Stable Isotope Mixing Models using SIAR, SIBER and MixSIAR (SIMM03) Delivered by Dr. Andrew Parnell and Dr. Andrew Jackson
http://prstatistics.com/course/stable-isotope-mixing-models-using-siar- siber-and-mixsiar-simm/ This 4day course will run from 28th - 3rd March 2017 at Millport field centre, Isle of Cumbrae, Scotland (please note that although the filed centre in on an island it is extremely easy and uncomplicated to reach by public transport form both within and outside the UK) This course will cover the concepts, technical background and use of stable isotope mixing models (SIMMs) with a particular focus on running them in R. This course will cover the concepts, technical background and use of stable isotope mixing models (SIMMs) with a particular focus on running them in R. Recently SIMMs have become a very popular tool for quantifying food webs and thus the diet of predators and prey in an ecosystem. Starting with only basic understanding of statistical models, we will cover the do’s and don’ts of using SIMMs with a particular focus on the widely used package SIAR and the new, more advanced MixSIAR. Participants will be taught some of the advanced features of these packages, which will enable them to produce a richer class of output, and are encouraged to bring their own data sets and problems to study during the round-table discussions. (PLEASE NOT THIS COURSE IS FOLLOWED BY 'NETWORK ANALYSIS OF ECOLOGICAL DATA USING R - A COMBINED COURSE PACKAGE IS AVAILABLE) Course content is as follows Tuesday 28th – Classes from 09:00 to 17:00 Basic concepts. Module 1: Introduction; why use a SIMM? Module 2: An introduction to bayesian statistics. Module 3: Differences between regression models and SIMMs. Practical: Revision on using R to load data, create plots and fit statistical models. Round table discussion: Understanding the output from a Bayesian model. Wednesday 1st – Classes from 09:00 to 17:00 Understanding and using SIAR. Module 4: Do’s and Don’ts of using SIAR. Module 5: The statistical model behind SIAR. Practical: Using SIAR for real-world data sets; reporting output; creating richer summaries and plots. Round table discussion: Issues when using simple SIMMs. Thursday 2nd – Classes from 09:00 to 17:00 SIBER and MixSIAR. Module 6: Creating and understanding Stable Isotope Bayesian Ellipses (SIBER). Module 7: What are the differences between SIAR and MixSIAR? Practical: Using MixSIAR on real world data sets; benefits over SIAR. Round table discussion: When to use which type of SIMM. Friday 3rd – Classes from 09:00 to 17:00 Advanced SIMMs. Module 8: Using MixSIAR for complex data sets: time series and mixed effects models. Module 9: Source grouping: when and how? Module 10: Building your own SIMM with JAGS. Practical: Running advanced SIMMs with JAGS. Round table discussion: Bring your own data set. There will be a 15 minute morning coffee break, an hour for lunch, and a15 minute afternoon coffee break. We keep the timing of these flexible depending how the course advances. Breakfast is from 08:00-08:45 and dinner is at 18:00 each day. Please email any inquiries to oliverhoo...@prstatistics.com or visit our website www.prstatistics.com Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details oliverhoo...@prstatistics.com 1. INTRODUCTION TO PYTHON FOR BIOLOGISTS (October) 2. LANDSCAPE GENETIC DATA ANALYSIS USING R (October) 3. PHYLOGENETIC DATA ANALYSIS USING R (October/November) 4. SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (November) 5. ADVANCING IN STATISTICAL MODELLING USING R (December) 6. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January) 7. ADVANCED PYTHON FOR BIOLOGISTS (February) 8. NETWORK ANALYSIS FOR ECOLOGISTS USING R (March) 9. INTRODUCTION TO GEOMETRIC MORPHOMETRICS USING R (June) Dates still to be confirmed - email for details oliverhoo...@prstatistics.com • INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS • BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS • GENETIC DATA ANALYSIS USING R • INTRODUCTION TO BIOINFORMATICS USING LINUX • INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING Oliver Hooker PR Statistics
