Accelerometers, Ground Truthing, and Supervised Learning
Accelerometers are sensitive to movement and the lack of it. They are not sentient and must recognise animal behaviour based on a human observer’s cognition. Therefore, remote recognition of behaviour using accelerometers requires ground truth data which is based on human observation or knowledge. The need for validated behavioural information and for automating the analysis of the vast amounts of data collected today, have resulted in many studies opting for supervised machine learning approaches.
In such approaches, the process of ground truthing involves time-synchronising acceleration signals with simultaneously recorded video, having an animal behaviour expert create an ethogram, and then annotate the video according to this ethogram. This links the recorded acceleration signal to the stream of observed animal behaviours that produced it. After this, acceleration signals are chopped up into finite sections of pre-set size (e.g. two seconds), called windows. From acceleration data within windows, quantities called ‘features’ are engineered with the aim of summarising characteristics of the acceleration signal. Typically, ~15-20 features are computed. Good features will have similar values for the same behaviour, and different values for different behaviours.
It’s more important than ever for us to have accurate information to help marine conservation efforts. Jordan Goetze and his colleagues have provided the first comprehensive guide for researchers using diver operated stereo-video methods (or stereo-DOVs) to survey fish assemblages and their associated habitat.
But what is Stereo DOV? What makes it a better method than the traditional UVC (Underwater Visual Census) method? And when should you use it? Find out in this video:
Quantifying animal movement is central to research spanning a variety of topics. It’s an important area of study for behavioural ecologists, evolutionary biologists, ecotoxicologists and many more. There are a lot of ways to track animals, but they’re often difficult, especially for people who don’t have a strong background in programming.
Vivek Hari Sridhar, Dominique G. Roche and Simon Gingins have developed a new, simple software to help with this though: Tracktor. This package provides researchers with a free, efficient, markerless video-based tracking solution to analyse animal movement of single individuals and groups.
Vivek and Simon explain the features and strengths of Tracktor in this new video:
Many animals rely on movement to find prey and avoid predators. Movement is also an essential component of the territorial displays of lizards, comprising tail, limb, head and whole-body movements.
For the first time, digital animation has been used as a research tool to examine how the effectiveness of a lizard’s territorial display varies across ecological environments and conditions. The new research was published today in the journal Methods in Ecology and Evolution.
“I am broadly interested in developing and applying statistical tools to infer behavioural and population processes from empirical data. My work tends to focus on marine and polar mammals, but the methods I develop are often applicable to a wide range of species and ecosystems. My recent work has centred on modelling animal behaviour using movement data and I generally analyse data with spatial and/or temporal structure.”
At the last ISEC, in Montpellier in 2014, an informal survey suggested that Methods in Ecology and Evolution was the most cited journal in talks. This reflects the importance of statistical methods in ecology and it is one reason for the success of the journal. For this year’s International Statistcal Ecology Conference in Seattle we have produced a virtual issue that presents some of our best recent papers which cross the divide between statistics and ecology. They range over most of the topics covered at ISEC, from statistical theory to abundance estimation and distance sampling.
We hope that Methods in Ecology and Evolution will be equally well represented in talks in Seattle, and also – just as in Montpellier – some of the work presented will find its way into the pages of the journal in the future.
This month’s issue contains two Applications articles and two Open Access articles, all of which are freely available.
– piecewiseSEM: A practical implementation of confirmatory path analysis for the R programming language. This package extends the method to all current (generalized) linear, (phylogenetic) least-square, and mixed effects models, relying on familiar R syntax. The article also includes two worked examples.
–RPANDA: An R package that implements model-free and model-based phylogenetic comparative methods for macroevolutionary analyses. It can be used to:
Characterize phylogenetic trees by plotting their spectral density profiles
Compare trees and cluster them according to their similarities
Identify and plot distinct branching patterns within trees
Compare the fit of alternative diversification models to phylogenetic trees
Estimate rates of speciation and extinction
Estimate and plot how these rates have varied with time and environmental variables
Animal movement is a driving factor underlying many ecological processes including disease transmission, extinction risk and range shifts. Understanding why, when and how animals traverse a landscape can provide much needed information for landscape-level conservation and management practices.
However, location-based data sets are often time consuming and costly to collect. For many species, especially those that are rare and elusive, pre-existing data sets may be the only viable data source to inform management decisions. Continue reading →
The February issue of Methods is now online! As you may have seen already, it includes the BES cross-journal Special Feature: “Demography Beyond the Population“. There are also eight other wonderful articles to read.