Advanced course 8 to 12 February 2021

Prerequisite

This course is hosted by ICES and intended for people with previous experience with R and vmstools (in particular, participants are expected to be familiar with practicals 1, 2, 3, 4 and 9).

Registration for this online course is arranged by ICES.

Deadline to register: 25 January 2021

Program

In addition to the following topics covered during the course, there will be room for students problems. The first session will be used to answer questions regarding the practicals 1-4 and 9. Additional chat sessions will be held to answer remaining questions (see time schedule below).

1. ISLA: Individual Stress Level Analyses

The economic importance of specific fishing grounds to fishers varies within a fleet. To capture this variation and understand how dependent fishers are to an area we use the individual stress level analysis. We calculate the proportion of income coming from a specific area at the individual level and show the distribution of the individual stress level for the fleet considered. The stress level can be given for different groups (home harbours, vessel size, main gear), helping decision maker understand the sensitivity of closing particular areas and identify the part of the fishery impacted by their decision.

2. Aggregation of fishing

Swept Area Ratios for bottom gears are often calculated to quantify the impact on the benthic community. We demonstrate how to easily calculate SARs but also look at the location and intensity of fishing within ICES rectangles using a statistical approach. We use the underlying distribution of fishing intensity to more appropriately predict small scale (within an ICES rectangle) distribution of fishing under changes in effort.

3. Bycatch & high risk areas

The risk to repeatedly catch small sized fish or vulnerable species has strong spatial correlation. We demonstrate how to display spatial species distribution-at-length from survey data and calculate spatial overlap with the fisheries from VMS and logbook data. We calculate a measure of spatial correlation of unwanted bycatch (either by species or by length) to come up with a measure that indicates the distance between consecutive fishing tows with low probability of similar catch composition.

4. Uncertainty in spatial fisheries data

VMS and logbook data are linked a posteriori to increase the spatial resolution of fishing activities. In this part we investigate how the assumptions made to 1) define when a vessel is fishing based on speed thresholds and 2) distribute the daily catch per ICES rectangle (resolution in logbooks) on fishing VMS points, influence the resulting maps. We also relate the temporal resolution of VMS data (interval between to pings) to the spatial resolution of maps as more frequent pings allow higher resolution maps.

Time schedule

This is a 5 day online course, in which the participants follow online sessions of 4 hours each day. During the remainder of the day, participants will work on their assignments. During self-study assignment hours, students are expected to discuss problems among themselves using functionality in Microsoft Teams. The instructors keep a close watch and intervene where necessary, both during the morning sessions in CET and evening sessions in EST.