of two estimated locations per day. We iteratively ran the HMM model with different diffusion speeds (i.e., the speed parameter controlling the hypothetical distance an animal could travel between observations) ranging from 0.75 meters per second (m/s) to 2 m/s (in intervals of 0.25 m/s) and selected the speed that resulted in the highest model score (model scores provided by the manufacturer; selected speed was 1.75 m/s). The minimum diffusion speed at which the model would converge was 0.9 m/s, so the 0.9 m/s run was used instead of the 0.75 m/s run. The range of speeds tested was selected according to the manufacturer's recommendation of 1.5-2x the average sustained swimming speed of the animal; recent studies using animal-borne biologgers have estimated mean cruising speeds for shortfin mako ranging from 0.53 m/s (Saraiva et al., 2023) to 0.91 m/s (Waller et al., 2023). Plots of tracks from all GPE3 model runs are included as Supplemental Figure S1.We additionally estimated animal positions using the methods developed in Block et al. (2011) and Wilson et al. (2015). This model also uses an HMM framework, yet there are key differences. Most notably, the latter framework incorporates a Markov chain Monte Carlo (MCMC) sampling approach to further refine the posterior probability distribution, and as such, we refer to this model as the HMM_MCMC model for the duration of the manuscript. Furthermore, the HMM_MCMC model only estimated one position per day.The tag was physically recovered on the 17 th of July 2023, while drifting 20 meters from a beach in central-eastern Sardinia, and returned to us, allowing us to access the raw, 3-second interval data records for depth and temperature rather than relying on the time-binned data that is transmitted via satellite. We analyzed the raw data to characterize time-at-depth (TAD) and time-at-temperature (TAT) distributions according to diel period. All analyses were conducted using R version 4.3.1 (R Core Team, 2023) using RStudio version 2023.09.1+494 (RStudio Team, 2023). Data manipulation was performed using packages within the tidyverse (Wickham et al., 2019), as well as the package suncalc (Thieurmel and Elmarhraoui, 2022) for assigning local sunrise and sunset times. Data visualization was performed using the following packages: ggplot2 (Wickham, 2016), marmap (Pante et al., 2023), viridis (Garnier et al., 2024) and scales (Wickham et al., 2023).On the 10 th of July 2023, after 54 DAL, the PAT's DTR was activated, causing the tag to release from its tether and float to the surface to begin satellite transmission of the binned data. MiniPAT tags are rated to withstand pressure to depths of 2,000 m; the DTR protects the tag by causing it to release at 1,800 m before it achieves crush depth. Given our knowledge of the vertical ecology of shortfin mako sharks (Vaudo et al., 2016;Andrzejaczek et al., 2022) and the rapid, consistent speed at which the tag moved to depth, the juvenile shark likely suffered a putative mortality event and sank into deep waters, causing the DTR to activate ahead of the programmed 180-day deployment period. The tag surfaced approximately 64 kilometers (km) east of Sardinia, a total linear displacement of 408 km from the point of tagging, although the actual track was significantly longer according to both models (Figure 1). There were differences in the model outputs between the GPE3 and HMM_MCMC models. The GPE3-estimated track was slightly longer (summed distance between points of 1405 km) than the HMM_MCMC track (summed distance of 1207 km), taking the shark south across the Gulf of Gabès and then east into the waters north of Libya during the second half of May and the first half of June (Figure 1A). In mid-June, GPE3 estimated that the shark began to swim consistently to the northwest, passing through the Strait of Sicily and into the Tyrrhenian Sea, covering more than 700 km in approximately three weeks. In contrast, the HMM_MCMC-estimated track suggested the shark performed much more constrained movements during the first part of its track (late May and early June), moving off the coastal shelf of the Tunisian plateau in early June into the deeper waters of the Strait of Sicily, but at a similar latitude to where it was tagged (Figure 1B). As with the GPE3estimated track, the HMM_MCMC model also showed directed movements to the Tyrrhenian Sea beginning in mid-June, although the scale of this estimated movement was smaller given the more constrained movements in the first part of the track.Notably, the depth-temperature profiles for the shark showed that for the four weeks post-tagging, the shark remained within the uppermost 50 m of the water column, primarily in the mixed layer and thermocline (Figure 2). In late May and early June, the shark made several dives in the 100 m range. By mid-June, the shark began a pattern of frequent diving to depths of 150-200 m, which continued for approximately two weeks (Figure 2A). From the start of July, diving depths were generally constrained within the uppermost 125 m of the water column; however, beginning on July 6, the mako shark began diving deeper than it had previously, reaching depths of approximately 400 m for several consecutive days, despite spending most of its time above 50 m (Figure 2B).After a prolonged period at the surface in the early morning hours of July 10, the PAT experienced a pulse of light, after which it recorded a rapid descent from the surface to approximately 110 m, followed by a slightly slower but still rapid descent, to approximately 505 m, the deepest observations recorded up until this point (Supplementary Figure S2). Over the following approximately 8 hours, the tag recorded depths ranging between 500 m and 650 m, with a general pattern of slow descent observed. This was followed by a rapid ascension from 650 m to approximately 400 m. The tag then recorded a slow descent from 400 m to 475 m over approximately 3 hours before another period of ascent, after which the tag rapidly descended to 1,800 m, activating the DTR.Overall, the shark spent 26.6% of its time within 10 m of the surface and 73.9% within the uppermost 50 m, although this pattern varied slightly by month. It was more surface-oriented during May and July, spending 40.5% and 37.5% of its time in the upper 10 m, respectively, while that figure dropped to 16.9% during June. Although the tag recorded dives to depths > 250 m and 450 m, respectively during the months of June and July, the shark spent > 90% of its time in the epipelagic (upper 100 m) both overall and within each individual month (Figure 2B).The satellite track reported here represents the first documented fine-scale movements of a shortfin mako shark in the Mediterranean, and despite representing the movements of only one animal, it reveals that juvenile mako sharks in the region can be highly mobile even at early life stages.Although the Tunisian plateau and are to a nursery for mako sharks (Walls and Soldo, 2016;Cattano et al., 2023) and other regionally et al., 2020), the juvenile shark in our study made highly movements from this area even at a Although no curves are in the Mediterranean, on data from other populations, the study shark was likely between one and four et al., et al., rapid and highly movement km minimum displacement in 54 at an early life may have conservation particularly the shortfin mako within the Mediterranean studies have documented the of and juvenile shortfin mako sharks to potential nursery areas in locations around the Mediterranean Sea, the coastal waters of and et al., et al., and the et al., 2023), the and Tyrrhenian et al., 2023), the Gulf et al., 2023), and the Sea (Udovičić et al., 2019). The track we while only for one that even early life shortfin mako sharks are of movements across the Mediterranean over time their potential to between and the nursery movements by in the Mediterranean, with additional telemetry would not be to the shortfin mako sharks tagged in and commonly km after tagging, and and individual movement that included of both and with patterns commonly but not observed et al., et al., In there is a relatively high of in shortfin mako shark movements across all life A of studies in the has documented a of movement in both and ranging from primarily with high to individuals performed movements and of and and et al., et al., 2021). This the need for further tagging studies in the Mediterranean, as we here that even at early life the nursery areas for shortfin mako sharks in the region may not be a that would have conservation implications given the on using records of to nursery areas as for both tracks directed movements the Tyrrhenian Sea, the different model outputs in the early part of the not different in total the tracks have conservation The GPE3-estimated track the shark south across the Tunisian plateau before moving east into waters, the coastal waters of the two Mediterranean with the highest of shark (Bradai et al., et al., 2021). In contrast, the movements estimated by the HMM_MCMC model during the first of the track were more at the of the Tunisian plateau and the shelf In both the shark was estimated to have quickly the need for in any conservation et al., 2023). Given the of data on the ecology of the species the deployment of additional tags across a range of life be tagging studies in the region to constrain light-level model estimates and to refine the use of and other similar HMM models in the Mediterranean during the study period is the vertical movements by the tagged shark during its time at between the horizontal position and profiles are given the in light-level the of diving during the early part of the track is likely due to the bathymetric of the position on the Tunisian where bottom depths than 50 meters are in June and July, the shark spent to of its time at depths than 100 m, while in this figure was than As the tagged shark moved from into deeper waters, it began to its vertical and notably, during the days of the track, the shark its vertical range even depths of m in the days up to the fishery drivers for the vertical the track and et al., et al., et al., et al., et al., et al., may have not vertical but also the observed movement the Tyrrhenian Sea at the of the SSTs on the Tunisian plateau frequently approach in the and while of shortfin mako are likely to vary juvenile in other of the have been to waters with temperatures to et al., et al., 2021). As SSTs regionally into the the tagged shark moved and began diving deeper and more diel profiles showed an to time in the mixed layer temperatures are during than during the day. it be that in our as the tagged shark more frequently in June and July, it continued its dives the mixed layer and continuing to to depths of meters more despite relatively temperatures meters depth (Figure even at the of the track the animal began diving to depths of 400 m Furthermore, profiles during the and were highly similar (Figure bottom the that any diel in diving was directed a the surface waters experienced in early July may have the shark to deeper waters for longer of given the to at the surface following a et al., et al., et al., additional profiles are to drivers of vertical for juvenile shortfin mako sharks temperature both horizontal and vertical movements to some et al., et al., et al., et al., 2021). likely at a in both the movements during June and July as SSTs as well as the in vertical tagging studies to the of shortfin mako sharks regionally are key given the rapid in SST in the Mediterranean over recent et al., 2022) and potential in species distributions that may from such et al., potential for the diving is that the was by has been as a for vertical in shortfin mako sharks et al., et al., 2023), with patterns in diving to the diel period. mako sharks across of the water and have been observed to their vertical range during hours et al., et al., while spending hours to the where can on et al., 2023). We did not any consistent diel patterns in vertical use during the study time at though this is an of the bathymetric to diving during significant of the track where it across the Tunisian even diving was not coupled with the movements of diel vertical the observed vertical is likely to have for the study shark as it particularly the of the track in the Tyrrhenian Sea, it began diving to m such depths the study shark to with in deep which have been identified at similar depths in other of the Mediterranean et al., predators are to use as an of their et al., et al., et al., et al., with shortfin mako sharks a species that may particularly this et al., for the observed in vertical may be with a in state as the study shark left the Tunisian plateau and began its directed movements mako sharks have been to their diving patterns are in a travel state as a with sharks diving deeper and more particularly in waters (Vaudo et al., 2024) and et al., 2021). In shortfin mako sharks may to while to that are more distributed in areas et al., et al., travel can several weeks sharks most likely even during et al., et al., Furthermore, diving while may for et al., et al., Given the limited sample size and the patterns we any drivers for the observed vertical by the study however, an animal's state and vertical of both and and drivers likely in to the study use of deep the depth recorded on the morning of the 10 th of July, the shark likely experienced a mortality event the surface in the early morning hours, after which the rapidly sank to the The of this mortality is to from tag data however, there is significant fishing pressure in the region et al., et al., et al., In and the tag recorded a of light before its rapid descent, the shark experienced an additional fishery The of the tagged shark the by sharks The tagged shark was captured via which in animal of the time (Megalofonou et al., and despite the that the study shark was tagged and it suffered a mortality event after than two satellite telemetry has that data can significantly fishing mortality in shortfin mako sharks et al., and the mortality due to a fishing further this we the that this was a mortality from our capture and tagging we not the horizontal and vertical movements during its time at liberty the movements of a deployment additionally the of with local of hours of directed shark fishing with over two were in sharks for telemetry studies (Ferretti et al., In while similar studies have encountered similar et al., 2023), the encounter rates with the of fishing this et al., 2023). Given the relatively low encounter rates of as well as the at which fishers in encounter sharks, shortfin et al., et al., 2019), and sharks (Bradai et al., with local fishers represents a to animal encounter rates and the of local into the and of research and management that are to the populations of large sharks in the only one track, we here the movement of juvenile shortfin mako sharks in the Mediterranean, to the reported of and from areas across the Mediterranean Sea by the of even sharks to travel over time The study mortality additionally the risk that shortfin mako sharks are to regionally even at early life which represents a threat to the yet can be using fisheries data additional tagging are here we to deeper into the movements and ecology of shortfin mako sharks in the Mediterranean Sea. bottom with distributions in and distributions in that for distributions vary between

  PublisherOA PDFDOI

• Environmental stress reduces shark residency to coral reefs

  Communications Biology · 2024-09-09 · 7 citations

  articleOpen access

  Coral reef ecosystems are highly threatened and can be extremely sensitive to the effects of climate change. Multiple shark species rely on coral reefs as important habitat and, as such, play a number of significant ecological roles in these ecosystems. How environmental stress impacts routine, site-attached reef shark behavior, remains relatively unexplored. Here, we combine 8 years of acoustic tracking data (2013-2020) from grey reef sharks resident to the remote coral reefs of the Chagos Archipelago in the Central Indian Ocean, with a satellite-based index of coral reef environmental stress exposure. We show that on average across the region, increased stress on the reefs significantly reduces grey reef shark residency, promoting more diffuse space use and increasing time away from shallow forereefs. Importantly, this impact has a lagged effect for up to 16 months. This may have important physiological and conservation consequences for reef sharks, as well as broader implications for reef ecosystem functioning. As climate change is predicted to increase environmental stress on coral reef ecosystems, understanding how site-attached predators respond to stress will be crucial for forecasting the functional significance of altering predator behavior and the potential impacts on conservation for both reef sharks and coral reefs themselves.

  PublisherOA PDFDOI

• SharkTrack: an accurate, generalisable software for streamlining shark and ray underwater video analysis

  arXiv (Cornell University) · 2024-07-30

  preprintOpen access

  Elasmobranchs (shark sand rays) represent a critical component of marine ecosystems. Yet, they are experiencing global population declines and effective monitoring of populations is essential to their protection. Underwater stationary videos, such as those from Baited Remote Underwater Video Stations (BRUVS), are critical for understanding elasmobranch spatial ecology and abundance. However, processing these videos requires time-consuming manual analysis that can delay conservation. To address this challenge, we developed SharkTrack, a semi-automatic underwater video analysis software. SharkTrack uses Convolutional Neural Networks (CNN) and Multi-Object Tracking to automatically detect and track elasmobranchs and provides an annotation pipeline to manually classify elasmobranch species and compute species-specific MaxN (ssMaxN), the standard metric of relative abundance. When tested on BRUVS footage from locations unseen by the CNN model during training, SharkTrack computed ssMaxN with 89% accuracy over 207 hours of footage. The semi-automatic SharkTrack pipeline required two minutes of manual classification per hour of video, an estimated 95% reduction of manual analysis time compared to traditional methods. Furthermore, we demonstrate SharkTrack accuracy across diverse marine ecosystems and elasmobranch species, an advancement compared to previous models, which were limited to specific species or locations. SharkTrack applications extend beyond BRUVS, facilitating the analysis of any underwater stationary video. By making video analysis faster and more accessible, SharkTrack enables research and conservation organisations to monitor elasmobranch populations more efficiently, thereby improving conservation efforts. To further support these goals, we provide public access to the SharkTrack software.

  PublisherOA PDFDOI

Frequent coauthors

• Barbara A. Block

  Stanford University

  143 shared

• Taylor K. Chapple

  107 shared

• Robert J. Schallert

  Pacific University

  102 shared

• Aaron B. Carlisle

  University of Delaware

  101 shared

• David J. Curnick

  98 shared

• David Tickler

  91 shared

• David Jacoby

  91 shared

• Michael J. Williamson

  Zoological Society of London

  79 shared

Labs

• SeaQL LabPI

Education

• PhD, Biology

  Dalhousie University

  2010

• MSc, Marine Science

  Politechnic University of Marche

  2003