pre‐construction aerial survey report 2018

Pre‐construction Aerial Survey Report 2018

Moray East Offshore Wind Farm

November 2018

Moray Offshore Windfarm (East) Limited

Moray Offshore Windfarm (East) Limited Pre‐construction Aerial Survey Report 2018

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Produced by APEM Ltd on behalf of Moray Offshore Windfarm (East) Limited

Produced by Dr Rob Catalano, Stephanie McGovern, Laura Jervis

Reviewed by Dr Roger Buisson

Document Status Final for information

File Name (Moray East) 8460001‐ PCA0010‐APE‐REP‐002

File Name (APEM) P00002313_Moray East Pre‐construction Aerial Surveys 2018 Annual Report

Date 15/11/18

Review / Approval

Moray East Ecological Clerk of Works Moray East

Fiona Moffatt

[Royal HaskoningDHV]

Catarina Rei

[Offshore Consents Manager]

Sarah Pirie

[Head of Development]

Moray Offshore Windfarm (East) Limited Pre‐construction Aerial Survey Report 2018

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© Moray Offshore Windfarm (East) Limited 2018

This document contains proprietary information which belongs to Moray Offshore Windfarm (East) Limited and / or affiliated companies and shall be used only for the purpose for which it is supplied. Moray Offshore Windfarm (East) Limited shall have no liability for any loss, damage, injury, claim, expense, cost or other consequence arising as a result of use or reliance upon any information contained in or this document where it is not used the purpose for which it is supplied.

Moray Offshore Windfarm (East) Limited Pre‐construction Aerial Surveys 2018 Annual Report

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Table of Contents List of Abbreviations ..................................................................................................................................... 7

Executive Summary ...................................................................................................................................... 8

1 Introduction .......................................................................................................................................... 9

1.1 Ornithological monitoring requirements ..................................................................................... 9

1.2 Objectives of the pre‐construction aerial surveys ..................................................................... 10

2 Methods ............................................................................................................................................. 12

2.1 Survey Methods ......................................................................................................................... 12

2.1.1 Data collection .................................................................................................................... 12

2.2 Data Analysis Methods ............................................................................................................... 14

2.2.1 Design‐based abundance estimates ................................................................................... 14

2.2.2 Spatial abundance mapping ............................................................................................... 15

2.2.3 Flight height frequency distribution ................................................................................... 16

2.3 Flight direction............................................................................................................................ 16

3 Results ................................................................................................................................................ 17

3.1 Survey Information ..................................................................................................................... 17

3.1.1 Survey timings .................................................................................................................... 17

3.1.2 Weather .............................................................................................................................. 17

3.1.3 Shipping information .......................................................................................................... 17

3.2 Primary Species Accounts........................................................................................................... 18

3.2.1 Puffin .................................................................................................................................. 18

3.2.2 Great black‐backed gull ...................................................................................................... 23

3.3 Secondary Species Accounts ...................................................................................................... 26

3.3.1 Herring gull ......................................................................................................................... 26

3.3.2 Guillemot ............................................................................................................................ 29

3.3.3 Razorbill .............................................................................................................................. 32

3.4 Tertiary Species Accounts........................................................................................................... 35

3.4.1 Kittiwake ............................................................................................................................. 35

3.4.2 Gannet ................................................................................................................................ 38

3.5 Comparison of flight heights with the 2010‐2012 boat based surveys...................................... 42

4 Discussion ........................................................................................................................................... 45

4.1 Abundance Estimates and Distributions .................................................................................... 45

4.1.1 Primary Species .................................................................................................................. 46

4.1.2 Secondary Species .............................................................................................................. 46

4.1.3 Tertiary Species .................................................................................................................. 46

4.2 Comparison with 2010‐2012 boat data from the ES .................................................................. 46


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5 Conclusion .......................................................................................................................................... 50

6 References .......................................................................................................................................... 51

Appendix 1 ‐ Weather Reporting Scales ..................................................................................................... 53

Appendix 2 ‐ JNCC Species Groups and Group Codes ................................................................................ 54

Appendix 3 ‐ Scientific Names of Species Recorded .................................................................................. 55

Appendix 4 ‐ Auk availability bias ............................................................................................................... 56

Appendix 5 ‐ Puffin Modelling Outputs ...................................................................................................... 57

A5.1 Model selection outputs ............................................................................................................. 57

A5.2 Puffin confidence interval maps ................................................................................................. 60

A5.2.1 May ..................................................................................................................................... 60

A5.2.2 June ..................................................................................................................................... 61

A5.2.3 July ........................................................................................................................................... 62

Appendix 6 Distribution Maps .................................................................................................................... 63

A6.1 Primary species ........................................................................................................................... 63

A6.1.1 Great black‐backed gull ...................................................................................................... 63

A6.2 Secondary species ...................................................................................................................... 65

A6.2.1 Herring gull ......................................................................................................................... 65

A6.2.2 Guillemot ............................................................................................................................ 67

A6.2.3 Razorbill .............................................................................................................................. 68

A6.3 Tertiary species ........................................................................................................................... 70

A6.3.1 Kittiwake ............................................................................................................................. 70

A6.3.2 Gannet ................................................................................................................................ 72

Appendix 7 Abundance of other Species / Species Groups Accounts ........................................................ 74

List of Figures Figure 1.1: Location of the Moray East site and Survey Area. ..................................................................... 9

Figure 2.1: Survey transects for coverage of the Moray East site plus 10 km buffer. ............................... 12

Figure 3.2.1. Density surface distribution for puffins in May. .................................................................... 19

Figure 3.2.2. Density surface distribution for puffins in June. ................................................................... 20

Figure 3.2.3. Density surface distribution for puffins in July. ..................................................................... 20

Figure 3.2.4. Flight directions for puffin across the Survey Area. .............................................................. 22

Figure 3.2.5 Great black‐backed gull spatial distribution and numbers for the combined surveys of the

Survey Area. ................................................................................................................................................ 24

Figure 3.2.6. Great black‐backed gull flight height distribution. ................................................................ 24

Figure 3.2.7. Flight directions for great black‐backed gull across the Survey Area. ................................... 25

Figure 3.3.1 Herring gull spatial distribution and numbers for the combined surveys of the Survey Area.

.................................................................................................................................................................... 27

Figure 3.3.2. Herring gull flight height distribution. ................................................................................... 27


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Figure 3.3.3. Flight directions for herring gull across the entire survey area. ........................................... 28

Figure 3.3.4 Guillemot spatial distribution and numbers for the combined surveys of the Survey Area. 30

Figure 3.3.5. Guillemot flight height distribution. ...................................................................................... 31

Figure 3.3.6. Flight directions for guillemot across the entire survey area. .............................................. 32

Figure 3.3.7 Razorbill spatial distribution and numbers for the combined surveys of the Survey Area. .. 34

Figure 3.3.8 Flight directions for razorbill across the entire survey area. .................................................. 35

Figure 3.4.1 Kittiwake spatial distribution and numbers for the combined surveys of the Survey Area. . 37

Figure 3.4.2 Kittiwake flight height distribution. ........................................................................................ 37

Figure 3.4.3 Flight directions for kittiwakes across the Survey Area. ........................................................ 38

Figure 3.4.4 Gannet spatial distribution and numbers for the combined surveys of the Survey Area. .... 40

Figure 3.4.5 Gannet flight height distribution. ........................................................................................... 40

Figure 3.4.6 Flight directions for gannets across the Survey Area. ............................................................ 41

Figure 4.2.1 Densities for the key species recorded during the 2018 pre‐construction surveys in

comparison to the boat data taken from the Moray East ES 2012. ........................................................... 49

Figure A5.1.1. Knot grid locations (green) for the 2d spatial smooth of x and y coordinates ................... 57

Figure A5.1.2. ACF plot showing correlation in each block (grey lines), and the mean correlation by lag

across blacks (red line) ............................................................................................................................... 57

Figure A5.1.3. Partial fit plots for continuous variable Distance and factor Month on the response scale

.................................................................................................................................................................... 58

Figure A5.1.4. Partial fit plots for continuous variable Distance and factor Month on the link scale ....... 59

Figure A5.1.5. Lower and upper confidence interval distribution maps .................................................... 60



Figure A6.1.1. Great black‐backed gull distribution in May ....................................................................... 63

Figure A6.1.2. Great black‐backed gull distribution in June ....................................................................... 64

Figure A6.1.3. Great black‐backed gull distribution in July ........................................................................ 64

Figure A6.2.1. Herring gull distribution in May .......................................................................................... 65

Figure A6.2.2. Herring gull distribution in June .......................................................................................... 66

Figure A6.2.3. Herring gull distribution in July ........................................................................................... 66

Figure A6.2.4. Guillemot distribution in May ............................................................................................. 67

Figure A6.2.5. Guillemot distribution in June ............................................................................................. 67

Figure A6.2.6. Guillemot distribution in July .............................................................................................. 68

Figure A6.2.7. Razorbill distribution in May ............................................................................................... 68

Figure A6.2.8. Razorbill distribution in June ............................................................................................... 69

Figure A6.2.9. Razorbill distribution in July ................................................................................................ 69

Figure A6.3.1. Kittiwake distribution in May .............................................................................................. 70

Figure A6.3.2. Kittiwake distribution in June ............................................................................................. 71

Figure A6.3.3. Kittiwake distribution in July ............................................................................................... 71

Figure A6.3.4. Gannet distribution in May ................................................................................................. 72

Figure A6.3.5. Gannet distribution in June ................................................................................................. 72

Figure A6.3.6. Gannet distribution in July .................................................................................................. 73


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List of Tables Table 1.1: Key species, breeding colonies and key wind farm effects to be monitored. ........................... 10

Table 3.1.1: Dates and times of the 2018 pre‐construction aerial surveys of Survey Area. ...................... 17

Table 3.1.2: Weather conditions recorded during the 2018 pre‐construction aerial surveys of Survey

Area (see Appendix 1 for weather reporting scales). ................................................................................. 17

Table 3.2.1. Puffin modelled abundance estimates. .................................................................................. 18

Table 3.2.2. Model specifications for puffin, including smooth function and covariates. The GEE based p‐

value for the terms in the model are also shown. ..................................................................................... 19

Table 3.2.3 Puffin abundance estimates. ................................................................................................... 21

Table 3.2.4 Puffin density estimates per km2. ............................................................................................ 21

Table 3.2.5 Puffin flight directions. ............................................................................................................ 22

Table 3.2.6. Great black‐backed gull abundance estimates. ...................................................................... 23

Table 3.2.7. Great black‐backed gull density estimates per km2. .............................................................. 23

Table 3.2.8. Great black‐backed gull flight directions. ............................................................................... 25

Table 3.3.1 Herring gull abundance estimates ........................................................................................... 26

Table 3.3.2 Herring gull density estimates per km2 .................................................................................... 26

Table 3.3.3. Herring gull flight directions. .................................................................................................. 28

Table 3.3.4. Guillemot abundance estimates. ............................................................................................ 29

Table 3.3.5 Guillemot density estimates per km2. ..................................................................................... 29

Table 3.3.6 Guillemot flight directions. ...................................................................................................... 31

Table 3.3.7 Razorbill abundance estimates. ............................................................................................... 33

Table 3.3.8 Razorbill density estimates per km2. ....................................................................................... 33

Table 3.3.9 Razorbill flight directions ......................................................................................................... 34

Table 3.4.1 Kittiwake abundance estimates. .............................................................................................. 36

Table 3.4.2 Kittiwake density estimates per km2. ...................................................................................... 36

Table 3.4.3 Kittiwake flight directions. ....................................................................................................... 38

Table 3.4.4 Gannet abundance estimates. ................................................................................................. 39

Table 3.4.5 Gannet density estimates per km2. ......................................................................................... 39

Table 3.4.6 Gannet flight directions. .......................................................................................................... 41

Table 3.5.1 Comparison of flight height distributions flying at rotor height by species between the 2018

aerial survey and the 2010‐2012 boat surveys. ......................................................................................... 42

Table 3.5.2 Comparison of the proportion of birds flying at rotor height from the 2018 aerial survey, the

2010‐2012 boat surveys and the publication by Johnston et al (2014). .................................................... 43

Table 3.5.3 Comparison of selected flight heights with those reported in the literature ......................... 44

Table A7.1: Comparison of abundance of bird and marine mammal species recorded during the May

2018, June 2018 and July 2018 surveys in the Moray East site. ................................................................ 74

Table A7.2: Comparison of abundance of bird and marine mammal species recorded during the May

2018, June 2018 and July 2018 surveys in the Survey Area. ...................................................................... 76


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List of Abbreviations

2D Two‐Dimensional

ACF Autocorrelation Function

a.s.l. Above Sea Level

BTO British Trust for Ornithology

CF Correction Factor

CI Confidence Interval

CV Coefficient of Variation

ES Environmental Statement

GEE‐CReSS Generalised Estimating Equations‐Complex Region Spatial Smoother

GIS Geographical Information System

GPS Global Positioning System

GSD Ground Sample Distance

HAT Highest Astronomical Tide

JNCC Joint Nature Conversation Committee

MFRAG Moray Firth Regional Advisory Group

MFRAG‐O Moray Firth Regional Advisory Group Board – Ornithology Subgroup

MMMP Mitigation Management and Monitoring Plan

MRSea Marine Renewables Strategic Environmental Assessment

OWF Offshore Wind Farm

PEMP Project Environmental Monitoring Programme

SALSA Spatially Adaptive Local Smoothing Algorithm

SMRU Sea Mammal Research Unit

SPA Special Protection Area

UTM Universal Transverse Mercator

QA Quality Assurance

WGS World Geodetic System


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Executive Summary

The Moray East Offshore Wind Farm is located in the Moray Firth, at its closest point 22.2 km from the Caithness Coast. Pre‐construction digital aerial surveys were conducted between May and July 2018 to provide updated information on seabird and marine mammal distribution and abundance previously collected for the Moray Firth, and to provide a baseline dataset for later comparison with construction and post‐construction phase surveys. The construction of the wind farm is due to commence in May 2019.

Prior to the surveys commencing a power analysis was undertaken to inform the survey design of the pre‐construction aerial surveys. The aim was to have sufficient power to detect 30 % displacement of puffins from the wind farm. The survey design was agreed upon by the Moray Firth Regional Advisory Group – Ornithology Subgroup (MFRAG‐O).

Surveys of the Moray East Offshore Wind Farm and a 10 km buffer area were conducted using twin engine Vulcanair P68 survey aircraft capturing digital still imagery at 2 cm resolution. Transects were spaced 2.53 km apart to obtain a 10 % minimum coverage. Each of the three surveys was successfully completed within one day. Data presented within this report include bird locations, abundance and behavioural observations, including flight height and flight direction.

This report describes the results of the key species relating to potential impacts on breeding populations of great black‐backed gull and puffin (primary species), herring gull, common guillemot and razorbill (secondary species) and black‐legged kittiwake and northern gannet. With the exception of gannet all of these species breed within the East Caithness Cliffs Special Protection Area (SPA). Overall, seabird abundance and distributions in the Survey Area (wind farm plus buffer) were similar to those seen in previous surveys, with guillemot the most numerous species (peak > 22,650) followed by kittiwake (peak >11,300), razorbill (peak > 4450), herring gull (peak >3000), gannet (peak >2050), puffin (peak >1100) and great black‐backed gull (peak >300).

Evidence for connectivity between the Survey Area and the East Caithness Cliffs SPA for great black‐backed gull, puffin, and razorbill was limited due to the low numbers of individuals observed in flight. No inferred connectivity could be made for gannets as they displayed a statistically random flight direction. Potential connectivity could be inferred to the East Caithness Cliffs SPA for guillemot, kittiwake and herring gull.

Flight heights are reported for key species although only gannet and kittiwake contained 100 records or more for establishing flight height distributions. The method used currently generates estimates with poor precision, limiting the conclusions which can be drawn, although the median height distributions obtained were comparable with previous estimates.


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1 Introduction

Moray Offshore Windfarm (East) Limited commissioned APEM Ltd (APEM) to undertake three monthly pre‐construction digital aerial surveys of the Moray East Offshore Windfarm (Moray East site) plus a 10 km buffer area (hereafter referred to as the Survey Area; Figure 1.1) to provide information on the abundance, distribution and behaviour of birds and marine mammals.

Figure 1.1: Location of the Moray East site and Survey Area.

The Moray East site is located 22.2 km from the Caithness coast at its closet point to shore in the Moray Firth. The Moray Firth area supports internationally important numbers of breeding seabirds. Areas designated for breeding seabirds include East Caithness Cliffs Special Protected Area (SPA), North Caithness Cliffs SPA, Cromarty Firth and Inner Moray Firth SPAs and the Troup, Pennan and Lion’s Head SPA.

1.1 Ornithological monitoring requirements

As part of the Project Environmental Monitoring Programme (PEMP) for the Moray East Offshore Wind Farm, ornithological monitoring is required (Section 36 consents, condition 26) “to ensure that appropriate and effective monitoring of the impacts of the Development is undertaken”. The following is stated under the condition:

“The PEMP must set out measures by which the Company must monitor the environmental impacts of the Development. Monitoring is required throughout the lifespan of the Development where this is deemed necessary by the Scottish Ministers. Lifespan in this context includes pre‐construction, construction, operational and decommissioning phases.


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Monitoring should be done in such a way as to ensure that the data which is collected allows useful and valid comparisons as between different phases of the Development. Monitoring may also serve the purpose of verifying key predictions in the ES. Additional monitoring may be required in the event that further potential adverse environmental effects are identified for which no predictions were made in the ES.

The PEMP, of relevance to these surveys, stated the following matters to be covered:

a. Pre‐construction, construction (if considered appropriate by the Scottish Ministers) and post‐construction monitoring surveys as relevant in terms of the ES and any subsequent surveys for birds.

b. The participation by the Company in surveys to be carried out in relation to marine mammals as set out in the MMMP; and

c. The participation by the Company in surveys to be carried out in relation to regional and strategic bird monitoring.”

In consultation with the MFRAG, to comply with the above monitoring requirements, the key species and key effects to be monitored for the 2018 pre‐construction aerial surveys are as follows:

Table 1.1: Key species, breeding colonies and key wind farm effects to be monitored.

Common Name Scientific Name

Key Colonies Windfarm Effect Population Effect

Primary Great black‐backed gull

Larus marinus

East Caithness Cliffs SPA Collision mortality Adult survival

Atlantic puffin Fratercula

arctica

East Caithness Cliffs SPA Displacement effects

Adult productivity

North Caithness Cliffs SPA

Secondary Herring gull Larus

argentatus East Caithness Cliffs SPA Collision mortality Adult survival

Common guillemot

Uria aalge East Caithness Cliffs SPA Displacement effects

Adult productivity

Razorbill Alca torda East Caithness Cliffs SPA Displacement effects

Adult productivity

Tertiary Black‐legged kittiwake

Rissa

tridactyla

East Caithness Cliffs SPA Collision mortality Adult survival

Displacement effects

Adult productivity

Northern gannet Morrus

bassanus

Gamrie and Pennan Coast SSSI

Collision mortality Adult survival

Displacement effects

Adult productivity

1.2 Objectives of the pre‐construction aerial surveys

Construction of the Moray East Offshore Windfarm is due to commence in May 2019. Since 2009 a number of ornithology surveys have been undertaken in the Moray Firth, associated with pre‐construction monitoring of offshore wind farm developments (Moray East, Moray West and Beatrice Offshore Wind Farms) (Beatrice Offshore Windfarm Limited, 2016). As well as updating the seabird and marine mammal distribution and abundance data previously collected for the Moray Firth, the data presented within this report is aimed at providing a baseline dataset for later comparison with post‐construction phase surveys.


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During the 2018 breeding season three aerial surveys of the Survey Area were undertaken. Transects were spaced 2.53 km apart to achieve a minimum coverage of 10 % and imagery was captured at 2 cm resolution. Prior to the 2018 pre‐construction aerial surveys taking place a power analysis was carried out to inform the survey design so that a 30 % displacement effect of puffins in the Survey Area could be detected (Moray East, 2018), which was approved by the Moray Firth Regional Advisory Board – Ornithology Subgroup (MFRAG‐O) in May 20181.

The objectives of the pre‐construction aerial surveys were to:

Conduct pre‐construction breeding season surveys (May‐July) for one year to acquire information on seabird abundance, distribution, flight height and flight direction to enable comparisons of seabird data before and after construction;

Produce abundance estimates for each species (including age and gender, where possible) of birds in flight and on the sea by calendar month and season;

Produce spatial abundance maps of each species in flight and on the sea within the season and / or month (where appropriate);

Produce spatial abundance confidence interval maps for each map produced above;

Estimate densities (and associated error) from spatial abundance maps; and

Estimate the inferred connectivity between the Survey Area and East and North Caithness Cliffs SPAs by analysis of seabird flight direction.

Additional data was also collected on flight heights, and although this was not a key aim of the aerial surveys the results are presented in this report for information. The information presented includes flight height frequency distribution (with associated errors and sample size) and a comparison with Moray East boat‐based data (2010 to 2012; Moray Offshore Renewables, 2012) and Johnston et al. (2014) models.

This report describes the results of the objectives described above with particular emphasis on the key species and effects as shown in Table 1.1.

1 Please see https://www2.gov.scot/Resource/0053/00536268.pdf for the May 2018 MFRAG‐O meeting minutes.


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2 Methods

2.1 Survey Methods

The methodologies for the digital aerial surveys were designed to conform to the recommendations resulting from the power analysis undertaken in 2018 (Moray Offshore Renewables Limited, 2018), and were approved by MFRAG‐O prior to surveys commencing. Following discussions with MFRAG‐O in May 2018 the finalised survey methodology comprised aerial digital surveys of the Moray East site plus 10 km buffer (Survey Area), covering a total area of 1,398 km2. The surveys were conducted using twin‐engine P68 survey aircraft and captured digital still imagery at 2 cm resolution. Transects were orientated perpendicular to the coastline in a south‐east to north‐west direction (Figure 2.1) and were spaced 2.53 km apart to achieve a minimum coverage of 10 %. As highlighted in the “Power Analysis for Pre‐Construction Aerial Surveys” report (Moray East, 2018) the transects were aligned to match up with existing digital aerial transects that have been undertaken in the Beatrice Offshore Wind Limited (BOWL) windfarm.

Figure 2.1: Survey transects for coverage of the Moray East site plus 10 km buffer.

2.1.1 Data collection

Surveys were conducted by APEM using high definition digital still imagery and each survey was completed within a single day. Bespoke flight planning software was used to program the survey flight lines and define the required flying altitude and speed according to the camera, lens and required resolution (2 cm). The on‐board GPS systems ensured that the survey tracks were flown to an accuracy of 45 m across track and 5‐10 m along track. The following survey data was provided as a GIS shapefile in WGS84 UTM 30N format for each survey:

GPS locations of each image (easting and northing);


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Image capture filename ID;

Date and time of image capture;

Transect number; and

Transect orientation.

During each survey the camera technician recorded additional details on the following:

Shipping observations within 1.6 km either side of a transect;

Cloud cover;

Wind speed and direction;

Outside air temperature;

Pressure;

Turbidity;

Visibility; and

Sea state.

The camera technician also made a record of the order of transects flown, the time which the first and last node of each transect was captured, transect orientation and ground speed.

2.1.1.1 Image analysis

The following data relevant to birds and marine mammals were collected as standard:

Species identification and confidence;

Date and time of each bird and marine mammal recorded;

GPS co‐ordinate for each bird and marine mammal (easting and northing);

Unique identifying numbers for each bird and marine mammal, with reference to the survey line (transect line), the image number and individual camera that captured that image;

Age, gender and moult status (where possible);

Behavioural information including whether a bird is sitting, flying or diving as well as information on whether an individual is part of a group, carrying food or nursing a juvenile;

Orientation of birds in flight; and

Flight height of flying birds with associated +/‐ error.

The digital still imagery acquired by the aerial surveys was analysed by APEM staff using bespoke image analysis software to determine species identification, abundance, distribution and other information relevant to seabirds (and marine megafauna) present within the Survey Area.

Highly experienced image analysts determined species identification using APEM’s in‐house image archive library as a guide, as well as measuring the body length and wingspan as input parameters within bespoke image analysis software.

All birds detected were assigned to a species group and where possible, each of these was identified to species levels consistent with JNCC classified species groups (Appendix 2).

2.1.1.2 Flight heights

The flight heights of the birds were estimated using trigonometry. The size of the bird is directly proportional to its distance from the camera lens and therefore the further it is from the lens, and the closer it is to the sea surface, the smaller it appears in the image. The trigonometric calculation is based


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on species‐specific bird measurements, image ground sample distance (GSD) (the distance between pixel centres) and the known height of the aircraft at the time that the image was taken. These parameters were entered into APEM’s flight height calculator to estimate the height of each individual bird captured in survey images. Flight height estimates being less reliable for birds that are diving or turning sharply (this affects the measurement of body length and wing span from the image) such birds have been removed from the sample used to calculate flight heights. Each image, identified bird and flight height estimate has been subjected to Quality Assurance (QA) before the data have been finalised.

2.1.1.3 Quality Assurance

QA was carried out for each survey. Images were assessed in batches with a different staff member responsible for each batch. Each image containing birds and/or marine mammals was reviewed and checked by APEM’s dedicated QA Manager, ensuring that 100% of birds found were subject to internal QA to ensure the species identification is correct. Images containing no birds and/or marine mammals were removed and kept separately for further internal QA. Of these ‘blank’ images, 10% were randomly selected for QA. If there was less than 90% agreement, the entire batch was re‐analysed by a different staff member to who initially analysed the imagery. A selection of species was then subject to external QA by the British Trust for Ornithology (BTO) for birds and the Sea Mammal Research Unit (SMRU) for marine mammals to ensure species ID was correct. The scientific names of all species recorded during the 2018 pre‐construction aerial surveys are presented in Appendix 3.

2.2 Data Analysis Methods

The following analyses were required for the 2018 pre‐construction aerial surveys of the Survey Area

Abundance estimates of each species of birds in flight and on the sea by age, gender, survey (month), and season (where appropriate and possible).

Spatial abundance maps of each species in flight and on the sea within the season and / or month (where appropriate);

Spatial abundance confidence interval maps for each map produced above;

Densities (and associated error) estimated from spatial abundance maps;

Flight height frequency distribution (with associated errors and sample size); and

Comparison of flight height frequency distribution with Moray East boat‐based data (2010 to 2012; Moray Offshore Renewables Limited, 2012) and Johnston et al. (2014) models.

Sections 2.2.1 to 2.2.4 describe how each of the analysis objectives was achieved. The results of the data analysis comprises only positively identified species. Data for individuals that have not been identified to species level such as; guillemot/razorbill, small gull and large gull species is in Appendix 7.

2.2.1 Design‐based abundance estimates

The methods described in this section were used to meet the following analyses objectives:

Abundance estimates of each species of birds in flight and on the sea by age, gender, survey, calendar month and season (where appropriate and possible).

Abundance estimates were calculated for each species of birds in flight and on the sea. Analysis was conducted by behaviour for each survey month. Design‐based abundance estimates were generated by adding up the raw counts from geo‐referenced images and dividing this number by the total number of transects to give a mean number of birds per transect (i). Relative abundance estimates (N) for each survey month were then generated by multiplying the mean number of birds per transect by the total number of transects required to cover the entire study area (A). This is analogous to abundance estimation outlined in Borchers et al. (2002).


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N = i A

Non‐parametric bootstrap methods were used for variance estimation. A variability statistic was generated by re‐sampling 999 times with replacement from the raw count data. The statistic was evaluated from each of these 999 bootstrap samples and upper and lower 95% confidence intervals of these 999 values taken as the variability of the statistic over the population (Efron & Tibshirani, 1993).

Measures of precision were calculated using a Poisson estimator, suitable for over dispersed distribution (Elliott, 1977). This produced a CV (coefficient of variation) based on the relationship of the standard error to the mean.

All analysis and data manipulation was conducted in the R programming language (R Development Core Team, 2015) and non‐parametric 95 % confidence intervals were generated using the ‘boot’ library of functions (Canty & Ripley, 2010).

2.2.1.1 Availability bias of birds underwater

Diving birds, such as guillemots and razorbills, spend time foraging beneath the water surface. As a result of this, an unknown number of birds may go undetected due to the snap shot nature of aerial survey techniques. To account for this, a correction factor, the ‘availability bias’ has to be applied. The correction factor applied to each relevant auk species was based on that recommended by JNCC in a submission during the examination phase of the East Anglia One Offshore Wind Farm, referred to by JNCC as Method C (JNCC, 2013) with a copy of the specific text provided in Appendix 4. This applies a correction factor on the basis of aerial surveys recording 76 % of sitting guillemots and 83 % of sitting razorbills, as 24 % and 17 % respectively, of these species will be underwater when aerial imagery is captured. The correction factor for puffins is taken from the “Power Analysis for Pre‐Construction Aerial Surveys” report (Moray East, 2018) a copy of the text is provided in Appendix 4. The correction factor is based on the assumption that puffins spend approximately 20.2 % of their time at sea underwater. Therefore to correct for availability bias the ‘unavailable’ birds are added to the bird totals on a monthly basis to create revised population estimates. The ‘corrected’ abundance estimates for puffin, guillemots and razorbills are presented later in the relevant sections of this report.

2.2.2 Spatial abundance mapping


Spatial abundance maps of each species in flight and on the sea within the season and / or month (where appropriate);

Spatial abundance confidence interval maps for each map produced above; and

Densities (and associated error) estimated from spatial abundance maps.

Where possible, the bird survey data was analysed using the CReSS approach in a GEE framework with SALSA for model selection (Mackenzie et al., 2013). Environmental data was used to predict the density and distribution of species across a defined grid covering the Survey Area. The following environmental covariates were used to predict the species’ distributions:

Bathymetry;

X and Y coordinates;

Distance to coastline;

The CReSS modelling technique was developed specifically to deal with data collected for offshore wind farm projects. The modelling technique allowed both spatially auto‐correlated and zero‐inflated data to be modelled in a robust method. The confidence intervals generated using CReSS incorporate both the uncertainty in the detection function fitting (where applicable) and in the spatial model fitting process (Mackenzie et al. 2013). Using a CReSS modelling method also enabled any spatial auto‐correlation within the dataset to be incorporated providing more robust confidence intervals. Autocorrelation Function


16

(ACF) plots allowed detection of spatial autocorrelation, and an appropriate blocking structure was specified within the model to account for any autocorrelation detected. This method was appropriate for analysing zero‐inflated count data through specification of an appropriate family within the modelling process. The MRSea package in R allowed the data to be modelled using regression splines and CReSS smoothing with SALSA for model selection. The MRSea package will also enable statistically significant differences before and after impact to be detected once data is available.

2.2.3 Flight height frequency distribution


Flight height frequency distribution (with associated errors and sample size); and

Comparison of flight height frequency distribution with Moray East boat‐based data (2010 to 2012; Moray Offshore Renewables Limited, 2012) and Johnston et al. (2014) models.

The methodology used for capturing digital still imagery is able to provide the flight heights of the individual birds recorded during each survey. The calculation used relies upon known measurements of bird species length, the altitude of the aircraft, surface resolution, and the camera resolution.

Flight height frequency distribution graphs were produced for the seabird species by combining the suitable flight height data collected from the 2018 pre‐construction aerial surveys. Error bars were calculated as standard, and they and the sample size were incorporated into ranked flight height graphs.

For species commonly observed during the 2018 pre‐construction aerial surveys, a qualitative comparison of the flight height distributions collected during the 2018 surveys was made with those presented in Johnston et al. (2014) which were based on data gathered from ship‐based observations.

Flight height graphs are interpreted as follows;

(Graph A) boxplots show flight height above sea level of stated species from the combined surveys. The box represents the interquartile range (the difference between 75th and 25th percentiles), the line that divides the box into two parts is the median and the upper and lower whiskers represent the max. and min. values, respectively.

(Graph B) ranks individual flight height estimates across all surveys.

2.3 Flight direction

The direction of birds in flight was recorded from all digital still images. This was undertaken by measuring the axis of bill to tail, within APEM’s bespoke image analysis software, taking the bearing relative to the bird’s head. This bearing is linked to the geo‐referenced image and thus provides an accurate representation of bird orientation at time of image capture. These data can be used to explore connectivity of seabirds to nearby SPAs.

Flight direction rose diagrams are interpreted as follows; proportions of flight directions are given for each survey and the combined surveys. Proportions are shown by dashed circles and the length of each wedge (shaded in blue) indicates the relative proportions of flights recorded in a particular direction. The black line running from the centre to the outer edge represents the mean flight direction. The arcs extending to either side of the black line represent the 95 % confidence limits of the mean and if the confidence limit is unreliable the arc is displayed in red.


17

3 Results

3.1 Survey Information

3.1.1 Survey timings

Three aerial surveys were conducted between May and July 2018 inclusive at intervals of 26 and 33 days respectively. Each survey was conducted within a single day with variable start times (Table 3.1.1).

Table 3.1.1: Dates and times of the 2018 pre‐construction aerial surveys of Survey Area.

Survey Number Survey Date Start Time End Time

1 29th May 2018 15:52 20:03

2 24th June 2018 09:53 14:59

3 27th July 2018 12:55 17:59

3.1.2 Weather

Each survey was conducted in good visibility, sea state predominately ‘calm’ to ‘smooth’ and turbidity ‘slightly turbid’ (Table 3.1.2).

Table 3.1.2: Weather conditions recorded during the 2018 pre‐construction aerial surveys of Survey Area (see Appendix 1 for weather reporting scales).

Survey Number

Visibility (km)

Sea State

Turbidity Cloud Cover (%) Outside Air Temperature (°C)

Wind Speed / Direction

1: Start 10+ 2 1 0 15 10 knots / SE

1: End 10+ 1 1 60 15 5 knots / SE

2: Start 10+ 2 1 0 9 8 knots / NW

2: End 10+ 1 1 0 11 Calm / ‐‐‐

3: Start 10+ 3 1 80 21 20 knots / NW

3: End 10+ 2 1 0 21 27 knots / NW

3.1.3 Shipping information

During the May 2018 survey nine vessels were observed by the on‐board aerial survey technician. These comprised three fishing boats, one tug, two wind farm construction vessels and three rig vessels, only two of the fishing vessels were within the Moray East site. One supply vessel was captured in the imagery in the buffer area.

During the June 2018 survey nine vessels were observed by the on‐board aerial survey technician comprising four rig vessels, one sailing boat, one fishing trawler, two fishing boats and a wind farm support vessel. Two rig vessels and two fishing boats were captured in the imagery, all vessels except the sailing boat were in the buffer area.

During the July 2018 survey twelve vessels were observed by the on‐board aerial survey technician, comprising, four fishing vessels and eight wind farm support vessels. Three support vessels were captured in the imagery. All vessels were recorded in the buffer area.


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3.2 Primary Species Accounts

3.2.1 Puffin

3.2.1.1 Model derived spatial abundance and density estimates

The following environmental and spatial covariates were used in the GEE‐CReSS analyses:

Bathymetry;

X and Y coordinates; and

Distance to coastline.

To prepare for the GEE‐CreSS analyses, a complete grid of abutting cells based on the survey grid and environmental covariates was constructed to cover the entire survey area. All variables except X and Y co‐ordinate were included in the one‐dimensional Spatially Adaptive Local Smoothing Algorithm (SALSA) model selection method (Walker et al. 2011) and automatic model simplification using non‐significant p‐values was carried out. An appropriate blocking structure using transect ID was included as there was evidence of autocorrelation. Month was fitted as a factor term. This provided the base model for assessment of the 2D spatial smoother.

CReSS was used to fit the spatial density surface and GEEs were used to provide realistic model based estimates (see Figure A5.1.3 within Appendix 5 for the GEE‐CReSS partial plots for assessing one‐dimensional covariates in the final model). The GEE‐CReSS grid knot locations are included in Appendix 5. An interaction with Month was included to allow the density surface to vary between survey months.

Following predictions, bootstrapping was used to generate 95 % confidence intervals for each grid cell to allow for an assessment of uncertainty. The bootstrapping procedure incorporated any autocorrelation specified within the prediction model following the CReSS method. CReSS modelling was only undertaken for total puffin counts due to low numbers of birds in flight.

Table 3.2.1 below presents the puffin modelled abundance estimates for the Moray East site and Survey Area using Equation 1 for the model specification. Table 3.2.2 below presents the model specifications.

Table 3.2.1. Puffin modelled abundance estimates.

Month Moray East site Survey Area (Moray East site plus buffer)

Total 95% CI Density km2 Total 95% CI Density km2

May 168 87‐347 0.57 798 370‐1838 0.57

June 35 13‐86 0.12 166 60‐477 0.12

July 34 15‐131 0.12 217 98‐734 0.16

Equation 1 Final puffin model specification

. , 2 , 3 ,


19

Table 3.2.2. Model specifications for puffin, including smooth function and covariates. The GEE based p‐value for the terms in the model are also shown.

Model term p‐value

Month 0.0001

Distance 0.078

Spatial smoother (X, Y coordinates) <0.0001

Spatial smoother (Month interaction) 0.0027

Figures 3.2.1 to 3.2.3 below show the resulting density surface distribution for the months of May, June and July 2018 respectively.

Figure 3.2.1. Density surface distribution for puffins in May.


20

Figure 3.2.2. Density surface distribution for puffins in June.

Figure 3.2.3. Density surface distribution for puffins in July.


21

The modelling predicted the highest density in May with an average of 0.57 puffins per km2. The abundance of puffins in June and July were similar although lower than in May. There was higher confidence in the modelled estimates in June, however. During May, the highest densities of puffin were estimated to be in the south east and north‐west with a peak of 1.295 birds per km2. June showed a similar distribution to May, although densities were more broadly spread through the survey area and were lower with a peak of 0.272 birds per km2. The July distribution showed a similar site wide pattern with a higher concentration in the east of the site, with a peak of 0.350 birds per km2.

3.2.1.2 Design based abundance and density estimates

The puffin design based abundance and density estimates for the wind farm alone and the wind farm plus buffer are presented in Table 3.2.3 and Table 3.2.4 below, respectively.

Table 3.2.3 Puffin abundance estimates.


Total Flying Sitting Diving Total Flying Sitting Diving

May 210 6 199 6 882 27 848 7

95% CI 37‐437 1‐17 35‐443 1‐17 354‐1523 7‐53 327‐1496 1‐20

CV 0.16 1 0.17 1 0.09 0.5 0.09 1

CF* 258 0 252 0 1101 0 1074 0

June 63 0 63 0 194 13 180 0

95% CI 11‐159 0 11‐159 0 53‐361 2‐40 47‐354 0

CV 0.3 0 0.3 0 0.19 0.71 0.19 0

CF* 80 0 80 0 241 0 228 0

July 34 23 11 0 240 100 140 0

95% CI 6‐79 4‐68 2‐28 0 47‐534 15‐294 40‐274 0

CV 0.41 0.5 0.71 0 0.17 0.26 0.22 0

CF* 37 0 14 0 277 0 177 0

*CF; correction factor for adjustment of abundance estimates to account for birds underwater

Table 3.2.4 Puffin density estimates per km2.



May 0.71 0.02 0.67 0.02 0.63 0.02 0.61 0.01

CF* 0.87 0 0.85 0 0.79 0 0.77 0

June 0.21 0 0.21 0 0.14 0.01 0.13 0

CF* 0.27 0 0.27 0 0.17 0 0.16 0

July 0.12 0.08 0.04 0 0.17 0.07 0.1 0

CF* 0.13 0 0.05 0 0.20 0 0.13 0

3.2.1.3 Flight height distribution

Although 21 puffins were recorded in flight, all of the images of puffins were unsuitable for inclusion in flight height estimates.


22

3.2.1.4 Flight directions

Flight directions for puffins were not statistically significant in terms of a preferred flight heading with broad unreliable confidence intervals (Figure 3.2.4 below). Given the low numbers with respect to flight directions, and prevailing north westerly winds across the survey area no conclusions can be drawn from their general south easterly heading from the survey data (Table 3.2.5 below).

Table 3.2.5 Puffin flight directions.

May June July Combined Surveys

Number of Observations 4 2 15 21

Mean Compass Heading 155.941 0 147.878 141.906

Mean Heading (degrees) SSE N SSE SE

Lower 95% Confidence Interval 73.922 n/a 102.673 93.87

Upper 95% Confidence Interval 237.96 n/a 193.083 189.942

Rayleigh Test (Z) 1.146 2 3.145 2.562

Rayleigh Test (p) 0.34 0.137 0.04 0.076

Figure 3.2.4. Flight directions for puffin across the Survey Area.

Please see Section 2.2.3 above for interpretation of flight direction graphs.


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3.2.2 Great black‐backed gull

Great black‐backed gulls were recorded in all three surveys although only within the windfarm area in May. Due to too few records, it was not possible to obtain a fit of the model to the distribution data for great black‐backed gull, therefore only design based abundance and density estimates are presented.


The great black‐backed gull design based abundance and density estimates for the wind farm alone and the wind farm plus buffer are presented in Table 3.2.6 and Table 3.2.7 below respectively.

Numbers peaked in June with an estimated 307 individuals across the Survey Area, although the majority of individuals (65 %) estimated from the June survey were perched on structures associated with the Beatrice Offshore Windfarm (Table 3.2.6 below). Therefore the peak abundance estimated does not represent an influx of individuals foraging within the windfarm but birds recorded in association with artificial structures in the buffer area. Discounting birds perched on these artificial structures, abundance estimates of 107 for the Survey Area are the same for May and June, and thereafter decline.

Table 3.2.6. Great black‐backed gull abundance estimates.


Total Flying Sitting Perched Total Flying Sitting Perched

May 6 0 6 0 107 20 87 0

95% CI 1‐17 0 1‐17 0 20‐214 3‐40 13‐200 0

CV 1 0 1 0 0.25 0.58 0.28 0

June 0 0 0 0 307 27 80 200

95% CI 0 0 0 0 46‐722 7‐53 12‐180 30‐554

CV 0 0 0 0 0.15 0.5 0.29 0.18

July 0 0 0 0 13 0 13 0

95% CI 0 0 0 0 2‐33 0 2‐33 0

CV 0 0 0 0 0.71 0 0.71 0

This pattern is also reflected in the density estimates (when discounting for birds perched in the June survey) that are the same between the May and June surveys at 0.08 per km2, thereafter declining to 0.01 per km2 across the Survey Area (Table 3‐2.7 below).

Table 3.2.7. Great black‐backed gull density estimates per km2.



May 0.02 0 0.02 0 0.08 0.01 0.06 0

June 0 0 0 0 0.22 0.02 0.06 0.14

July 0 0 0 0 0.01 0 0.01 0

3.2.2.2 Spatial abundance mapping

The great black‐backed gull spatial distribution and abundance is presented in Figure 3.2.5 below.


24

The majority of great black‐backed gulls were recorded in the NW buffer area and were predominantly perched birds associated with artificial structures. Comparison of bird behaviour across all surveys, other than those perched, indicated birds were more often sitting (71%) than flying (29%) (see Appendix 6 for individual spatial abundance maps for each survey). These birds were loosely distributed and did not form aggregations with only one individual recorded within the Moray East site (Figure 3.2.5 below).

Figure 3.2.5 Great black‐backed gull spatial distribution and numbers for the combined surveys of the Survey Area.


The great black‐backed gull flight height distribution is presented in Figure 3.2.6.

The median flight of great black‐backed gulls above sea level was 13.65 m with an interquartile range of 10.24 to 70.04 m, based on 5 individuals from a total of 7 recorded in flight.

(A) (B) Figure 3.2.6. Great black‐backed gull flight height distribution.

Please see Section 2.2.3 above for interpretation of flight height graphs.


25


The great black‐backed gull flight direction recorded information and analysis is presented Table 3.2.8 and the flight direction illustrated in Figure 3.2.7 below.

Although few great black‐backed gulls were recorded in flight (n=7), with none recorded in the July survey, the general flight direction was south‐easterly (Table 3.2.8 below). Given the low numbers with respect to flight directions and prevailing winds across the survey area being from the north‐west, no definitive conclusions can be drawn to potential connectivity to the SPA colony.

Table 3.2.8. Great black‐backed gull flight directions.



Mean Compass Heading SE ESE SE

Mean Heading (degrees) 135 101 n/a 125

Lower 95% Confidence Interval 94 61 n/a 91

Upper 95% Confidence Interval 175 140 n/a 159

Rayleigh Test (Z) 2.703 3.284 n/a 4.674

Rayleigh Test (p) 0.053 0.025 n/a 0.005

Figure 3.2.7. Flight directions for great black‐backed gull across the Survey Area.

Please see Section 2.3 above for interpretation of flight direction graphs.


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3.3 Secondary Species Accounts

3.3.1 Herring gull

Herring gulls were recorded in all three surveys except within the Moray East site in the July survey.


The herring gull design based abundance and density estimates for the Moray East site and the Moray East site plus buffer are presented in Table 3.3.1 and Table 3.3.2 below respectively.

Numbers peaked in June with an estimated 3020 individuals across the Survey Area, although the majority of individuals (67%) estimated from the June survey were perched on structures associated with the Beatrice Offshore Windfarm (Table 3.3.1 below). Therefore the peak abundance estimated does not represent an influx of individuals foraging within the wind farm but birds recorded in association with artificial structures in the buffer area. Discounting birds perched on these artificial structures, the abundance estimate still peaks in June at 996 individuals.

Table 3.3.1 Herring gull abundance estimates



May 34 0 34 0 108 0 108 0

95% CI 6‐74 0 6‐74 0 73‐307 0 73‐307 0

CV 0.41 0 0.41 0 0.19 0 0.19 0

June 51 0 51 0 3020 421 575 2024

95% CI 11‐119 0 11‐119 0 548‐7442 120‐782 234‐1015 303‐5993

CV 0.33 0 0.33 0 0.05 0.13 0.11 0.06

July 0 0 0 0 87 0 87 0

95% CI 0 0 0 0 13‐220 0 13‐220 0

CV 0 0 0 0 0.28 0 0.28 0

Density estimates are 0.13 km2 in May, peak in June at 0.71 km2 (after discounting for birds perched in the June survey) and thereafter decline to 0.06 km2 across the Survey Area (Table 3.3.2).

Table 3.3.2 Herring gull density estimates per km2



May 0.12 0 0.12 0 0.13 0 0.13 0

June 0.17 0 0.17 0 2.16 0.3 0.41 1.45

July 0 0 0 0 0.06 0 0.06 0

3.3.1.2 Spatial abundance mapping and behaviour

The herring gull spatial distribution and abundance is presented in Figure 3.3.1 below.

The majority of herring gulls were recorded in the NW buffer area and were predominantly perched birds associated with artificial structures. Comparison of bird behaviour across all surveys, other than those


27

perched, indicated birds were more often sitting (67 %) than flying (33 %) (see Appendix 6 for individual spatial abundance maps for each survey). The birds were loosely distributed throughout the survey area but formed several aggregations of 2‐5 individuals mostly in the June survey and to the south of the survey area (Figure 3.3.1 below).

Figure 3.3.1 Herring gull spatial distribution and numbers for the combined surveys of the Survey Area.


The herring gull flight height distribution is presented in Figure 3.3.2.

The median flight of herring gulls above sea level was 23.83 m with an interquartile range of 4.56 m to 53.74 m, based on 26 individuals from a total of 63 recorded in flight.

(A) (B) Figure 3.3.2. Herring gull flight height distribution.



28


The herring gull flight direction recorded information and analysis is presented Table 3.3.3 and the flight direction illustrated in Figure 3.3.3 below.

Herring gulls were only observed in flight during the June survey with 63 individuals recorded, with a statistically significant (p<0.001) heading in a mean north‐north‐east direction with approximately 30% heading in an east‐north‐east direction (Table 3.3.3 below). This would suggest birds flying from the East Caithness Cliffs SPA. Although, given numbers are relatively low with respect to flight directions, caution should be used before conclusions can be drawn to potential connectivity to the SPA colony.

Table 3.3.3. Herring gull flight directions.



Mean Compass Heading n/a NNE n/a NNE

Mean Heading (degrees) n/a 32 n/a 32.386

Lower 95% Confidence Interval n/a 9 n/a 9.498

Upper 95% Confidence Interval n/a 55 n/a 55.275

Rayleigh Test (Z) n/a 10.952 n/a 10.952

Rayleigh Test (p) n/a 1.75E‐05 n/a 1.75E‐05

Figure 3.3.3. Flight directions for herring gull across the entire survey area.



29

3.3.2 Guillemot

Guillemots were recorded in all three surveys and were the most abundant species recorded.


The guillemot design based abundance and density estimates for the windfarm alone and the windfarm plus buffer are presented in Table 3.3.4 and Table 3.3.5 below respectively.

Numbers peaked in May with an estimated 17,532 individuals across the Survey Area and 3,227 within the Moray East site (Table 3.3.4 below). To account for birds underwater at the time of the survey a correction factor (see Appendix 4) was included in the abundance estimates. This increased the peak abundance estimate to 22,684 in the Survey Area and 4,172 in the Moray East site.

Table 3.3.4. Guillemot abundance estimates.



May 3227 187 3039 0 17532 988 16543 0

95% CI 1221‐5568 62‐341 1051‐5170 0 9591‐27156 541‐1603 8442‐26268 0

CV 0.04 0.17 0.04 0 0.02 0.08 0.02 0

CF* 4172 ‐ 3985 ‐ 22684 ‐ 21696 ‐

June 574 108 466 0 5331 1577 3741 13

95% CI 131‐1132 57‐165 82‐1029 0 2766‐8431 989‐2318 1543‐6494 2‐40

CV 0.1 0.23 0.11 0 0.04 0.07 0.04 0.71

CF* 719 ‐ 611 ‐ 6483 ‐ 4906 ‐

July 363 28 335 0 2036 107 1929 0

95% CI 159‐573 6‐62 148‐522 0 1275‐2890 20‐240 1128‐2757 0

CV 0.12 0.45 0.13 0 0.06 0.25 0.06 0

CF* 467 ‐ 439 ‐ 2637 ‐ 2530 ‐

*CF; correction factor for adjustment of abundance estimates to account for birds underwater.

Density estimates peak in May at 12.56 per km2 and thereafter decline to 3.82 per km2 and 1.46 per km2 in June and May, respectively, across the Survey Area (Table 3.3.5 below). After applying a correction factor for availability bias peak density estimates in May are 16.23 per km2 in the Total Survey Area.

Table 3.3.5 Guillemot density estimates per km2.



May 10.93 0.63 10.29 0 12.56 0.71 11.85 0

CF* 14.13 ‐ 13.50 ‐ 16.23 ‐ 15.52 ‐

June 1.94 0.37 1.58 0 3.82 1.13 2.68 0.01

CF* 2.43 ‐ 2.07 ‐ 4.64 ‐ 3.51 ‐

July 1.23 0.09 1.13 0 1.46 0.08 1.38 0

CF* 1.58 ‐ 1.48 ‐ 1.88 ‐ 1.81 ‐


30


The guillemot spatial distribution and abundance is presented in Figure 3.3.4 below.

Guillemots were widely distributed across the Survey Area, with congregations around the area of the Beatrice Offshore Windfarm turbine platforms (in the NW buffer area) during the May and June surveys. In July the distribution changed with greater numbers recorded to the south‐east. Comparison of bird behaviour across all surveys, indicated birds were more often sitting (89.2%) than flying (10.7%) and 0.1% diving (see Appendix 6 for individual spatial abundance maps for each survey). Guillemots tended to form aggregations of up to approximately 100 birds throughout the Survey Area (Figure 3.2.4 below).

Figure 3.3.4 Guillemot spatial distribution and numbers for the combined surveys of the Survey Area.


The guillemot flight height distribution is presented in Figure 3.3.5 below.

The median flight of guillemots above sea level was 13.87 m with an interquartile range of ‐2.79 to 35.89 m, based on 97 individuals from a total of 400 recorded in flight.


31

(A) (B) Figure 3.3.5. Guillemot flight height distribution.



The guillemot flight direction recorded information and analysis is presented Table 3.3.6 and the flight direction illustrated in Figure 3.3.6 below.

The majority of guillemots recorded in flight were from the May and June surveys (148 and 236, respectively) with 16 recorded in July. Flight headings were calculated for all but one observation from the June survey. During peak abundance in June the mean flight direction is shown as north but this was bimodal with the majority of birds heading along a north‐westerly ‐ easterly axis (Table 3.3.6 below). Statistical analysis showed that this flight heading distribution was not random. This would suggest birds flying to and from the East Caithness Cliffs SPA. When combining the data across all surveys flight headings suggest that guillemots travel along a north‐westerly – south‐easterly/easterly axis. Given the high numbers with respect to flight directions there is good evidence to infer connectivity of guillemots in the Survey Area during May and June to the East Caithness Cliffs SPA colony.

Table 3.3.6 Guillemot flight directions.



Mean Compass Heading 128 7 176 91

Mean Heading (degrees) SE N S E

Lower 95% Confidence Interval 117 347 148 70

Upper 95% Confidence Interval 139 27 205 113

Rayleigh Test (Z) 45.81 15.054 6.051 13.224

Rayleigh Test (p) < 1E‐12 2.9E‐07 0.001 1.81E‐06


32

Figure 3.3.6. Flight directions for guillemot across the entire survey area.


3.3.3 Razorbill

Razorbills were record in all three surveys.


The razorbill design based abundance and density estimates for the Moray East site alone and the Moray East site plus buffer are presented in Table 3.3.7 and Table 3.3.8 below respectively.

Numbers peaked in May with an estimated 3,700 individuals across the Survey Area and 699 within the Moray East site (Table 3.3.7 below). To account for birds underwater at the time of the survey a correction factor (see Appendix 4) was included in the abundance estimates. This increased the peak abundance estimate to 4,477 in the Survey Area and 820 in the Moray East site.


33

Table 3.3.7 Razorbill abundance estimates.



May 699 6 693 0 3700 7 3693 0

95% CI 267‐1267 1‐17 250‐1187 0 2399‐4996 1‐20 2371‐4842 0

CV 0.09 1 0.09 0 0.04 1 0.04 0

CF* 845 0 839 0 4477 0 4470 0

June 62 0 62 0 822 7 815 0

95% CI 9‐125 0 9‐125 0 314‐1517 1‐20 281‐1510 0

CV 0.33 0 0.33 0 0.09 1 0.09 0

CF* 60 0 60 0 993 0 986 0

July 250 0 250 0 1268 27 1242 0

95% CI 97‐448 0 97‐448 0 647‐1922 4‐80 627‐1983 0

CV 0.15 0 0.15 0 0.07 0.5 0.07 0

CF* 302 0 302 0 1530 0 1503 0

*CF; correction factor for adjustment of abundance estimates to account for birds underwater.

Density estimates peak in May at 2.65 per km2 and thereafter decline to 0.59 per km2 and 0.91 per km2 in June and July, respectively, across the Survey Area (Table 3.3.8 below). After applying a correction factor for availability bias peak density estimates in May are 3.20 per km2 in the Survey Area.

Table 3.3.8 Razorbill density estimates per km2.



May 2.37 0.02 2.35 0 2.65 0.01 2.65 0

CF* 2.86 ‐ 2.84 ‐ 3.20 ‐ 3.19 ‐

June 0.17 0 0.17 0 0.59 0.01 0.58 0

CF* 0.20 ‐ 0.20 ‐ 0.69 ‐ 0.70 ‐

July 0.85 0 0.85 0 0.91 0.02 0.89 0

CF* 1.02 0 1.02 0 1.09 0 1.07 0


The razorbill spatial distribution and abundance is presented in Figure 3.3.7 below.

Razorbills were loosely distributed across the Survey Area, although less abundant to the south west of the Survey Area. Razorbills tended to form small aggregations of up to 24 individuals being recorded throughout the Survey Area (Figure 3.3.7 below). Razorbills tended to congregate around the area of the Beatrice Offshore Windfarm turbine platforms (in the NW buffer area) during the May and June surveys. In July the distribution changed with greater numbers recorded to the south‐east. Comparison of bird behaviour across all surveys, indicated birds generally sitting (99.3 %) than flying (0.7 %) (see Appendix 6 for individual spatial abundance maps for each survey).


34

Figure 3.3.7 Razorbill spatial distribution and numbers for the combined surveys of the Survey Area.


Although 6 razorbills were recorded in flight all images of razorbills were unsuitable for inclusion in flight height estimates.


The razorbill flight direction recorded information and analysis is presented Table 3.3.9 and the flight direction illustrated in Figure 3.3.8 below.

Except for the July survey records, flight directions for razorbill were not statistically significant in terms of a preferred flight heading with broad unreliable confidence intervals (Figure 3.3.8). Given the low numbers with respect to flight directions, no conclusions can be drawn from their general north‐north‐westerly heading from the survey data (Table 3.3.9 below).

Table 3.3.9 Razorbill flight directions



Mean Compass Heading n/a 180 348 344

Mean Heading (degrees) S N NNW

Lower 95% Confidence Interval n/a n/a 331 285

Upper 95% Confidence Interval n/a n/a 6 44

Rayleigh Test (Z) n/a 1 3.848 1.739

Rayleigh Test (p) n/a 0.512 0.01 0.181


35

Figure 3.3.8 Flight directions for razorbill across the entire survey area.


3.4 Tertiary Species Accounts

3.4.1 Kittiwake

Kittiwakes were recorded in all three surveys.


The kittiwake design based abundance and density estimates for the Moray East site alone and the Moray East site plus buffer are presented in Table 3.4.1 and Table 3.4.2 below respectively.

Numbers peaked in June with an estimated 11,304 individuals across the Survey Area and 1,217 within the Moray East site; approximately half of the individuals were captured in flight (Table 3.4.1 below). The numbers recorded in May and July were similar in the Moray East site with 443 and 522 individuals recorded respectively. However a greater number was recorded in the Survey Area in May with 4,548 individuals in comparison to the number of individuals recorded in July (Table 3.4.1 below).


36

Table 3.4.1 Kittiwake abundance estimates.



May 443 420 23 0 4548 2705 1837 7

95% CI 102‐1034 85‐932 6‐45 0 1576‐8335 1329‐4168 301‐4014 1‐20

CV 0.11 0.12 0.5 0 0.04 0.05 0.06 1

June 1217 654 563 0 11304 5939 5365 0

95% CI 512‐2002 296‐1088 99‐1297 0 5238‐18432 2699‐9780 1349‐9680 0

CV 0.07 0.09 0.1 0 0.02 0.03 0.04 0

July 522 386 136 0 2463 2169 294 0

95% CI 148‐1010 142‐744 24‐369 0 1348‐3932 1108‐3645 80‐634 0

CV 0.1 0.12 0.2 0 0.05 0.06 0.15 0

A similar pattern was noticeable in the density estimates, with June having the highest density of individuals in the Survey Area (8.10 birds per km2). The density of kittiwakes in the Moray East site was approximately half (4.12 birds per km2), suggesting that a greater number of individuals were recorded in the buffer (Table 3.4.2 below). This was also the case with the density of kittiwakes in May with 3.26 birds per km2 recorded in the Survey Area, and 1.50 birds per km2 in the Moray East site. In July, the density of the kittiwakes was similar in the Moray East site and Survey Area with 1.77 and 1.76 birds per km2 respectively (Table 3.4.2 below).

Table 3.4.2 Kittiwake density estimates per km2.



May 1.5 1.42 0.08 0 3.26 1.94 1.32 0.01

June 4.12 2.21 1.91 0 8.1 4.26 3.84 0

July 1.77 1.31 0.46 0 1.76 1.55 0.21 0


The kittiwake spatial distribution and abundance is presented in Figure 3.4.1 below.

Kittiwakes were distributed throughout the Survey Area. The majority of kittiwakes were recorded in the buffer area, with large aggregations recorded in the NW and SE areas (Figure 3.4.1). Large aggregations were also recorded in the Moray East site, the majority of these aggregations were recorded in the east.


37

Figure 3.4.1 Kittiwake spatial distribution and numbers for the combined surveys of the Survey Area.


The kittiwake flight height distribution is presented in Figure 3.4.2 below.

The median flight of kittiwakes above sea level was 28.89 m with an interquartile range of 13.51 to 52.94 m, based on 1,160 individuals from a total of 1,619 recorded in flight.

(A) (B)

Figure 3.4.2 Kittiwake flight height distribution.



The kittiwake flight direction recorded information and analysis is presented Table 3.4.3 and the flight direction illustrated in Figure 3.4.3 below.

Kittiwakes were recorded in flight during all of the surveys (Table 3.4.3 below). The flight direction was predominantly south‐easterly in June and July, and north‐easterly in May. The overall predominated


38

direction for all surveys combined was easterly. This would suggest birds were flying from the East Caithness Cliffs SPA.

Table 3.4.3 Kittiwake flight directions.



Mean Compass Heading NE SE SE E

Mean Heading (degrees) 45 158 135 113

Lower 95% Confidence Interval 44 104 124 90

Upper 95% Confidence Interval 57 167 136 106

Rayleigh Test (Z) 114.164 6.268 143.692 92.666

Rayleigh Test (p) <0.001 <0.001 <0.001 <0.001

Figure 3.4.3 Flight directions for kittiwakes across the Survey Area.


3.4.2 Gannet

Gannets were recorded in all three surveys.


The gannet design based abundance and density estimates for the windfarm alone and the windfarm plus buffer are presented in Table 3.4.4 and Table 3.4.5 below respectively.


39

Numbers peaked in June with an estimated 2,051 individuals across the Survey Area; the majority of individuals (66%) were recorded sitting on the water (Table 3.4.4). Thereafter 695 individuals were recorded in May, and July had the least number of individuals with 134 recorded.

Table 3.4.4 Gannet abundance estimates.



May 91 57 34 0 695 301 387 7

95% CI 16‐216 10‐125 6‐102 0 381‐1049 140‐481 160‐681 1‐20

CV 0.25 0.32 0.41 0 0.1 0.15 0.13 1

June 324 114 210 0 2051 695 1349 7

95% CI 85‐592 20‐256 51‐461 0 889‐3641 307‐1149 501‐2365 1‐20

CV 0.13 0.22 0.16 0 0.06 0.1 0.07 1

July 23 6 17 0 134 80 53 0

95% CI 6‐40 1‐17 3‐34 0 53‐234 20‐154 20‐93 0

CV 0.5 1 0.58 0 0.22 0.29 0.35 0

A similar pattern was noticeable in the density estimates, with June having the highest density of individuals in the Survey Area (1.47 birds per km2). The density of gannets in May was 0.50 bird per km2 in the Survey Area and 0.31 birds per km2 in the Moray East site In July, the density of the gannets was similar in the Moray East site and Survey Area with 0.80 and 0.10 birds per km2 respectively (Table 3.4.5 below).

Table 3.4.5 Gannet density estimates per km2.



May 0.31 0.19 0.12 0 0.5 0.22 0.28 0.01

June 1.1 0.39 0.71 0 1.47 0.5 0.97 0.01

July 0.08 0.02 0.06 0 0.1 0.06 0.04 0


The gannet spatial distribution and abundance is presented in Figure 3.4.4 below.

Gannets were loosely distributed throughout the Survey Area, with very few individuals recorded along the NE and SW buffer areas. A number of large aggregations of gannets were recorded in the NW and SE buffer areas. One aggregation of gannets was recorded in the Moray East site (Figure 3.4.4 below).


40

Figure 3.4.4 Gannet spatial distribution and numbers for the combined surveys of the Survey Area.


The gannet flight height distribution is presented in Figure 3.4.5 below.

The median flight of gannets above sea level was 16.00 m with an interquartile range of ‐2.82 to 35.67 m, based on 109 individuals from a total of 161 recorded in flight.

(A) (B)

Figure 3.4.5 Gannet flight height distribution.



The gannet flight direction recorded information and analysis is presented Table 3.4.6 and the flight direction illustrated in Figure 3.4.6 above.


41

Gannets were recorded in flight during all surveys (Table 3.4.6 below). The mean flight direction was easterly in May, suggesting the birds were flying from the East Caithness Cliffs SPA, although the direction was multi‐modal and connectivity should be treated with caution. The results of analysis of the flight directions in June, July, and the combined surveys did not present any statistically significant flight direction (Table 3.4.6 below).

Table 3.4.6 Gannet flight directions.



Mean Compass Heading E WNW SE NNE

Mean Heading (degrees) 90 293 135 n/a*

Lower 95% Confidence Interval 54 240 62 n/a*

Upper 95% Confidence Interval 138 342 210 n/a*

Rayleigh Test (Z) 3.48 2.416 1.509 0.015

Rayleigh Test (p) 0.03 0.089 0.225 0.985

* Result could not be calculated due to randomness of headings

Figure 3.4.6 Flight directions for gannets across the Survey Area.



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3.5 Comparison of flight heights with the 2010‐2012 boat based surveys

The comparison of flight height distributions and proportions flying at rotor height by species between the 2018 aerial survey and the 2010‐2012 boat surveys are presented in Table 3.5.1 and Table 3.5.2 and to those reported in the literature Table 3.5.3.

The proposed lower and upper limits of the Moray East rotor swept area are 26.7‐ 30.2 m and 190.7‐194.2 m HAT respectively (Moray East DSLP 2018). The percentage of birds flying at rotor height was defined as 20 – 200 m a.s.l. for comparison with the Moray East boat based survey data (2010‐2012). The data from the boat based surveys comprises the total observations recorded across all 28 surveys between 2010 to 2012.

Table 3.5.1 Comparison of flight height distributions flying at rotor height by species between the 2018 aerial survey and the 2010‐2012 boat surveys.

Survey Species Height Band

Total <5 m 5‐10 m 10‐20 m 20‐200 m >200 m

2010‐12 boat Fulmar 3834 137 7 3978

2018 aerial 68 22 17 79 186

2010‐12 boat Gannet 362 72 103 71 608

2018 aerial 43 6 12 48 109

2010‐12 boat Kittiwake 958 507 561 97 2123

2018 aerial 179 61 153 764 3 1160

2010‐12 boat Common gull 1 1 2

2018 aerial 1 1 2

2010‐12 boat Great black‐backed gull 64 33 48 62 207

2018 aerial 1 2 2 5

2010‐12 boat Herring gull 74 32 101 105 1 313

2018 aerial 7 3 1 15 26

2010‐12 boat Commic Tern 1 1

2018 aerial 1 3 4

2010‐12 boat Great skua 84 16 9 1 10

2018 aerial 1 4 5

2010‐12 boat Guillemot 3046 50 2 3098

2018 aerial 38 4 14 41 97


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Table 3.5.2 Comparison of the proportion of birds flying at rotor height from the 2018 aerial survey, the 2010‐2012 boat surveys and the publication by Johnston et al (2014).

Species

2018 aerial surveys 2010‐12 boat surveys Johnston et al (2014)

% at rotor height

(20‐200 m)

% at rotor height

(20‐200 m)

% at rotor height

(20‐120 m)

Fulmar 42.5 0.0 1.0

Gannet 44.0 11.7 12.6

Kittiwake 65.9 4.6 15.0

Common gull 50.0 0.0 21.9

Great black‐backed gull 40.0 30 31.9

Herring gull 57.7 33.5 32.5

‘Commic’ tern 75.0 0.0 n/a

Great skua 80.0 0.9 5.9

Guillemot 42.3 0.0 0.04

The percentage of birds (for the 2018 aerial surveys) flying at rotor height on the basis of the individual mean height estimates was: fulmar 42.5 %, gannet 44.0 %, kittiwake 4.6 %, common gull 50.0 %, great black‐backed gull 40.0 %, herring gull 57.7 %, commic tern 75 %, great skua 80.0 % and guillemot 42.3 %. With the exception of fulmar, gannet and kittiwake (in bold in Table 3.5.2 above), height sample sizes for all other species did not attain the recommended minimum number of records (n=100) for generating robust estimates of height distribution (Natural England, 2013).

The modelled data from Johnston et al. (2014) combined 32 potential offshore wind farm sites to estimate continuous flight height distributions. The majority of data sets used by Johnston et al. were boat surveys (n=27) the remaining from offshore observations on platforms (n=3) or shore‐based observations (n=3) close to offshore wind farm sites. It is recognised that shore and boat based observations used to estimate flight heights are negatively biased, as recording birds at higher altitudes is difficult. It should also be recognised that there currently no publications validating flight heights from aerial surveys for accuracy and precision.

It is important to note however, that calculation of the aerial survey flight heights were not made for all birds observed flying, for example of those with over 100 flight height records; fulmar, gannet and kittiwake flight height calculations were only suitable from 62 %, 68 % and 72 %, respectively. This may account for a degree of positive bias in flight height calculations, although even if all the birds without flight heights are included as outside the rotor heights (giving values for fulmar, gannet and kittiwake of 27 %, 30 % and 47 %, respectively, at rotor height) this still does not account for the differences seen between the boat based survey and those in the publication of Johnston et al. (2014). The larger confidence interval produced for the flight heights more likely suggests that overall higher precision of the height estimates obtained are required. The aerial survey data set is positively skewed which would account for the higher proportions reported at rotor height. Furthermore, the median values obtained from the flight height calculations in the aerial survey closely reflects mean flight height values reported in the literature (Table 3.5.3 below), suggesting the aerial flight height calculations have acceptable accuracy but low precision. It should be highlighted that flight height calculations from the aerial surveys should be considered with regards to the influence of the Beatrice Offshore Windfarm under construction. Reports from the literature do suggest that seabird species adjust their flight heights when in proximity to a wind farm, but this is variable (lower, higher, no change) depending on the species concerned (Jongbloed, 2016).


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The percentage of birds flying at rotor height was defined as 20 – 200 m a.s.l. for comparisons to be made to previous surveys. Therefore the results cannot be extrapolated to the identification of birds at risk from collision (as it is acknowledged that the majority of the flights would be at lower heights and therefore a significant proportion of the flights may be between 20‐26 m and out with the Moray East rotor swept area).

Table 3.5.3 Comparison of selected flight heights with those reported in the literature

Source Flight height (m)

Gannet Fulmar Kittiwake

2018 aerial survey (median values) 16 13 30

Reported flight height from the literature (mean values); Cleasby et al. 2015, Mendel et al. 2014, Cook et al. 2012, Garthe & Hüppop et al. 2004

12‐27 0‐5 5‐20


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4 Discussion

This report presents the results of three surveys conducted between May and July 2018 and comprises the breeding season. These data make up the pre‐construction aerial survey data collected across Moray East Offshore Wind Farm and places the results in the context of the objectives of the Ornithological Monitoring Programme as agreed through the MFRAG‐O. Species were classified as primary, secondary, and tertiary in terms of the importance for monitoring the effects of the development. The importance of the species were categorised as following.

Primary

o Puffin: Displacement effects

o Great black‐backed gull: Collision mortality

Secondary

o Herring gull: Collision mortality

o Guillemot: Displacement effects

o Razorbill: Displacement effects

Tertiary

o Kittiwake: Displacement effects and collision mortality

o Gannet – Displacement effects and collision mortality

The data presented in this report summarise the abundance and distribution of these species across the Moray East Offshore Wind Farm. In order to detect and quantify any changes in the abundance and distribution of these species in subsequent construction phases, the following sections discuss the current abundance and distribution data. This is discussed in relation to bird importance thresholds and comparisons are made with data collected from boat surveys collection during 2010 and 2012 to inform the Moray East ES 2012.

4.1 Abundance Estimates and Distributions

The most abundant species estimated (derived from design‐based analysis) in the Survey Area, when combining the monthly estimates of birds on the water and in flight, during the breeding season (May‐July) was guillemot (n=24,899). Thereafter guillemot / razorbill (n=20,092) was the second most abundant; followed by kittiwake (18,315), razorbill (n=5,790), herring gull (n=3,287), fulmar (n=3,172), gannet (n=2,880), puffin ((n=1,619), design based abundance), ‘commic’ tern (694), great black‐backed gull (n=427), common gull (n=227), lesser black‐backed gull (n=201), great skua (n=180), red‐throated diver (87), small gull species (n=67), large gull species (n=53), tern species (n=13), and cormorant / shag (n=7).

The most abundant species estimated in the Moray East site was similar to that recorded across the Survey Area, with guillemot (n=5,358) being the most abundant. This was followed by guillemot / razorbill (n=3,466), kittiwake (n=2,182), razorbill (n=1,207), fulmar (n=506), gannet (n=438), puffin ((n=375), design based abundance), ‘commic’ tern (209), herring gull (n=85), red‐throated diver (n=29), lesser black‐backed gull (n=17), large gull species (n=17), small gull species (n=12), tern species (n=11), great skua (n=6), and great black‐backed gull (n=6). Patterns in the estimated abundance of the key species within the windfarm footprint are discussed in further detail in the sections below (4.1.1, 4.12, and 4.13).

The proportion of birds in flight and birds sitting on the water was to be expected for certain species based on their life history feeding traits. The small and large gulls and gannets were recorded with greater numbers of individuals in flight whereas the auks had greater proportions of individuals sitting on the water.

The key species were distributed throughout the Survey Area. In general, many of the species were recorded in greater densities in the NW and SE buffer area. These key species included puffin, great black‐backed gull, herring gull, gannet and kittiwake. Guillemots were recorded in high numbers across the


46

entire Survey Area. Large aggregations were particularly notable in the NW buffer area, and the SE area of the windfarm. The majority of razorbills were also recorded in the SE area of the buffer.

4.1.1 Primary Species

Model‐based abundance estimates were generated for puffin using a GEE‐CReSS framework using the MRSea R Package (Mackenzie et al., 2013). The peak month of puffin abundance in the Moray East site was May where 168 individuals were estimated. The estimated numbers subsequently decreased but remained similar for the next two months in the breeding season: June (n=35) and July (n=34). Design‐based abundance estimates split by behaviour were also generated for puffin; the estimated numbers and pattern of abundance was similar to those created by modelling. In the Survey Area, the pattern of abundance remained similar with the peak estimate occurring in May (n=882), with the subsequent months June and July remaining similar (n=194 and n=240 respectively).

It was not possible to generate model‐based abundance estimates for great black‐backed gull because there were too few individuals for the model to converge successfully. As such design‐based abundance estimates were generated for this species. Great black‐backed gulls were only recorded in May in the Moray East site with an estimated six individuals. However in the Survey Area, greater numbers (relating to a greater density) were estimated in two of the surveys June (n=307) and May (n=107). Relatively few numbers were estimated in July (n=13).

4.1.2 Secondary Species

For the secondary species, design‐based abundance estimates were generated. Herring gull was recorded in relatively low numbers in the Moray East site in May and June, with estimated abundances of 34 and 51 respectively. No herring gulls were recorded in July. In the Survey Area, relatively greater numbers of herring gulls were recorded in June corresponding to a greater density with an estimated abundance of 3,020 individuals.

Guillemots were the most numerous species recorded in May in the Moray East site with an estimated 3,227 individuals, with numbers decreasing to an estimated 574 and 363 individuals respectively in June and July. The pattern of razorbills was similar to that of guillemots with the peak month being May (n=699), but far fewer were recorded. Thereafter the numbers dropped off in June (n=51) but increased slightly in July (n=250). For both guillemot and razorbill abundance patterns between surveys were similar In the Survey Area.

4.1.3 Tertiary Species

For the tertiary species, design‐based abundance estimates were generated. Kittiwake was the most numerous species recorded in June (n=11,304) and July (n=2,463), and the third most numerous species in May (n=4,548) within the Survey Area. The peak month for gannet abundance was June (n=2,351), followed by May (n=695) and July (n=134) for the Survey Area.

4.2 Comparison with 2010‐2012 boat data from the ES

Comparison between the density estimates from the Moray East ES 2012 for May, June and July in 2010 and 2011 undertaken as part of the pre‐application surveys within the Moray East site and the density estimates from the aerial surveys in the same months in 2018 are shown in Figure 4‐2.1 below. Despite different survey methods being employed and general fluctuations in bird numbers in the area, density estimates were similar between years. Design‐based abundances were used in the comparison.

Puffin showed a large difference in density in May with a peak in 2010 of 16.22 birds per km2 reducing down to 5.79 and 0.87 birds per km2 in 2011 and 2018 respectively. This may reflect anecdotal evidence that the breeding season may be later during the 2018 breeding season in the area (as discussed during


47

the May MRAG‐O meeting1). Values for June and July 2018 were similar to 2010, but both these years were lower than the 2011 peak in these two months.

Great black‐backed gull densities within the Moray East site were similar across the three years with a peak abundance in May 2011 of 3.77 birds per km2. The pattern of densities seen across the breeding season was similar in all three years.

There were similarities in guillemot and razorbill densities across the three years, with both species showing a peak in density in May 2010 of 88.67 and 29.91 birds per km2 respectively. Both species showed a decline from peaks in May in each year with densities reducing in June and July. Similar densities were found in 2011 and 2018 for both species.

Herring gull densities were generally low (less than 0.2 birds per km2) within the Moray East site with a peak of 0.17 birds per km2 in June 2018. The pattern of densities changed between years with no consistent pattern between months being shown.

The same was true for gannet with patterns between months being inconsistent between years. Similar densities were found between all three years however with densities generally being less than 1 bird per km2 (usually less than 0.5 birds per km2).

Kittiwake densities showed a consistent pattern between 2010 and 2011 with a peak in May in each year. The 2018 surveys detected a peak in densities in June, although these values were much lower than the previous peaks in 2010 and 2011 (4.12 birds per km2 June 2018, versus 37.61 and 19.55 birds per km2 in May 2010 and 2011 respectively). June and July densities across all three years were similar however.

Overall, the 2018 pre‐construction surveys recorded similar patterns of densities as the pre‐application surveys. Some species showed lower densities than the peaks recorded in 2010 but were more in line with estimates from the 2011 surveys. However consideration should be made to the impact (positive and negative) on bird abundance and densities from construction activities on the adjacent Beatrice Offshore wind farm. The wind farm is located to the north west of the Moray East site with several turbines being positioned in the buffer area. At the time of the surveys between May and June 2018 construction had reached the stage of jacket substructure installation.


48

A: Primary species (puffin and great black‐backed gull)

0

5

10

15

20

25

May June July

Density(birds/km

2)

Month

Puffin

2010

2011

2018

0

5

10

15

20

25

30

May June July

Density (birds/km

2)

Month

Great black‐backed gull

2010

2011

2018

0

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40

60

80

100

120

140

160

May June July

Density (birds/km

2)

Month

Guillemot

2010

2011

2018

0

10

20

30

40

50

May June JulyDensity (birds/km

2)

Month

Razorbill

2010

2011

2018


49

B: Secondary species (guillemot, razorbill and herring gull)

C: Tertiary species (gannet and kittiwake)

Figure 4.2.1 Densities for the key species recorded during the 2018 pre‐construction surveys in comparison to the boat data taken from the Moray East ES 2012.

0

0.1

0.2

0.3

0.4

0.5

0.6

May June July

Density (birds/km

2)

Month

Herring gull

2010

2011

2018

0

0.5

1

1.5

2

2.5

May June July

Density (birds/km

2)

Month

Gannet

2010

2011

2018

0

20

40

60

80

100

120

140

160

180

May June JulyDensity (birds/km

2)

Month

Kittiwake

2010

2011

2018


50

5 Conclusion

The aim of the surveys was to provide updated abundance and density estimates this was achieved by undertaking surveys in May, June and July which comprised the breeding season. Density estimates were found to be similar for species between years with some fluctuations in peak density abundance however similar patterns were found throughout.


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6 References

Beatrice Offshore Windfarm Ltd (2016) Beatrice Offshore Wind Farm Pre‐construction Aerial Survey Report: Document Reference: LF000005‐REP‐690 Rev 02

Borchers, D.L., Buckland, S.T. and Zucchini, W. (2002). Estimating Animal Abundance. Closed Populations. Springer. London.

Canty, A. and Ripley, B. (2010). Boot: Bootstrap R (S‐Plus) Functions. R package version 1. 2‐43.

Cleasby, I.R., Wakefield, E.D., Bearhop, S., Bodey, T.W., Votier, S.C., Hamer, K.C. (2015) Three‐dimensional tracking of a wide‐ranging marine predator: flight heights and vulnerability to offshore Wind Farms. Journal of Applied Ecology, doi: 10.1111/1365‐2664.12529.

Cook, A.S.C.P, Johnston, A., Wright, L.J., Burton, N.H.K. (2012) A review of flight height and avoidance rates of birds in relation to offshore Wind Farms. Strategic Ornithological Support Services Project SOSS‐02. BTO Research Report No. 618. BTO, Thetford.

Efron, B. and Tibshirani, R.J. (1993). An Introduction to the Bootstrap. London: Chapman and Hall.

Elliott, J.M. (1977). Some methods for the statistical analysis of samples of benthic invertebrates. Freshwater Biological Association, Scientific Publication no. 25.

Garthe, S. and Hüppop, O. (2004). Scaling possible adverse effects of marine wind farms on seabirds: developing and applying a vulnerability index. Journal of Applied Ecology 41: 724‐734.p

Johnston, A., Cook, A.S.C.P., Wright, L.J., Humphreys, E.M. & Burton, N.H.K. (2014). Modelling flight heights of marine birds to more accurately assess collision risk with offshore wind turbines. Journal of Applied Ecology 51: 31–41.

Joint Nature Conservation Committee (2013). JNCC Expert Statement on Ornithological Issues for Written Representations in Respect of East Anglia ONE Offshore Windfarm by Dr Sophy Allen. Joint Nature Conservation Committee, Aberdeen.

Jongbloed, R,H. (2016) Flight height of seabirds. A literature study. Institute for marine resources and ecosystem studies. Report number C024/16.

Mackenzie, M.L., Scott‐Hayward, L.A.S., Oedekoven, C.S., Skov, H., Humphreys, E., Rexstad, E. (2013) Statistical modelling of seabird and cetacean data: guidance document. University of St Andrews contract for Marine Scotland; SB9 (CR/2012/05).

Mendel, B., Kotzerka, J., Sommerfeld, J., Schwemmer, H., Sonntag, N. and Garthe, S. (2014). Effects of the alpha ventus offshore test site on distribution patterns, behaviour and flight heights of seabirds. In Ecological Research at the Offshore Windfarm alpha ventus (pp. 95‐110). Springer Fachmedien Wiesbaden.

Moray East (2018). Power Analysis for Pre‐construction Aerial Surveys. Moray Offshore Windfarm (East) Limited, Edinburgh. Available through https://www2.gov.scot/Resource/0053/00536269.pdf.

Moray Offshore Renewables Ltd (2016) Western Development Area Offshore Wind Farm Infrastructure Scoping Report. Edinburgh.

Moray Offshore Renewables Limited (2012) Environmental Statement Technical Appendix 4.5A – Ornithology Final. Moray Offshore Limited, Edinburgh [Moray East ES 2012].

Natural England and JNCC (2013) The Joint Nature Conservation Committee’s and Natural England’s Relevant Representations in Respect of Hornsea Project One Offshore Wind Farm (Planning Inspectorate Reference: EN010033) http://infrastructure.planningportal.gov.uk/wp‐content/uploads/2013/10/NE‐JNCC‐Hornsea‐Project‐One‐Relevant‐Representations.pdf

R Development Core Team (2015). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3‐900051‐07‐0, http://www.R‐project.org/.


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Walker, CG, Mackenzie, ML, Donovan C.R. and O'Sullivan, M. J. SALSA – a spatially adaptive local

smoothing algorithm (2011). Journal of Statistical Computation and Simulation 81, 179‐191.


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Appendix 1 ‐ Weather Reporting Scales

Seastate Turbidity Cloud Cover

Scale Condition Scale Condition Scale Condition

0 Calm (glass) 0 Clear 0% Clear

1 Calm (rippled) 1 Slightly Turbid 1‐10% Few

2 Smooth 2 Moderately Turbid 11‐50% Scattered

3 Slightly Moderate 3 Highly Turbid 51‐95% Broken

96‐100% Overcast


54

Appendix 2 ‐ JNCC Species Groups and Group Codes

JNCC Code Grouping Species Code Species

00020 Red‐throated diver 00020 Red‐throated diver

00220 Fulmar 00220 Fulmar

00710 Gannet 00710 Gannet

95009 Cormorant / Shag 00720 Cormorant

00800 Shag

05690 Great skua 05690 Great skua

94003 Small gull species 05750 Mediterranean gull

05780 Little gull

05820 Black‐headed gull

05900 Common gull

06020 Kittiwake

95034 Large gull species 05910 Lesser black‐backed gull

05920 Herring gull

05990 Glaucous gull

06000 Great black‐backed gull

95037 Tern species 06110 Sandwich tern

06150 Common tern

06160 Arctic tern

06240 Little tern

95038 ‘Commic’ tern (common or Arctic tern) 06150 Common tern

06160 Arctic tern

95040 Auk species 06340 Guillemot

06360 Razorbill

06380 Black guillemot

06540 Puffin

80150 Minke whale 80150 Minke Whale

80000 Cetacean species 82410 Harbour porpoise

82000 Dolphin species

7100 Phocid species 70010 Grey seal

70020 Common seal


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Appendix 3 ‐ Scientific Names of Species Recorded

Common Name Scientific Name

Red‐throated diver Gavia stellate

Fulmar Fulmarus glacialis

Gannet Morus bassanus

Cormorant Phalacrocorax carbo

Shag Phalacrocorax aristotelis

Kittiwake Rissa tridactyla

Common gull Larus canus

Great black‐backed gull Larus marinus

Herring gull Larus argentatus

Lesser black‐backed gull Larus fuscus

Common tern Sterna hirundo

Arctic tern Sterna paradisaea

Great skua Stercorarius skua

Black guillemot Cepphus grylle

Guillemot Uria aalge

Razorbill Alca torda

Puffin Fratercula arctica

Minke whale Balaenoptera acutorostrata

Harbour porpoise Phocoena phocoena

Common seal Phoca vitulina

Grey seal Halichoerus grypus


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Appendix 4 ‐ Auk availability bias

The correction factor applied to each relevant species is based on that recommended by JNCC in a

submission during the examination phase of the East Anglia ONE OWF, referred to by JNCC as Method C.

A copy of the text on Method C is provided below. This has been taken from Paragraph 5.6.5 of this

document:

Joint Nature Conservation Committee (2013). JNCC Expert Statement on Ornithological Issues for

Written Representations in Respect of East Anglia ONE Offshore Windfarm by Dr Sophy Allen. Joint

Nature Conservation Committee, Aberdeen.

The correction factor for puffins is taken from “Power Analysis for Pre‐Construction Aerial Surveys” report

(Moray East, 2018) a copy of the text is shown below:

‘ HiDef provided information regarding their adjustment for availability bias (the same approach was

applied to the data for the Dogger Bank ES) which is based on the assumption that puffins spend

approximately 20.2% of their time at sea underwater. Time at sea includes time spent flying, on the water

and diving. Puffins do not dive from flight, but from the sea surface. As this analysis is concerned with

birds on the water (and not birds in flight), there is a requirement to remove the component of

‘unavailability’ from the proportion of birds in flight. From the baseline data from the MORL wind farm,

95.7% of predicted puffins were assumed to be ‘on the water’ versus ‘in flight’. From the unavailability

figure provided by HiDef, 0.9%1 would have been attributable to birds in flight. However, all of the birds

underwater must be attributable to the proportion of birds on the water, as birds dive from the surface

of the water. Therefore it was calculated that approximately 21.1% of birds on the water would be

unavailable for detection as a result of diving for food’.


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Appendix 5 ‐ Puffin Modelling Outputs

A5.1 Model selection outputs

Figure A5.1.1. Knot grid locations (green) for the 2d spatial smooth of x and y coordinates

Figure A5.1.2. ACF plot showing correlation in each block (grey lines), and the mean correlation by lag across blacks (red line)


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Figure A5.1.3. Partial fit plots for continuous variable Distance and factor Month on the response scale


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Figure A5.1.4. Partial fit plots for continuous variable Distance and factor Month on the link scale


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A5.2 Puffin confidence interval maps

A5.2.1 May

A) Lower CI

B) Upper CI

Figure A5.1.5. Lower and upper confidence interval distribution maps


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A5.2.2 June

A) Lower CI

B) Upper CI



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A5.2.3 July

A) Lower CI

B) Upper CI



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Appendix 6 Distribution Maps

A6.1 Primary species

A6.1.1 Great black‐backed gull

Figure A6.1.1. Great black‐backed gull distribution in May


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Figure A6.1.2. Great black‐backed gull distribution in June

Figure A6.1.3. Great black‐backed gull distribution in July


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A6.2 Secondary species

A6.2.1 Herring gull

Figure A6.2.1. Herring gull distribution in May


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Figure A6.2.2. Herring gull distribution in June

Figure A6.2.3. Herring gull distribution in July


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A6.2.2 Guillemot

Figure A6.2.4. Guillemot distribution in May

Figure A6.2.5. Guillemot distribution in June


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Figure A6.2.6. Guillemot distribution in July

A6.2.3 Razorbill

Figure A6.2.7. Razorbill distribution in May


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Figure A6.2.8. Razorbill distribution in June

Figure A6.2.9. Razorbill distribution in July


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A6.3 Tertiary species

A6.3.1 Kittiwake

Figure A6.3.1. Kittiwake distribution in May


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Figure A6.3.2. Kittiwake distribution in June

Figure A6.3.3. Kittiwake distribution in July


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A6.3.2 Gannet

Figure A6.3.4. Gannet distribution in May

Figure A6.3.5. Gannet distribution in June


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Figure A6.3.6. Gannet distribution in July


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Appendix 7 Abundance of other Species / Species Groups Accounts

The non‐key species abundance for all surveys across the Moray East site and the Survey Area are presented in Table A7.1 and Table A7.2 below.

A total of 12,235 birds were recorded across all surveys during the 2018 aerial survey of the Moray East site and 10 km buffer from May to July. This consisted of 6,152, 4,744 and 1,339 birds recorded in May, June and July, respectively (Table A7.1).

A total of 47 marine mammals were recorded across all surveys during the 2018 aerial survey of the Moray East site and 10 km buffer from May to July. This consisted of 11, 34 and 3 marine mammals recorded in May, June and July, respectively (Table 15.1).

Table A7.1: Comparison of abundance of bird and marine mammal species recorded during the May 2018, June 2018 and July 2018 surveys in the Moray East site.

Species Raw Count Abundance Lower CI Upper CI CV Density (birds km‐2)

May‐18

Commic' Tern 2 11 2 34 0.71 0.04

Fulmar 40 227 125 347 0.16 0.77

Guillemot / Razorbill 344 1,954 710 3,392 0.05 6.62

Lesser Black‐backed Gull 3 17 3 34 0.58 0.06

Red‐throated Diver 4 23 4 57 0.50 0.08

Small Gull Species 1 6 1 17 1.00 0.02

Marine mammals

Grey seal 1

Jun‐18

Commic' Tern 2 11 2 34 0.71 0.04

Fulmar 23 131 51 228 0.21 0.44

Guillemot / Razorbill 233 1,325 427 2,372 0.07 4.49

Large Gull Species 3 17 3 46 0.58 0.06


Marine mammals

Harbour porpoise 5

Phocid 2

Jul‐18

Commic' Tern 33 187 33 465 0.17 0.63

Fulmar 26 148 85 210 0.20 0.50

Great Skua 1 6 1 17 1.00 0.02

Guillemot / Razorbill 33 187 51 369 0.17 0.63


Tern Species 2 11 2 34 0.71 0.04


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Species Raw Count Abundance Lower CI Upper CI CV Density (birds km‐2)

Marine mammals

Harbour Porpoise 2


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Table A7.2: Comparison of abundance of bird and marine mammal species recorded during the May 2018, June 2018 and July 2018 surveys in the Survey Area.

Species Raw Count Abundance Lower CI Upper CI CV Density

(birds km‐2)

May‐18

Black Guillemot 2 13 2 33 1 0.01

Commic' Tern 2 13 2 40 1 0.01

Common Gull 19 127 40 274 0 0.09

Fulmar 223 1,489 922 2,237 0 1.07

Great Skua 1 7 1 20 1 0.01

Guillemot / Razorbill 1,726 11,528 4,942 19,816 0 8.26

Large Gull Species 2 13 2 33 1 0.01

Lesser Black‐backed Gull 26 174 73 301 0 0.12

Red‐throated Diver 9 60 20 114 0 0.04

Small Gull Species 3 20 3 53 1 0.01

Marine mammals

Harbour porpoise 3

Dolphin / Porpoise 4

Grey seal 1

Phocid 3

Jun‐18

Commic' Tern 21 140 21 381 0 0.10

Common Gull 12 80 12 207 0 0.06

Fulmar 133 889 501 1,363 0 0.64

Great Skua 18 120 18 327 0 0.09

Guillemot / Razorbill 1,102 7,362 3,494 12,493 0 5.28

Large Gull Species 6 40 7 80 0 0.03


Red‐throated Diver 4 27 4 60 1 0.02

Marine mammals

Minke whale 3

Harbour porpoise 11

Dolphin / Porpoise 7

Dolphin species 2

Common seal 2

Phocid 5

Jul‐18

Commic' Tern 81 541 140 1,035 0 0.39


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Species Raw Count Abundance Lower CI Upper CI CV Density

(birds km‐2)

Common Gull 3 20 3 40 1 0.01

Cormorant / Shag 1 7 1 20 1 0.01

Fulmar 119 794 407 1,255 0 0.57

Great Skua 8 53 27 80 0 0.04

Guillemot / Razorbill 180 1,202 614 1,882 0 0.86


Small Gull Species 7 47 13 87 0 0.03

Tern Species 2 13 2 40 1 0.01

Marine mammals

Dolphin/Porpoise 1

Harbour Porpoise 2


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Contact Moray Offshore Windfarm (East) Limited

5th Floor, Atria One, 144 Morrison Street

Edinburgh EH3 8EX

Tel: +44 (0)131 556 7602

pre‐construction aerial survey report 2018

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