Multivariate analysis of ecological communities in R with the VEGAN package (VGNR02)
21 October 2019 - 25 October 2019£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 – 20 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments and welcome meal Monday evening.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, refreshments and welcome dinner Monday evening. Self-catering facilities are available in the accommodation.Accommodation is approximately a 6-minute walk from the PR informatics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 20th October (between 17:00-21:00) and departure Friday 25th October (accommodation must be vacated by 09:15).
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
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 email@example.com. 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
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Meet at Flat 2/1, 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.
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)