1 Apportioning (Appendix 11.4)

1.1 Introduction

Apportioning provides a means of estimating the proportion of total impact, arising from a development, expected to be received by each individual colony with connectivity to that development. Predicted impacts of a development can be assigned to colonies by calculating apportioning factors as a function of their population size, distance from a development's array area and the amount of the colony's foraging range that falls within open sea. For each colony, the calculated apportioning factor can then be multiplied by the total precited impact to estimate the proportion of that impact which will be experienced by birds from that colony. Thus, the sum of each colonies apportioned impacts will equal the total predicted impact. This technical appendix presents the methodology used to seasonally apportion the predicted collision and/or distributional response impacts of the Proposed Development. Apportioning factors were calculated for puffin, kittiwake, guillemot, herring gull, gannet and razorbill.

This digital report contains outputs associated with the SPAs that are used for assessment. Non-SPA apportioning can be found in the main body of Annex 11.4 of the Muir Mhòr Ornithology report.

1.2 Methodology

1.2.1 Species Screening

Species included in apportioning were screened based on the level of impact predicted. As such, the species for which apportioning factors were calculated were determined by the results of the collision risk modelling and displacement assessment, the details of which can be found in the relevant technical appendices (Offshore Ornithology Distributional Responses Report (Volume 3, Appendix 11.3) and Offshore Ornithology Collision Risk Modelling (CRM) Report (Volume 3, Appendix 11.2)). The guidance on displacement assessments, discussed in NatureScot (2023a) and detailed in statutory nature conservation bodies (SNCB) (2022), advises that a range of displacement values are carried forward to the assessment of population impacts. Table 2.1 comes from the NatureScot guidance on distributional responses (NatureScot 2023a) and shows the range of mortality rates which should be used in displacement assessments during both the breeding and non-breeding seasons.

For all species, both the breeding and non-breeding season each have a higher and lower displacement estimate because of the range of rates applied for mortality. As such, two separate displacement scenarios are apportioned here:

The upper displacement estimate comprised of the higher breeding and higher non-breeding season estimates.
The lower displacement estimate comprised of the lower breeding and lower non-breeding season estimates.

1.2.2 Population Counts

Table 1: SPAs, for which the listed species are a feature or assemblage feature, used in the apportioning calculations for each species, along with their by sea, centroid to centroid, distances from the Array area, the number of individual breeding adults in the SPA and the year count data were collected.

1.3 Results

1.3.1 Breeding Season Apportioning Factors

Table 2: The calculated breeding season impact apportioning factor for each relevant SPA for each species and the total sum of each species’ relevant non-SPA colonies. Blank cells are where the species and SPA combination is not relevant, either due to no connectivity with the Array area, or the species not being a feature of the SPA. Values are rounded to 3 decimal places for display purposes only.

1.3.2 Non-Breeding Season Apportioning Factors

Table 3: The number of individuals each SPA contributes to the regional UK North Sea BDMPS population during the non-Breeding period (either Autumn or Spring). Along with the proportion of the regional UK North Sea BDMPS population this equates to. The residual sum attributed of all non-SPA colonies summed is also given.

1.3.3 Apportioned Impact Estimates

Table 4: All impacts (displacement or collision) apportioned out to SPAs for each species, phenological period and age class. Values in the table represent the number of impacted individuals.

2 Population Viability Analysis (Appendix 11.5)

2.1 Introduction

Population viability analysis (PVA) is a method to predict the trajectory of a population based on different life history parameters relevant to population growth (e.g., survival rates and reproductive rates). This technique can be used to make predictions regarding baseline population growth or decline over time. Predicted anthropogenic impact levels can then be incorporated and the models re-run to understand how the course of the population over time might be affected by the predicted level of impact. In an Environmental Impact Assessment (EIA) context, PVA can be used to assess the potential effects of mortality associated with a development upon local populations at varying population scales.

This digital report is a supplement to the PVA appendix and provides details of PVA carried out to predict population level impacts of the Proposed Development on key seabird populations, both individually (hereafter referred to as project-only scenarios) and in combination with other developments (hereafter referred to as cumulative impact scenarios).

2.2 Methods

2.2.1 NEPVA tool

Models were run using the Natural England PVA tool (NEPVA, Tool v 2 (Code: v 4.18 Interface: v 1.7). Full details are available in Appendix 11.5 of the impact assesssment report.

The NEPVA tool is based around a simple age-class based model in which individuals in a simulated population progress from a chick age class, through annual immature age classes to an adult age class, with individuals that have reached the adult stage contributing to productivity (i.e., the measure of successful reproduction in a breeding season). These relationships among age classes are captured in a population projection matrix, also known as a Leslie matrix.

2.2.2 Species and populations modelled

Predicted collision and distributional response impacts from the Proposed Development were apportioned for six key species (kittiwake, herring gull, guillemot, razorbill, puffin and gannet - see Volume 3, Appendix 11.4, Ornithology Apportionment Technical Report). For each of these species, PVA modelling was considered for both project-only impacts, and cumulative impacts at both the regional population level and for individual Special Protection Areas (SPAs) for which that species is designated, either individually or as part of an assemblage.

2.2.2.1 Project-only

Table 5: Species-SPA combinations brought forward for project-only PVA analysis. Calculation of the percentage point change in mortality is presented in Annex A of Chapter 11.5

2.2.2.2 Cumulative

Table 6: Species-SPA combinations brought forward for cumulative PVA analysis. The project-only mortalities are based on all impacts across both the breeding and non-breeding seasons and the higher distributional response mortality rate scenario. The cumulative percentage point change is based on a scenario assuming higher distributional response mortality rates and including fatalities associated with Green Volt and Berwick Bank. (Scenarios run are described in Section 2.6.2 of Chapter 11.5). Annual mortalities are presented in the “Annual predicted impact mortality rates” tables in Annex A and percentage changes in mortality are calculated as 100 * the PVA rates presented in tables in Annex B of Chapter 11.5

2.2.3 Population size data

Table 7: Population sizes and the associated year of the count used in the PVA modelling, by species and SPA. Details derivation methodsare provided in Volume 3, Appendix 11.4 (Ornithology Apportionment Technical Report). Where counts were collected over several years, the midpoint (rounded up) of the range of years was used for PVA modelling. Where this is the case, years are marked with an asterisk.

2.2.4 Impact values used

2.2.4.1 Project-only

Table 8: Relative proportion by which demographic rates are decreased as a result of predicted impacts of the windfarm, used in the PVA modelling.

2.2.4.2 Cumulative

Table 9: Relative proportion by which demographic rates are decreased as a result of predicted impacts of the windfarms, used in the PVA modelling. BB and GV relate to Berwick Bank and Green Volt respectively.

2.3 Results

The following tables are summaries of the CPS and CGR values as calculated from the PVAs for the project-only and cumulative impacts. More specific details, including population trajectories and tables showing specific maths related to the calculation of mortality rates can be found in Appendices A - E of Chapter 11.5 of the Ornithology report.

2.3.1 Project-only

Table 10: Summary of population viability analysis and the key output metrics, counterfactual population size (CPS) and counterfactial growth rate (CGR), for the Proposed Development.

2.3.2 Cumulative

Table 11: Summary of population viability analysis and the key output metrics, counterfactual population size (CPS) and counterfactial growth rate (CGR), for cumulative effects.