Estimating fishing effort and spatio-temporal distribution of longline vessels in the Indian Ocean

Protein from fish is essential for feeding the world’s population and is increasingly recognized as critical for food security. To ensure that fisheries resources can be sustainably maintained, fisheries management must be appropriately implemented. When logbook and landing records data are not complete or are incorrect, it is challenging to have an accurate understanding of catch volume. Focusing on Indonesian longline vessels operating in the Indian Ocean from 2012–2019 (n = 1124 vessels), our aims were to (1) assess compliance through identification of landing sites and potentially illicit behavior inferred by interruptions in VMS transmission, and (2) understand how the fishery operates along with quantifying the spatio-temporal distribution of fishing intensity by applying a Hidden Markov Model, which automatically classified each VMS position as fishing, steaming and anchoring. We found vessel compliance gaps in 90% of vessels in the dataset. Compliance was questionable due both to the widespread occurrence of long intermissions in relaying VMS positions (mean = 17.8 h, n = 973 vessels) and the use of unauthorized landing sites. We also observed substantial changes in fishing effort locations among years. The introduction of regulatory measures during the study period banning transshipment and foreign vessels may be responsible for the spatial shift in fishing activity we observed, from encompassing nearly the whole Indian Ocean to more recent intense efforts off western Sumatra and northern Australia

Outcomes of the International Oceanographic Data and Information Exchange Ocean Biogeographic Information System OBIS-Event-Data Workshop on Animal Tagging and Tracking

The Ocean Biogeographic Information System (OBIS) began in 2000 as the repository for data from the Census of Marine Life. Since that time, OBIS has expanded its goals beyond simply hosting data to supporting more aspects of marine conservation (Pooter et al. 2017). In order to accomplish those goals, the OBIS secretariat in partnership with its European node (EurOBIS) hosted at the Flanders Marine Institute (VLIZ, Belgium), and the Intergovernmental Oceanographic Commission (IOC) Committee on International Oceanographic Data and Information Exchange (IODE, 23rd session, March 2015, Brugge) established a 2-year pilot project to address a particularly problematic issue that environmental data collected as part of marine biological research were being disassociated from the biological data. OBIS-Event-Data is the solution that was developed from that pilot project, which devised a method for keeping environmental data together with the biological data (Pooter et al. 2017). OBIS is seeking early adopters of the new data standard OBIS-Event-Data from among the marine biodiversity monitoring communities, to further validate the data standard, and develop data products and scientific applications to support the enhancement of Biological and Ecosystem Essential Ocean Variables (EOVs) in the framework of the Global Ocean Observing System (GOOS) and the Marine Biodiversity Observation Network of the Group on Earth Observations (GEO BON MBON). After the successful 2-year IODE pilot project OBIS-ENV-DATA, the IOC established a new 2-year IODE pilot project OBIS-Event-Data for Scientific Applications (2017-2019). The OBIS-Event-Data data standard, building on Darwin Core, provides a technical solution for combined biological and environmental data, and incorporates details about sampling methods and effort, including event hierarchy. It also implements standardization of parameters involved in biological, environmental, and sampling details using an international standard controlled vocabulary (British Oceanographic Data Centre Natural Environment Research Council). A workshop organized by IODE/OBIS in April brought together major animal tagging and tracking networks such as the Ocean Tracking Network (OTN), the Animal Telemetry Network (ATN), the Integrated Marine Observing System (IMOS), the European Tracking Network (ETN) and the Acoustic Tracking Array Platform (ATAP) to test the OBIS-Event- Data standard through the development of some data products and science applications. Additionally, this workshop contributes to the further maturation of the GOOS EOV on fish as well as the EOV on birds, mammals and turtles. We will present the outcomes as well as any lessons learned from this workshop on problems, solutions, and applications of using Darwin Core/OBIS-Event-Data for biologging data

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

1. 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. 2. 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. 3. 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. 4. Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and intergovernmental 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

Continental-scale animal tracking reveals functional movement classes across marine taxa

Acoustic telemetry is a principle tool for observing aquatic animals, but coverage over large spatial scales remains a challenge. To resolve this, Australia has implemented the Integrated Marine Observing System’s Animal Tracking Facility which comprises a continental-scale hydrophone array and coordinated data repository. This national acoustic network connects localized projects, enabling simultaneous monitoring of multiple species over scales ranging from 100 s of meters to 1000 s of kilometers. There is a need to evaluate the utility of this national network in monitoring animal movement ecology, and to identify the spatial scales that the network effectively operates over. Cluster analyses assessed movements and residency of 2181 individuals from 92 species, and identified four functional movement classes apparent only through aggregating data across the entire national network. These functional movement classes described movement metrics of individuals rather than species, and highlighted the plasticity of movement patterns across and within populations and species. Network analyses assessed the utility and redundancy of each component of the national network, revealing multiple spatial scales of connectivity influenced by the geographic positioning of acoustic receivers. We demonstrate the significance of this nationally coordinated network of receivers to better reveal intra-specific differences in movement profiles and discuss implications for effective management

A review of acoustic telemetry in Europe and the need for a regional aquatic telemetry network

Background Globally, there are a large and growing number of researchers using biotelemetry as a tool to study aquatic animals. In Europe, this community lacks a formal network structure. The aim of this study is to review the use of acoustic telemetry in Europe and document the contribution of cross-boundary studies and inter-research group collaborations. Based on this, we explore the potential benefits and challenges of a network approach to identify future priorities and best practices for aquatic biotelemetry research in Europe. Results Over the past decade, there was an approximately sevenfold increase in the number of acoustic telemetry studies published on marine and diadromous species in Europe compared to a sixfold increase globally. Over 90% of these studies were conducted on fishes and undertaken in coastal areas, estuaries, or rivers. 75% of these studies were conducted by researchers based in one of five nations (Norway, UK, France, Portugal, and Spain) and, even though 34% were based on collaborations between scientists from several countries, there was only one study with an acoustic receiver array that extended beyond the borders of a single country. In recent years, acoustic telemetry in European waters has evolved from studying behavioural aspects of animals (82.2%), into more holistic approaches addressing management-related issues (10%), tagging methods and effects (5%), and technology and data analysis development (2.8%). Conclusions Despite the increasing number of publications and species tracked, there is a prominent lack of planned and structured acoustic telemetry collaborations in Europe. A formal pan-European network structure would promote the development of (1) a research platform that could benefit the acoustic telemetry community through capacity building, (2) a centralized database, and (3) key deployment sites and studies on priority species requiring research in Europe. A network may increase efficiency, expand the scope of research that can be undertaken, promote European science integration, enhance the opportunities and success of acquiring research funding and, ultimately, foster regional and transatlantic collaborations. It may also help address research priorities such as the large-scale societal challenges arising from climate change impacts and assist the EU’s Marine Strategy Framework Directive via identification of good environmental status of endangered or commercially important species.info:eu-repo/semantics/publishedVersio

A continuous-time state-space model for rapid quality-control of Argos locations from animal-borne tags

This is the final version. Available on open access from BMC via the DOI in this recordState-space models are important tools for quality control of error-prone animal movement data. The near real-time (within 24 h) capability of the Argos satellite system aids dynamic ocean management of human activities by informing when animals enter intensive use zones. This capability also facilitates use of ocean observations from animal-borne sensors in operational ocean forecasting models. Such near real-time data provision requires rapid, reliable quality control to deal with error-prone Argos locations. We formulate a continuous-time state-space model for the three types of Argos location data (Least-Squares, Kalman filter, and Kalman smoother), accounting for irregular timing of observations. Our model is deliberately simple to ensure speed and reliability for automated, near real-time quality control of Argos data. We validate the model by fitting to Argos data collected from 61 individuals across 7 marine vertebrates and compare model-estimated locations to GPS locations. Estimation accuracy varied among species with median Root Mean Squared Errors usually < 5 km and decreased with increasing data sampling rate and precision of Argos locations. Including a model parameter to inflate Argos error ellipse sizes resulted in more accurate location estimates. In some cases, the model appreciably improved the accuracy of the Argos Kalman smoother locations, which should not be possible if the smoother uses all available information. Our model provides quality-controlled locations from Argos Least-Squares or Kalman filter data with slightly better accuracy than Argos Kalman smoother data that are only available via reprocessing. Simplicity and ease of use make the model suitable both for automated quality control of near real-time Argos data and for manual use by researchers working with historical Argos data.Macquarie UniversityOffice of Naval ResearchIntegrated Marine Observing System - Animal Tracking FacilityOcean Tracking NetworkTaronga Conservation SocietyBirds CanadaInnovasea/VemcoCSIRO Oceans & AtmosphereNational Science Foundation Office of Polar Project

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

A database of chlorophyll a in Australian waters

© The Author(s) 2018. Chlorophyll a is the most commonly used indicator of phytoplankton biomass in the marine environment. It is relatively simple and cost effective to measure when compared to phytoplankton abundance and is thus routinely included in many surveys. Here we collate 173, 333 records of chlorophyll a collected since 1965 from Australian waters gathered from researchers on regular coastal monitoring surveys and ocean voyages into a single repository. This dataset includes the chlorophyll a values as measured from samples analysed using spectrophotometry, fluorometry and high performance liquid chromatography (HPLC). The Australian Chlorophyll a database is freely available through the Australian Ocean Data Network portal (https://portal.aodn.org.au/). These data can be used in isolation as an index of phytoplankton biomass or in combination with other data to provide insight into water quality, ecosystem state, and relationships with other trophic levels such as zooplankton or fish