- The aim of this project was to review the potential issue of 'turnover' of individual seabirds at sea during the breeding season and to assess how this may lead abundance estimates derived from boat or aerial surveys to underestimate the total number of birds that use an area during the course of the breeding season. We estimate turnover rates in species for which sufficient data were available.
- The following candidate species were identified for inclusion in the project: red-throated diver, common guillemot, razorbill, black guillemot, Atlantic puffin, European shag, common eider, northern gannet, black-legged kittiwake and northern fulmar. Turnover was estimated in four species for which sufficient data were available: common guillemot; razorbill; Atlantic puffin and black-legged kittiwake, using the Forth/Tay region as the study area. A literature review on input parameters required to estimate turnover was undertaken on the remaining species to establish data gaps.
- We defined turnover as the total number of birds that will use a particular area of sea at any point during the breeding season, divided by the number of birds that will be present in that area at a particular snapshot in time.
- We estimate turnover using modelled foraging densities of the Forth-Tay area derived from real GPS data (as produced and described in Searle et al., 2014) to simulate the daily foraging locations of individual birds on individual days throughout the breeding season. By assuming that birds rest at their foraging locations, and travel in a straight line between the colony and foraging location, these simulations can also be used to evaluate the locations that are associated with foraging, commuting and resting at sea.
- We then use empirical data on the daily activity budget of birds as a basis for simulating the number of birds that would be seen performing each behaviour (foraging, commuting, resting at sea) within each wind farm footprint during a "snapshot" survey of the entire footprint area. This allows us to produce a direct estimate of turnover.
- Foraging site fidelity will clearly affect estimates of turnover, however, it is not well understood or parameterised in these species. We have, therefore, estimated turnover under a number of different scenarios regarding the extent of site fidelity: both in terms of the level of the site fidelity, as well as the spatial scale associated with it.
- As well as being contingent upon particular levels and scales of foraging site fidelity, the calculations also depend heavily upon the accuracy of the input data (bird density and time activity) and upon a number of other simplifying assumptions: that birds will only visit one foraging location on a day, that they will rest at the same location as they feed, and that they will travel to this location in a straight line from the colony.
- Our results indicate that: (a) turnover decreases as site fidelity increases; (b) turnover decreases as birds exhibit site fidelity at finer spatial scales; (c) turnover is typically much higher for "commuting" behaviour than for "foraging" or "resting at sea" behaviours; (d) variation in turnover between the simulated snapshot surveys is generally very substantial. The results also highlight more subtle differences between individual species and wind farm footprints.
- In general, kittiwake and razorbill had higher levels of turnover than did guillemots or puffins. This is true for both foraging and resting at sea. For all wind farm footprints, kittiwake and razorbill had estimates of turnover between approximately 100 and 150 with a site fidelity level of zero, in comparison to guillemot and puffin that had estimates between approximately 60 and 100. These differences may, in part, be explained by variation in the foraging ecology of each species (foraging range and observed time activity budgets).
- Within a species, there was variation in estimates of turnover between wind farm footprints. Guillemots displayed the lowest variation in turnover estimates between the different footprints. Razorbills also exhibited relatively low variation in turnover estimates between wind farm footprints. Kittiwakes displayed a similar pattern in relation to variation amongst wind farm footprints as seen for razorbills, although overall turnover estimates for kittiwake were slightly higher than those estimated for razorbills, for both foraging and resting at sea. While puffins had the lowest overall estimates of turnover for both foraging and resting at sea of the four species, they did have noticeably higher estimates of turnover for foraging birds at the NnG and Bravo wind farm footprints in comparison to the other wind farm footprints.
- Turnover is calculated in relation to a "census snapshot", thereby assuming that it is possible to survey the entire population within an area completely and instantaneously. This is a useful approach, because it separates out the effects of turnover from those of other effects ( e.g., non-detection). However, in order to relate the results of this work directly to the output from at-sea or aerial surveys it is important to account for the fact that these types of data will typically constitute a sample rather than a census, and that they will not take place instantaneously.
- Conclusions: This project provides relevant information to assist Marine Scotland Science with identifying knowledge gaps that may benefit from further data collection. It will also enable Marine Scotland Licensing Operations Team and Marine Renewables Developers to make more informed assessments of the potential impacts of development projects as part of the required environmental evaluations. The project, therefore, has significant strategic relevance for site characterisation and monitoring in Scotland and beyond. Turnover is clearly only one factor that will need to be considered when assessing the risks to seabird populations from offshore developments. A related task will involve quantifying the fate of birds that lie within the development footprint. Further work is needed in order to understand whether higher levels of turnover lead, all else being equal, to higher or lower estimates of development-related mortality.
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