Non-breeding season

Surveys in the offshore ornithology aerial survey study area indicate that during the generic non-breeding season (September to March), auks remained the most frequently recorded species group, where over half of all birds recorded during this period were guillemots. Other frequently recorded species (in descending order of frequency) were fulmar, puffin, kittiwake, gannet, razorbill and great black-backed gull. Species recorded infrequently (less than ten occasions during the generic non-breeding season) were herring gull, common gull and little auk (Alle alle).
All species were distributed relatively evenly across the offshore ornithology aerial survey study area. This change in the distribution of records when compared with the breeding season is likely explained by the known ecology of colonial seabirds. Outside the breeding season, breeding birds are not constrained by requirements to visit nests to incubate eggs or provision chicks. They are assumed to range more widely and to mix with birds of all age classes. In the case of many species, there is also mixing of birds from breeding colonies situated closer to the Array, with birds from breeding colonies in the UK and further afield.
Seaducks, divers, grebes, and waders, which spend the non-breeding season in the inner Firth of Forth and Firth of Tay in nationally important numbers, were absent from the offshore ornithology aerial survey study area and the area to the west of it during the first year of surveys. It is presumed that this is due to the distance between this area and the coast.
Very small numbers of some migratory species were recorded during the first year of surveys in the offshore ornithology aerial survey study area. Observations were limited to Arctic tern, common tern, little gull and Manx shearwater.
Passage movements are generally considered difficult to assess comparatively, using aerial survey methods. This is because they generally occur over relatively short periods and therefore may be missed by monthly surveys. Movements can also take place at high altitudes, and/or at night when detection is difficult. It is therefore considered possible that other seabird species such as petrels, in addition to non-seabird ornithology receptors, may use the offshore ornithology aerial survey study area during passage, but were not detected during the first 12 months of surveys. Many species are known to cross the North Sea in spring and autumn in large numbers.
Where possible, existing information in the literature will be used to characterise potential use of the offshore ornithology aerial survey study area by passage species.

Designated conservation sites for birds

A full screening of European designated sites with qualifying bird species has been undertaken and is detailed within the LSE Screening Report for the Array. The LSE Screening Report has been circulated for consultation alongside this Scoping Report. Relevant qualifying species of European designated sites screened into the ornithology assessment will be fully considered and assessed in the Array EIA Report. The assessment on the European designated sites themselves will be deferred to the RIAA.
Designated sites including SPAs, proposed SPAs (pSPAs) and Ramsar sites, will be identified through the process described for identification of the offshore ornithology regional study area. This will generate a ‘long-list’ of designated sites with potential connectivity to the offshore ornithology aerial survey study area. Breeding season connectivity with qualifying features of breeding seabird colony SPAs will be defined by species’ breeding season foraging ranges (using the mean maximum plus one standard deviation (Woodward et al., 2019)). Outside the breeding season, there is potential for connectivity with a greater range of qualifying features from breeding seabird colony SPAs than during the breeding season. Consideration of the potential for non-breeding season effects associated with the Array will be based upon information on Biologically Defined Minimum Population Scales (BDMPS) presented in Furness (2015) for all species other than guillemot and herring gull (NatureScot, 2021; Marine Scotland, 2022b). For both guillemot and herring gull, the breeding season foraging range will be used as these species are not considered to disperse as widely from the breeding areas compared to other seabird species during the non-breeding season (noting that for herring gull a correction, analogous to that used in the BDMPS approach, will also be applied to account for the influx of continental breeding birds to the wintering population on the east coast of the UK (Royal Haskoning DHV, 2022).
Based upon the above, there is potential for connectivity with a wide range of the breeding seabird colonies in the UK, particularly those on the east coast, and it is recognised that there will be many colonies, including designated sites, that could be impacted by both project alone effects and cumulative effects with other developments. The LSE Screening Report will provide full details of the relevant designated sites and features which are considered to have connectivity with the Array and will identify the potential effect pathways, so enabling the determination of sites and features for which LSE cannot be excluded. The subsequent RIAA will undertake the assessment for those sites and features for which LSE cannot be excluded.

Summary of first year of data from the baseline aerial survey programme

Based upon data from the first year of surveys, it is apparent that the following species comprise the vast majority of the birds occurring within the offshore ornithology aerial survey study area during both the breeding and non-breeding periods ( Table 6.15 Open ▸ ):

gannet;
kittiwake;
guillemot;
razorbill;
puffin; and
fulmar.

Other species tend to be recorded sporadically within the aerial survey data and at a level of abundance which is at least one order of magnitude less than that of the six species listed above. Subject to similar findings emerging from the second year of the aerial survey programme, it is therefore highly likely that the key species for the assessment will be included amongst the six species listed above.

Table 6.15: Occurrence and Abundance of Seabird Species Recorded in the Offshore Ornithology Aerial Survey Study Area During the First Year of Surveys1

Species	Breeding Season2		Non-Breeding Season2
Species	Number of Surveys in which Species Recorded	Mean Abundance (Number of Individuals per Survey) with 95% Confidence Interval3	Number of Surveys in which Species Recorded	Mean Abundance (Number of Individuals per Survey) with 95% Confidence Interval3
Gannet	7	2728 2038 - 3526	4	990 762 - 1216
Kittiwake	5	5585 3616 - 8167	7	596 277 - 1044
Guillemot	5	33666 23576 - 45515	7	9122 7257 - 11170
Razorbill	5	2665 1545 - 4016	6	206 111 - 312
Puffin	5	2161 1569 - 2875	6	786 585 - 1002
Fulmar	5	1572 1048 - 2282	7	1029 720 - 1415
Herring gull	5	46 4 - 126	3	12 1 - 26
Lesser black-backed gull	2	4 0 - 14	0	0 0 - 0
Great black-backed gull	1	2 0 - 6	4	81 45 - 128
Common gull	3	14 0 - 32	5	15 3 - 39
Little gull	1	2 0 - 6	0	0 0 - 0
Great skua	3	6 0 - 16	1	1 0 - 4
Arctic / common tern	2	454 128 - 911	0	0 0 - 0
Little auk	0	0 0 - 0	2	4 0 - 11
Manx shearwater	3	31 6 - 65	0	0 0 - 0
Wigeon Anas penelope	0	0 0 - 0	1	1 0 - 4

Notes:

1 – Data are presented without any apportioning of records identified to a broader group level to the species level, and without correction for availability bias.

2 – To avoid complications with half-months, and for the purpose of this preliminary presentation of the aerial survey data, the breeding season is defined as April to August for all species other than gannet for which it is defined as March to September.

3 – Values for the confidence intervals are derived by taking the average of these as calculated for the estimate from each individual survey (as opposed to calculating them on the basis of averaging across the mean estimates from each survey).

6.4.4. Designed In MeasuresDesigned In Measures

Full consideration will be given to the potential to minimise any impacts via the adoption of appropriate designed in measures. At this stage it is not possible to identify the range of designed in measures that may be adopted but examples of designed in measures that are likely to be considered, including how these could reduce potential for impact, ( Table 6.16 Open ▸ ) include:

the use of low order deflagration techniques during UXO clearance;
the incorporation of an appropriate air gap into wind turbine design to reduce collision rates between offshore ornithology receptors and operational turbines; and
optimised layout scenarios.

The options for adopting such designed in measures will be kept under review during the assessment process.

6.4.5. Potential Impacts After the Implementation of Designed in MeasuresPotential Impacts After the Implementation of Designed in Measures

The impacts that have been scoped into the Array assessment are outlined in Table 6.16 Open ▸ together with a description of any additional supporting analyses (e.g. modelling) that will be required to enable a full assessment of the impacts. No impacts are proposed to be scoped out as a consequence of the designed in measures implemented.

Table 6.16: Impacts Proposed to be Scoped Into the Array Assessment for Offshore Ornithology. Project Phase Refers to Construction (C), Operation and Maintenance (O) and Decommissioning (D) Phase of the Array

Impact	Project Phase			Justification (including consideration of embedded mitigation measures)	Data Collection and Analysis Required to Characterise the Baseline Environment for the EIA	Summary of Proposed Approach to Assessment
Impact	C	O	D			Summary of Proposed Approach to Assessment
Temporary habitat loss and disturbance				The presence of vessels and construction or decommissioning works (including wet storage facilities) may temporarily disturb and/or displace offshore ornithology receptors present in the vicinity of works. This has the potential to affect productivity or survival.	Offshore ornithology abundance estimates from baseline aerial surveys will be used to estimate the numbers of birds potentially impacted.	Best practice methodologies and latest published information will be drawn upon to estimate potential disturbance distances and rates for key species.
Indirect Impacts from construction/decommissioning noise				The reduction or disruption of prey availability may cause reduced energy intake in offshore ornithology receptors, which could potentially affect productivity or survival.	The use of site-specific baseline data is not proposed.	Potential impacts will be estimated using best practice methodologies and latest published information.
Indirect impacts from UXO clearance				The potential for physical injury and death to diving offshore ornithology receptors below water at time of detonation. The reduction or disruption of prey availability due to detonations may cause reduced energy intake affecting productivity or survival of offshore ornithology receptors. This will be mitigated by low-order clearance.	The use of site-specific baseline data is not proposed.	Potential impacts will be estimated using best practice methodologies and latest published information.
Disturbance and displacement from the physical presence of wind turbines and maintenance activities				The presence of operational wind turbines and the maintenance activities associated with their operation may disturb offshore ornithology receptors and displace them from their foraging or resting areas. This has the potential to affect productivity or survival.	Offshore ornithology abundance estimates from baseline aerial surveys will be used to estimate the numbers of birds potentially impacted.	Potential impacts will be estimated using best practice methodologies (e.g. a matrix-based approach for all species scoped into assessment, and potentially SeaBORD for relevant species during specific times of year). For any population for which it is required, Population Viability Analysis (PVA) will be used to assess the consequences of predicted impacts at the population level.
Barrier to movement				The presence of operational wind turbines may result in additional energy and/or time expenditure as migrating or commuting offshore ornithology receptors fly longer distances either over, under, or around the wind farm. This has the potential to affect productivity or survival.	Offshore ornithology abundance estimates from baseline aerial surveys will be used to estimate the numbers of birds potentially impacted.	Potential impacts will be estimated using best practice methodologies (e.g. a matrix-based approach for all species scoped into assessment, and potentially SeaBORD for relevant species during specific times of year). For any population for which it is required, PVA will be used to assess the consequences of predicted impacts at the population level.
Collision with wind turbines				Collisions between offshore ornithology receptors will result in direct mortality. This will result in reductions in seabird populations and/or breeding success. This will be mitigated by the selection of an appropriate air gap between the sea surface and the lowest part of the rotor swept area. This air gap has not yet been selected but will be informed by the results of the preliminary Collision Risk Model (CRM).	Offshore ornithology abundance estimates from baseline aerial surveys will be used to estimate the numbers of birds potentially impacted.	Potential impacts will be estimated using best practice methodology (e.g. stochastic CRM (sCRM)). For any population for which it is required, PVA will be used to assess the consequences of predicted impacts at the population level.
Changes to prey availability				Indirect impacts on seabirds may occur as a result of changes in prey distribution, availability or abundance, caused by construction/decommissioning activities that disturb the seabed (and cause increased SSCs) or increase subsea noise levels.	Offshore ornithology abundance estimates from baseline aerial surveys will be used to estimate the numbers of birds potentially impacted.	Best practice methodologies and latest published information and other available evidence will be drawn upon to estimate potential effects on key species.
Entanglement				With the advent of floating offshore wind, the potential for entanglement of diving seabirds with floating foundations during the operation and maintenance period has been raised.	Offshore ornithology abundance estimates from baseline aerial surveys will be used to estimate the numbers of birds potentially impacted.	Best practice methodologies and latest published information and other available evidence will be drawn upon to estimate potential effects on key species.

6.4.6. Relevant ConsultationsRelevant Consultations

A summary of the details of the consultations with relevant stakeholders and Statutory Nature Conservation Bodies (SNCBs) undertaken to date is presented in Table 6.17 Open ▸ .

Table 6.17: Summary of Key Consultation on the Scoping Assessment for the Array

Date	Consultee	Type of Consultation	Summary of Consultation	Where Addressed?
14 November 2022	MS-LOT, MSS, NatureScot and RSPB	Scoping workshop	NatureScot advised use of the Marine Renewables Strategic Environmental Assessment (MRSea) package to derive bird densities from the baseline aerial survey data (i.e. model-based), as opposed to using design-based approaches. However, based on their understanding of the different approaches and of recent experience in other projects, the Applicant considers that design-based approaches are likely to be more appropriate.	The proposed approach (and associated rationale) to deriving bird densities for use in the EIA is outlined in section 6.4.7.
			NatureScot requested access to end of year survey reports, which they think may be useful in determining what has happened to bird populations as a result of HPAI.	Summary data on preliminary bird abundance from the first year of baseline surveys are presented in Table 6.15 Open ▸ . Further analyses of baseline data to estimate densities and abundance will not be available until after completion of the survey programme (with these expected to be available by June 2023). The report detailing these data will be made available to stakeholders.
			The Applicant requested information on when NatureScot guidance on the implications of the HPAI outbreak for offshore wind farm assessments would become available, with NatureScot confirming that work on this is ongoing and that it would be made available as soon as possible.	The requirement for consultation on HPAI is highlighted in sections 6.4.7 and 6.4.10.
			NatureScot indicated that publication of the Apportioning Guidance Note may be slightly later than for other guidance notes. The Applicant indicated their interest in accessing this guidance.	The proposed approach to undertaking apportioning is outlined in section 6.4.7.
			The Applicant highlighted the need for guidance to be available on CRM approaches, with NatureScot agreeing that the approach outlined by the Applicant is what they were expecting. NatureScot stated that they are currently working on the timings for releasing the guidance. The Applicant indicated that further consultation on this will be important following receipt of the Scoping Opinion.	The proposed approach to undertaking CRMs is outlined in section 6.4.7.
			The Applicant emphasised the importance of maintaining good communications with key stakeholders, particularly in the context of the impending emergence of nine different guidance notes that will have critical importance to the assessment.	Specific issues on which further, focussed, engagement is considered to be essential are outlined in section 6.4.10.

6.4.7. Proposed Approach to the Environmental Impact Assessment Proposed Approach to the Environmental Impact Assessment

The Array EIA Report will be supported by a number of technical appendices, which will provide full details of the approaches that underpin key areas of the assessment. These include:

baseline report and approach to density estimation;
apportioning;
CRM;
assessments of operational phase displacement;
PVA; and
inter-related effects approach.

The following sections provide an overview of key considerations which are pertinent to each of the bullet points listed above. For the purposes of this Scoping Report, all relevant species recorded during the first year of baseline surveys are considered. Any species not recorded during the first year of baseline surveys but subsequently recorded during the second year of surveys will be added to the assessment.
During recent consultation (November 2022) with MS-LOT, MSS and NatureScot, the imminent publication of NatureScot guidance on assessing the potential impacts of offshore wind farms on ornithology receptors was discussed (noting that most of this guidance has now been published, as of early February 2023). Whilst they have been produced with regard to current best practice for such assessment in mind, the following sections of this Scoping Report will be considered in light of the new guidance, which is now largely published, so as to update any assessment methodologies required prior to the assessment being undertaken, in discussion with key stakeholders as is necessary.
It is also recognised that it is best practice to seek further focused engagement with stakeholders beyond scoping as the assessment progresses, to ensure alignment between the technical assessment and the expectations of stakeholders and, consequently, the production of an assessment which provides as much confidence to all parties as is possible. Focused engagement with stakeholders will be undertaken following the approach set out within the dSEP (Appendix 1).

Density estimation

It is proposed to base the Array assessment on abundance and density estimates of offshore ornithology receptors within the offshore ornithology aerial survey study area, and appropriate reporting regions within it, as calculated using design-based methods. Recently NatureScot and MSS have indicated preferences for such abundance/density estimates to be derived using model-based approaches, most notably the MRSea package [9] (e.g. NatureScot 2020a; Marine Scotland 2022b). It is unclear what advantages such approaches currently offer, with MRSea specifically designed for another purpose (i.e. testing for temporal effects following marine renewables developments, whilst accounting for spatial variation in densities), and with the apparent benefit of the approach in estimating densities being dependent on having environmental variables that are correlated with the spatial variation in the density of the target species. Such correlations are rarely identified within offshore survey data for the seabird species that are likely to be of key interest for the Array. This may be due, in part, to the relatively coarse level environmental co-variates that are currently available for such modelling exercises, but it is also likely to be attributable to the fact that the birds occurring on such survey areas will comprise a proportion that are simply commuting through the site and roosting or loafing, as opposed to being actively engaged in foraging. The distribution of birds engaged in such different activities is likely to be determined by different effects, making it unlikely that they will show consistent responses to particular co-variates.
Perhaps most importantly, recent experience in applying model-based approaches to the estimation of seabird densities using offshore survey data appears to demonstrate no advantages over design-based methods and, rather, may point towards potential pitfalls. Thus, work undertaken for the Berwick Bank Offshore Wind Farm application demonstrated that the monthly density estimates for a range of the key seabird species, as derived by design-based and model-based approaches, were generally very similar (Harker et al., 2022). However, there were notable exceptions to this, which, in some instances at least, could be attributed to the modelling producing unrealistic estimates due to an inability to resolve spatial and temporal gaps in survey coverage, with such gaps often being unavoidable in large-scale offshore survey programmes. Furthermore, variability about the model-based estimates was greater than for the design-based estimates, whilst the stochasticity within the modelling process meant that markedly different outputs could be generated from different model runs based on identical input data and parameters. Consequently, the Berwick Bank Offshore Wind Farm application relied upon the outputs from the design-based density estimates.
It is expected that any potential benefits of using model-based approaches for estimating seabird densities within offshore survey areas are more likely to be realised when such approaches are applied to large survey areas which are relatively close to the coast and have high densities of seabirds. Such situations are more likely to provide adequate sample sizes for model-fitting, incorporate more marked environmental gradients (increasing the chances of identifying correlates of seabird density) and include higher proportions of seabirds engaged in foraging activities, at least during the breeding season (e.g. Wakefield et al. 2017; Bogdanova et al. 2022). Despite these conditions being met by the Berwick Bank Offshore Wind Farm application, model-based approaches to density estimation did not provide benefits over design-based approaches. In relation to the Array, the considerably greater distance offshore when compared with the Berwick Bank Offshore Wind Farm will likely result in relatively low densities of the key seabird species, with less marked broad-scale environmental gradients. Thus, it is likely that model-based approaches offer considerably less potential to the Array than for the Berwick Bank Offshore Wind Farm and, as such, it is proposed that design-based approaches are used.

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