Use of Aerial Surveys to Detect Bird Displacement by Offshore Windfarms

Report

Title: Use of Aerial Surveys to Detect Bird Displacement by Offshore Windfarms
Publication Date:
October 01, 2006
Document Number: COWRIE DISP-03-2006
Pages: 58
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Citation

Maclean, I.; Skov, H.; Rehfisch, M.; Piper, W. (2006). Use of Aerial Surveys to Detect Bird Displacement by Offshore Windfarms. Report by British Trust for Ornithology (BTO) and Danish Hydraulic Institute (DHI). pp 58.
Abstract: 

Offshore wind farms are likely to become one of Europe’s most extensive technical interventions in marine habitats. European inshore coastal and offshore marine waters support globally significant numbers of seabirds and UK Government has legal obligations to monitor the effects coastal developments will have on populations of these species.

 

Aerial surveys potentially provide a cost-effective means of monitoring bird populations rapidly over large and inaccessible areas. However, the extent to which current survey protocols enable changes in bird numbers to be detected during wind farm construction and operation is poorly understood.

 

In this report we make use of existing aerial survey data and use power analyses to assess whether the current DTI aerial survey scheme can be used to assess whether changes in bird numbers occur, given that there are large background fluctuations in seabird numbers at any given site. Four taxa were selected for analysis: red-throated diver (Gavia stellata), common scoter (Melanitta nigra), sandwich tern (Sterna sandvicensis) and lesser and greater black-backed gulls (Larus fuscus and L. marinus). Aerial surveyors are not usually able to distinguish between these two large gull species. In addition, we tested the importance of using a higher resolution of collected distances in relation to the detection probability of target species during current DTI aerial surveys.

 

Increasing the number of distance bands used results in no perceptible reduction in the error associated with estimating detection functions using DISTANCE software. Greater precision is best achieved by increasing the number of transects flown over any given area, thus increasing the frequency with which birds are encountered.

 

Current aerial survey methods provide adequate means for detecting changes in the numbers for most species that are dispersed and not prone to large inter-annual fluctuations, like sandwich terns and black-backed gulls in the DTI data analysed. For those species, which are aggregated and prone to larger inter-annual fluctuations, like red-throated diver and common scoter in the DTI data analysed, existing aerial survey methods only provide restrained means of detecting changes in regions in which these species are particularly abundant.

 

Extending the duration of aerial surveys would increase the likelihood that changes in numbers could be detected, but not by a substantial amount. The probability of detecting change is influenced strongly by the average number of birds present and consequently a more efficient means of increasing the likelihood of detecting changes would be to increase the frequency of surveys at times of year when the target species are most abundant.

 

Analysing data using the same spatial-scale as that of the expected wind farm “footprint” and “buffer” maximises the probability of detecting changes in bird numbers. In order to distinguish between changes in bird numbers due to wind farm development from changes induced by other factors, changes within wind farm footprint and buffer areas should be compared to those in a nearby control or “reference” area (i.e. using a “before-after-control-impact” or BACI approach). Statistical comparison of changes between the footprint plus buffer and reference area increases the probability of detecting small wind farm induced changes within the footprint and buffer areas. However, the size of the reference area has little predictable effect on the likelihood of detecting changes in numbers. It is therefore advisable that selection of such reference areas is based on the biology and behaviour of the bird species present and not on the statistical likelihood of detecting changes.

 

Obtaining synoptic hydro-dynamic variables concurrently with bird data and incorporating these into analysis is likely to help explain some of the temporal variation in numbers. Consequently doing so will increase the probability of distinguishing wind farm induced changes in bird numbers from background fluctuations. This method is likely to be the most cost-effective means of increasing the power of aerial surveys to detect changes in bird numbers.

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