Issue 8.2

Issue 8.2 is now online!

The February issue of Methods 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.

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Testing the Effects of Underwater Noise on Aquatic Animals

Post provided by Karen de Jong

Most people assume that research equipment is expensive and complicated. But, it doesn’t need to be and the noise egg is a perfect example of this. It consists of a watertight container (as used by scuba divers) and the buzzer from a cellphone and does exactly what it says: it produces low frequency noise. This allows researchers to test the effect of noise on underwater life. It is a small, simple and cheap device that anyone can build.

Why Test Effects of Noise?

A painted goby in front of his nest ©K. de Jong

A painted goby in front of his nest ©K. de Jong

Underwater noise is rapidly increasing due to, for example, boat traffic and offshore wind farms. This can lead to stress for animals and difficulties in communication. Just as people have a hard time communicating in a noisy pub, animals may struggle to get their messages across when background noise is high. A nice description of how animals use sound and how noise may affect this can be found at

While there is some knowledge on the effect of noise on large aquatic animals, we still know very little about how fish and other small aquatic animals are affected. Such knowledge is vital for management of protected areas. It’s also important to know whether wind farms and boat traffic can affect reproduction in populations of underwater resources such as fish and mussels. The answers to these questions are likely to be species specific, so we’ll need data on a large number of species in different habitats. Continue reading

Animal Density and Acoustic Detection: An Interview with Ben Stevenson

David Warton (University of New South Wales) interviews  interviews  Ben Stevenson (University of St Andrews) about his 2015 Methods in Ecology and Evolution paper ‘A general framework for animal density estimation from acoustic detections across a fixed microphone array’. They also discuss what Ben is currently up to, including an interesting new method for dealing with uncertain identification in capture-recapture, published in Statistical Science as ‘Trace-Contrast Models for Capture–Recapture Without Capture Histories’.

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Issue 7.9

Issue 7.9 is now online!

The September issue of Methods is now online!

This month’s issue contains two Applications articles and three Open Access articles, all of which are freely available.

– Arborist Throw-Line Launcher: A cost-effective and simple alternative for collecting leaves and seeds from tall trees. The authors have also provided some tutorial videos on YouTube.

– ctmm: An R package which implements all of the continuous-time stochastic processes currently in use in the ecological literature and couples them with powerful statistical methods for autocorrelated data adapted from geostatistics and signal processing.

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Biggest Library of Bat Sounds Compiled

Below is a press release about the Methods paper ‘Acoustic identification of Mexican bats based on taxonomic and ecological constraints on call design‘ taken from the University College London.

The Funnel-eared bat (Natalus stramineus)

The Funnel-eared bat (Natalus stramineus)

The biggest library of bat sounds has been compiled to detect bats in Mexico – a country which harbours many of the Earth’s species and has one of the highest rates of species extinction and habitat loss.

An international team led by scientists from UCL, University of Cambridge and the Zoological Society of London, developed the reference call library and a new way of classifying calls to accurately and quickly identify and differentiate between bat species.

It is the first time automatic classification for bat calls has been attempted for a large variety of species, most of them previously noted as hard to identify acoustically. Continue reading

The Overlooked Commotion of Particle Motion in the Ocean

Below is a press release about the Open Access Methods paper ‘Particle motion: the missing link in underwater acoustic ecology‘ taken from the University of Bristol, the University of Exeter and the Centre for Environment, Fisheries  & Aquaculture Science (CEFAS).

Fish and invertebrates predominantly or exclusively detect particle motion.

Fish and invertebrates predominantly or exclusively detect particle motion.

A growing number of studies on the behaviour of aquatic animals are revealing the importance of underwater sound, yet these studies typically overlook the component of sound sensed by most species: particle motion. In response, researchers from the Universities of Bristol, Exeter and Leiden and CEFAS have developed a user-friendly introduction to particle motion, explaining how and when it ought to be measured, and provide open-access analytical tools to maximise its uptake. Continue reading

Progress and Future Directions for Passive Acoustic Monitoring: Listening Out for New Conservation Opportunities

Post provided by Ammie Kalan (Post-doctoral researcher at the Max Planck Institute for Evolutionary Anthropology, Department of Primatology)

A Primate Call in a Forest is like a ‘Needle in a Haystack’

An ARU powered by solar energy recording in the Taï national park, Côte d’Ivoire. ©Ammie Kalan

A solar-powered ARU recording in the Taï national park, Côte d’Ivoire.
©Ammie Kalan

Finding a call of a particular primate species within hours and hours of audio recordings of a forest is no easy task; like finding a ‘needle in a haystack’ so to speak. Automated acoustic monitoring relies on the ability of researchers to easily locate and isolate acoustic signals produced by species of interest from all other sources of noise in the forest, i.e. the background noise. This can be much harder than it sounds. Think about whenever you have to use any kind of voice recognition system: seeking out a quiet room will greatly improve the chances you are understood by the robot-like voice on the other end of the phone. If you ever set foot in a rainforest the first thing you’ll notice is that it is anything but quiet. In fact characterizing and quantifying soundscapes has become a marker for the complexity of the biodiversity present in a given environment.

Primate monitoring programmes can learn a great deal from cetacean research where Passive Acoustic Monitoring (PAM) is the norm (since individuals are rarely observable visually). Research on bats and birds can provide excellent examples to follow as well. Automated algorithm approaches including machine learning techniques, spectral cross-correlation, Gaussian mixture models, and random forests have been used in these fields to be able to detect and classify audio recordings using a trained automated system. Such automated approaches are often investigated for a single species but impressive across-taxa efforts have also been initiated within a framework of real-time acoustic monitoring. Implementing these in other research fields could lead to significant advances. Continue reading