Dataset Information

Looking inside the Ocean: Toward an Autonomous Imaging System for Monitoring Gelatinous Zooplankton.

ABSTRACT: Marine plankton abundance and dynamics in the open and interior ocean is still an unknown field. The knowledge of gelatinous zooplankton distribution is especially challenging, because this type of plankton has a very fragile structure and cannot be directly sampled using traditional net based techniques. To overcome this shortcoming, Computer Vision techniques can be successfully used for the automatic monitoring of this group.This paper presents the GUARD1 imaging system, a low-cost stand-alone instrument for underwater image acquisition and recognition of gelatinous zooplankton, and discusses the performance of three different methodologies, Tikhonov Regularization, Support Vector Machines and Genetic Programming, that have been compared in order to select the one to be run onboard the system for the automatic recognition of gelatinous zooplankton. The performance comparison results highlight the high accuracy of the three methods in gelatinous zooplankton identification, showing their good capability in robustly selecting relevant features. In particular, Genetic Programming technique achieves the same performances of the other two methods by using a smaller set of features, thus being the most efficient in avoiding computationally consuming preprocessing stages, that is a crucial requirement for running on an autonomous imaging system designed for long lasting deployments, like the GUARD1. The Genetic Programming algorithm has been installed onboard the system, that has been operationally tested in a two-months survey in the Ligurian Sea, providing satisfactory results in terms of monitoring and recognition performances.

SUBMITTER: Corgnati L

PROVIDER: S-EPMC5191104 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Looking inside the Ocean: Toward an Autonomous Imaging System for Monitoring Gelatinous Zooplankton.

Corgnati Lorenzo L Marini Simone S Mazzei Luca L Ottaviani Ennio E Aliani Stefano S Conversi Alessandra A Griffa Annalisa A

Sensors (Basel, Switzerland) 20161214 12

Marine plankton abundance and dynamics in the open and interior ocean is still an unknown field. The knowledge of gelatinous zooplankton distribution is especially challenging, because this type of plankton has a very fragile structure and cannot be directly sampled using traditional net based techniques. To overcome this shortcoming, Computer Vision techniques can be successfully used for the automatic monitoring of this group.This paper presents the GUARD1 imaging system, a low-cost stand-alon ...[more]

PMID: 27983638

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Project description:Nonindigenous species pose a major threat for coastal and estuarine ecosystems. Risk management requires genetic information to establish appropriate management units and infer introduction and dispersal routes. We investigated one of the most successful marine invaders, the ctenophore Mnemiopsis leidyi, and used genotyping-by-sequencing (GBS) to explore the spatial population structure in its nonindigenous range in the North Sea. We analyzed 140 specimens collected in different environments, including coastal and estuarine areas, and ports along the coast. Single nucleotide polymorphisms (SNPs) were called in approximately 40 k GBS loci. Population structure based on the neutral SNP panel was significant (F ST .02; p < .01), and a distinct genetic cluster was identified in a port along the Belgian coast (Ostend port; pairwise F ST .02-.04; p < .01). Remarkably, no population structure was detected between geographically distant regions in the North Sea (the Southern part of the North Sea vs. the Kattegat/Skagerrak region), which indicates substantial gene flow at this geographical scale and recent population expansion of nonindigenous M. leidyi. Additionally, seven specimens collected at one location in the indigenous range (Chesapeake Bay, USA) were highly differentiated from the North Sea populations (pairwise F ST .36-.39; p < .01). This study demonstrates the utility of GBS to investigate fine-scale population structure of gelatinous zooplankton species and shows high population connectivity among nonindigenous populations of this recently introduced species in the North Sea. OPEN RESEARCH BADGES:This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at: The DNA sequences generated for this study are deposited in the NCBI sequence read archive under SRA accession numbers SRR6950721-SRR6950884, and will be made publically available upon publication of this manuscript.

Dataset Information

Looking inside the Ocean: Toward an Autonomous Imaging System for Monitoring Gelatinous Zooplankton.

Publications

Looking inside the Ocean: Toward an Autonomous Imaging System for Monitoring Gelatinous Zooplankton.

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