Movement ecology (MOVE01)
19th February 2018 - 23rd February 2018260.00£ - 620.00£
The course will cover the concepts, technology and software tools that can be used to analyse movement data (from ringing/CMR to VHF/GPS to novel biologging data) in ecology and evolution, covering analysis techniques applicable broadly to most taxa, from micro-organisms to plants and animals. We will cover elementary and advanced analysis and modelling techniques broadly applicable across taxa, highlighting the advantages of a unified Movement Ecology framework. We will provide the necessary bases in ecology (especially behavioural ecology), physics and mathematics/statistics, to be able to identify for any specific research question the most appropriate study species, logging technology (incl. attachment methods), and statistical/mathematical modelling approach. We will specifically address the challenges and opportunities at each of the steps of the proposed ‘question-driven approach’, combining hands-on sessions with new biologging technology with computer-based practicals in R and specialized software for biologging data developed by the SLAM lab at Swansea University. We will also address the challenges of applying the results of the analyses to applied management problems and communicate the findings to non-experts.
Research postgraduates, practicing academics and primary investigators in ecology and management and environmental professionals in government and industry. The course will also be of interest to researchers in geography, mathematics and computer science working on movement analyses.
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
COURSE ONLY – Includes lunch and refreshments.
ACCOMMODATION PACKAGE – (to be purchased in addition to the course only option) – Includes breakfast, lunch, dinner, refreshments. Accommodation is multiple occupancy (max. 3 people) single sex en-suite rooms. Arrival Sunday 18th February and departure Friday 23rd February PM.
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email firstname.lastname@example.org
Cancellation policy: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com Failure to attend will result in the full cost of the course being charged. In the unfortunate event that PR~statistics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PR~statistics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
Introductory lectures on the concepts and refreshers on R usage. Intermediate-level lectures interspersed with hands-on mini practicals and longer projects. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
Assumed quantitative knowledge
A basic understanding of statistical, mathematical and physical concepts. Specifically, generalised linear regression models, including mixed models; basic knowledge of trigonometry, basic knowledge of calculus; basic knowledge of physics as relevant for biological systems (e.g forces and work, magnetism).
Assumed computer background
Good familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models (up to GLM) & generate simple exploratory and diagnostic plots. Knowledge of more advanced models, such as mixed models, will be helpful, as will a basic recollection of mathematical analysis.
Equipment and software requirements
A laptop/personal computer with a working version or R and RStudio installed and sufficient RAM to to load and analyse moderately large datasets. The DDMT software for biologging data visualization and analysis will be provided during the course. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Meet at Margam Discovery Centre 18:00 (Download directions PDF).
Monday 19th – Classes from 09:00 to 17:00
Module 1: Introduction to Movement Ecology – Theory, followed by hands on experience of deploying and collecting GPS & Biologging data (Daily Diary tags), incl. attachment methods & data quality
Module 2: Accelerometers & pressure/depth sensors– quantifying speed, behaviour, individual state & energetics
Tuesday 20th – Classes from 09:00 to 17:00
Module 3: Magnetometers – identifying orientation and animal behaviour
Module 4: Dead reckoning – reconstructing sub-second animal trajectories
Wednesday 21st – Classes from 09:00 to 17:00
Module 5: Movement path analysis I – from steps and turns to movement path segmentation
Module 6: Movement path analysis II – the squared displacement method and movement modes (foraging trips, home range, dispersal, migration, nomadism)
Thursday 22nd – Classes from 09:00 to 17:00
Module 7: Space use analysis – Home range estimation (2D & 3D) and quantification of individual interactions (static and dynamic approaches)
Module 8: Modelling animal movements: statistical and mathematical approaches
Friday 23rd – Classes from 09:00 to 16:00
Module 9: Habitat use and resource selection: from classical models to integrated step selection models
Modules 10: Joint modelling of animal movement and behaviour
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.
Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.
In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.”
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)