– We studied the effects of catch‐and‐release fishing upon the Ponoi River's Atlantic salmon populations. The Ponoi River is located on the Kola Peninsula of the Russian Federation, and has recently been developed for sports fishing. Angler exploitation rates are estimated to range from 10.4% to 19% of the river's salmon, thus the possibility of significant levels of post‐release mortality is of concern. We radio‐tracked fish caught and released by anglers in 1995 and 1996. Despite our simple equipment and the large size of the river, we were able to relocate most fish. These fish had high rates of survival, and anglers recaptured about 11% of them per year a second time. This is very similar to the recapture rates observed for Floy‐tagged fish released in an angler‐based mark‐recapture assessment. We also held 62 angled fish for 24 hours in a live cage to evaluate rates of delayed mortality. Only one of the 62 fish died, and it was heavily scarred with gillnet marks. Most fish that are fatally stressed by angling die within 24 h (e.g., Booth et al. 1995). In 1996, up to 10% of our Floy‐tagged fish were angled and released twice, and about 0.5% were angled and released three times. No significant biases were detected in the post‐angling movement patterns of these fish. The multiple captures and lack of movement bias suggest that fish behavior was little altered by the angling experience. Nine fish Floy tagged prior to spawning have been recovered as typical emaciated kelts. Three were killed, and a post mortem exam showed all had spawned. Parr numbers at all monitored sites have been steadily increasing since the advent of catch‐and‐release fishing. By contrast, parr growth rates are generally unchanged or significantly better.NOTE

This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmerc ial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Genetic stock identification (GSI) using molecular markers is an important tool for management of migratory species. Here, we tested a cost-effective alternative to individual genotyping, known as allelotyping, for identification of highly informative SNPs for accurate genetic stock identification. We estimated allele frequencies of 2880 SNPs from DNA pools of 23 Atlantic salmon populations using Illumina SNP-chip. We evaluated the performance of four common strategies (global F ST, pairwise F ST, Delta and outlier approach) for selection of the most informative set of SNPs and tested their effectiveness for GSI compared to random sets of SNP and microsatellite markers. For the majority of cases, SNPs selected using the outlier approach performed best followed by pairwise F ST and Delta methods. Overall, the selection procedure reduced the number of SNPs required for accurate GSI by up to 53% compared with randomly chosen SNPs. However, GSI accuracy was more affected by populations in the ascertainment group rather than the ranking method itself. We demonstrated for the first time the compatibility of different large-scale SNP datasets by compiling the largest population genetic dataset for Atlantic salmon to date. Finally, we showed an excellent performance of our top SNPs on an independent set of populations covering the main European distribution range of Atlantic salmon. Taken together, we demonstrate how combination of DNA pooling and SNP arrays can be applied for conservation and management of salmonids as well as other species.

Most exploitation of Atlantic salmon (Salmo salar) is restricted to “homewater fisheries”, which operate close to or within the rivers of origin of the stocks, but two “distant-water fisheries” are permitted to operate off the west coast of Greenland and in the Norwegian Sea, and take salmon from a large number of rivers over a wide geographical area. Providing robust quantitative catch advice for these mixed-stock fisheries depends upon the ability to forecast stock abundance for about 2000 salmon river-stocks around the North Atlantic, more than 1500 of which are in Europe. A “run-reconstruction” model is presented for estimating the historic pre-fishery abundance (PFA) of salmon for countries or regions around the Northeast Atlantic, based upon catch data and estimates of non-reporting rates and exploitation rates. These estimates are then used to develop predictive models of PFA on the basis of estimates of the egg deposition, derived from the run-reconstruction model and various environmental data. Although the selected environmental indices correlated with the PFA of both southern and northern European stock complexes, the main statistical significance in the forecast models was provided by temporal trends in the PFA. Clearly, such a model is only tenable in the short term, and will be poor at predicting a major change in stock status. Alternative approaches, based upon juvenile production indices and including Bayesian techniques, are therefore being considered.