Biosciences Seminar Series - Spring 2014
22 May 2014 - 1pm - Zoology Museum (Wallace 129)
Disease detection in dairy cows through the analysis of individual and social movement behaviour
|Downloaded from: thenextweb.com|
Radiotracking, telemetry, GPS and biologging techniques have revolutionized the study of animal behavioural and population ecology in the last several decades, as it has become possible to observe the behaviour and survival of animals over long distances, at night and day, under the sea and in the air, etc. Whilst the advantages of these technologies for studying species like polar bears or wandering albatrosses are obvious, one might wonder why one should put similar high-tech biologgers on dairly cows in a barn ... which is what our seminar speaker of this week is doing! It turns out, though, that there are strong biological and economic reasons for doing that and Dr. Ed Codling, senior lecturer at the Maths Department at the University of Essex, will show us why. For example, it is even not easy to reliably track and record the behaviour of cows within a barn!
Before providing more information on the cow project, a bit more information about our speaker. Ed is a mathematical biologist and is interested in movement and behavioural ecology as well as in the population dynamics and optimal management of fisheries and marine ecosystems. For example, current research focusses on how humans respond to different sources of directional information during crowd evacuations (see here) as well as on multitrophic interactions in the sea (see here) or on zooplankton grazing (see here). Ed might also be considered a front runner in the award for ‘best study of your name’ scientist ever with his publication on Cod fisheries (see here) ...
|Image by Glenn Gorick|
So, now here why putting collars on cows in a barn is actually important and interesting:
Thanks to new technological developments there are potential solutions. Novel local positioning wireless sensors can be deployed over large networks of animals and give positioning information for individuals over long periods of time. It is known that diseases such as lameness in dairy cattle can affect general behaviour, such as how long cows spend lying down. Similarly, social interactions between individual animals, such as how much time they spend close to each other or how closely they synchronise their behaviour, have been suggested as possible measures of animal welfare. However, it is a non-trivial problem to determine and quantify changes in individual and social behaviour and subsequently to use such changes to predict the onset of disease.
|Cow with collar (image by Ed Codling)|
I will explain how we can use space utilisation methods, hidden Markov models and/or change point analysis to monitor individual behavioural states and highlight abnormal periods of behaviour that may be indicative of reduced welfare. I will also explain how social network analysis techniques will allow us to determine the social hierarchy within the herd and how this may also be used to monitor welfare status. I will illustrate these methods with data from two preliminary trials involving lame v non-lame dairy cows, and a small herd of beef cows.
The project serves as an ideal case study to test and develop new methods for the analysis and modelling of animal movement and behaviour at both the individual and collective level. Our ultimate goal is to develop an on-farm automated 'early warning' system for disease detection. Such a system would be invaluable for improving the welfare and productivity of dairy cows.
Co-authors: Jon Amory, Zoe Barker, Nick Bell, Darren Croft, Holly Hodges and Jorge Vazquez Diosdado
Everyone is most welcome to come and listen!