The potential role of turbulence in modulating the migration of demersal zooplankton

Tanaka, Mamoru; Genin, Amatzia; Endo, Yuki; Ivey, Gregory; Yamazaki, Hidekatsu

doi:10.1002/lno.11646

Cited by 14 publications

(5 citation statements)

References 49 publications

(82 reference statements)

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“…In addition to enhancing imaging quality, minimizing phototaxis-induced unnatural distribution of underwater organisms [70], [74] of our lighting design could be critical for long-term in situ stationary color imaging of plankton using white-light illumination. Although color information was believed to provide distinctive features of the plankton [75], [76], it was alerted that the unconstrained white lighting by conventional darkfield imagers could lead to biased plankton composition and abundance observations [77].…”

Section: Discussion 1) Optics Performancementioning

confidence: 99%

Development of a Buoy-Borne Underwater Imaging System for In Situ Mesoplankton Monitoring of Coastal Waters

Chen

Yang

et al. 2022

IEEE J. Oceanic Eng.

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This article reports the development of an underwater imaging system and its trial on a moored surface buoy for in situ plankton monitoring of coastal waters. The imager features shadowless white light illumination by an orthogonal lamellar lighting design, resulting in high-quality underwater darkfield color imaging of planktonic particles in the size range of ∼200 µm to 40 mm and effective reduction of zooplankton phototaxis. Through raft and buoy trials, 46 804 plankton and suspending particle images have been annotated through a human-machine mutually assisted effort into a data set with 90 categories. In the meanwhile, a deep learning model based on a triclassification VGGNet-11 and multiclassification ResNet-18 convolutional neuron networks in a two-staged hierarchy has also been trained and developed. The model has been applied with human supervision to semiautomatically analyze a total of 1 545 187 images obtained from a buoy trial for six months from late spring to early winter of 2020. The high temporal resolution results well documented the variation of the mesoplankton community structure in two time series of 38 days in summer and 54 days in autumn of the target sea region. In addition, the dominant species in the trial period and a zooplankton outbreak that had threatened the safety of the nearby nuclear power plants were quantitatively Manuscript

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Section: Discussion 1) Optics Performancementioning

confidence: 99%

Development of a Buoy-Borne Underwater Imaging System for In Situ Mesoplankton Monitoring of Coastal Waters

Chen

Yang

et al. 2022

IEEE J. Oceanic Eng.

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“…In this experiment, the negative relationship between wind speeds and FIZ bias was likely caused by water currents sweeping zooplankton away from fluorometers and overwhelming any phototactic response. Wind and other physical forcing can disrupt normal zooplankton migrations (Easton and Gophen 2003; Rinke et al 2007; Tanaka et al 2020). Given that increases in wind speeds, currents, and turbulence may have a generalized depressive effect on DVM, it may be impossible to isolate any additional effect these factors may have on zooplankton behavior localized around the sensor.…”

Section: Discussionmentioning

confidence: 99%

Fluorometer optical path interference via zooplankton phototaxis: Implications for high‐frequency data collection

Moriarty¹,

Lucius

Johnston

et al. 2021

Limnology & Ocean Methods

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To measure chlorophyll a (Chl a) fluorescence (Fchl), fluorometers use an excitation wavelength that is within the visible spectrum of most zooplankton, and as a result has the potential to cause a phototactic response in zooplankton. The transparent bodies of herbivorous zooplankton may allow viable chlorophyll a within an individual's digestive tract to fluoresce in response to sensor excitation light, resulting in measurement bias. To test for this bias, a fully factorial (± zooplankton and ± light) experiment was conducted in an oligotrophic lake. Excitation light from fluorometers triggered a positive phototactic response during nighttime hours, resulting in swarms of zooplankton congregating beneath the sensor. The maximum hourly mean Fchl from nighttime/open treatments was higher and more variable than nighttime/zooplankton exclusion treatments, with the greatest single hour difference of 7.34 relative fluorescence units (RFU) vs. 0.26 RFU. In open treatments, sustained periods of Fchl exceeded 31x the values of exclusion treatments. A second series of experiments pulsed excitation lights in alternating periods in order to characterize zooplankton response times. Sensor bias was detected in as little as 20 s after initial illumination. Collectively, these results suggest that swarms of phototactic zooplankton can cause substantial bias in Fchl measurements at night. To correct for this bias, post‐processing methods using time series decomposition were demonstrated to remove the majority of Fchl bias.

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“…1). Different imaging systems such as the Cytobuoy (Dubelaar & Gerritzen 2000), IFCB (Olson & Sosik 2007), Planktoscope (Pollina et al 2022), FlowCam (Poulton 2016), CPICS (Tanaka et al 2021), Plankton Imager (Pitois et al 2021), ZooScan (Gorsky et al 2010), ZooCAM (Romagnan et al 2016), LOKI (Schulz et al 2010), UVP5 (Picheral et al 2010), UVP6 (Picheral et al 2022), Video Plankton Recorder (Davis et al 2005), PlanktonScope (Bi et al 2022), ISIIS (Cowen & Guigand 2008) and PELAGIOS (Hoving et al 2019), among others are in use to cover the entire size range from microscopic plankton organisms to large fish or gelatinous animals.…”

Section: Targets Of Pelagic Imagingmentioning

confidence: 99%

Towards a distributed and operational pelagic imaging network

Kiko,

Lopes,

Soviadan

et al. 2023

Ocean Coast. Res.

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Dimensions of particulate matter found in the water column of marine and freshwater environments (the pelagic realm) range from nanometers to tens of meters. Included in this enormous size range are miniature bacteria, phytoplankton (photosynthetic microalgae), mixoplankton (mixotrophic microorganisms), micro-to meter sized drifting animals (zooplankton), plastic particles, detrital aggregates and fecal pellets, fish, whales and many others. These particles and organisms are involved in many different processes and perform a multitude of services, such as in oceanic biogeochemistry (carbon fixation, oxygen production, carbon export and others) or human nourishment (fisheries). Digital optical tools used in pelagic imaging approaches now allow to bridge this enormous size span and to image micro-to meter-sized objects in situ or on discrete samples. Monitoring plankton, nekton, and particle dynamics at spatial and temporal scales that enable effective management of marine and freshwater environments poses a collective challenge for society. We here argue that a global, distributed and operational network for pelagic imaging is needed and within reach, and we provide recommendations how it can be attained via the voluntary activities of the pelagic imaging community and strategic support from funding agencies and other stakeholders.

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The potential role of turbulence in modulating the migration of demersal zooplankton

Cited by 14 publications

References 49 publications

Development of a Buoy-Borne Underwater Imaging System for In Situ Mesoplankton Monitoring of Coastal Waters

Development of a Buoy-Borne Underwater Imaging System for In Situ Mesoplankton Monitoring of Coastal Waters

Fluorometer optical path interference via zooplankton phototaxis: Implications for high‐frequency data collection

Towards a distributed and operational pelagic imaging network

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