Researchers are increasingly interested in how social behaviour influences a range of biological processes. Social data have the interesting mathematical property that the number of potential connections among individuals is typically much larger than the number of individuals (because individuals can interact with every other member of their group). This introduces a huge challenge when it comes to collecting data on social interactions—not only does the amount of data needed increase exponentially with group size, the data can also be more difficult to record.
Larger groups have more simultaneous interactions, making it harder for observers to capture a complete or representative sample. It’s also more difficult for observers to tell individuals apart in larger groups. Coloured markers are often used to distinguish different members of a group – the bigger the group, the more complex the markers are needed.
Group-level properties or behaviours can also emerge or change rapidly over time or depending on the situation. This means that observations have to be made at high temporal resolution. To study social behaviour with group sizes that resemble those occurring in nature, we need new techniques to extract sufficient information from social groups. Continue reading →
Ecologists have long been fascinated by animal sounds and in recent decades there’s been growing interest in the field of ‘bioacoustics’. This has partially been driven by the availability of high-definition digital audio recorders that can withstand harsh field conditions, as well as improvements in software technology that can automate sound analysis.
The rise of trait ecology led to many quantitative frameworks to understand the underlying rules that determine how species are assembled into local communities from regional pools. Ecologists are interested in understanding whether environmental features select for particular traits that optimise local fitness and regulate species co-existence.
In ‘Assessing the joint behaviour of species traits as filtered by environment’, Erin Schliep and her co-authors aimed to develop a joint probabilistic model under a Bayesian framework to help explain the correlations among traits and how trait distributions differ across species and their environments. The end product is a model of trait-environmental relationships that takes full advantage of information on intra- and interspecific variation typically found within and among species. Continue reading →
Animal biologging is a technique that’s quickly becoming popular in many cross-disciplinary fields. The main aim of the method is to record aspects of an animal’s behaviour and movement, alongside the bio-physical conditions they encounter, by attaching miniaturised devices to it. In marine ecosystems, the information from these devices can be used not only to learn how we can protect animals, many of whom are particularly vulnerable to disturbance (e.g. large fish, marine mammals, seabirds and turtles), but also more about the environments they inhabit.
Challenges when Tracking Marine Animals
Many marine animals have incredibly large ranges, travelling 1000s of kilometres. A huge advantage of biologging technologies is the ability to track an individual remotely throughout its range. For animals that dive, information on sub-surface behaviour can be obtained too. This information can then be retrieved when an animal returns to a set location. If this isn’t possible (e.g. individuals that make trips that are too long or die at sea), carefully constructed summaries can be relayed via satellite. This option provides information in real time, which can be very useful for researchers.
Tracks of juvenile southern elephant seals. Red tracks are individuals that returned to their natal colony. Grey are those individuals whose information would have been lost had it not been transmitted via the Argos satellite system.
“My research is focused on using new mathematical and computational techniques to study problems in biology and ecology. In particular, I’m interested in movement ecology, and specifically the development of theoretical models and empirical analysis tools that give insights into animal movement and behaviour. I am also interested in spatial population dynamics and the application of modelling and analysis tools to marine fisheries and other natural resource management questions.”
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.
Understanding how animals perceive, learn and remember stimuli is critical for understanding both how cognition is shaped by natural selection, and how ecological factors impact behaviour.Unfortunately, the limited number of protocols currently available for studying insect cognition has restricted research to a few commercially available bee species, in almost exclusively laboratory settings.
In a new video Felicity Muth describes a simple method she developed with Trenton Cooper, Rene Bonilla and Anne Leonard for testing both lab- and wild-caught bees for their preferences, learning and memory. They hope this method will be useful for students and researchers who have not worked on cognition in bees before. The video includes a tutorial for carrying out the method and describes the data presented in their Methods in Ecology and Evolutionarticle, also titled ‘A novel protocol for studying bee cognition in the wild‘.
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.
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:
Animal-borne devices/tags (biologging science, Hooker et al., 2007) and/or remote sensing technology to quantify movement and collect data from remote or otherwise challenging environments
Computational power sufficient to manipulate, process and analyse substantial volumes of data
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.
Verreaux’s eagles lay one to two eggs but only raise one chick. These are normally hatch during mid-winter and stay on the nest for around 90 days. The parents provision the chick during this time, delivering prey to the nest. Rock hyrax is a frequent item on the menu, as seen here. Having concurred data from accelerometers and nest cameras for the same bird could allow for activity level to be linked to successful prey acquisition or prey type. (Photo taken by a nest camera installed as part of the Black Eagle Project, Megan Murgatroyd)