Ecological and social pressures interfere with homeostatic sleep regulation in the wild

Loftus, Judith; Harel, Roi; Núñez, Chase L.; Crofoot, Margaret C.

doi:10.1101/2021.09.26.461870

Cited by 3 publications

(1 citation statement)

References 96 publications

(130 reference statements)

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“…It can be useful to vary GPS sampling across time to focus data collection on certain time windows over others. For example, diurnal species are largely inactive at night (Isbell et al, 2017; but see Loftus et al, 2021), meaning that GPS devices are often switched off at night to conserve battery. It can also be worthwhile to programme devices to increase sampling frequency during periods when animals are more active (e.g.…”

Section: Some Strategic Considerationsmentioning

confidence: 99%

A guide to sampling design for GPS‐based studies of animal societies

Klarevas‐Irby

Papageorgiou

et al. 2022

Methods Ecol Evol

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GPS-based tracking is widely used for studying wild social animals. Much like traditional observational methods, using GPS devices requires making a number of decisions about sampling that can affect the robustness of a study's conclusions. For example, sampling fewer individuals per group across more distinct social groups may not be sufficient to infer group-or subgroup-level behaviours, while sampling more individuals per group across fewer groups limits the ability to draw conclusions about populations. Here, we provide quantitative recommendations when designing GPS-based tracking studies of animal societies. We focus on the trade-offs between three fundamental axes of sampling effort:(1) sampling coverage-the number and allocation of GPS devices among individuals in one or more social groups; (2) sampling duration-the total amount of time over which devices collect data and (3) sampling frequency-the temporal resolution at which GPS devices record data. We first test GPS tags under field conditions to quantify how these aspects of sampling design can affect both GPS accuracy (error in absolute positional estimates) and GPS precision (error in the estimate relative position of two individuals), demonstrating that GPS error can have profound effects when inferring distances between individuals. We then use data from whole-group tracked vulturine guineafowl Acryllium vulturinum to demonstrate how the trade-off between sampling frequency and sampling duration can impact inferences of social interactions and to quantify how sampling coverage can affect common measures of social behaviour in animal groups, identifying which types of measures are more or less robust to lower coverage of individuals. Finally, we use data-informed simulations to extend insights across groups of different sizes and cohesiveness. Based on our results, we are able to offer a range of recommendations on GPS sampling strategies to address research questions across social organizational scales and social systems-from group movement to social network structure and collective decision-making. Our study provides practical advice for empiricists to navigate their decision-making processes when designing GPS-based field studies of animal social behaviours, and highlights the importance of identifying the optimal deployment decisions for drawing informative and robust conclusions.

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Section: Some Strategic Considerationsmentioning

confidence: 99%

A guide to sampling design for GPS‐based studies of animal societies

Klarevas‐Irby

Papageorgiou

et al. 2022

Methods Ecol Evol

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Using a Homeogram to Detect Sleep in Free-living Animals

Gaidica

Studd

Wishart

et al. 2021

Preprint

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Sleep is appreciated as a behavior critical to homeostasis, performance, and fitness. Yet, most of what we know about sleep comes from humans or controlled laboratory experiments. Assessing sleep in wild animals is challenging, as it is often hidden from view, and electrophysiological recordings that define sleep states are difficult to obtain. Accelerometers have offered great insight regarding gross movement, although ambiguous quiescent states like sleep have been largely ignored, limiting our understanding of this ubiquitous behavior. We developed a broadly applicable sleep detection method called a homeogram that can be applied to accelerometer data collected from wild animals. We applied our methodology to detect sleep in free-ranging North American red squirrels (Tamiasciurus hudsonicus) in a region that experiences drastic seasonal shifts in light, temperature, and behavioral demands. Our method characterized sleep in a manner consistent with limited existing studies and expanded those observations to provide evidence that red squirrels apply unique sleep strategies to cope with changing environments. Applying our analytical strategy to accelerometer data from other species may open new possibilities to investigate sleep patterns for researchers studying wild animals.

show abstract

A guide to sampling design for GPS-based studies of animal societies

Klarevas‐Irby

Papageorgiou

et al. 2022

Preprint

View full text Add to dashboard Cite

GPS-based tracking is a widely used automated data collection method for studying wild animals. Much like traditional observational methods, using GPS devices to study social animals requires making a number of decisions about sampling that can affect the robustness of a study's conclusions. For example, sampling fewer individuals per group across many distinct social groups may not be informative enough for inferring behavioural patterns at a finer social organizational scale, while sampling more individuals per group across fewer groups limits the ability to draw conclusions about populations. Here, we integrate previous insights from animal social network analysis with simulated and empirical data to provide quantitative recommendations when designing GPS-based tracking studies of animal societies. We outline the trade-offs faced by researchers, and how these trade-offs should vary across social organizational scales and social systems in relation to questions of interest, such as those defined within versus among groups, and spanning from cohesive, stable groups through to more open societies. We discuss three fundamental axes of sampling effort requiring consideration when deploying GPS devices to study animal societies: 1) Sampling coverage—the number and allocation of GPS devices among individuals in one or more social groups; 2) Sampling duration—the total amount of time over which devices collect data; 3) Sampling frequency—the temporal resolution at which GPS devices record data. Exploring each axis, we quantify the relationship between sampling effort and sampling error, giving recommendations on GPS sampling design to address research questions across social organizational scales and social systems—from group movement to social network structure and collective decision-making. In doing so, we also highlight practical limitations on deploying GPS tracking. Our study provides practical advice for empiricists to navigate their decision-making processes when designing GPS-based field studies of animal social behaviours, and highlights the importance of identifying the optimal deployment decisions for drawing informative and robust conclusions.

show abstract

Ecological and social pressures interfere with homeostatic sleep regulation in the wild

Cited by 3 publications

References 96 publications

A guide to sampling design for GPS‐based studies of animal societies

A guide to sampling design for GPS‐based studies of animal societies

Using a Homeogram to Detect Sleep in Free-living Animals

A guide to sampling design for GPS-based studies of animal societies

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