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"Spatial analysis of ecological data using R" Delivered by Prof. Jason Matthiopoulos http://prstatistics.com/course/spatial-analysis-of-ecological-data-using-r-spae/ This course will run from 11th - 17th April 2016 at Millport Field Station, Isle of Cumbrae, Scotland The course will cover the concepts and R tools that can be used to analyse spatial data in ecology covering elementary and advanced spatial analysis techniques applicable to both plants and animals. We will investigate analyses appropriate to transect (e.g. line surveys, trapping arrays), grid (e.g. occupancy surveys) and point data (e.g. telemetry). The focal questions will be on deriving species distributions, determining their environmental drivers and quantifying different types of associated uncertainty. Novel methodology for generating predictions will be introduced. We will also address the challenges of applying the results of these methods to wildlife conservation and resource management and communicate the findings to non-experts. Course content is as follows Day 1: Elementary concepts Module 1 Introductory lectures and practical; this will cover the key questions in spatial ecology, the main types of data on species distributions, concepts and challenges and different types of environmental data, concepts and challenges; useful concepts from statistics; Generalised Linear Models Module 2 GIS tools in R: Types and structure of spatial objects in R, generating and manipulating spatial objects, projections and transformations, cropping and masking spatial objects, extracting covariate data and other simple GIS operations in R, optionally plotting simple maps Day 2: Overview of basic analyses Module 3 Density estimation, Spatial autocorrelation, Smoothing, Kernel Smoothers, Kriging, Trend-fitting (linear, generalised linear, generalised additive models) Module 4 Habitat preference, Resource selection functions, MaxEnt: What’s it all about? Overview and caveats related to Niche models Day 3: Challenging problems Module 5 Analysing grid data, Poisson processes, Occupancy models, Use-availability designs Module 6 Analysing telemetry data, Presence-only data, Spatial and serial autocorrelation, Partitioning variation by mixed effects models Day 4: Challenging problems Module 7 Analysing transect data, Detection functions for point and line transects, Using covariates in transect models. Afternoon for catch up and/or excursion Day 5: Challenging problems Module 8 Advanced methods, Generalised Estimation Equations for difficult survey designs, Generalised additive models for habitat preference, Dealing with boundary effects using soap smoothers, Spatial point processes with INLA Day 6: Delivering advice Module 9 Prediction, Validation by resampling, Generalised Functional Responses for species distribution, Quantifying uncertainty, Dealing with the effects of population density Module 10 Applications, Designing protected areas, thinking about critical habitat, Representing uncertainty Day 7: Hands-on problem solving Module 11 Round table discussions, About 4 groups, each of 5-10 people working on a particular problem. This 7 day course costs £630 for course only including lunch or £965 all inclusive, including all accommodation and meals. Please email any inquiries to [log in to unmask] or visit our website www.prstatistics.com Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details [log in to unmask] STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R ADVANCING IN STATISTICAL MODELLING USING R TIMES SERIES DATA ANALYSIS FOR ECOLOGISTS AND CLIMATOLOGISTS INTRODUCTION TO PYTHON FOR BIOLOGISTS ADVANCES IN DNA TAXONOMY USING R GENETIC DATA ANALYSIS USING R MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R Dates still to be confirmed - email for details [log in to unmask] INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R PHYLOGENETIC DATA ANALYSIS USING R BIONFROMATICS FOR GENETICISTS AND BIOLOGISTS Oliver Hooker PR~Statistics