Anglia Ruskin Research Online (ARRO)
Browse
Syposz_et_al_2018.pdf (560.72 kB)

Factors influencing Manx Shearwater grounding on the west coast of Scotland

Download (560.72 kB)
journal contribution
posted on 2023-07-26, 14:18 authored by Martyna Syposz, Filipa Gonçalves, Martin Carty, William J. E. Hoppitt, Fabrizio Manco
Grounding of thousands of newly fledged petrels and shearwaters (family Procellariidae) in built‐up areas due to artificial light is a global problem. Due to their anatomy these grounded birds find it difficult to take off from built‐up areas and many fall victim to predation, cars, dehydration or starvation. This research investigated a combination of several factors that may influence the number of Manx Shearwater Puffinus puffinus groundings in a coastal village of Scotland located close to a nesting site for this species. A model was developed that used meteorological variables and moon cycle to predict the daily quantity of birds that were recovered on the ground. The model, explaining 46.32% of the variance of the data, revealed how new moon and strong onshore winds influence grounding. To a lesser extent, visibility conditions can also have an effect on grounding probabilities. The analysis presented in this study can improve rescue campaigns of not only Manx Shearwaters but also other species attracted to the light pollution by predicting conditions leading to an increase in the number of groundings. It could also inform local authorities when artificial light intensity needs to be reduced.

History

Refereed

  • Yes

Volume

160

Issue number

4

Page range

846-854

Publication title

Ibis

ISSN

1474-919X

Publisher

Wiley

File version

  • Published version

Language

  • eng

Legacy posted date

2018-03-26

Legacy creation date

2018-03-26

Legacy Faculty/School/Department

ARCHIVED Faculty of Science & Technology (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC