Kukulya
Amy L.
Kukulya
Amy L.
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ArticleAutonomous water sampler for oil spill response(MDPI, 2022-04-11) Gomez-Ibanez, Daniel ; Kukulya, Amy L. ; Belani, Abhimanyu ; Conmy, Robyn N. ; Sundaravadivelu, Devi ; DiPinto, LisaA newly developed water sampling system enables autonomous detection and sampling of underwater oil plumes. The Midwater Oil Sampler collects multiple 1-L samples of seawater when preset criteria are met. The sampler has a hydrocarbon-free sample path and can be configured with several modules of six glass sample bottles. In August 2019, the sampler was deployed on an autonomous underwater vehicle and captured targeted water samples in natural oil seeps offshore Santa Barbara, CA, USA.
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ArticleImproved biodiversity detection using a large-volume environmental DNA sampler with in situ filtration and implications for marine eDNA sampling strategies(Elsevier, 2022-09-22) Govindarajan, Annette F. ; McCartin, Luke ; Adams, Allan ; Allan, Elizabeth ; Belani, Abhimanyu ; Francolini, Rene ; Fujii, Justin ; Gomez-Ibañez, Daniel ; Kukulya, Amy ; Marin, Fredrick ; Tradd, Kaitlyn ; Yoerger, Dana R. ; McDermott, Jill M. ; Herrera, SantiagoMetabarcoding analysis of environmental DNA samples is a promising new tool for marine biodiversity and conservation. Typically, seawater samples are obtained using Niskin bottles and filtered to collect eDNA. However, standard sample volumes are small relative to the scale of the environment, conventional collection strategies are limited, and the filtration process is time consuming. To overcome these limitations, we developed a new large – volume eDNA sampler with in situ filtration, capable of taking up to 12 samples per deployment. We conducted three deployments of our sampler on the robotic vehicle Mesobot in the Flower Garden Banks National Marine Sanctuary in the northwestern Gulf of Mexico and collected samples from 20 to 400 m depth. We compared the large volume (∼40–60 L) samples collected by Mesobot with small volume (∼2 L) samples collected using the conventional CTD rosette – mounted Niskin bottle approach. We sequenced the V9 region of 18S rRNA, which detects a broad range of invertebrate taxa, and found that while both methods detected biodiversity changes associated with depth, our large volume samples detected approximately 66% more taxa than the CTD small volume samples. We found that the fraction of the eDNA signal originating from metazoans relative to the total eDNA signal decreased with sampling depth, indicating that larger volume samples may be especially important for detecting metazoans in mesopelagic and deep ocean environments. We also noted substantial variability in biological replicates from both the large volume Mesobot and small volume CTD sample sets. Both of the sample sets also identified taxa that the other did not – although the number of unique taxa associated with the Mesobot samples was almost four times larger than those from the CTD samples. Large volume eDNA sampling with in situ filtration, particularly when coupled with robotic platforms, has great potential for marine biodiversity surveys, and we discuss practical methodological and sampling considerations for future applications.•A large-volume eDNA sampler was developed and deployed on the midwater robot Mesobot.•Compared to conventional small-volume samples, the sampler detected more metazoan taxa.•Both sampling approaches detected community changes with depth on the scale of 10's of meters.•The metazoan eDNA signal declined with depth.•Large volume sampling may be especially important in the mesopelagic and deep sea.
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ArticleLinking glacially modified waters to catchment-scale subglacial discharge using autonomous underwater vehicle observations(Copernicus Publications on behalf of the European Geosciences Union, 2016-02-24) Stevens, Laura A. ; Straneo, Fiamma ; Das, Sarah B. ; Plueddemann, Albert J. ; Kukulya, Amy L. ; Morlighem, MathieuMeasurements of near-ice (< 200 m) hydrography and near-terminus subglacial hydrology are lacking, due in large part to the difficulty in working at the margin of calving glaciers. Here we pair detailed hydrographic and bathymetric measurements collected with an autonomous underwater vehicle as close as 150 m from the ice–ocean interface of the Saqqarliup sermia–Sarqardleq Fjord system, West Greenland, with modeled and observed subglacial discharge locations and magnitudes. We find evidence of two main types of subsurface glacially modified water (GMW) with distinct properties and locations. The two GMW locations also align with modeled runoff discharged at separate locations along the grounded margin corresponding with two prominent subcatchments beneath Saqqarliup sermia. Thus, near-ice observations and subglacial discharge routing indicate that runoff from this glacier occurs primarily at two discrete locations and gives rise to two distinct glacially modified waters. Furthermore, we show that the location with the largest subglacial discharge is associated with the lighter, fresher glacially modified water mass. This is qualitatively consistent with results from an idealized plume model.
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ArticleTurtleCam: A "smart" autonomous underwater vehicle for investigating behaviors and habitats of sea turtles(Frontiers Media, 2018-03-20) Dodge, Kara L. ; Kukulya, Amy L. ; Burke, Erin ; Baumgartner, Mark F.Sea turtles inhabiting coastal environments routinely encounter anthropogenic hazards, including fisheries, vessel traffic, pollution, dredging, and drilling. To support mitigation of potential threats, it is important to understand fine-scale sea turtle behaviors in a variety of habitats. Recent advancements in autonomous underwater vehicles (AUVs) now make it possible to directly observe and study the subsurface behaviors and habitats of marine megafauna, including sea turtles. Here, we describe a “smart” AUV capability developed to study free-swimming marine animals, and demonstrate the utility of this technology in a pilot study investigating the behaviors and habitat of leatherback turtles (Dermochelys coriacea). We used a Remote Environmental Monitoring UnitS (REMUS-100) AUV, designated “TurtleCam,” that was modified to locate, follow and film tagged turtles for up to 8 h while simultaneously collecting environmental data. The TurtleCam system consists of a 100-m depth rated vehicle outfitted with a circular Ultra-Short BaseLine receiver array for omni-directional tracking of a tagged animal via a custom transponder tag that we attached to the turtle with two suction cups. The AUV collects video with six high-definition cameras (five mounted in the vehicle nose and one mounted aft) and we added a camera to the animal-borne transponder tag to record behavior from the turtle's perspective. Since behavior is likely a response to habitat factors, we collected concurrent in situ oceanographic data (bathymetry, temperature, salinity, chlorophyll-a, turbidity, currents) along the turtle's track. We tested the TurtleCam system during 2016 and 2017 in a densely populated coastal region off Cape Cod, Massachusetts, USA, where foraging leatherbacks overlap with fixed fishing gear and concentrated commercial and recreational vessel traffic. Here we present example data from one leatherback turtle to demonstrate the utility of TurtleCam. The concurrent video, localization, depth and environmental data allowed us to characterize leatherback diving behavior, foraging ecology, and habitat use, and to assess how turtle behavior mediates risk to impacts from anthropogenic activities. Our study demonstrates that an AUV can successfully track and image leatherback turtles feeding in a coastal environment, resulting in novel observations of three-dimensional subsurface behaviors and habitat use, with implications for sea turtle management and conservation.
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PreprintSubsurface observations of white shark predatory behaviour using an autonomous underwater vehicle( 2015-09) Skomal, Gregory B. ; Hoyos-Padilla, E. Mauricio ; Kukulya, Amy L. ; Stokey, Roger P.Investigations of animal habitat use and behaviour are important for understanding the ecology of animals and are vital for making informed conservation decisions. Most of what is known about shark behaviour comes from direct observations at shallow depths, captive studies, baited and chance encounters, and inferences from tracking and tagging data. Over the course of the last two decades, new technologies have been developed to track the movements of marine animals over multiple spatial and temporal scales, but they do little to reveal what these animals are actually doing. It is well established that the white shark, Carcharodon carcharias, is a top predator of marine mammals and fishes, but virtually all published observations of white shark predatory behaviour are based on surface interactions with pinnipeds at well-studied white shark aggregation areas. Guadalupe Island off the coast of Mexico is a seasonal aggregation site for white sharks, which are presumably drawn to the island to feed upon pinnipeds, yet predation has rarely been observed. In this study, an Autonomous Underwater Vehicle (AUV) was used to test this technology as a viable tool for directly observing the behaviour of marine animals and to investigate the behaviour, habitat use, and feeding ecology of white sharks off Guadalupe Island. During the period 31 October – 7 November 2013, six AUV missions were conducted to track one male and three female white sharks, ranging in estimated total length (TL) from 3.9-5.7 m, off the northeast coast of Guadalupe Island. In doing so, the AUV generated over 13 hours of behavioral data for white sharks at depths up to 90 m. The white sharks remained in the area for the duration of each mission and moved through broad depth and temperature ranges from the surface to 163.8 m (mean ± SD = 112.5 ± 40.3 m) and 7.9-27.1 °C (mean ± SD = 12.7 ± 2.9 °C), respectively. Video footage and AUV sensor data revealed that two of the white sharks being tracked and eight other white sharks in the area approached (n=17), bumped (n=4), and bit (n=9) the AUV during these tracks. In this study, it was demonstrated that an AUV can be used to effectively track and observe the behaviour of a large pelagic animal, the white shark. In doing so, the first observations of subsurface predatory behaviour were generated for this species. At its current state of development, this technology clearly offers a new and innovative tool for tracking the fine-scale behaviour of marine animals.
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ArticleAutonomous tracking of salinity-intrusion fronts by a long-range autonomous underwater vehicle(Institute of Electrical and Electronics Engineers, 2022-04-18) Zhang, Yanwu ; Yoder, Noa ; Kieft, Brian ; Kukulya, Amy L. ; Hobson, Brett W. ; Ryan, Svenja ; Gawarkiewicz, Glen G.Shoreward intrusions of anomalously salty water along the continental shelf of the Middle Atlantic Bight are often observed in spring and summer. Exchange of heat, nutrients, and carbon across the salinity-intrusion front has a significant impact on the marine ecosystem and fisheries. In this article, we developed a method of using an autonomous underwater vehicle (AUV) to detect a salinity-intrusion front and track the front's movement. Autonomous front detection is based on the different vertical structures of salinity in the two distinct water types: the vertical difference of salinity is large in the intruding saltier water because of the salinity “tongue” at mid-depth, but is small in the nearshore fresher water due to absence of the salinity anomaly. Every time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to cross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzags sweep back and forth to track the front as it moves over time. From June 25 to 30, 2021, a Tethys-class long-range AUV mapped and tracked a salinity-intrusion front on the southern New England shelf. The frontal tracking revealed the salinity intrusion's 3-D structure and temporal evolution with unprecedented detail.