When | Where | Purpose | Content | Recommended Skills | Fees | What to bring along
When
Monday 2nd to Friday 6th of February 2015
Where
Room 12 0G 069 (Building 12, Ground Floor Lecture/Seminar room, Zoology Department)
Nelson Mandela Metropolitan University, South Campus
Summerstrand, Port Elizabeth, South Africa
Click here for maps
Purpose
This workshop fits into a broad initiative from the recently formed South African Movement Ecology Group to unify and strengthen research in the field of animal movement ecology, across both marine and terrestrial realms, at a national level.
Through training with international experts, the objective of the workshop is to develop skills for analysing animal movement data, from pre-processing data to modelling movement. The workshop will combine lectures on theory and practicals on own data. The idea is for you to come back home with a kit of tools that you would directly apply to conduct your research!
Content
The workshop will cover topics relating to:
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Pre-processing data: filtering data, estimating positions, reconstructing trajectories
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Estimating parameters from movement data: geographical distance, speed, turning angles
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All sorts of random walks
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Measuring density: brownian bridges and kernel-density estimations, home range analysis
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Behavioural estimates: sinuosity, first-passage time, residence time, fractal dimensions
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Reconstructing hidden states from estimated parameters: markov models, random forests, neural networks
See the programme for details
Recommended skills
We very strongly recommend: (1) prior experience in R and/or Matlab, (2) and an understanding of basic statistics (e.g., what are means, variance, correlations, distributions, conditional distributions, etc).
Fees
This is a non-profit workshop: the fees are R1500 for students and R2000 for postdocs/researchers to cover expenses only. Daily tea/coffee and snacks, lunches, and a shirt are included in the fees.
What to bring along
Please bring your own laptop and a dataset that you can analyse. The last day is dedicated to working on your own data with the help of the guest lecturers, so make sure you have some data to work with.