adding value to monitoring: the impact of offshore ...

ADDING VALUE TO MONITORING: THE IMPACT OF OFFSHORE WIND FARM DEVELOPMENTS ON BENTHIC ORGANISMS AND SEDIMENTS IN THE EASTERN IRISH SEA

by 0338788

Thesis presented in part-fulfilment of the degree of Master of Science in accordance with the regulations of the University of East Anglia

School of Environmental Sciences University of East Anglia University Plain Norwich NR4 7TJ ©2012 Georgia Bayliss-Brown This copy of the dissertation has been supplied on condition that anyone who consults it is understood to recognise that its copyright resets with the author and that no quotation from the dissertation, nor any information derived there from, may be published without the author’s prior written consent. Moreover it is supplied on the understanding that it represents an internal University document and that neither the University nor the author are responsible for the factual or interpretive correctness of the dissertation.

Abstract The development of offshore wind farms (OWFs) in UK waters is becoming increasingly evident. In line with EU policy and legislation, the significance of the impacts that these constructions have upon the environment are assessed. In addition, licenses required to begin construction often include legally-binding conditions to monitor the developments’ effects on stated receptors. Monitoring programmes are an expensive undertaking, and are often not performed unless mandatory. This study investigates which additional benefits, if any, the data resulting from these programmes can have upon strengthening or simplifying subsequent environmental impact assessments (EIAs) and if its analysis can lead to a better understanding of OWFs’ impacts upon the environment. Looking at the benthic environment, fauna and sediment data, collected from 1m2 day grab surveys in the Eastern Irish Sea, was interpolated using Gaussian Kriging and Euclidean allocation techniques providing predictions of species diversity, richness and evenness and sediment type, class and sorting for a planned OWF development at Gwynt y Môr (GyM). These forecasts were then compared to actual data to demonstrate that species diversity can be accurately predicted. The inter-annual variability of the faunal data, for 2005 and 2010, for two operating sites (Burbo Bank, BB, and Rhyl Flats, RF) and GyM, was analysed to quantify the impact of construction upon the benthic organisms present. It was concluded that construction, at BB and RF, although not altering the attributes defining the benthic communities, prevented the natural improvement experienced at GyM, where development had not occurred.

This

postulates that a development site should be compared to reference sites to fully assess its impacts. This study highlights the importance of evaluating monitoring data to contribute to decisionmaking and the development of mitigation and ecosystem management programmes; thus adding value to a costly, enforced requirement. Keywords: offshore wind farm, monitoring, environmental impact assessment, Eastern Irish Sea, Gaussian Kriging, Euclidean allocation, benthic organisms 1

Contents Abstract ...................................................................................................................................... 1 Contents ..................................................................................................................................... 2 List of Tables ............................................................................................................................. 7 List of accompanying material................................................................................................... 9 Acknowledgements .................................................................................................................. 10 1.0 Introduction ........................................................................................................................ 11 1.1 UK offshore wind farm development – Background ......................................................... 11 1.1.1 International and European political context .............................................................. 12 1.1.1.1 Renewable energy .................................................................................................... 12 1.1.1.2 The marine environment .......................................................................................... 12 1.1.2 UK political context .................................................................................................... 13 1.1.3 Legal and regulatory framework ................................................................................. 14 1.1.3.1 The Crown Estate and FEPA ................................................................................... 14 1.1.2.2 Strategic Environmental Assessment ....................................................................... 14 1.1.2 Environmental context ................................................................................................ 15 1.2 Environmental Impact Assessment (EIA) ......................................................................... 15 1.2.1 Post Decision Monitoring and Auditing ..................................................................... 17 1.2.2 Value-added monitoring ............................................................................................. 18 1.3 Project Scope ..................................................................................................................... 19 1.3.1 Location ...................................................................................................................... 19 1.3.2 Receptor ...................................................................................................................... 20 2

1.3.2.1 The benthic environment ......................................................................................... 20 1.4 Aims & Objectives ............................................................................................................. 21 2.0 Data and Methods .............................................................................................................. 24 2.1 Methodology ...................................................................................................................... 24 2.1.1 Baseline assimilation .................................................................................................. 24 2.1.2 Impact quantification .................................................................................................. 25 2.2 Sources of data ................................................................................................................... 26 2.2.1 Baseline assimilation .................................................................................................. 26 2.2.2 Impact quantification .................................................................................................. 27 2.2.3 Data collection ............................................................................................................ 27 2.2.4 Laboratory Analysis .................................................................................................... 27 2.2.4.1 Benthic infauna ........................................................................................................ 28 2.2.4.2 Benthic sediment ...................................................................................................... 28 2.3

Techniques .................................................................................................................... 29

2.3.1 Species inventory and abundance data entry .............................................................. 29 2.3.2 ArcGIS 10.0 ................................................................................................................ 30 2.3.2.1 Map creation ............................................................................................................ 31 2.3.2.1 Interpolation ............................................................................................................. 31 2.3.2.1.1 Kriging .................................................................................................................. 32 2.3.2.1.2 Euclidean allocation .............................................................................................. 33 2.3.2.1.3 Extracting of multiple points ................................................................................ 33 2.3.3 PRIMER v6.0 .............................................................................................................. 33 3

2.3.3.1 Transform ................................................................................................................. 33 2.3.3.2 Univariate analysis ................................................................................................... 34 2.3.3.2.1 DIVERSE .............................................................................................................. 34 2.3.3.3 Multivariate analysis ................................................................................................ 35 2.3.3.3.1 ANOSIM ............................................................................................................... 35 2.3.3.3.2 CLUSTER ............................................................................................................. 35 2.3.3.3.3 Multi-dimensional scaling (MDS) ........................................................................ 35 2.3.3.3.4 SIMPER ................................................................................................................ 35 2.3.4 Simple statistics .......................................................................................................... 35 2.3.4.1 Microsoft Excel ........................................................................................................ 35 2.3.4.2 PASW Statistics ....................................................................................................... 36 2.3.5 Particle Size Analysis ................................................................................................. 36 2.3.6 Biotope Classification ................................................................................................. 36 CHAPTER THREE: RESULTS .............................................................................................. 37 3.0 Results ................................................................................................................................ 37 3.1 Baseline assimilation ......................................................................................................... 37 3.1.1 Interpolation of Study Area A..................................................................................... 37 3.1.1.1 Faunal data and Kriging – A visual comparison ...................................................... 38 3.1.1.2 Faunal data and Kriging – A statistical comparison ................................................ 41 3.1.1.3 Sediment data and Euclidean Allocation ................................................................. 44 3.1.2 Interpolation of Study Area B ..................................................................................... 46 3.1.2.1 Spatial variation – A visual comparison .................................................................. 46 4

3.1.2.2 Temporal variation – A visual comparison .............................................................. 49 3.1.2.3 Temporal and Spatial variation – A statistical comparison ..................................... 51 3.1.3 Summary of findings................................................................................................... 54 3.2 Impact quantification ......................................................................................................... 54 3.2.1 Correlations between 2005 and 2010 faunal data ....................................................... 55 3.2.2 Magnitude in variation between 2005 and 2010 ......................................................... 59 3.2.3 Impacts upon the benthic environment post-construction .......................................... 60 3.2.4 Changes in biotopes – identifying clusters ................................................................. 60 3.2.5 Changes in biotopes – analysing clusters.................................................................... 63 3.2.6 Summary of findings................................................................................................... 70 4.0 Discussion .......................................................................................................................... 71 4.1 Interpolation as a hypothesis-driven investigation ............................................................ 71 4.2 Findings in context ............................................................................................................. 72 4.3 Recommendations .............................................................................................................. 72 4.4 Limitations of this study .................................................................................................... 73 4.4 Further studies .................................................................................................................... 74 4.4.1 Habitat mapping .......................................................................................................... 74 4.4.2 Impact Assessment...................................................................................................... 75 5.0 Conclusion ......................................................................................................................... 76 APPENDICES ......................................................................................................................... 86 Appendix 1: List of Species identified within the surveys ...................................................... 87 Appendix 2: Resultant data after Kriging ................................................................................ 95 5

Appendix 3: Forecasts for Study Area B compared to actual, measured values in 2005 ...... 102 Appendix 4: Forecasts for Study Area B compared to actual, measured values in 2010 ...... 105 Appendix 5: Pair-wise sampling codes .................................................................................. 106 Appendix 6: Actual measured faunal attributes for BB, RF and GyM for 2005 and 2010 ... 107 Appendix 7: Characterising species, and % overall contribution, for all clusters ................. 109 Appendix 8: Sedimnet attributes for Super-cluster sample ................................................... 112 Appendix 9: Colonial species where noted as present (P) in the raw data ............................ 115 Appendix 10: Ethics questionnaire ........................................................................................ 116

List of Figures Figure 1: The current status of constructed and planned UK OWFs ....................................... 16 Figure 2: The EIA process ....................................................................................................... 17 Figure 3: Seabed sediments of Liverpool Bay ......................................................................... 21 Figure 4: Areas of study and data interpolation, Study Area A and Study Area B ................. 25 Figure 5: Classification by sediment class ............................................................................... 29 Figure 6: Semivariance models by type ................................................................................... 32 Figure 7: Location of grab samples and OWFs contributing to the study .............................. 37 Figure 8: GyM grab sample locations for 2005 ....................................................................... 38 Figure 9: Actual versus predicted √H’ for multiple Kriging techniques ................................. 39 Figure 10: Actual versus predicted √d and √J’ for multiple Kriging techniques ..................... 40 Figure 11: Correlations of actual versus predicted values for √d for Study Area A in 2005 .. 42 Figure 12: Correlations of actual versus predicted values for √H’ for Study Area A in 2005 43 6

Figure 13: Correlations of actual versus predicted values for √J’ for Study Area A in 2005 . 43 Figure 14: Actual versus predicted sediment (a) type, (b) class and (c) sorting ...................... 45 Figure 15: 2005 and 2010 grab sample sites for Study Area B ............................................... 47 Figure 16: Interpolation results compared to actual measured values in 2005 ........................ 48 Figure 17: Interpolation results compared to actual measured values in 2010 ........................ 49 Figure 18: Correlations of actual versus predicted values for for varying spatial and temporal samples ..................................................................................................................................... 52 Figure 19: Locations (and new codes) of grab samples collected in both 2005 and 2010 ...... 55 Figure 20: Correlations of 2005 and 2010 values .................................................................... 56 Figure 21: Faunal impacts from 2005 to 2010 ......................................................................... 61 Figure 22: Sediment impacts from 2005 to 2010..................................................................... 62 Figure 23: Dendrograms showing clusters for 2005 and 2010 ................................................ 64 Figure 24: MDS representation of the identified clusters ........................................................ 65 Figure 25: “Super-cluster” locations in 2005 and 2010 ........................................................... 66 Figure 26: Sediment attributes by cluster for 2005 .................................................................. 67 Figure 27: Sediment attributes by cluster for 2010 .................................................................. 68 Figure 28: Sediment class of each “super-cluster” .................................................................. 69 Figure 29: Inter-annual variability in faunal attributes ............................................................ 76 List of Tables Table 1: Faunal assemblages in soft sediments occurring in Liverpool Bay, the Thames Estuary and the Greater Wash (directly extracted from BMT Cordah, 2003) ......................... 23 Table 2: Classification by sediment: a) type; and, b) sorting (Buchanan, 1984) ..................... 28

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Table 3: Example of the abundance of species identified at five grab sites (For illustrative purposes only - extracted from the GyM 2010 dataset) ........................................................... 34 Table 4: Significance of correlation between actual and predicted values for GyM using various Kriging techniques ...................................................................................................... 44 Table 5: Comparative table showing mean predicted and actual values for √H', √d and √J' for Study Area A and B in 2005 and 2010. ................................................................................... 50 Table 6: Significance of correlation between actual and predicted values for GyM looking at a reduced size study site and different years of study .............................................................. 53 Table 7: The similarities between faunal attributes measured in 2005 and 2010 for BB, GyM and RF (nb. significance levels of p≤0.01 are shown in bright yellow and levels of 0.01256mm Scale (mm) 64 - 256mm 4 - 64mm 2 - 4mm 1 - 2mm 0.5 - 1mm 250 - 500μm 125 - 250μm 63 - 125μm 2.6) in the mid to north-eastern section of the GyM survey area showing a decrease towards the coast (√H’0.000 0.02 0.125

The statistics indicate that RF show best correlation between 2005 and 2010 faunal data with 24.2% of 2010 data being linearly-dependent on the √J’ measured at the same site in 2005;

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√H’ is linearly-dependent for 43% of 2010 data and the 2010 measures of √S, √N and √d are linearly-dependent for over 50% of all 2005 locations. Data collected in 2010 for BB is linearly-dependent upon over 50% of all 2005 data points for √H’ (r2=0.654), √d (r2=0.521) and √J’ (r2=0.542), and, 39.3% √N. GyM’s 2010 data is never more than 40% linearly dependent upon 2005 data when there is a significance of (negative) correlation; present for the √N (r2=0.348), √d (r2=0.375) and √H’ (r2=0.366). It can be extracted from these statistics that BB and RF show greater correlation, and less change, over the five year time period than GyM. The main lack of correlation is in √N measured for both GyM and BB; where a change great enough to influence the correlation between each sample point has occurred. This is likely to have caused the resulting change in √J’ at GyM. 3.2.2 Magnitude in variation between 2005 and 2010 Stimulated by the findings in Section 3.2.1, the mean change in the number of individuals, √N, and species, √S, and their respective diversity, √H’, richness, √d, and evenness, √J’, was devised and is provided in Table 8.

As in Table 7, the cells are highlighted where

significance in correlation, between 2005 and 2010, was determined; dark yellow shows strong significance (p≤0.01) and pale yellow shows slight significant (0.01