Stable Isotope Mixing Models using SIAR, SIBER and MixSIAR (SIMM03) Delivered by Dr. Andrew Parnell and Dr. Andrew Jackson
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r- simm03/ This 4 day 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) (PLEASE NOT THIS COURSE IS FOLLOWED BY 'NETWORK ANALYSIS OF ECOLOGICAL DATA USING R – this course concentrates a lot of food webs and therefore may also be of interest. (A COMBINED COURSE PACKAGE IS AVAILABLE) http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/ 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. 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. 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. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January 2017) #MBMV http://www.prstatistics.com/course/model-base-multivariate-analysis-of- abundance-data-using-r-mbmv01/ 2. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB http://www.prstatistics.com/course/advanced-python-biologists-apyb01/ 3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R (February 2017) #SIMM http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r- simm03/ 4. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/ 5. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April 2017) #MVSP http://www.prstatistics.com/course/advances-in-spatial-analysis-of- multivariate-ecological-data-theory-and-practice-mvsp02/ 6. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB http://www.prstatistics.com/course/introduction-to-statistics-and-r-for- biologists-irfb02/ 7. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR http://www.prstatistics.com/course/advancing-statistical-modelling-using-r- advr05/ 8. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (May 2017) #IBHM http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical- modelling-using-r-ibhm02/ 9. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/ 10. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE http://www.prstatistics.com/course/multivariate-analysis-of-spatial- ecological-data-using-r-mase01/ 11. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME) 12. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB http://www.prstatistics.com/course/bioinformatics-for-geneticists-and- biologists-bigb02/ 13. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r- spae05/ 14. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR http://www.prstatistics.com/course/ecological-niche-modelling-using-r- enmr01/ 15. INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL 16. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (November 2017) #ABME http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists- epidemiologists-abme03/ 17. INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS 18. INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB 19. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017) #DVMP 20. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR 21. GENETIC DATA ANALYSIS USING R (October TBC) 22. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November TBC) 23. PHYLOGENETIC DATA ANALYSIS USING R (November TBC) 24. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (TBC)