SEPA's Sea Lice Regulatory Framework
The science and evidence used to justify and inform SEPA’s Sea Lice Regulatory Framework are areas of concern for the aquaculture industry. Ministers requested CSA Marine to engage with the sector and report back on these concerns.
3. Key areas of concern mapped to recommendations.
11. Having listened carefully to the industry, eight broad categories of concern have been identified and are synthesised below. The discussions were wide ranging, concerns were filtered according to their relevance to the science evidence base (see below and Annex B), some concerns were viewed to be out with the competence of this report. The relevant concerns were gathered together by their commonality into one of the eight categories below.
12. After reviewing publicly available documentation, peer-reviewed scientific literature, case studies provided by industry to CSA Marine on request, and discussions between CSA Marine and SEPA the following responses have been drawn up. The responses are linked in some cases to one of the five recommendations.
Summarised: Concerns raised by industry (categorised) and this report’s response.
Concern 3.1, Transparency and clarity
Response
R1: Improve documentation and communication.
The current description of SLRF is spread across several consultation and response documents and lacks clarity in key places. The phrase “will be” is used often and the methodology is presented in different stages of revision in different documents. A formal SLRF software release cycle should exist with a clear note of which version was used on which occasions. Each release version needs clear methodological diagrams and descriptors that would allow for reproducibility, the required standard for a scientific method. Implementing a formal SLRF documentation structure will help with communication by providing a single reference point.
R5: Update the review of underpinning science.
A claim of “misrepresentation” of scientific findings by the regulator is unfounded. There is a genuine scientific debate/disagreement over the quantitative statistics regarding the effect of parasites on the return-rate of wild salmon. A paper published in 2025 (Gargan et al 2025) gives some clarity to this debate. The view of CSA Marine is that the balance of scientific evidence does indicate a statistically significant negative impact of parasites on wild salmon return rates, and that this evidence is not misrepresented by the regulator.
Concern 3.2, Model parameter choices / uncertainty
Response
R2: Full sensitivity analyses to be undertaken.
The screening model has not undergone a comprehensive sensitivity analysis. Sensitivity of the screening model outcomes (i.e. the designation of relative risk category for each farm) has been undertaken for some but not all parameters. There is good scientific reason to undertake a more comprehensive sensitivity analysis, independently reviewed by a third party (non-government or non-government agency).
Coastal systems are sensitive to extremes in weather (wind strength and direction, and rainfall in particular). The effects of weather extremes should be included in a sensitivity study of the screening model.
Concern 3.3, Historic baseline data
Response
A specific concern raised was that SEPA would in future change their methodology used to determine the historic baseline sea lice count, used as the standstill limit. If adopted, such a procedure could lead to a reduction in the limit of sea lice permitted on an individual farm – a “ratchet effect.” SEPA have stated as a matter of record that this will not happen.
Another concern expressed was that “baseline data” on sea lice numbers around Scotland should be determined (i.e. sea lice numbers in the absence of aquaculture). There are limited historic data, which do show geographic differences (detailed in Annex B), but historic records are sparse, and we cannot retrospectively know that which was not measured.
Concern 3.4, Adaptive use of near-real-time data
Response
R3: Full framework to be implemented.
The framework has been applied without a clear adaptive mechanism. It needs to be stated clearly when, and on what evidence-base, adaptation of the framework will take place. As an active field of research, improvements will be forthcoming. For example, adapting to an approach in setting sea lice limits that incentivises good fish husbandry and a provision to adapt regulation on a near-real-time basis in line with near-real-time reporting of lice numbers.
Concern 3.5, Refined modelling
Response
R3: Full framework to be implemented.
“Refined modelling” is required for higher relative risk farms if relative risk re-categorisation is to be considered, and for some relative risk category new farms. Unambiguous technical and scientific descriptions of what acceptable refined modelling looks like should be published by the regulator (relates to R1).
Concern 3.6, Fish health
Response
This is an intersection between two different regulations: consented biomass, and sea lice limit. It is common for an industry to have different regulations that interact on the ground. It is for the industry to decide how to comply with all pertinent regulation. In this case, if the primary concern is worker wellbeing or fish health, then stocks must be held below consented biomass, or other techniques devised to reduce lice-per-fish. This is deemed not to be an issue for the regulator, who is aware and has published their consideration of the issue.
Concern 3.7, Proportionality
Response
It is accepted by the regulator that reasons for the universal decline in wild salmon numbers in east and west coast rivers over the last few decades are unclear. There are a complex range of reasons, some related to well-documented oceanic changes. The historic decline is not relevant to the SLRF. The SLRF addresses whether the present-day pressure of sea lice is now significant on wild salmon whose stocks are at historically low levels.
This concern is part-related to Concern 3.8 (Efficacy), to which recommendation R4 applies.
Concern 3.8, Efficacy
Response
R4: Shape of success to be defined.
It is unclear how and when it will be judged whether the SLRF has been a success. Experience from Norway suggests this will not be trivial. Details of monitoring programme arrangement, and how success criteria will be assessed including disentangling other pressures and natural variation, which requires explicit consideration of compounded uncertainty of many pressures on wild salmon. There are regulator statements that this will be done, but insufficient detail: how (statistical methodology, including uncertainty analysis), by whom and when.
SLRF implementation
13. The SLRF uses observations and predictive numerical models to solve two aspects of the classic “encounter problem”. A detailed process description is given in Annex C, here we summarise using figures 1 and table 1.
14. The screening model sets out to quantify the post-smolt/sea lice encounter problem: how many sea lice does a seaward-migrating salmon post-smolt encounter, and where did those sea lice originate? A problem trivial to state and complex to solve.
15. The SLRF uses the same physics as weather forecasting models, here applied to the water flow around Scotland. Every farm is treated as a point source of sea lice, the size of each source is derived from fish numbers, generated from the farms authorised biomass limit and a standardised number of adult female sea lice per fish (see Annex C for details).
16. The SLRF simulates the natural variation in post-smolt migration routes by moving virtual post-smolts through the simulated moving water that contains sea lice released from point-source farms, and by varying the smolt route many times to estimate how much the precise route matters to the number of sea lice encountered.
17. The SLRF only attempts to solve the encounter problem at the main season for post-smolt migration from rivers to sea (April and May). These elements of the SLRF are shown in the top boxes of the flow diagram in Figure 1.
18. SLRF keeps track of every sea louse the post-smolt encounters and from which farm the lice originated, in addition to the total number of encounters. If the total number of encounters is less than some threshold considered acceptable for wild post-smolt health, then there is “remaining environmental capacity” for smolts to encounter a greater number of sea lice without undue detriment. Remaining environmental capacity forms the x-axis of the “relative risk matrix” in Figure 1. How much did each farm contribute to the total number of encounters? This forms the y-axis of the relative risk matrix.
19. In this way every single farm occupies a single box in the relative risk matrix: x-axis determined by all farms, y-axis determined by the farm in question. The relative risk matrix is then partitioned diagonally into four relative risk categories (1=low/green, 2=medium/yellow, 3=considerable/amber, 4=high/red).
20. All farms with a relative risk category 1 or “low relative risk” as designated by SEPA are not subject to sea lice limit conditions. They are subject to sea lice monitoring and reporting conditions allowing SEPA to track sea lice numbers on the farms and intervene if those numbers are rising to levels likely to result in the sea lice exposure threshold being exceeded.
21. Farms in relative risk categories 2, 3 and 4 are all subject to (standstill) sea lice limit conditions and have measures applied by the regulator (detailed in Annex C). For this reason, the methodology of SLRF just described is called the “screening model”. Note: the screening model is applied only to farms in areas designated as Wild Salmon Protection Zones (WSPZs)[3], though the effects of lice from farms out with WSPZs are accounted for (Annex C).
Relative Risk Assessment Matrix
The matrix combines two assessments to assign a relative risk category (1–4) to each salmon farm. The rows represent a farm's individual contribution to sea lice exposure in the Wild Salmon Protection Zone (WSPZ); the columns represent the remaining environmental capacity in the WSPZ after all farm contributions are summed.
| Farm contribution to sea lice exposure | Remaining environmental capacity in WSPZ | ||
|---|---|---|---|
| Large remaining capacity | Intermediate remaining capacity | Little or no remaining capacity | |
| Substantial contribution | 2 – Medium | 3 – Considerable | 4 – High |
| Moderate contribution | 1 – Low | 2 – Medium | 3 – Considerable |
| Small contribution | 1 – Low | 1 – Low | 2 – Medium |
| Negligible contribution | 1 – Low | 1 – Low | 1 – Low |
Key: 1 = Low relative risk; 2 = Medium relative risk; 3 = Considerable relative risk; 4 = High relative risk.
Higher risk scores indicate greater regulatory focus is needed. Risk increases when a farm contributes substantially to sea lice exposure and/or little environmental capacity remains in the WSPZ. New farms receive risk-based permit conditions and numeric lice limits; existing farms receive standstill or reduction conditions depending on their score.
Figure 1. Plain text description and flow chart of the SLRF process – based on an interpretation of published information on data processing undertaken by the regulator in establishing the farm-based relative risk assessment matrices.
22. There is a further complexity around sea trout (for example in Northern Isles where there are no designated salmon rivers), where instead the protection zones for sea trout will cover defined areas of sea. Within sea loch systems, they will extend up to 20 km from the relevant river mouths. For rivers flowing out into open sea areas, they will extend outward from the river mouth for 5 km. The use of the word “will” accurately reflects the language used by the regulator on this matter.
23. Figure 2 lists the numerical values of the technical parameters used in the screening model, based on scientific literature. The individual accuracy of the numerical values of the technical parameters used in the screening model and the combinatory effects of their accuracy on the outcomes of the screening process are relevant to the recommendation R2 of this report.
24. Detailed textural expansion of Figures 1 and Table 1 is given in Annex C. Much of this explanation is also attempted in SEPA’s documentation[4], the reason to revisit in such detail here and in Annex C is relevant to recommendation R1.
Relative risk-categorised interventions
25. Annex C summarises the interventions and conditions applied to salmon farms according to which of the four relative risk categories they are assigned. Existing farms and new or expanding farms are treated differently.
The key point regarding new or expansion applications is that data from the preapplication process are used to run the screening model, and those that are categorised as 3 or 4 require sea lice limits to be set by using what is termed as “additional refined modelling”, relevant to recommendation R3. Table 1. Published parameter values and descriptions for use in determining aspects of the screening model processes as part of the risk assessment process.
| Technical Parameter | Value | Notes |
|---|---|---|
| Post-smolt speed | 12.5 cm/s | ≈ 1 body length/second |
| Exposure threshold | 0.7 lice m⁻² days | 95th percentile |
| Lice development |
After 4 days to attachment: Mortality at 17 days Temperature dependent (10°C applied) |
|
| Protection period |
Salmon: Weeks 12–22 Sea trout: Weeks 12–44 |
|
| Lice mortality | 17% daily mortality post-hatching | Applied to particle mass |
| Lice production | 30 new sea lice per female/day | |
| Sea lice biology (post-hatching) |
Mortality: 17% per day (applied to particle mass) Infective window: age> 4 days and < 17 days Upward swimming speed velocity: 0.0014 m/s |
|
| Relative contribution categories |
Negligible: <10% Small: 10 – <20% Moderate: 20 – <30% Substantial: ≥30% |
These are not exposure thresholds but categories of relative contribution to exposure as percentage of the sea lice exposure threshold |
27. For all farms, weekly sea lice counts, and fish numbers reporting are required between Week 12 – 22 (approximately 16th March - 30th May) every year adhering to SEPA specified counting protocols. The stated plan is to use these data to re-run screening assessments each year.
Contact
Email: CSAMarine@gov.scot