Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking
Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid
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Yn: Frontiers in Ecology and Evolution, Cyfrol 7, Rhif 333, 24.09.2019.
Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid
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T1 - Matches and Mismatches Between Seabird Distributions Estimated From At-Sea Surveys and Concurrent Individual-Level Tracking
AU - Carroll, Matthew
AU - Wakefield, Ewan
AU - Scragg, Emily
AU - Owen, Ellie
AU - Pinder, Simon
AU - Bolton, Mark
AU - Waggitt, James
AU - Evans, Peter
PY - 2019/9/24
Y1 - 2019/9/24
N2 - Mapping the distribution of seabirds at sea is fundamental to understanding theirecology and making informed decisions on their conservation. Until recently, estimates ofat-sea distributions were generally derived from boat-based visual surveys. Increasinglyhowever, seabird tracking is seen as an alternative but each has potential biases. Tocompare distributions from the two methods, we carried out simultaneous boat-basedsurveys 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 onthe Shiant Islands, one of the main breeding centers of razorbills, and guillemots in theUK. 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 assmooth functions of latitude and longitude, mapping estimated densities. We then usedkernel density estimation to map the utilization distributions of the GPS tracked birds.These two distribution estimates corresponded well for razorbills but were lower forguillemots. Both methods revealed areas of high use around the focal colony, but overthe wider region, differences emerged that were likely attributable to the influencesof neighboring colonies and the presence of non-breeding birds. The magnitude ofdifferences 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 datawere obtained equally during day and night. For guillemots, there was little effect ofcalculating separate night and day distributions from GPS records, but for razorbillsthe daytime distribution matched boat-based distributions better. When GPS-baseddistribution estimates were restricted to the exact times when boat surveys were carriedout, similarity with boat survey distributions decreased, probably due to reduced samplesizes. Our results support the use of tracking data for defining seabird distributionsaround tracked birds’ home colonies, but only when nearby colonies are neither largenor numerous. Distributions of animals around isolated colonies can be determined usingGPS loggers but that of animals around aggregated colonies is best suited to at-seasurveys or multi-colony tracking.
AB - Mapping the distribution of seabirds at sea is fundamental to understanding theirecology and making informed decisions on their conservation. Until recently, estimates ofat-sea distributions were generally derived from boat-based visual surveys. Increasinglyhowever, seabird tracking is seen as an alternative but each has potential biases. Tocompare distributions from the two methods, we carried out simultaneous boat-basedsurveys 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 onthe Shiant Islands, one of the main breeding centers of razorbills, and guillemots in theUK. 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 assmooth functions of latitude and longitude, mapping estimated densities. We then usedkernel density estimation to map the utilization distributions of the GPS tracked birds.These two distribution estimates corresponded well for razorbills but were lower forguillemots. Both methods revealed areas of high use around the focal colony, but overthe wider region, differences emerged that were likely attributable to the influencesof neighboring colonies and the presence of non-breeding birds. The magnitude ofdifferences 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 datawere obtained equally during day and night. For guillemots, there was little effect ofcalculating separate night and day distributions from GPS records, but for razorbillsthe daytime distribution matched boat-based distributions better. When GPS-baseddistribution estimates were restricted to the exact times when boat surveys were carriedout, similarity with boat survey distributions decreased, probably due to reduced samplesizes. Our results support the use of tracking data for defining seabird distributionsaround tracked birds’ home colonies, but only when nearby colonies are neither largenor numerous. Distributions of animals around isolated colonies can be determined usingGPS loggers but that of animals around aggregated colonies is best suited to at-seasurveys or multi-colony tracking.
M3 - Article
VL - 7
JO - Frontiers in Ecology and Evolution
JF - Frontiers in Ecology and Evolution
SN - 2296-701X
IS - 333
ER -