Marine recreational fishing is popular in Norway, but current estimates of the catches by resident and tourist anglers are lacking due to several challenges, in particular Norway's long and intricate coastline with no defined access points and the large tourist fishery. To test methods for long-term monitoring of boat-based marine recreational anglers, estimate their catches, and characterize the fishery, we conducted a roving creel survey based on a novel spatial sampling frame and a survey of tourist fishing businesses in Troms and Hordaland County. These surveys showed that cod (Gadus morhua) and saithe (Pollachius virens) dominated the catches in Troms, while mackerel (Scomber scombrus) and saithe dominated the catches in Hordaland. The estimated total annual harvest of cod by all marine recreational anglers was 2 160 tonnes (relative standard error, or RSE 44%) in Troms and 73 tonnes (RSE 29%) in Hordaland, of which similar to 40% (in weight) were landed in registered tourist fishing businesses, based on data from the tourist fishing survey. The results indicate that recreational anglers in Hordaland harvest more cod in coastal waters than commercial fishers. This study provides information for developing marine recreational fisheries monitoring in challenging survey situations to support science-based fisheries management.

Identifying spawning sites of fish often involves extensive egg and larval sampling surveys over potential spawning sites, or by backward-tracking advected larvae to their source. Due to the vastness of the Barents Sea capelin spawning areas, back-tracking methods have limited application. Egg and larval surveys that provide information about spawning sites have also been discontinued in recent years. This paper aims at using alternative data sources to egg and larval distribution information, to infer potential spawning regions of the Barents Sea capelin during the period 1994–2020. We use the K-Means clustering technique to cluster historical spawning sites into spawning regions, and the Self Organizing Map (SOM) algorithm to define observed data clusters, which we assign to specific regions. The observation data consists of survey data sets from capelin pre-spawning and post-spawning periods during winter and spring respectively, as well as data from the Norwegian Directorate of Fisheries Electronic Reporting System database (ERS). Our method was efficient in reproducing capelin spawning regions and approximate time windows for commencement of spawning. The results showed that spawning occurred mainly over the eastern part of historical spawning areas during the whole period. A westward extension of the preferred spawning areas occurred in several years regardless of the rising Barents Sea water temperatures, especially during the second half of the period. The ERS data can be used to identify the arrival times and migration fronts of pre-spawning capelin along the coast.