Variation in incubation length and hatching asynchrony in Eastern Kingbirds: Weather eclipses female effects

Gillette, Samantha; Klehr, Amanda L; Murphy, Michael T.

doi:10.1093/ornithology/ukab031

Cited by 7 publications

(2 citation statements)

References 74 publications

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“…The incubation period for each known breeder was defined as the 24 consecutive days with the lowest total of average daily ODBA, while the individual was in Greenland as this is the likely minimum incubation period required to hatch a clutch [23]. A three day buffer on either side of the 24 day window was applied to represent uncertainty in the exact length of incubation due to individual variation in the duration required for a clutch to hatch [35]. All remaining days, while an individual was in Greenland, were designated as non-incubating (Fig.…”

Section: Incubation Classification Scheme (Fig 1)mentioning

confidence: 99%

Wearable reproductive trackers: quantifying a key life history event remotely

et al. 2022

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Advancements in biologging technology allow terabytes of data to be collected that record the location of individuals but also their direction, speed and acceleration. These multi-stream data sets allow researchers to infer movement and behavioural patterns at high spatiotemporal resolutions and in turn quantify fine-scale changes in state along with likely ecological causes and consequences. The scope offered by such data sets is increasing and there is potential to gain unique insights into a suite of ecological and life history phenomena. We use multi-stream data from global positioning system (GPS) and accelerometer (ACC) devices to quantify breeding events remotely in an Arctic breeding goose. From a training set of known breeders we determine the movement and overall dynamic body acceleration patterns indicative of incubation and use these to classify breeding events in individuals with unknown reproductive status. Given that researchers are often constrained by the amount of biologging data they can collect due to device weights, we carry out a sensitivity analysis. Here we explore the relative merits of GPS vs ACC data and how varying the temporal resolution of the data affects the accuracy of classifying incubation for birds. Classifier accuracy deteriorates as the temporal resolution of GPS and ACC are reduced but the reduction in precision (false positive rate) is larger in comparison to recall (false negative rate). Precision fell to 94.5%, whereas recall didn’t fall below 98% over all sampling schedules tested. Our data set could have been reduced by c.95% while maintaining precision and recall > 98%. The GPS-only classifier generally outperformed the ACC-only classifier across all accuracy metrics but both performed worse than the combined GPS and ACC classifier. GPS and ACC data can be used to reconstruct breeding events remotely, allowing unbiased, 24-h monitoring of individuals. Our resampling-based sensitivity analysis of classifier accuracy has important implications with regards to both device design and sampling schedules for study systems, where device size is constrained. It will allow researchers with similar aims to optimize device battery, memory usage and lifespan to maximise the ability to correctly quantify life history events.

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Section: Incubation Classification Scheme (Fig 1)mentioning

confidence: 99%

Wearable reproductive trackers: quantifying a key life history event remotely

et al. 2022

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“…The incubation period for each known breeder was defined as the 24 consecutive days with the lowest total of average daily ODBA while the individual was in Greenland as this is the likely minimum incubation period required to hatch a clutch [23]. A three day buffer on either side of the 24 day window was applied to represent uncertainty in the exact length of incubation due to individual variation in the duration required for a clutch to hatch [34]. All remaining days, while an individual was in Greenland, were designated as non-incubating (Fig 2).…”

mentioning

confidence: 99%

Wearable reproductive trackers: quantifying a key life history

Ozsanlav-Harris

Griffin²,

Weegman

et al. 2022

Preprint

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Advancements in biologging technology allow terabytes of data to be collected that record the location of individuals but also their direction, speed and acceleration. These multi-stream data sets allow researchers to determine movement and behavioural patterns at high spatiotemporal resolutions and in turn quantify fine-scale changes in state along with likely ecological causes and consequences. The scope offered by such data sets is only increasing there is potential to gain unique insights into a suite of ecological and life history phenomena. We use multi-stream data from global positioning system (GPS) and accelerometer (ACC) tags to quantify breeding events remotely in an Arctic breeding goose. From a training set of known breeders we determine the movement and energy expenditure patterns indicative of incubation and use these to classify breeding events in individuals with unknown reproductive status. Given that researchers are often constrained by the amount of biologging data they can collect due to tag weights, we carry out a sensitivity analysis. Here we explore the relative merits of GPS vs ACC data and how varying the temporal resolution of the data affects the accuracy of classifying incubation. Classifier accuracy deteriorates as the temporal resolution of GPS and ACC are reduced but the reduction in precision (false positive rate) is larger in comparison to recall (false negative rate). Precision fell to 95.5% were as recall rarely fell below 98% over all sampling schedules tested. Our dataset could have been reduced by c.95% while maintaining precision and recall >98%. The GPS-only classifier generally outperformed the ACC-only classifier across all accuracy metrics but both performed worse than the combined GPS and ACC classifier. GPS and ACC data can be used to reconstruct breeding events remotely, allowing unbiased, 24-hour monitoring of individuals. Our resampling-based sensitivity analysis of classifier accuracy has important implications with regards to both tag design and sampling schedules for study systems where tag size is constrained. It will allow researchers with similar aims to optimize tag battery, memory usage and lifespan to maximise the ability to correctly quantify life history events.

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Investing in a nest egg: intraspecific variation in the timing of egg laying across a latitudinal gradient

Lundblad

Conway

2023

Oecologia

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Variation in incubation length and hatching asynchrony in Eastern Kingbirds: Weather eclipses female effects

Cited by 7 publications

References 74 publications

Wearable reproductive trackers: quantifying a key life history event remotely

Wearable reproductive trackers: quantifying a key life history event remotely

Wearable reproductive trackers: quantifying a key life history

Investing in a nest egg: intraspecific variation in the timing of egg laying across a latitudinal gradient

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