This video is based on the article ‘A novel protocol for studying bee cognition in the wild‘ by Muth et al.
This video is based on the article ‘A novel protocol for studying bee cognition in the wild‘ by Muth et al.
To understand the factors shaping vocal communication, we need reliable information about the communicating individuals on different levels. First, vocal behaviour should be recorded from undisturbed animals in meaningful settings. Then we have to separate and assign the individuals’ vocalisations. Finally, the precise timing of vocal events needs to be stored.
Microphone backpacks allow researchers to record the vocal behaviour of individual animals in naturalistic settings – even in acoustically challenging environments! In the video below, Lisa Gill, Nico Adreani and Pietro D’Amelio demonstrate the lightweight radio-transmitter microphone backpacks that have been developed and built at the Max Planck Institute for Ornithology, Seewiesen, Department of Behavioural Neurobiology. They show the attachment and setup of this system in detail, evaluate its behavioural effects, and discuss what makes it so useful for studying vocal communication, especially in small animals.
This video is based on the article ‘A minimum-impact, flexible tool to study vocal communication of small animals with precise individual-level resolution‘ by Gill et al.
“Movement is the glue that ties ecological processes together”
from Francesca Cagnacci et al. 2010
Movement ecology is a cross-disciplinary field. Its main aim is to quantitatively describe and understand how movement relates to individual and population-level processes for resource acquisition and, ultimately, survival. Today the study of movement ecology hinges on two 21st century advances:
Although datasets often involve small numbers of individuals, each individual can have thousands – sometimes even millions – of data points associated with it. Study species have tended to be large birds and mammals, due to the ease of tag attachment. However, the trend for miniaturisation of tags and the development of remote detection technologies (such as radar, e.g. Capaldi et al., 2000), have allowed researchers to track and study ever smaller animals. Continue reading
Around the world there are concerns over the impacts of land use change and the developments (such as wind farms). These concerns have led to the implementation of tracking studies to better understand movement patterns of animals. Such studies have provided a wealth of high-resolution data and opportunities to explore sophisticated statistical methods for analysis of animal behaviour.
We use accelerometer data from aerial (Verreaux’s eagle in South Africa) and marine (blacktip reef shark in Hawai’i) systems to demonstrate the use of hidden Markov models (HMMs) in providing quantitative measures of behaviour. HMMs work really well for analysing animal accelerometer data because they account for serial autocorrelation in data. They allow for inferences to be made about relative activity and behaviour when animals cannot be directly observed too, which is very important.
In addition to this, HMMs provide data-driven estimates of the underlying distributions of the acceleration metrics – and the probability of switching between states – possibly as a function of covariates. The framework that we provide in ‘Analysis of animal accelerometer data using hidden Markov models‘ can be applied to a wide range of activity data. It opens up exciting opportunities for understanding drivers of individual animal behaviour.
To find out more, read our Methods in Ecology and Evolution article ‘Analysis of animal accelerometer data using hidden Markov models’.
Issue 8.2 is now online!
This issue contains four(!) Applications articles and two Open Access articles. These six papers are freely available to everyone – no subscription required.
– Earth Mover’s Distance: The Earth Mover’s Distance (or EMD) is a method commonly used in image retrieval applications. The authors of this paper propose its use to calculate similarity in space use in the framework of movement ecology. This will be helpful for many questions regarding behavioural ecology, wildlife management and conservation.
– warbleR: The R package warbleR is a new package for the analysis of animal acoustic signal structure. It offers functions for downloading avian vocalisations from the open-access online repository Xeno-Canto, displaying the geographic extent of the recordings, manipulating sound files, detecting acoustic signals or importing detected signals from other software, and much more.
– meteR: The open-source R package, meteR directly calculates all of Maximum entropy theory of ecology’s (METE’s) predictions from a variety of data formats; automatically handles approximations and other technical details; and provides high-level plotting and model comparison functions to explore and interrogate models.
– Noise Egg: The Noise Egg is a device that can produce a low-frequency sound, which can be used as an experimental source of noise both in aquaria and in the field. It was developed to study the effects of noise on communication and behaviour in small aquatic animals; however, it could be used for other purposes, such as testing the propagation of certain frequencies in shallow-water habitats.
Today we are welcoming three new Associate Editors to Methods in Ecology and Evolution: Nick Golding (University of Melbourne, Australia), Rachel McCrea (University of Kent, UK) and Francesca Parrini (University of the Witwatersrand, South Africa). They have all joined on a three-year term and you can find out more about them below.
“I develop statistical models and software for mapping the distributions of species and diseases. I’m particularly interested in tools that make it easy for researchers to add more mechanistic structure into their correlative models (and vice versa) so that they can use all available information when making predictions. I also develop software and other tools to bring research communities together and help them advance ecology by enabling and incentivising reproducible and extensible research.”
Nick has recently had an article published in Methods in Ecology and Evolution (currently in Early View). In ‘Fast and flexible Bayesian species distribution modelling using Gaussian processes‘ Nick and his co-author (Bethan Purse) introduce Gaussian process (GP) models and their application to species distribution modelling (SDM), illustrate how ecological knowledge can be incorporated into GP SDMs via Bayesian priors and formulate a simple GP SDM that can be fitted efficiently. The article is Open Access, so it’s freely available to everyone.
“I am a NERC research fellow and lecturer in statistics at the University of Kent. My particular areas of interest include capture-recapture modelling, multistate models, modelling population dynamics and methods of model assessment. My research is motivated by interesting discussions with ecologists and I strive to find innovative, but practical statistical solutions to ecological questions.”
Rachel is one of the authors of Analysis of Capture-Recapture Data (along with Byron Morgan). The book covers the many modern developments of capture-recapture (and related) methods and will be of interest to researchers and graduate students in statistics, ecology and demography. It contains 130 exercises designed to complement and extend the text and help readers to assimilate the material.
“My broad research interests lie in the ecology and behaviour of mammalian herbivores, their interaction with biotic and abiotic factors and the integration of factors governing decisions at the small foraging scale and factors governing decisions at the landscape level. As such, my research lies at the interface of remote sensing, behavioural ecology and conservation. Recently I have become interested in the application of graph theory and network analysis to ecological settings, in particular to study the spatio-temporal structure of animal movement patterns.”
Last year Francesca had her article (co-authored with Maria Miranda) ‘Congruence between species phylogenetic and trophic distinctiveness‘ published in Biodiversity and Conservation. In this paper the authors investigate the relationship between species’ phylogenetic history and patterns of resource use. They show that there is congruence between species phylogenetics and interaction distinctiveness and propose that this relationship could provide a possible novel approach to the conservation of ecosystem diversity.
We are thrilled to welcome Nick, Rachel and Francesca to the Associate Editor Board and we look forward to working with them over the coming years.
Issue 6.6 is now online!
This month’s issue contains one Applications article and one Open Access article.
– VirtualCom: A simple and readily usable tool that will help to resolve theoretical and methodological issues in community ecology. VirtualCom simulates the evolution of the pool of regionally occurring species, the process-based assembly of native communities and the invasion of novel species into native communities. One of the authors of this Application is the 2014 Robert May Young Investigator Prize Winner, Laure Gallien.
Calibrating animal-borne proximity loggers, this month’s only Open Access article, comes from Christian Rutz et al. The authors calibrated a recently developed digital proximity-logging system (‘Encounternet’) for deployment on a wild population of New Caledonian crows. They show that, using signal-strength information only, it is possible to assign crow encounters reliably to predefined distance classes, enabling powerful analyses of social dynamics. Their study demonstrates that well-calibrated proximity-logging systems can be used to chart social associations of free-ranging animals over a range of biologically meaningful distances.
Issue 6.5 is now online!
We have two freely available articles this month: one Application and one Open Access Article.
– rSPACE: An open-source R package for implementing a spatially based power analysis for designing monitoring programs. This method incorporates information on species biology and habitat to parameterize a spatially explicit population simulation.
Tim Lucas et al. provide this month’s Open Access article: A generalised random encounter model for estimating animal density with remote sensor data. The authors have developed a Generalised Random Encounter Model (gREM) to estimate absolute animal density from count data from both camera traps and acoustic detectors. They show that gREM produces accurate estimates of absolute animal density for all combinations of sensor detection widths and animal signal widths. This model is applicable for count data obtained in both marine and terrestrial environments, visually or acoustically. It could be used for big cats, sharks, birds, echolocating bats, cetaceans and much more. Continue reading