Integrated Management and Visualization of Electronic Tag Data with Tagbase

Electronic tags have been used widely for more than a decade in studies of diverse marine species. However, despite significant investment in tagging programs and hardware, data management aspects have received insufficient attention, leaving researchers without a comprehensive toolset to manage their data easily. The growing volume of these data holdings, the large diversity of tag types and data formats, and the general lack of data management resources are not only complicating integration and synthesis of electronic tagging data in support of resource management applications but potentially threatening the integrity and longer-term access to these valuable datasets. To address this critical gap, Tagbase has been developed as a well-rounded, yet accessible data management solution for electronic tagging applications. It is based on a unified relational model that accommodates a suite of manufacturer tag data formats in addition to deployment metadata and reprocessed geopositions. Tagbase includes an integrated set of tools for importing tag datasets into the system effortlessly, and provides reporting utilities to interactively view standard outputs in graphical and tabular form. Data from the system can also be easily exported or dynamically coupled to GIS and other analysis packages. Tagbase is scalable and has been ported to a range of database management systems to support the needs of the tagging community, from individual investigators to large scale tagging programs. Tagbase represents a mature initiative with users at several institutions involved in marine electronic tagging research

The Gulf of Maine biogeographical information system project: developing a spatial data management framework in support of OBIS

Central to the development of an inventory of marine life and improved conceptual understanding of the mechanisms that dynamically shape species distribution patterns is the implementation of strategies aimed at enhancing assimilation and access to existing biogeographical information. Using the Internet as a medium, the Gulf of Maine Biogeographic Information System (GMBIS) project provides a framework and a set of reusable tools for the integration, visualization, analysis and dissemination of diverse types of biogeographical and oceanographic information. End-to-end viability of this approach is demonstrated in the context of a series of scientific storylines and a pilot application for the Gulf of Maine (GoM), a well-studied ecosystem that has been subject to large-scale perturbation due to overfishing. Databases at the core of the information system include those of the DFO Bedford Institution of Oceanography and Atlantic Reference Center, which are the product of multidisciplinary research efforts over the last several decades. Development of GMBIS may serve not only as a model for OBIS, but it may also provide a tool supporting new international and Canadian directives for integrated marine resource management. This paper summarizes the status of the GMBIS project, currently in its final phase, and outlines possible future directions in information system development for the CoML.Le développement d’une stratégie pour faciliter l’accès et l’assimilation à une information biogéographique est essentiel au développement d’un inventaire sur la vie marine. En utilisant Internet, le Système d’information biogéographique du golfe du Maine a développé une architecture et un ensemble d’outils pour l’intégration, la visualisation, l’analyse et la dissémination de divers types d’informations biogéographiques et océanographiques. La viabilité de cette approche est prouvée dans le cadre d’une application pilote et de scénarios scientifiques pour le golfe du Maine, un écosystème bien étudié, objet d’une perturbation à grande échelle par surpêche. La base de données initiale est celle de l’Institut Bedford et du Centre de référence atlantique, produit de la recherche pluridisciplinaire durant les dernières décennies. Le développement du Système d’information biogéographique du golfe du Maine ne doit pas seulement servir de modèle pour Obis ; il doit également fournir des outils pour des directives canadiennes et internationales pour la gestion intégrée des ressources marines. Cet article fait le point sur ce projet et souligne les directions possibles pour un système d’information pour le programme « Recensement de la vie marine »

VMSbase: An R-Package for VMS and Logbook Data Management and Analysis in Fisheries Ecology

VMSbase is an R package devised to manage, process and visualize information about fishing vessels activity (provided by the vessel monitoring system--VMS) and catches/landings (as reported in the logbooks). VMSbase is primarily conceived to be user-friendly; to this end, a suite of state-of-the-art analyses is accessible via a graphical interface. In addition, the package uses a database platform allowing large datasets to be stored, managed and processed vey efficiently. Methodologies include data cleaning, that is removal of redundant or evidently erroneous records, and data enhancing, that is interpolation and merging with external data sources. In particular, VMSbase is able to estimate sea bottom depth for single VMS pings using an on-line connection to the National Oceanic and Atmospheric Administration (NOAA) database. It also allows VMS pings to be assigned to whatever geographic partitioning has been selected by users. Standard analyses comprise: 1) métier identification (using a modified CLARA clustering approach on Logbook data or Artificial Neural Networks on VMS data); 2) linkage between VMS and Logbook records, with the former organized into fishing trips; 3) discrimination between steaming and fishing points; 4) computation of spatial effort with respect to user-selected grids; 5) calculation of standard fishing effort indicators within Data Collection Framework; 6) a variety of mapping tools, including an interface for Google viewer; 7) estimation of trawled area. Here we report a sample workflow for the accessory sample datasets (available with the package) in order to explore the potentialities of VMSbase. In addition, the results of some performance tests on two large datasets (1×10(5) and 1×10(6) VMS signals, respectively) are reported to inform about the time required for the analyses. The results, although merely illustrative, indicate that VMSbase can represent a step forward in extracting and enhancing information from VMS/logbook data for fisheries studies

A standardisation framework for bio-logging data to advance ecological research and conservation

Bio-logging data obtained by tagging animals are key to addressing global conservation challenges. However, the many thousands of existing bio-logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability and effective translation of bio-logging data into research and management recommendations. We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (a) decoded raw data, (b) curated data, (c) interpolated data and (d) gridded data. Our framework allows for integration of simple tabular arrays (e.g. csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy-of-use, rightful attribution (ensuring data providers keep ownership through the entire process) and data preservation security. We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing. Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter-governmental assessments (e.g. the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio-logging data formats across all fields in animal ecology. </div

Animal Borne Ocean Sensors - AniBOS - an essential component of the Global Ocean Observing System

Marine animals equipped with biological and physical electronic sensors have produced long-term data streams on key marine environmental variables, hydrography, animal behavior and ecology. These data are an essential component of the Global Ocean Observing System (GOOS). The Animal Borne Ocean Sensors (AniBOS) network aims to coordinate the long-term collection and delivery of marine data streams, providing a complementary capability to other GOOS networks that monitor Essential Ocean Variables (EOVs), essential climate variables (ECVs) and essential biodiversity variables (EBVs). AniBOS augments observations of temperature and salinity within the upper ocean, in areas that are under-sampled, providing information that is urgently needed for an improved understanding of climate and ocean variability and for forecasting. Additionally, measurements of chlorophyll fluorescence and dissolved oxygen concentrations are emerging. The observations AniBOS provides are used widely across the research, modeling and operational oceanographic communities. High latitude, shallow coastal shelves and tropical seas have historically been sampled poorly with traditional observing platforms for many reasons including sea ice presence, limited satellite coverage and logistical costs. Animal-borne sensors are helping to fill that gap by collecting and transmitting in near real time an average of 500 temperature-salinity-depth profiles per animal annually and, when instruments are recovered (∼30% of instruments deployed annually, n = 103 ± 34), up to 1,000 profiles per month in these regions. Increased observations from under-sampled regions greatly improve the accuracy and confidence in estimates of ocean state and improve studies of climate variability by delivering data that refine climate prediction estimates at regional and global scales. The GOOS Observations Coordination Group (OCG) reviews, advises on and coordinates activities across the global ocean observing networks to strengthen the effective implementation of the system. AniBOS was formally recognized in 2020 as a GOOS network. This improves our ability to observe the ocean’s structure and animals that live in them more comprehensively, concomitantly improving our understanding of global ocean and climate processes for societal benefit consistent with the UN Sustainability Goals 13 and 14: Climate and Life below Water. Working within the GOOS OCG framework ensures that AniBOS is an essential component of an integrated Global Ocean Observing System.</p