- Course Editor / Instructor: Clyde Blanco
- Course Editor / Instructor: Julia Jung
- Course Editor / Instructor: Shanna Vanblaere
IOC/HAB Centre training course in collaboration with Kuwait Institute for Scientific Research.
Course Dates: 10 - 21 March 2019
Course Venue: Kuwait Institute for Scientific Research, Food Resources & Marine Sciences†Mariculture and Fisheries FacilitiesP.O Box 24885 - 13109 Safat, Kuwait
Instructors: Jacob Larsen
The APC, initiated in the 1970s at the University of Oslo with the support of UNESCO and its Intergovernmental Oceanographic Commission, has been held from 1985 to 2015 at the Stazione Zoologica of Naples and in 2012 at the University of Copenhagen. APC12 will be the first edition held in France. The course is open to 20 selected researchers, technical staff, and/or PhD/postdoctoral students from around the world who already have expertise in taxonomy of marine phytoplankton and routinely need to identify it in a professional context. The aim is to provide participants with updated and in-depth high-level theoretical and practical training on how to identify and classify members of the major marine phytoplankton groups (diatoms, dinoflagellates, coccolithophores and other phytoflagellates), including species responsible for the formation of exceptional or harmful algal blooms.
The 20-day program consists of lectures and practical sessions during which participants will receive training in classical techniques (such as light and electron microscopy) as well as integration of new approaches (such as flow cytometry and molecular genetics) into the study of microalgae. The faculty of APC12 includes an international team of leading experts in the taxonomy of different groups of marine phytoplankton. Over the last 4 decades the APC has made an outstanding contribution to disseminating the vast body of highly specialist knowledge on phytoplankton taxonomy, which is almost completely overlooked in mainstream educational curricula in spite of its renovated importance, e.g. for interpreting data produced by modern high-throughput methods. Many of the international scientists trained during previous APC editions have gone on to apply, develop and spread the knowledge gained during the course in their local regions.
The course will be held at the Station Biologique de Roscoff (SBR), which is jointly operated by the Sorbonne Université and the French National Scientific Research Council (CNRS). The SBR hosts a renowned group of scientists and students focusing on the study of marine microalgae and protists, as well as the Roscoff Culture Collection that is one of the largest and most diverse open-access collections of marine microalgae cultures in the world. The RCC is part of the European infrastructure “EMBRC” (European Marine Biological Resource Centre). The APC12 scientific organizing committee also includes scientists from IFREMER (Brest, France) and the Stazione Zoologica Anton Dohrn (Naples, Italy). APC12 will exploit the extensive conference facilities (lecture theaters, practical labs, hotel, restaurant, etc.) available at the SBR.
Marine scientific research (MSR) plays a critical role in sustainable development as consistently recognized by the UN General Assembly in its annual resolutions on oceans and the law of the sea. Research, and the tools required to conduct it, are essential for the sustainable development of the oceans and the seas and their resources, including by supporting informed decisions on the conservation and sustainable use of the marine environment and its resources, and by helping to understand, predict and respond to natural disasters and climate change. Increased MSR through capacity--development strengthening the capacity of States, in particular Small Island Developing States (SIDS), to implement the relevant MSR provisions of the United Nations Convention on the Law of the Sea (UNCLOS) as well as similar provisions in other instruments, is essential for increasing the MSR being conducted in the world’s oceans. This course will provide an overview of the legal, technical and scientific aspects of the MSR regime, particularly with respect to consent procedures, so as to reinforce the participants’ knowledge of the rights and obligations of coastal and researching States. It will also touch upon matters relating to the development and transfer of marine technology under the United Nations Convention on the Law of the Sea.
This course provides an overview of regional/international marine observation, application and quality control of CTDs (Conductivity, Temperature, and Depth) and their measurements. It will provide an opportunity for participants to exchange the research progress on regional marine observation, and to learn the quality control procedures of CTDs to improve the in-situ oceanographic measurements.
This course will provide knowledge and hands-on experience for the data, satellites and instrumentation, access and formats, tools and software for operational activities. A pre-course phase of the training will provide an essential overview of data, products and tools used to monitor the ocean and will focus on preparation for the classroom phase where students will work on a short project to learn more about the data and its applications.
This course will focus on integrated coastal zone management, in the sense that it needs to take on board the ecological, environmental, social and economic aspects of managing a coastal area or zone. The course provides an overview and hands approach on GIS applications necessary towards integrated coastal zone management including the data acquisition, processing, analysis and interpretation of spatial data. Participants will develop and build their own case study and make a short presentation at the end of the training course.
O curso fornece uma introdução ao fenómeno das marés (elevação e correntes) e a sua importância para a ecologia e desenvolvimento costeiros, operações de pesca, gestão portuária, desportos náuticos e outros serviços marítimos e geração de energia natural a partir do mar. O curso incluirá uma introdução teórica sobre as forças geradoras de marés e seus constituintes, equipamentos usados para a medição de marés, aquisição de dados, processamento, análise e interpretação para diferentes aplicações.
Os participantes ganharão conhecimentos sobre análise e previsão de marés usando o programa t-tide, e serão incentivados a usar dados de mares das suas instituições e/ou países de origem e processá-los para as suas necessidades específicas. Os participantes desenvolverão projetos individuais ou em grupo para apresentação no final do curso.
This course provides a comprehensive introduction to a wide variety of earth science datasets, formats and analysis software. Students will learn and practice methods using a common ocean area, and they are expected to create a personal project of data products for a marine region of their own choosing. Personal projects are presented by the students at the end of the course.
Aims and Objectives:
The MBON Pole to Pole effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).
This course a follow up of the MBON Pole to Pole of the Americas: using OBIS as data sharing and integration platform. The course will take place in Cancun, Mexico, between 2 to 5 April 2019.
El curso proporciona una introducción al Sistema de Información Biogeográfica de los Océanos (The Ocean Biogeographic Information System - OBIS). Esto incluye las mejores prácticas en la gestión de los datos biogeográficos marinos, publicación de los datos para su libre acceso (IPT), acceso a los datos, organización, análisis y su visualización, utilización de R.
Metas y Objetivos
El curso busca sentar las bases respecto a los conceptos y prácticas relacionadas con carbono azul (mitigación – captura de CO2) y adaptación en ecosistemas marinos y costeros, en el marco de la convención de cambio climático, el plan estratégico Ramsar 2016 – 2024 y los objetivos de Desarrollo Sostenible 13 y 14. Busca también una retroalimentación e intercambio de experiencias por parte de todos los participantes de acuerdo a sus conocimientos y lecciones aprendidas en temas de conservación y manejo de ecosistemas marinos y costero o planificación de usos en el territorio. Se busca la apropiación y producción del conocimiento, así como el desarrollo de la capacidad crítica del estudiante orientada a prepararse para afrontar los efectos del cambio climático y generar redes y alianzas estratégicas regionales para cooperación.
Leader: Eric Orenstein (SIO-UCSD)
Scientists are increasingly relying on digital imaging technology to study marine organisms. These tools promise to yield new insight into ecosystem function by densely sampling in space and time. But drawing conclusions and developing long term monitoring programs based on imaging systems is challenging due to the sheer volume of data they produce.
This tutorial will use a labeled plankton data set drawn from the Scripps Plankton Camera System to illustrate a variety of supervised image classification methods. The materials will cover basic image manipulation, feature extraction, margin, ensemble, and neural network classification. All coding examples and exercises will be presented in Python. These techniques are broadly applicable to all sorts of image data, from the macro- to the microscale. Participants are encouraged to bring their own images for experimentation.
Leaders: Tristan Cordier (University of Geneva), Anders Lanzén (AZTI-Tecnalia)
High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) is a molecular technique that enables profiling of both the composition and diversity (both known and unknown “species”) of biological communities, directly from environmental samples. It provides biologists with an unprecedented amount of ecologically meaningful data. These tools have been recently tested in an environmental monitoring context, in which the bioindicator values of the species present in an environment indicate its Ecological Quality Status (EQS), i.e. its level of disturbance, usually caused by anthropogenic pressures. Those studies showed that anthropogenic impact can be clearly detected from metabarcoding data, although the taxonomic identification of many sequences remain challenging, hampering the transition of existing monitoring tools and practices into the genomics era. Recent studies have shown that Supervised Machine Learning (SML) algorithms can be successfully used to overcome this challenge in many cases, enabling robust predictive models that can provide EQS predictions from metabarcoding data, regardless of the taxonomic affiliations.
This tutorial will first provide a brief overview of general bioinformatics practices for processing of metabarcoding data, to obtain an exploitable contingency matrix (“OTU table”). We will then focus on the training and testing (cross-validation) of SML models to predict the EQS of samples in a monitoring context. Data collected along a pollution gradient in coastal environments in Norway will be provided and analysed, with the possibility to explore participants’ own data as well. The tutorial will be carried out using command line tools and R, and therefore requires basic familiarity with GNU/Linux (bash) as well as basic statistics commands and data manipulation (“programming”) in R.
Leaders: Danelle Cline (MBARI), John Ryan (MBARI)
Passive acoustic sensing in the ocean provides a wealth of information about the presence and activity of marine life, as well as anthropogenic noise that can negatively impact marine life. This mode of sensing generates very large and complex data sets. In this research domain, ML is proving to be highly effective. This tutorial will cover ML fundamentals, optimum decimation filtering, spectrogram enhancement methods, and classification using convolutional neural networks (CNN). We will focus on end-to-end analysis methods for one type of sound source: low frequency whale calls, including detection and classification. Some basic experience in Python programming in Jupyter notebooks would be beneficial. Data will be provided for the tutorial. If you wish to bring your own data for experimenting outside of class time, please contact us to understand required dataset organization.