Developing and assessing methods to census and monitor burrow-nesting seabirds in Ireland

Simple item page
dc.check.embargoformatEmbargo not applicable (If you have not submitted an e-thesis or do not want to request an embargo)en
dc.check.infoNot applicableen
dc.check.opt-outNoen
dc.check.reasonNot applicableen
dc.check.typeNo Embargo Required
dc.contributor.advisorQuinn, Johnen
dc.contributor.advisorJessopp, Mark Johnen
dc.contributor.authorArneill, Gavin E.
dc.contributor.funderNational Parks and Wildlife Serviceen
dc.date.accessioned2019-01-25T09:35:17Z
dc.date.available2019-01-25T09:35:17Z
dc.date.issued2018
dc.date.submitted2018
dc.description.abstractCensusing and monitoring populations are key priorities in conservation. This is particularly challenging for seabirds, where several life history characteristics and the remote nature of breeding colonies of many species make them difficult to study. Burrow-nesting species are the most difficult of all seabird groups to census due to their cryptic breeding habits, nocturnal behaviours within breeding colonies, and coexistence with other burrowing species. Historically estimates of population size in these species were obtained subjectively from the activity within colonies on a given day/night, though the relatively recent development of methodologies such as tape-playbacks have made it possible to generate population estimates using quantitative data. Nevertheless, gaps remain in our knowledge, such as the appropriate sampling approaches to take, the efficacy of some recently established automated methods, and the use of predictive species distribution modelling that could guide these time consuming efforts. In my thesis, we address some of these issues for three key burrow-nesting species in the northern hemisphere: the Manx shearwater (Puffinus puffinus), the European storm petrel (Hydrobates pelagicus) and the Atlantic puffin (Fratercula arctica). In the first paper, we explore a range of sampling approaches to estimate and detect changes in population size, using data from Manx shearwater censuses as a case study. This demonstrated that a priori knowledge of the density and distribution in a colony allows multi-stage stratification that dramatically improves the accuracy of population estimates at low levels of sampling. Power analyses found that many existing monitoring efforts are likely to fail to detect population trends due to the enormous effect of high variation of densities between randomly selected plots. However, subjectively sampling within areas of highest density significantly increases the power to detect declines. My thesis also shows that these breeding distributions can be predicted a priori using ensemble species distribution models built on density data from censuses, habitat assessments, and digital elevation models. Another paper in my thesis examines the efficacy of emerging automated techniques, which is far from clear. Results here show, for the first time, that soundscapes obtained from passive acoustic monitoring in the Manx shearwater are driven by in-colony flight paths rather than local nest density, although a decline in density within the colony over two years coincided with a decline in acoustic activity. The final empirical paper reports new population size estimates for several colonies and uses matrix population models to retrodict populations to explicate discrepancies between our estimates and those of the only previous census, Seabird 2000 (1998-2002). The findings here suggest that existing estimates for burrow-nesting Procellariiformes in Ireland are likely vast underestimates, however, the extent to which this is true for the national estimates cannot be quantified as factors that determine population size vary across a species range. Atlantic puffin populations appear to be in decline across the sites considered in this study. My thesis as a whole highlights the need for the revision and standardisation of the methods used to census and monitor burrow-nesting seabirds. For these breeding populations in the geographic region studied here, the Seabird Monitoring Handbook should be updated. Finally, the findings of this PhD research are synthesised in the form of an Irish Wildlife Manual, providing the National Parks and Wildlife service feasible options to fulfil their international obligations to report the conservation status of these populations.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationArneill, G. E. 2018. Developing and assessing methods to census and monitor burrow-nesting seabirds in Ireland. PhD Thesis, University College Cork.en
dc.identifier.endpage177en
dc.identifier.urihttps://hdl.handle.net/10468/7358
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2018, Gavin Euan Arneill.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectAtlantic puffinen
dc.subjectManx shearwateren
dc.subjectEuropean storm petrelen
dc.subjectSeabirden
dc.subjectZoologyen
dc.subjectCensus methodsen
dc.subjectMonitoring methodsen
dc.thesis.opt-outfalse
dc.titleDeveloping and assessing methods to census and monitor burrow-nesting seabirds in Irelanden
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhDen
ucc.workflow.supervisorj.quinn@ucc.ie
Files
Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
Gavin Arneill - E-thesis.pdf
Size:
13.33 MB
Format:
Adobe Portable Document Format
Description:
E-thesis
Download
Thumbnail Image
Name:
Gavin Arneill - PhD Abstract.pdf
Size:
58.18 KB
Format:
Adobe Portable Document Format
Description:
Abstract
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
5.62 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Doctoral Theses
Biological, Earth and Environmental Sciences - Doctoral Theses
Centre for Marine and Renewable Energy (MaREI) - Doctoral Theses
College of Science, Engineering and Food Science - Doctoral Theses
Environmental Research Institute - Doctoral Theses