Generating unbiased estimates of burrowing seabird populations

Maximising survey efficiency can help reduce the trade-off between spending limited conservation resources on identifying population changes and responding to those changes through management. Burrow-nesting seabirds are particularly challenging to survey because nests cannot be counted directly. We...

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Main Author: Bird, Jeremy
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2022
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Online Access:https://doi.org/10.5061/dryad.sn02v6x2d
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spelling ftzenodo:oai:zenodo.org:7306157 2024-09-15T17:43:44+00:00 Generating unbiased estimates of burrowing seabird populations Bird, Jeremy 2022-11-08 https://doi.org/10.5061/dryad.sn02v6x2d unknown Zenodo https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.sn02v6x2d oai:zenodo.org:7306157 info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode info:eu-repo/semantics/other 2022 ftzenodo https://doi.org/10.5061/dryad.sn02v6x2d 2024-07-25T20:41:03Z Maximising survey efficiency can help reduce the trade-off between spending limited conservation resources on identifying population changes and responding to those changes through management. Burrow-nesting seabirds are particularly challenging to survey because nests cannot be counted directly. We evaluated a stratified random survey design for generating unbiased population estimates simultaneously for four petrel species nesting on Macquarie Island, Australia, where the survey cue, burrow entrances, is similar for all species. We also compared the use of design-based and model-based analyses for minimising uncertainty in estimates. We recorded 2,845 Antarctic Prion burrows, 306 White-headed Petrel burrows and two Blue Petrel burrows while distance-sampling along 154 km of transects. For Blue Petrels and Grey Petrels, we completed nocturnal searches along a further 71 km and searched 249 km of tracks during follow-up ground searches. We failed to generate unbiased population estimates for two rare and localised species, Blue and Grey Petrels, from our stratified random survey. Only for the most widespread and abundant species, Antarctic Prion, did the estimate have reasonable power to detect a rapid population change. Model-based analyses of the stratified random survey data did not improve upon traditional design-based analyses in terms of uncertainty in population estimates, but they did provide useful spatial representation of current populations. Models that used the targeted survey data did not reflect current population sizes and distributions of the two rare and localised species. We found that when species ecologies, distributions and abundances vary, a multi-method approach to surveys is needed. Species with low abundance that occur patchily across large islands are likely to be best estimated using targeted surveys, whereas widespread and abundant species can be accurately and precisely estimated from randomised surveys using informative model-based analyses. Data are supplied as an .RData file ... Other/Unknown Material Antarc* Antarctic Antarctic prion Macquarie Island Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description Maximising survey efficiency can help reduce the trade-off between spending limited conservation resources on identifying population changes and responding to those changes through management. Burrow-nesting seabirds are particularly challenging to survey because nests cannot be counted directly. We evaluated a stratified random survey design for generating unbiased population estimates simultaneously for four petrel species nesting on Macquarie Island, Australia, where the survey cue, burrow entrances, is similar for all species. We also compared the use of design-based and model-based analyses for minimising uncertainty in estimates. We recorded 2,845 Antarctic Prion burrows, 306 White-headed Petrel burrows and two Blue Petrel burrows while distance-sampling along 154 km of transects. For Blue Petrels and Grey Petrels, we completed nocturnal searches along a further 71 km and searched 249 km of tracks during follow-up ground searches. We failed to generate unbiased population estimates for two rare and localised species, Blue and Grey Petrels, from our stratified random survey. Only for the most widespread and abundant species, Antarctic Prion, did the estimate have reasonable power to detect a rapid population change. Model-based analyses of the stratified random survey data did not improve upon traditional design-based analyses in terms of uncertainty in population estimates, but they did provide useful spatial representation of current populations. Models that used the targeted survey data did not reflect current population sizes and distributions of the two rare and localised species. We found that when species ecologies, distributions and abundances vary, a multi-method approach to surveys is needed. Species with low abundance that occur patchily across large islands are likely to be best estimated using targeted surveys, whereas widespread and abundant species can be accurately and precisely estimated from randomised surveys using informative model-based analyses. Data are supplied as an .RData file ...
format Other/Unknown Material
author Bird, Jeremy
spellingShingle Bird, Jeremy
Generating unbiased estimates of burrowing seabird populations
author_facet Bird, Jeremy
author_sort Bird, Jeremy
title Generating unbiased estimates of burrowing seabird populations
title_short Generating unbiased estimates of burrowing seabird populations
title_full Generating unbiased estimates of burrowing seabird populations
title_fullStr Generating unbiased estimates of burrowing seabird populations
title_full_unstemmed Generating unbiased estimates of burrowing seabird populations
title_sort generating unbiased estimates of burrowing seabird populations
publisher Zenodo
publishDate 2022
url https://doi.org/10.5061/dryad.sn02v6x2d
genre Antarc*
Antarctic
Antarctic prion
Macquarie Island
genre_facet Antarc*
Antarctic
Antarctic prion
Macquarie Island
op_relation https://zenodo.org/communities/dryad
https://doi.org/10.5061/dryad.sn02v6x2d
oai:zenodo.org:7306157
op_rights info:eu-repo/semantics/openAccess
Creative Commons Zero v1.0 Universal
https://creativecommons.org/publicdomain/zero/1.0/legalcode
op_doi https://doi.org/10.5061/dryad.sn02v6x2d
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