University of St Andrews
 
 
Sea Mammal Research Unit

SMRU News Centre

item 1359
[25-09-2012 to 31-03-2013]


News Item:
Monitoring marine mammals

A new instrument to detect whales, dolphins and other marine mammals, and provide immediate alerts during the development of offshore wind, wave and tidal installations, will be showcased to an international audience at the University of St Andrews on Thursday 27 September.

PAMBuoy™ was developed by SMRU Limited, a marine mammal consultancy which is a commercial spin out from the world renowned Sea Mammal Research Unit at the university. PAMBuoy™ is a cutting edge autonomous passive acoustic monitoring system for marine mammals. It operates 24/7 to automatically detect and classify vocalising marine mammals – whales, dolphins and porpoises, providing high resolution data that can be used to identify species present and determine temporal patterns in use.

“PAMBuoy™ “listens” for marine life, then delivers information about what’s swimming beneath, in real time back to a customer’s desk top, mobile phone or other hand held device, and if mounted in a buoy, derives its power from the sun via solar panels. Data is checked automatically for quality, and made available to clients immediately through secured parts of the PAMBuoy™ website.”

SMRU Ltd returns all its profits back to the University via Gift Aid, to fund further research in the academic departments whose expertise is used during project work. The company uses the wealth of scientific expertise available in the University through the Scottish Oceans Institute making this easy to access by the industrial world.

see here for further details


 

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  • Looking at telemetry data from above and below: some technological and methodological thoughts of an animal movement ecologist
    speaker: Dr Theoni Photopoulou (University of Cape Town)

    building: SOI
    room: Lecture Theatre
    see also: additional details
    host/contact: Dr Emma Defew

    Telemetry (the remote collection of data via communications systems) allows us to study animals that we would otherwise be unable to observe, in environments we don't have easy access to. The collection of such data is racing ahead of the analytical techniques we have available to understand the data and the systems under study. The type of information we can or should collect both determines, and is determined by, the questions we are able to address regarding the ecology, life-history and behaviour of animals. Challenging systems are often the most interesting, and sometimes the most important to study, but they present us with special practical and analytical challenges. Even though we now have the capacity to collect data in more detail and greater quantities than ever before, we often still have to make do with whatever we can get, or conversely, end up with data in large volumes or with more complexity than we know how to analyse. I will present examples of the data types and study systems I work with, including seals and black eagles, the importance of knowing how data are collected, and some of the methods I use to try to get the most out of these data.


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  • Keynote Speech: International Environmental Omics Synthesis Conference: Genomics and Inheritance
    speaker: Professor Elizabeth A. Thompson (University of Washington, School of Statistics)

    building: MBS
    room: Lecture Theatre
    see also: additional details
    host/contact: Prof Thomas Meagher

    More details about the 4-day International Environmental Omics Synthesis Conference in St Andrews, as well as speakers and programme, can be found on the iEOS web site.

    Genetic diversity in a species is key to its success in a changing environment, and a key determinant of genetic diversity is the ancestral history of the population.  Classically such ancestral structure was considered in terms of population demography and pedigree-based relationships.  Analyses were often constrained by the assumed pedigree structures, and by the assumption that individuals not specified as related have independent genetic data.  In reality, extended multi-generation pedigrees cannot be validated from genetic data on extant individuals, and any given pedigree can give rise to a wide variation of genetic descent patterns.
     
    Modern genetic data allow for the detection of this co-ancestry at specific genome locations, and it is this co-ancestry of DNA that provides a direct measure of genomic diversity. Recently, primarily in human genetics, numerous methods for the detection of segments of genome sharing between pairs of individuals have been developed.   However, combining these inferences into realized structures of the changing genome sharing across a chromosome jointly among multiple individuals has proven challenging.  I will discuss a new approach to this problem, and show how, even if only pairwise estimates are desired, joint inference provides improved estimates.


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