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Multivariate analysis of ecological communities in R with the VEGAN package (VGNR02) FREE ACCOMMODATION AVAILABLE
21 October 2019 - 25 October 2019£275.00 - £570.00
This 5-day course will cover the concepts, methods, and R tools that can be used to analyse community ecology data. The course will review data processing techniques relevant to multivariate data sets. We will cover diversity and null-model analysis, distance measures and distance based multivariate methods, clustering, classification, and dimension reduction techniques using the vegan R extension package. We will use real world data sets to motivate the analyses, e.g. describing patterns along environmental or anthropogenic disturbance gradients, quantifying the effects of continuous and discrete predictors, and making predictions based on multivariate model results. We will emphasize visualization and reproducible workflows. Modules will consist of introductory lectures, guided computer coding, and exercises for the participants. The course is intended for intermediate R users with interest in community ecology, especially in the fields of terrestrial and wetland ecology, microbial ecology, and natural resource management.
Research postgraduates, practicing academics and primary investigators in spatial ecology and management and environmental professionals in government and industry.
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google Map
Availability – 24 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3ECT’s
Language – English
Arrival Sunday 20th October (between 17:00-21:00) and departure Friday 25th October (accommodation must be vacated by 09:15).
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PLEASE READ – 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 firstname.lastname@example.org. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees (and accommodation fees if booked through PR statistics) will be credited. However, PR statistics will not be held responsible/liable for any travel fees, accommodation costs or other expenses incurred to you as a result of the cancellation. Because of this PR statistics strongly recommends any travel and accommodation that is booked by you or your institute is refundable/flexible and to delay booking your travel and accommodation as close the course start date as economical viable.
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 concepts. Specifically, generalised linear regression models, statistical significance, hypothesis testing.
Assumed computer background
Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots.
Equipment and software requirements
A laptop/personal computer with a working version or R and RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links
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Sunday 20th Meet at 43 Cook Street, Glasgow G5 8JN between 17:00-21:00
Monday 21st – Classes from 09:30 to 17:30
Module 1: Introduction to community data analysis, basics of programming in R
Module 2: Data processing (long and wide data representations, single and multiple table operations, data aggregation and transformation)
Tuesday 22nd – Classes from 09:30 to 17:30
Module 3: Diversity analysis, species-abundance distributions, null-model analysis
Module 4: Distance measures and distance based methods (Mantel test, distance decay, etc.)
Wednesday 23rd – Classes from 09:30 to 17:30
Module 5: Hierarchical and nonhierarchical clustering and classification
Module 6: Dispersion and permutational MANOVA
Thursday 24th – Classes from 09:30 to 17:30
Module 7: Response curves, ordination (correspondence analysis, nonmetric scaling, constrained ordination).
Module 8: Fitting environmental variables to ordination, permutation based testing of the significance of constraints.
Friday 25th – Classes from 09:30 to 16:00
Module 9: Indicator species analysis and multivariate calibration.
Modules 10: special topics and discussion, analyzing participants’ own data.
“PR-statistics offers a variety of courses, but ‘Introduction to Ecological Niche Modelling’ taught by an esteemed researcher of the field, Dr. Neftali Sillero, is definitely (either in their early in career or more experienced) a course any ecologist should attend.
The course started with a smooth and gentle introduction to the underlying principles of ecological niche modelling and provided a solid basis of how to build, test and evaluate an ecological niche model from start to finish. The instructor also took special care to point out which are the caveats you need to take care of when dealing with this kind of analysis. Dr. Sillero was always keen to answer our questions and attend to our needs and he even had time to discuss the problems we were facing with our own data (which ranged from plant/animal ecology to disease mapping).
It is an ideal course for anyone interested in species distribution modelling, either experienced or not, since it constitutes an extremely thorough and detailed step-by-step guide of how to approach the ever-growing ENM field. At least for me, it clarified a lot of concepts and I now feel confident about my modelling methodology.
Finally, Dr. Oliver Hooker, the heart and soul of PR-statistics, ensured that our stay in the Scottish Centre of Ecology and the Natural Environment (SCENE) would be as nice as possible and that we only had to worry about attending the lectures and nothing else. It was a memorable and fulfilling experience participating in the ENM course and I strongly recommend attending it.”
Kostas Kougioumoutzis, Ecologist
(Attended ENMR course)