Project Summary

Introduction

Marine developments, such as offshore windfarms (Figure 1), may impact marine mammals and seabirds which use the development site. Animals may move away from the site entirely or redistribute themselves within the site. Detecting these changes is difficult because the number of animals may change at a particular site, or move within the site, regardless of any disturbances. Hence, the challenge is to determine if any changes in abundance and distribution are due to an impact (either directly or indirectly) or if these changes would have occurred anyway in the absence of any development. Surveys of the site are thus generally conducted before any development takes place, during construction and after construction in order to reliably determine any effects. Statistical methods can be used to identify both temporal and spatial changes at the site.

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FIGURE 1: WIND TURBINE (COURTESY OF KIRSTY ZEALAND)

Surveys are expensive and often difficult to undertake. Therefore, it is important to determine the level of survey effort required to achieve study objectives before undertaking the survey. For example, it would be useful to know what survey frequency (or design) would be sufficient to meet the study demands and indeed determine if this is even possible given the site, species characteristics, survey regime and the time/budget available. The ability of a study to detect change is a statistical issue called ‘power’ and essentially quantifies the chance that a study will correctly identify a genuine change.

 

 

Research programme and methodology

FIGURE 2: GANNET MORUS BASSANUS (COURTESY OF ANDY WEBB, HIDEF)

FIGURE 2: GANNET MORUS BASSANUS (COURTESY OF ANDY WEBB, HIDEF)

This research will review existing methods used to estimate power considering a range of taxa (e.g. seabirds (see Figure 2) and marine mammals) and survey types (e.g. vantage point (see Figure 3) or aerial surveys (see Figure 4)) which are likely to be relevant to studies undertaken to monitor marine developments in Scottish waters. A development could be a large scale, off-shore wind farm or a smaller scale, near-shore wave or tidal installation.

 

FIGURE 3: VANTAGE POINT SURVEYING (COURTESY OF GORDON HASTIE, SMRU)

FIGURE 3: VANTAGE POINT SURVEYING (COURTESY OF GORDON HASTIE, SMRU)

FIGURE 4: AERIAL SURVEY (COURTESY OF HIDEF)

FIGURE 4: AERIAL SURVEY (COURTESY OF HIDEF)

 

 

 

 

 

 

Suitable power analysis methods will be identified in the review and then evaluated in more detail using range of typical scenarios. One of the scenarios will include `no change’ post development, while others will describe a decline in overall numbers and/or a redistribution of animals post-impact. The testing process for each scenario will involve:

  • Generating, or simulating, data many times from a scenario where the true abundance and distribution of animals is known;
  • For each simulated reality, the power of each method will be estimated by comparing the performance with the known truth (under the relevant scenario).

This testing process will allow the different power analysis approaches (or key aspects of a single `general’ approach) to be assessed for both cryptic and abundant animals and based on different survey types and a method to be recommended. Computer code will be written to implement the recommended method to facilitate uptake by the user community.

The study will be primarily undertaken by researchers at the University of St Andrews, however the project will have regular and timely input from industry experts and both conservation and government organisations.

Outcomes

The project will create user-friendly software to permit access to the recommended power analysis approach for a wide range of users. This software will generate power analysis results alongside abundance and distribution maps (as an example see Figure 5), and will be of value to the renewable energy industry, Scottish Government and statutory advisors alike. This tool could also be used to design surveys and their frequency given a set of finite resources.

FIGURE 5: MAP SHOWING CHANGE IN ABUNDANCE FROM BEFORE TO AFTER THE DEVELOPMENT OF A WINDFARM AT *: STATISTICALLY SIGNIFICANT CHANGES ARE INDICATED BY ‘+’ FOR AN INCREASE AND ‘O’ FOR A DECREASE. RESULTS ARE SIMULATED. (FROM THE MRSea R PACKAGE (v0.2.2) VIGNETTE; http://creem2.st-andrews.ac.uk/software/)

FIGURE 5: MAP SHOWING CHANGE IN ABUNDANCE FROM BEFORE TO AFTER THE DEVELOPMENT OF A WINDFARM AT *: STATISTICALLY SIGNIFICANT CHANGES ARE INDICATED BY ‘+’ FOR AN INCREASE AND ‘O’ FOR A DECREASE. RESULTS ARE SIMULATED.
(FROM THE MRSea R PACKAGE (v0.2.2) VIGNETTE; http://creem2.st-andrews.ac.uk/software/)

 

 

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