Report on in-country training in the FarFish project

Autor: Davidson, Mary Frances, Ba, Kamarel, Rincón Hidalgo, Margarita
Jazyk: angličtina
Rok vydání: 2021
Předmět:
DOI: 10.5281/zenodo.6427158
Popis: The FarFish in-country short course (Task 7.6) was delivered as a hybrid online/in person workshop September 29th-October 1st 2021. The course was broken into two sections, commencing with an open seminar on Data Limited Methods, and followed by a closed workshop on the use of the FarFish DLM Tool. A total of 50 participants attended the open seminar, and nine (9) attendees took part in the closed workshop that followed. The timing of the course, delivery methods, and target audience were modified in response to the COVID-19 pandemic. The scope and topic for the course were selected based upon the Training Needs Assessments (TNAs) carried out the first year of the project, in combination with other meetings and discussions with project partners. It was determined through those dialogues that the course would be most beneficial and useful to a wider variety of stakeholders and partners if it were offered as a regional course, rather than an in-country course targeting only one country. It was determined through the TNAs and subsequent conversations with case study partners that the concept of data limited methods for stock assessment, and more specifically, the Data Limited Methods (DLM) Tool developed through the FarFish project would be the most useful topic for the course. The course was originally intended to be held in Mindelo, Cabo Verde in April 2020, and was to be regional in focus, with participants nominated by their institutions. The FarFish case study partners were the original intended audience for this course, with participants hailing from the FarFish case study partner institutions, namely INDAP/IMar in Cabo Verde, ISRA/CRODT in Senegal, IMROP in Mauritania, and SFA in Seychelles. When it became clear that travel limitations due to the COVID-19 pandemic would make an in-person regional course impossible, a new solution was developed in which a hybrid online/in-person model could be used. As it is very difficult to remotely deliver the one-on-one attention required to support learning in the workshop to practice the DLM tool, the course was broken into two sections; one open to the public providing a general overview of Data Limited Methods, and how they can be useful in stock assessment, and the second a closed, intensive workshop for fellows of the GRÓ-FTP studying stock assessment as well as scientists from the case study countries who were interested to attend, albeit remotely. The course was delivered from GRÓ-FTP’s home institution, the Marine and Freshwater Research Institute in Iceland. The seminar part of the DLM course was held on the morning of September 29, 2021, and was open to participants who registered online beforehand, as well as those attending in person through the GRÓ-FTP six-month programme. In total, 30 people were onsite for the seminar, and 20 joined via teams. The seminar began with an introduction to another EU Horizon 2020-funded research project, EuroSea, in which the use of remote sensing via the Copernicus system was described. The seminar then included a combination of lectures and activities related to the theoretical development of data limited methods, and how they have evolved over time. The closed part of the workshop was attended by nine (9) individuals, from eight (8) countries. Notably, these include representatives from all the original target audience of FarFish case study institutions, including Senegal, Mauritania, Cabo Verde, and Seychelles, with the addition of GRÓ-FTP stock assessment fellows, hailing from Indonesia, Papua New Guinea, Sierra Leone, and El Salvador as well. Participants from Seychelles and Cabo Verde joined the workshop online, and the others were onsite. The course was taught by Margarita Rincon (IEO, Spain) and Kamarel Ba (ISRA/CRODT, Senegal).
The research leading to these results received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 727891/FarFish project.
Databáze: OpenAIRE
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