A Wake-Based Correlate of Swimming Performance and Foraging Behavior in Seven Co-Occurring Jellyfish Species

It is generally accepted that animal–fluid interactions have shaped the evolution of animals that swim and fly. However, the functional ecological advantages associated with those adaptations are currently difficult to predict on the basis of measurements of the animal–fluid interactions. We report the identification of a robust, fluid dynamic correlate of distinct ecological functions in seven jellyfish species that represent a broad range of morphologies and foraging modes. Since the comparative study is based on properties of the vortex wake – specifically, a fluid dynamical concept called optimal vortex formation – and not on details of animal morphology or phylogeny, we propose that higher organisms can also be understood in terms of these fluid dynamic organizing principles. This enables a quantitative, physically based understanding of how alterations in the fluid dynamics of aquatic and aerial animals throughout their evolution can result in distinct ecological functions

Transport and stirring induced by vortex formation

The purpose of this study is to analyse the transport and stirring of fluid that occurs owing to the formation and growth of a laminar vortex ring. Experimental data was collected upstream and downstream of the exit plane of a piston-cylinder apparatus by particle-image velocimetry. This data was used to compute Lagrangian coherent structures to demonstrate how fluid is advected during the transient process of vortex ring formation. Similar computations were performed from computational fluid dynamics (CFD) data, which showed qualitative agreement with the experimental results, although the CFD data provides better resolution in the boundary layer of the cylinder. A parametric study is performed to demonstrate how varying the piston-stroke length-to-diameter ratio affects fluid entrainment during formation. Additionally, we study how regions of fluid are stirred together during vortex formation to help establish a quantitative understanding of the role of vortical flows in mixing. We show that identification of the flow geometry during vortex formation can aid in the determination of efficient stirring. We compare this framework with a traditional stirring metric and show that the framework presented in this paper is better suited for understanding stirring/mixing in transient flow problems. A movie is available with the online version of the paper

Augmenting biologging with supervised machine learning to study in situ behavior of the medusa Chrysaora fuscescens

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Fannjiang, C., Mooney, T. A., Cones, S., Mann, D., Shorter, K. A., & Katija, K. Augmenting biologging with supervised machine learning to study in situ behavior of the medusa Chrysaora fuscescens. Journal of Experimental Biology, 222, (2019): jeb.207654, doi:10.1242/jeb.207654.Zooplankton play critical roles in marine ecosystems, yet their fine-scale behavior remains poorly understood because of the difficulty in studying individuals in situ. Here, we combine biologging with supervised machine learning (ML) to propose a pipeline for studying in situ behavior of larger zooplankton such as jellyfish. We deployed the ITAG, a biologging package with high-resolution motion sensors designed for soft-bodied invertebrates, on eight Chrysaora fuscescens in Monterey Bay, using the tether method for retrieval. By analyzing simultaneous video footage of the tagged jellyfish, we developed ML methods to: (1) identify periods of tag data corrupted by the tether method, which may have compromised prior research findings, and (2) classify jellyfish behaviors. Our tools yield characterizations of fine-scale jellyfish activity and orientation over long durations, and we conclude that it is essential to develop behavioral classifiers on in situ rather than laboratory data.This work was supported by the David and Lucile Packard Foundation (to K.K.), the Woods Hole Oceanographic Institution (WHOI) Green Innovation Award (to T.A.M., K.K. and K.A.S.) and National Science Foundation (NSF) DBI collaborative awards (1455593 to T.A.M. and K.A.S.; 1455501 to K.K.). Deposited in PMC for immediate release

ITAG : an eco-sensor for fine-scale behavioral measurements of soft-bodied marine invertebrates

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Animal Biotelemetry 3 (2015): 31, doi:10.1186/s40317-015-0076-1.Soft-bodied marine invertebrates comprise a keystone component of ocean ecosystems; however, we know little of their behaviors and physiological responses within their natural habitat. Quantifying ocean conditions and measuring organismal responses to the physical environment is vital to understanding the species or ecosystem-level influences of a changing ocean. Here we describe a novel, soft-bodied invertebrate eco-sensor tag (the ITAG), its trial attachments to squid and jellyfish, and the fine-scale behavioral measurements recorded on captive animals. Tags were deployed on five jellyfish (Aurelia aurita) and eight squid (Loligo forbesi) in laboratory conditions for up to 24 h. Using concurrent video and tag data, movement signatures for specific behaviors were identified. These behaviors included straight swimming (for jellyfish), and finning, jetting, direction reversal and turning (for squid). Overall activity levels were quantified using the root-mean-squared magnitude of acceleration, and finning was found to be the dominant squid swimming gait during captive squid experiments. External light sensors on the ITAG were used to compare squid swimming activity relative to ambient light across a ca. 20-h trial. The deployments revealed that while swimming was continuous for captive squid, energetically costly swimming behaviors (i.e., jetting and rapid direction reversals) occurred infrequently. These data reflect the usefulness of the ITAG to study trade-offs between behavior and energy expenditure in captive and wild animals. These data demonstrate that eco-sensors with sufficiently high sampling rates can be applied to quantify behavior of soft-bodied taxa and changes in behavior due to interactions with the surrounding environment. The methods and tool described here open the door for substantial lab and field-based measurements of fine-scale behavior, physiology, and concurrent environmental parameters that will inform fisheries management, and elucidate the ecology of these important keystone taxa.This work was supported by WHOI’s Ocean Life Institute and the Innovative Technology Program, Hopkins Marine Station’s Marine Life Observatory (to KK), as well as the National Science Foundation’s Ocean Acidification Program (to TAM) and NSF’s Program for Innovative Development of Biological Research (to TAM, KK and KAS)

Quantifying the swimming gaits of veined squid (Loligo forbesi) using bio-logging tags

Author Posting. © Company of Biologists, 2019. This article is posted here by permission of Company of Biologists for personal use, not for redistribution. The definitive version was published in Journal of Experimental Biology 222 (2019):jeb.198226, doi: 10.1242/jeb.198226.Squid are mobile, diverse, ecologically important marine organisms whose behavior and habitat use can have substantial impacts on ecosystems and fisheries. However, as a consequence in part of the inherent challenges of monitoring squid in their natural marine environment, fine-scale behavioral observations of these free-swimming, soft-bodied animals are rare. Bio-logging tags provide an emerging way to remotely study squid behavior in their natural environments. Here, we applied a novel, high-resolution bio-logging tag (ITAG) to seven veined squid, Loligo forbesii, in a controlled experimental environment to quantify their short-term (24 h) behavioral patterns. Tag accelerometer, magnetometer and pressure data were used to develop automated gait classification algorithms based on overall dynamic body acceleration, and a subset of the events were assessed and confirmed using concurrently collected video data. Finning, flapping and jetting gaits were observed, with the low-acceleration finning gaits detected most often. The animals routinely used a finning gait to ascend (climb) and then glide during descent with fins extended in the tank's water column, a possible strategy to improve swimming efficiency for these negatively buoyant animals. Arms- and mantle-first directional swimming were observed in approximately equal proportions, and the squid were slightly but significantly more active at night. These tag-based observations are novel for squid and indicate a more efficient mode of movement than suggested by some previous observations. The combination of sensing, classification and estimation developed and applied here will enable the quantification of squid activity patterns in the wild to provide new biological information, such as in situ identification of behavioral states, temporal patterns, habitat requirements, energy expenditure and interactions of squid through space–time in the wild.This work was supported by Woods Hole Oceanographic Institution’s Ocean Life Institute and the Innovative Technology Program, Hopkins Marine Station’s Marine Life Observatory (to K.K.), as well as the National Science Foundation Program for Instrument Development for Biological Research (award no. 1455593 to T.A.M., K.K. and K.A.S.). F.C. thanks the Presidentís International Fellowship Initiative (PIFI) of the Chinese Academy of Science. G.E.F. thanks the National Science Foundation GRFP and National Science Foundation REU programs for support of this research.2020-10-2

Mesobot : An Autonomous Underwater Vehicle for Tracking and Sampling Midwater Targets

Mesobot, a new class of autonomous underwater vehicle, will address specific unmet needs for observing slow-moving targets in the midwater ocean. Mesobot will track targets such as zooplankton, fish, and descending particle aggregates using a control system based on stereo cameras and a combination of thrusters and a variable buoyancy system. The vehicle will also be able to collect biogeochemical and environmental DNA (eDNA) samples using a pumped filter sampler

Propulsion in cubomedusae : mechanisms and utility

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS ONE 8 (2013): e56393, doi:10.1371/journal.pone.0056393.Evolutionary constraints which limit the forces produced during bell contractions of medusae affect the overall medusan morphospace such that jet propulsion is limited to only small medusae. Cubomedusae, which often possess large prolate bells and are thought to swim via jet propulsion, appear to violate the theoretical constraints which determine the medusan morphospace. To examine propulsion by cubomedusae, we quantified size related changes in wake dynamics, bell shape, swimming and turning kinematics of two species of cubomedusae, Chironex fleckeri and Chiropsella bronzie. During growth, these cubomedusae transitioned from using jet propulsion at smaller sizes to a rowing-jetting hybrid mode of propulsion at larger sizes. Simple modifications in the flexibility and kinematics of their velarium appeared to be sufficient to alter their propulsive mode. Turning occurs during both bell contraction and expansion and is achieved by generating asymmetric vortex structures during both stages of the swimming cycle. Swimming characteristics were considered in conjunction with the unique foraging strategy used by cubomedusae.This work was supported by an ONR MURI award (N000140810654) and National Science Foundation grant OCE 0623508 to JHC, SPC, JOD. And the work was supported by the Roger Williams University Foundation to Promote Scholarship

Demystifying image-based machine learning: a practical guide to automated analysis of field imagery using modern machine learning tools

Image-based machine learning methods are becoming among the most widely-used forms of data analysis across science, technology, engineering, and industry. These methods are powerful because they can rapidly and automatically extract rich contextual and spatial information from images, a process that has historically required a large amount of human labor. A wide range of recent scientific applications have demonstrated the potential of these methods to change how researchers study the ocean. However, despite their promise, machine learning tools are still under-exploited in many domains including species and environmental monitoring, biodiversity surveys, fisheries abundance and size estimation, rare event and species detection, the study of animal behavior, and citizen science. Our objective in this article is to provide an approachable, end-to-end guide to help researchers apply image-based machine learning methods effectively to their own research problems. Using a case study, we describe how to prepare data, train and deploy models, and overcome common issues that can cause models to underperform. Importantly, we discuss how to diagnose problems that can cause poor model performance on new imagery to build robust tools that can vastly accelerate data acquisition in the marine realm. Code to perform analyses is provided at https://github.com/heinsense2/AIO_CaseStudy

Fluid Interactions That Enable Stealth Predation by the Upstream-Foraging Hydromedusa Craspedacusta Sowerbyi

Unlike most medusae that forage with tentacles trailing behind their bells, several species forage upstream of their bells using aborally located tentacles. It has been hypothesized that these medusae forage as stealth predators by placing their tentacles in more quiescent regions of flow around their bells. Consequently, they are able to capture highly mobile, sensitive prey. We used digital particle image velocimetry (DPIV) to quantitatively characterize the flow field around Craspedacusta sowerbyi, a freshwater upstream-foraging hydromedusa, to evaluate the mechanics of its stealth predation. We found that fluid velocities were minimal in front and along the sides of the bell where the tentacles are located. As a result, the deformation rates in the regions where the tentacles are located were low, below the threshold rates required to elicit an escape response in several species of copepods. Estimates of their encounter volume rates were examined on the basis of flow past the tentacles, and trade-offs associated with tentacle characteristics were evaluated