Big Catch: On Friday 6th February Statistics Norway finally published the latest Norwegian river catch of salmon. The total catch has increased, even in Vestland. The most recent years catches are shown below:
Interestingly, the number of fish which had been caught and killed had also been in decline but in 2025 has increased t 40,670 breeding adult up from 30,137 in 2024.
Preliminary indications from Scotland also indicate increased catches, and those will be seen mostly in rivers which have absolutely no interaction with salmon farming. This suggests again that salmon farming should not be the focus of changing wild fish populations. as there is clearly something else at play.
Correlation: I recently discussed the Sea Lice Steering and Expert Group’s (SG and EG) response to the International Evaluation Committee’s 2021 recommendations however I would now like to focus specifically on recommendation number 14. This stated:
‘We recommend that the Expert Group expend more of its effort and scientific reporting on possibilities for demonstrating external validation of the approach. (It is our impression that the focus of the Expert Group has largely been on verifying the internal operation and predictions of the various modelling approaches.)’
In my opinion, this makes perfect sense. As I have previously pointed out, for example, the various sea lice models predict the location and concentration of infectious sea lice larvae in Norwegian fjords. Surely, it cannot be too difficult to sample in specific areas to confirm that the infectious lice larvae are where the Expert Group say that they will be. Clearly, if they are not there and the models cannot be validated, then the forecasts of what the Traffic Lights will be are simply meaningless.
The EG and SG have responded citing a different issue which also requires validation. Their full response states:
“Comments on R14: (Not the mandates of SG and EG) This recommendation is not within the mandates or budget of SG or EG. The proposal is to assess EG’s assessments of sea lice impact on the post-smolt stage against independent data on the number of salmon returning to spawn. As the evaluation committee points out, such analyses are not easy to conduct with the desired certainty because survival in the sea is also affected by many factors other than sea lice and because the number of smolts migrating out of each river also varies considerably between years. However, new studies shed light on this connection. Larsen et al. (2024) found a correlation between high levels of sea lice in fish farms and reduced catches of wild salmon in recreational fishing, and Jansen et al. (2026) found a correlation between high impact in VI’s virtual post-smolt model and low numbers of salmon in subsequent spawning fish counts. According to the calculations of Jansen et al., the percentage reduction in the number of salmon returning to spawn was somewhat greater than the proportion of postsmolts estimated to die due to sea lice. These studies support studies that have compared the sea survival of postsmolts of salmon with and without prophylactic drug treatment against sea lice (Vollset et al. 2016, 2023, Gargan et al. 2025)”.
As the EG and SG rightly point out, such analyses are not easy to conduct with any desired certainty, but this is not some academic study that is being considered, but the future of one of Norway’s most important industries. It is therefore critical that the EG and SG are absolutely certain that their assessments can be fully validated because otherwise the salmon farming industry risks being significantly impacted by poor science and in my opinion, this is exactly what is happening. It is only necessary to read the second half of their response to be concerned that the EG assessments are flawed.
For clarification, the EG response is a direct translation, and they say new studies have shed new light on the connection between salmon farming, smolt migration and returning adult salmon. The new studies are Larsen et al. (2024) and Jansen et al. (2025). In both examples, the SG and EG state that the papers show a ‘correlation’ between sea lice and wild fish numbers. Yet as every scientist knows (or should know) correlation does not imply causation. That is why the claims against salmon farming need to be validated and not just be based on correlation and conjecture.
Before I discuss the new studies, I would like to discuss the final sentence of the SG and EG response to recommendation 14. This states: “These studies support studies that have compared the sea survival of postsmolts of salmon with and without prophylactic drug treatment against sea lice (Vollset et al. 2016, 2023, Gargan et al. 2025)”. I would suggest that this selection of three papers represents cherry picking of the data. There is no mention of the Jackson et.al. paper which represents the biggest study of this type. Jackson found that the impact of sea lice on wild fish was about one percent. By comparison, Vollset uses data generated by others, mainly from Norway, and subjects it to different statistical analyses. Whilst the SG and EG say that these papers support the claim that there is an impact, the last line of the Abstract from Vollset 2015 paper states: ‘The results suggest that the population level effect of parasites cannot be estimated independently of other factor affecting the marine survival of salmon’. The Gargan paper extends the data used by Jackson and says that there is an effect on wild salmon from sea lice, however, I have previously discussed this paper and found errors in the data. In addition, the more recent data is subjected to an even greater natural mortality than say Jackson’s work. Jackson estimates that about 5% of migrating smolts returned to their home river regardless of sea lice. Today some rivers are experiencing return rates of just 1% which means many thousands of fish need to be included in a study to make the results meaningful. Scottish Government scientists conducted a similar experiment some years ago but using just a couple of thousand fish and they failed to recapture any of the treated or control fish.
Returning to the new studies, I have previously discussed the Larsen paper, so here I would like to examine the findings of the Jansen paper. The mention of this paper by the SG and EG is enough to raise concern with their comment that Jansen found a correlation between VI’s virtual post smolt model and low numbers of salmon in subsequent fish counts. In my opinion, validating the impacts of sea lice using the outcome of a model as one of the factors does not represent a true validation because the data is compared to the outcome of a model not real-life.
I will begin by looking at the material and methods section of the paper with consideration of the catch data. It is unclear why Statistics Norway group the salmon catch into three groups divided by weight, however, Jansen has used these groups in this study. There are three groups which are: – small (<3kg) medium (3-7kg) and large (>7kg). Jansen then goes on to suggest, based on the Larsen paper, that the small fish are those that spent one winter at sea (1SW), whilst medium sized fish spent two winters at sea (2SW) and large fish spent three winters at sea (3SW). I am not sure that it is possible to make such assumptions. I am more familiar with the terminology of grilse of 1SW for fish that return to the river after just one winter at sea and salmon for those fish and Multi Sea Winter or MSW fish for fish that have spent more than one winter at sea.
Certainly, ICES use the terminology as ISW and MSW, but even then, it is difficult to ascribe specific weights to such fish as there can be significant variation between them. For example, whilst most small fish are classed as 1SW, it is possible to find 1SW fish that are larger than some MSW. Typically, 1SW fish would be under 3 kg but 1SW fish can be over 5kg by the end of the season. The only way to distinguish between the groups is by reading the fish scales.
Anyway, Jansen has complicated the issue by creating groups depending on the exact number of years the fish had spent at sea. Although Jansen does not mention the numbers, the data indicates that a salmon catch of 60,564 1SW fish, 33,472 2SW fish and 10,448 3SW fish were included in their study.
Secondly, Jansen only includes fish that have been caught and killed in the study because the researchers believe that any fish caught and returned will be included in the separate count of fish in the river. I suspect that this is an assumption that cannot be proved and thus just adds to the uncertainty. This is because it is well-known that there is a mortality associated with catch and release and secondly, there is significant variation in the release rates between rivers. Some rivers have almost no fish returned whilst others can have release rates in excess of fifty percent.
Finally, Jansen only examines the data between 2019 and 2024, which is just a snapshot and doesn’t even cover the full period of the Traffic Light System. As the EG rightly say, “survival in the sea is also affected by many factors other than sea lice and because the number of smolts migrating out of each river also varies considerably between years”. Six years of data is relatively meaningless for these reasons, and especially, when the number of salmon returning to Norwegian rivers has been in decline since the 1970s.
I make no claims to be a statistician so for one interpretation of the data I suggest reading Aquablogg https://www.aquablogg.no/lus-med-bagatellmessig-pavirkning-av-villaksen/
I have taken a very different approach to Jansen in looking at the alleged impact of salmon farming on wild fish numbers. Jansen says that there was a significant negative effect on returns of 1SW salmon but it was not so clear for the larger fish. This does not come of any surprise because 1SW grilse and MSW salmon have in the past been impacted by factors outside those commonly considered. Over ten years ago, one of the biologists working on the River Tweed posted a You Tube video in which he discussed the history of salmon catches on the Tweed and the lessons for today. https://www.youtube.com/watch?v=5DjuyMzxpt4
The video discussed how records of catches of salmon caught by nets, stretching back to the 1700s, showed that over time, catches were dominated by 1SW grilse whilst at other times catches were dominated by large salmon. These periods of grilse or salmon domination could last tens of years, but something eventually caused them to switch over. In addition, fish weighing 7-10lbs from the Tweed were mainly 1SW grilse from 1995 to 1999, whilst from 2010 to 2014, fish of 7-10lbs were MSW salmon.
Anyway, following the appearance of this video, a biologist from one of the west coast rivers pose the question whether other rivers would show the same patterns of changes between high and low grisle numbers and low and high salmon numbers. He added that unfortunately they did not have the same rich source of data as the Tweed and therefore could not investigate whether the pattern was the same.
However, it made me think that there was rod catch data divided into 1SW and MSW available from 1952 for all rivers in Scotland and it might be worth looking at this data to see if any pattern was apparent and after conducting the analysis based purely on numbers, the same pattern as seen on the Tweed jumped out of the pages.
Seemingly, the declines seen on the west coast, which everyone blamed on sea lice and salmon farming, were more likely to be due to the switch from MSW catches to those of 1SW fish. As MSW fish outnumbered the grisle, the change from one to the other was initially masked, leading to a focus on salmon farming as the cause.
Interestingly, I wrote a paper about the cycle between 1SW and MSW fish and it was totally ignored by the scientific and wild fish communities, not least because it spoilt the story about sea lice and also because it was written by someone associated with the salmon farming sector, it must considered to be tobacco type industry research. https://researchopenworld.com/merged-data-hides-differences-in-the-catch-trends-of-scottish-salmon/
The results are summarised by the following graphs:
The top two graphs (a and b) show the total salmon catch from west coast rivers (blue) and across all of Scotland (orange). The anglers claim this shows the impact of salmon farming and especially sea lice with declining catches in the west whereas catches elsewhere have increased.
The middle graphs (c and d) show catches of MSW salmon from both the west coast (blue) and all of Scotland (orange). It can be seen that catches of these fish have declined not just along the west coast but across all Scotland. The final two graphs show catches of grilse (1SW) from the west (blue) and across all of Scotland. This is where the narrative about sea lice becomes confused because if sea lice associated with salmon farms are causing a decline in west coast catches, how can grilse catches have increased? Clearly sea lice are unable to differentiate between 1SW and MSW fish but more importantly the trends shown fit in exactly with changes on east coast rivers as highlighted in the Tweed video. The following image from the video comes from a 1995 paper by David Summer showing similar patterns on the major east coast rivers.
As the years have progressed and fewer fish have returned to their home rivers, it has become increasingly difficult to track such changes. However, using the data available from Statistics Norway, it is apparent that there are differences in the 1SW and MSW catches:
This illustrates the possible change from the 2000s with MSW again on the increase but with grilse catches on the decline. However, it can be seen that in recent years, the pattern has changed due to reduced fish and river closures impacting overall catches.
Returning to the Jansen paper, the researchers initially analysed the data from 143 rivers but then, using fiver different criteria, reduced the number to 104. These were: 1. Known infestation with Gyrodactylus,, 2. Video counting, 3. Less than 70% of river surveyed, 4. When conditions for counting were poor and 5. Rivers with no link to infection model.
Yet, interestingly, it was not whole rivers that were excluded from the analysis. Partial data from 27 rivers was also excluded. For example, the Innfjordeselva consisted of data just from three of the six years but then two of the years were also removed leaving just one year of data to be included in the final analysis.
Of the original 143 rivers, 24 had just one year of data, 12 had two years, 26 had three years, 13 has four years, 19 had five years and 49 had all six years of data. Clearly, as there can be a large variation in the data from year to year, rivers with one or two years of data cannot necessarily provide reliable data, especially when some of the years are not even consecutive.
However, when the data from the 104 rivers is analysed, 51 of the rivers show a positive catch trend from 1993 to 2024 whilst 51 others show a negative trend with 2 having no data.
Most of those rivers with an increased catch trend are located in Rogland, Vestland, Nordland and Troms and Finnmark. Overall, the catch trend for all rivers in Vestland shows a positive catch, whilst Finnmark with many fewer farms has a negative trend. I will look at this in more detail later.
The focus on catch data is because catches are said to reflect the local salmon stock according to Scottish Government scientists (MSS Report 01/15).
Statistics Norway lists over 700 rivers for salmon, so Jansen’s 104 rivers cover only a small percentage of the total. It has therefore been interesting to take a deeper dive in two areas. The first is Vestland which according to Statistics Norway covers 99 rivers (compared to 48 listed by NINA in their bestandlaks website. If all the data from the 99 rivers is plotted together to give a regional trend for salmon catches, the resulting graph is as follows:
Although the rate of change is small, there is a clear positive trend to catches in Vestland despite being at the heart of the salmon farming industry in Western Norway. When the data is broken down 40 rivers have no or a tiny salmon catch and of the 59 remaining rivers, 33 show a positive trend, 2 are stable and 24 show a decline.
By comparison, Finnmark which is in a PO which has been classified as green for most of the Traffic Light period shows a negative trend for salmon catches:
This makes no sense at all.
Statistics Norway list 86 rivers in Finnmark but 53 of them are significantly deficient in data to plot any trends. Of the remaining 33 rivers, 23 show a positive trend and just 10 show a trend that is negative. The reason for this contradiction is that it is the big salmon rivers that have shown the greatest decline whilst several of the positive trend rivers show data only for recent years suggesting that the decline in the main salmon rivers has encouraged anglers to visit the smaller rivers instead.
Interestingly, Aquablogg highlights 10 rivers that according to Jansen have more than 30% modelled average mortality. These make up just under 10% of the 104 rivers analysed by Jansen and are located in Vestland and PO3/PO4. Of these 10 rivers, four have a positive trend so the obvious question is how can rivers that are supposed to suffer a 30% plus mortality also have an increasing catch trend?
Finally, it is worth remembering that SG and EG in responding to the International Committee’s recommendations say that these analyses are not easy to conduct with the desired certainty because survival in the sea is also affected by many factors other than sea lice. I would like to remind the SG and EG that a fifty year comparison of catches, which Scotland Government scientists have said are a reflection of the size of the salmon stock, shows an almost parallel rate of decline of catches from rivers along a coastline where salmon farms are located to catches from rivers along a coastline where there are no salmon farms, nor have there ever been.
Sadly, not one of the SG and EG responded to my request for help explaining how sea lice can be implicated in declining salmon stocks when catches have declined at almost the same rate in areas where there are no salmon farms.