ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2021
A brief introduction to the analysis of time-series data from biologging studies.
Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Global Spatiotemporal Dynamics of African Swine Fever: An Integrated Multi-Scale Spatial and Time-Series Analysis.Viruses · 2026Article
- Body Condition and Temperature-Humidity Index Are Associated With Cortisol Levels as Indicators of Physiological Stress in Sumatran Elephants.Veterinary medicine international · 2026Article
- A behavioural approach to key area identification in seabirds for threat mitigation and spatial management.Animal biotelemetry · 2025Article
- Time synchronisation for millisecond-precision on bio-loggers.Movement ecology · 2024Article
- Physiological evidence of stress reduction during a summer Antarctic expedition with a significant influence of previous experience and vigor.Scientific reports · 2024Article
- Article
- Hemoglobin signal network mapping reveals novel indicators for precision medicine.Scientific reports · 2023Article
- Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model.Heliyon · 2023Article
- How Reproducibility Will Accelerate Discovery Through Collaboration in Physio-Logging.Frontiers in physiology · 2022Article
- Heart rate as a measure of emotional arousal in evolutionary biology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Review
- Introduction to the theme issue: Measuring physiology in free-living animals.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in tagging and biologging technology have yielded unprecedented insights into wild animal physiology. However, time-series data from such wild tracking studies present numerous analytical challenges owing to their unique nature, often exhibiting strong autocorrelation within and among samples, low samples sizes and complicated random effect structures. Gleaning robust quantitative estimates from these physiological data, and, therefore, accurate insights into the life histories of the animals they pertain to, requires careful and thoughtful application of existing statistical tools. Using a combination of both simulated and real datasets, I highlight the key pitfalls associated with analysing physiological data from wild monitoring studies, and investigate issues of optimal study design, statistical power, and model precision and accuracy. I also recommend best practice approaches for dealing with their inherent limitations. This work will provide a concise, accessible roadmap for researchers looking to maximize the yield of information from complex and hard-won biologging datasets. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.