Assessing penguin colony size and distribution using digital mapping and satellite remote sensing

Waluda, Claire M. ORCID: https://orcid.org/0000-0003-3517-5233; Dunn, Michael J. ORCID: https://orcid.org/0000-0003-4633-5466; Curtis, Michael L.; Fretwell, Peter T. ORCID: https://orcid.org/0000-0002-1988-5844. 2014 Assessing penguin colony size and distribution using digital mapping and satellite remote sensing. Polar Biology, 37 (12). 1849-1855. https://doi.org/10.1007/s00300-014-1566-y

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Abstract/Summary

Changes in penguin abundance and distribution can be used to understand the response of species to climate change and fisheries pressures, and as a gauge of ecosystem health. Traditionally, population estimates have involved direct counts, but remote sensing and digital mapping methodologies can provide us with alternative techniques for assessing the size and distribution of penguin populations. Here, we demonstrate the use of a field-based digital mapping system (DMS), combining a handheld geographic information system with integrated geographical positioning system as a method for: (a) assessing penguin colony area and (b) ground-truthing colony area as derived from satellite imagery. Work took place at Signy Island, South Orkneys, where colonies of the three congeneric pygoscelid penguins: Ade´lie Pygoscelis adeliae, chinstrap P. antarctica and Gentoo P. papua were surveyed. Colony areas were derived by mapping colony boundaries using the DMS with visual counts of the number of nesting birds made concurrently. Area was found to be a good predictor for number of nests for all three species of penguin. Using a maximum likelihood multivariate classification of remotely sensed satellite imagery (QuickBird2, 18 January 2010; Digital Globe ID: 01001000B90AD00), we were able to identify penguin colonies from the spectral signature of guano and differentiate between colonies of Ade´lie and chinstrap penguins. The area classified (all species combined) from satellite imagery versus area from DMS data was closely related (R2 = 0.88). Combining these techniques gives a simple and transferrable methodology for examining penguin distribution and abundance at local and regional scales.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1007/s00300-014-1566-y
Programmes:	BAS Programmes > Polar Science for Planet Earth (2009 - ) > Ecosystems BAS Programmes > Other
ISSN:	0722-4060
Additional Keywords:	Pygoscelid penguins, satellite remote sensing, digital mapping, population estimate
Date made live:	23 Sep 2014 08:32 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/508472

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