The role of individual variability on the predictive performance of machine learning applied to large bio-logging datasets

M Chimienti, A Kato, O Hicks, F Angelier, M Beaulieu… - Scientific Reports, 2022‏ - nature.com
Animal-borne tagging (bio-logging) generates large and complex datasets. In particular,
accelerometer tags, which provide information on behaviour and energy expenditure of wild …

Quantifying allo-grooming in wild chacma baboons (Papio ursinus) using tri-axial acceleration data and machine learning

C Christensen, AM Bracken… - Royal Society …, 2023‏ - royalsocietypublishing.org
Quantification of activity budgets is pivotal for understanding how animals respond to
changes in their environment. Social grooming is a key activity that underpins various social …

Predicting moose behaviors from tri-axial accelerometer data using a supervised classification algorithm

TM Kirchner, O Devineau, M Chimienti… - Animal …, 2023‏ - Springer
Background Monitoring the behavior of wild animals in situ can improve our understanding
of how their behavior is related to their habitat and affected by disturbances and changes in …

Identifying animal behaviours from accelerometers: Improving predictive accuracy of machine learning by refining the variables selected, data frequency, and sample …

CE Dunford, NJ Marks, RP Wilson… - Ecology and …, 2024‏ - Wiley Online Library
Observing animals in the wild often poses extreme challenges, but animal‐borne
accelerometers are increasingly revealing unobservable behaviours. Automated machine …

Behavioural inference from signal processing using animal-borne multi-sensor loggers: a novel solution to extend the knowledge of sea turtle ecology

L Jeantet, V Planas-Bielsa… - Royal Society …, 2020‏ - royalsocietypublishing.org
The identification of sea turtle behaviours is a prerequisite to predicting the activities and
time-budget of these animals in their natural habitat over the long term. However, this is …

Limitations of using surrogates for behaviour classification of accelerometer data: refining methods using random forest models in Caprids

ER Dickinson, JP Twining, R Wilson, PA Stephens… - Movement Ecology, 2021‏ - Springer
Background Animal-attached devices can be used on cryptic species to measure their
movement and behaviour, enabling unprecedented insights into fundamental aspects of …

Quantifying behavior and life‐history events of an Arctic ungulate from year‐long continuous accelerometer data

M Chimienti, FM van Beest, LT Beumer… - …, 2021‏ - Wiley Online Library
Bio‐logging technology is now the golden standard for assessing how individual animals
change their movement and behavior over time and space. Three‐dimensional …

Energetics as common currency for integrating high resolution activity patterns into dynamic energy budget-individual based models

M Chimienti, JP Desforges, LT Beumer… - Ecological …, 2020‏ - Elsevier
Dynamic energy budget individual-based models (DEB-IBMs) provide a well-tested
framework for modelling the acquisition and use of energy throughout the life cycle of …

Behaviour Classification on Giraffes (Giraffa camelopardalis) Using Machine Learning Algorithms on Triaxial Acceleration Data of Two Commonly Used GPS Devices …

S Brandes, F Sicks, A Berger - Sensors, 2021‏ - mdpi.com
Averting today's loss of biodiversity and ecosystem services can be achieved through
conservation efforts, especially of keystone species. Giraffes (Giraffa camelopardalis) play …

Integrative framework for long-term activity monitoring of small and secretive animals: validation with a cryptic pitviper

DL DeSantis, V Mata-Silva, JD Johnson… - Frontiers in Ecology …, 2020‏ - frontiersin.org
The use of miniature accelerometer (ACT) data-loggers for remote and continuous recording
of animal movement behavior is becoming increasingly common. Until recently, size …