Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking
Mapping the distribution of seabirds at sea is fundamental to understanding their ecology and making informed decisions on their conservation. Until recently, estimates of at-sea distributions were generally derived from boat-based visual surveys. Increasingly however, seabird tracking is seen as an...
Published in: | Frontiers in Ecology and Evolution |
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ftdoajarticles:oai:doaj.org/article:76e53d56685149f09b0cf0ae2267617c 2023-05-15T18:05:52+02:00 Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking Matthew J. Carroll Ewan D. Wakefield Emily S. Scragg Ellie Owen Simon Pinder Mark Bolton James J. Waggitt Peter G. H. Evans 2019-09-01T00:00:00Z https://doi.org/10.3389/fevo.2019.00333 https://doaj.org/article/76e53d56685149f09b0cf0ae2267617c EN eng Frontiers Media S.A. https://www.frontiersin.org/article/10.3389/fevo.2019.00333/full https://doaj.org/toc/2296-701X 2296-701X doi:10.3389/fevo.2019.00333 https://doaj.org/article/76e53d56685149f09b0cf0ae2267617c Frontiers in Ecology and Evolution, Vol 7 (2019) distribution mapping guillemot razorbill GPS tags tracking at-sea surveys Evolution QH359-425 Ecology QH540-549.5 article 2019 ftdoajarticles https://doi.org/10.3389/fevo.2019.00333 2022-12-31T05:50:18Z Mapping the distribution of seabirds at sea is fundamental to understanding their ecology and making informed decisions on their conservation. Until recently, estimates of at-sea distributions were generally derived from boat-based visual surveys. Increasingly however, seabird tracking is seen as an alternative but each has potential biases. To compare distributions from the two methods, we carried out simultaneous boat-based surveys and GPS tracking in the Minch, western Scotland, in June 2015. Over 8 days, boat transect surveys covered 950 km, within a study area of ~6,700 km2 centered on the Shiant Islands, one of the main breeding centers of razorbills, and guillemots in the UK. Simultaneously, we GPS-tracked chick-rearing guillemots (n = 17) and razorbills (n = 31) from the Shiants. We modeled counts per unit area from boat surveys as smooth functions of latitude and longitude, mapping estimated densities. We then used kernel density estimation to map the utilization distributions of the GPS tracked birds. These two distribution estimates corresponded well for razorbills but were lower for guillemots. Both methods revealed areas of high use around the focal colony, but over the wider region, differences emerged that were likely attributable to the influences of neighboring colonies and the presence of non-breeding birds. The magnitude of differences was linked to the relative sizes of these populations, being larger in guillemots. Whilst boat surveys were necessarily restricted to the hours of daylight, GPS data were obtained equally during day and night. For guillemots, there was little effect of calculating separate night and day distributions from GPS records, but for razorbills the daytime distribution matched boat-based distributions better. When GPS-based distribution estimates were restricted to the exact times when boat surveys were carried out, similarity with boat survey distributions decreased, probably due to reduced sample sizes. Our results support the use of tracking data for defining seabird ... Article in Journal/Newspaper Razorbill Directory of Open Access Journals: DOAJ Articles Frontiers in Ecology and Evolution 7 |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
distribution mapping guillemot razorbill GPS tags tracking at-sea surveys Evolution QH359-425 Ecology QH540-549.5 |
spellingShingle |
distribution mapping guillemot razorbill GPS tags tracking at-sea surveys Evolution QH359-425 Ecology QH540-549.5 Matthew J. Carroll Ewan D. Wakefield Emily S. Scragg Ellie Owen Simon Pinder Mark Bolton James J. Waggitt Peter G. H. Evans Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking |
topic_facet |
distribution mapping guillemot razorbill GPS tags tracking at-sea surveys Evolution QH359-425 Ecology QH540-549.5 |
description |
Mapping the distribution of seabirds at sea is fundamental to understanding their ecology and making informed decisions on their conservation. Until recently, estimates of at-sea distributions were generally derived from boat-based visual surveys. Increasingly however, seabird tracking is seen as an alternative but each has potential biases. To compare distributions from the two methods, we carried out simultaneous boat-based surveys and GPS tracking in the Minch, western Scotland, in June 2015. Over 8 days, boat transect surveys covered 950 km, within a study area of ~6,700 km2 centered on the Shiant Islands, one of the main breeding centers of razorbills, and guillemots in the UK. Simultaneously, we GPS-tracked chick-rearing guillemots (n = 17) and razorbills (n = 31) from the Shiants. We modeled counts per unit area from boat surveys as smooth functions of latitude and longitude, mapping estimated densities. We then used kernel density estimation to map the utilization distributions of the GPS tracked birds. These two distribution estimates corresponded well for razorbills but were lower for guillemots. Both methods revealed areas of high use around the focal colony, but over the wider region, differences emerged that were likely attributable to the influences of neighboring colonies and the presence of non-breeding birds. The magnitude of differences was linked to the relative sizes of these populations, being larger in guillemots. Whilst boat surveys were necessarily restricted to the hours of daylight, GPS data were obtained equally during day and night. For guillemots, there was little effect of calculating separate night and day distributions from GPS records, but for razorbills the daytime distribution matched boat-based distributions better. When GPS-based distribution estimates were restricted to the exact times when boat surveys were carried out, similarity with boat survey distributions decreased, probably due to reduced sample sizes. Our results support the use of tracking data for defining seabird ... |
format |
Article in Journal/Newspaper |
author |
Matthew J. Carroll Ewan D. Wakefield Emily S. Scragg Ellie Owen Simon Pinder Mark Bolton James J. Waggitt Peter G. H. Evans |
author_facet |
Matthew J. Carroll Ewan D. Wakefield Emily S. Scragg Ellie Owen Simon Pinder Mark Bolton James J. Waggitt Peter G. H. Evans |
author_sort |
Matthew J. Carroll |
title |
Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking |
title_short |
Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking |
title_full |
Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking |
title_fullStr |
Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking |
title_full_unstemmed |
Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking |
title_sort |
matches and mismatches between seabird distributions estimated from at-sea surveys and concurrent individual-level tracking |
publisher |
Frontiers Media S.A. |
publishDate |
2019 |
url |
https://doi.org/10.3389/fevo.2019.00333 https://doaj.org/article/76e53d56685149f09b0cf0ae2267617c |
genre |
Razorbill |
genre_facet |
Razorbill |
op_source |
Frontiers in Ecology and Evolution, Vol 7 (2019) |
op_relation |
https://www.frontiersin.org/article/10.3389/fevo.2019.00333/full https://doaj.org/toc/2296-701X 2296-701X doi:10.3389/fevo.2019.00333 https://doaj.org/article/76e53d56685149f09b0cf0ae2267617c |
op_doi |
https://doi.org/10.3389/fevo.2019.00333 |
container_title |
Frontiers in Ecology and Evolution |
container_volume |
7 |
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1766177404002238464 |