Analytical Services

We employ specialist technical experts including GIS analysts, statisticians and modellers, who regularly carry out a range of analyses to support our survey and monitoring work and environmental impact assessment. We take pride in outputs of the highest quality that are fit for publication in scientific journals where desired.

We have become industry leaders in developing methods and analytical techniques to assess the ornithological impacts of wind farms. This stems from a 'can do' attitude and a desire to further the standards of the ecological sciences and assessment that permeates the company ethos. Technical analyses routinely undertaken include modeling of avian collisions and analysis of boat-based, aerial and radar bird data to assess spatial and temporal distribution of birds (and marine mammals).

As a result of our first project in offshore wind development at Scroby Sands, we introduced the concept of indirect effects to EIA, whereby changes in habitat or food supply resulting from construction or operational activities have an indirect effect upon the abundance and/or distribution of a target species, perhaps with population scale consequences. At Scroby, we were also able to use the data gathered during telemetry in a novel way to assess the potential collision risk to birds, without the need for a separate and potentially very expensive programme or work.

When radio telemetry proved ineffective on Sandwich terns, we developed 'visual tracking' to understand the foraging movements of birds going on to become the first (and only) company to use the technique before and after the construction/operation of a large wind farm to validate actual collision risk, one of the key consent conditions. The project is currently producing unrivalled data quality that we think exceeds that produced by radar and camera systems as the decision-making process of the bird can be seen first-hand and in real-time both within and at considerable distance (several kilometres) from the wind farm. Handling this data has invariably led to a need to develop an analytical approach and this has been achieved in a stepwise manner from the macro-, to meso- to micro-scale in order to assess the actual avoidance rate.

In relation to collision risk, to the best of our knowledge we were the first company to incorporate collision risk modelling specifically developed for offshore data within an EIA in relation to a UK wind farm site. This became the standard in Round 2 developments in the Greater Wash strategic area and precipitated the development of an industry standard collision risk model developed through the Strategic Ornithological Support Services (SOSS). We provided detailed background information to aid model development and think we were then the first company to use advanced versions of the Band modelling system (i.e. Option 3) within EIA in relation to the proposed development of Atlantic Array. Options 3 and 4 have subsequently routinely been used in EIA of most proposed developments since. We then advanced the use of spatial collision risk modelling to identify hotspots of potential collision risk within a proposed Round 3 Zone. This allowed the relative effect of several proposed sites to be judged and helped structure site selection that was crucial to the development.

We worked with a colleague at the University of Essex to develop a simulation model of predicted foraging locations of breeding birds from colonies. This matched distribution patterns from aerial surveys and tracking studies. With our support our colleague then developed a version of Population Viability Analysis (PVA) to demonstrate the potential effect of predicted wind farm mortality on a breeding species within an internationally designated site. The study became a fundamental part of the Appropriate Assessment conducted on three proposed wind farms judged by the Secretary of State. This triggered the use of PVA to inform consenting decisions in relation to other seabird populations potentially affected by development. We think we were also the first to use Potential Biological Removal (PBR) as an assessment tool.

Following consent we continue to apply a range of available tools to assess changes in bird distribution including habitat and spatial modelling through generalised linear models (GLM), generalised additive models (GAM) and generalised additive mixed models (GAMM) and kernel density estimation (KDE). One member of the team has also recently completed training in the use of CReSS (Complex Region Spatial Smoother) developed by the Centre for Research into Ecological and Environmental Modelling (CREEM) at the University of St Andrews.

Prior to undertaking sophisticated analyses it is essential to visualise the data and to do this we routinely use ArcGIS v10. GIS is an extremely powerful instrument and contains a range of analytical tools that may be useful, as shown by our novel use of least cost path analysis to judge the extent of likely additional distance travelled by birds should barrier effects operate. Coupled with basic calculations of energy expenditure, we were able to demonstrate that deviation by breeding birds of the scale predicted was very unlikely to be important.


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