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Multivariate analysis of ecological communities in R with the VEGAN package (VGNR01)
23 April 2018 - 27 April 2018£275.00 - £540.00
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 – 15 places
Duration – 5 days
Contact hours – Approx. 37 hours
ECT’s – Equal to 3 ECT’s
Language – English
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, welcome dinner Monday evening, farewell dinner Thursday evening, refreshments and accommodation. Self-catering facilities are available in the accommodation. Accommodation is approximately a 6-minute walk from the PR statistics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 22nd April (after 5pm) and departure Friday 27th April (accommodation must be vacated by 9am). An additional nights accommodation can be purchased, departure 9am Saturday morning email for details.
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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 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 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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Meet at 43 Cook Street, Glasgow G5 8JN at approx. 17:00 onwards
Monday 23rd – Classes from 09:00 to 17:00
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 24th – Classes from 09:00 to 17:00
Module 3: Diversity analysis, species-abundance distributions, null-model analysis
Module 4: Distance measures and distance based methods (Mantel test, distance decay, etc.)
Wednesday 25th – Classes from 09:00 to 17:00
Module 5: Hierarchical and nonhierarchical clustering and classification
Module 6: Dispersion and permutational MANOVA
Thursday 26th – Classes from 09:00 to 17:00
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 27th – Classes from 09:00 to 16:30
Module 9: Indicator species analysis and multivariate calibration.
Modules 10: special topics and discussion, analyzing participants’ own data.
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.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)