"Spatial analysis of ecological data using R"
Delivered by Prof. Jason Matthiopoulos, Dr. Jana Jeglinski, Dr. James
Grecian
http://prstatistics.com/course/spatial-analysis-of-ecological-data-using-r-spae-2/
This course will run from 21st – 26th November 2016 at SCENE field
station, Loch Lomond national park, 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 and is
therefore highly relevant to researchers studying the ecology and
spatial patterns/movements of marine mammals. 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
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 (POPULATION) GENETIC DATA ANALYSIS USING R (October)
3. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(October)
4. PHYLOGENETIC DATA ANALYSIS USING R (October/November)
5. ADVANCING IN STATISTICAL MODELLING USING R (December)
6. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R
(January)
7. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March)
8. INTRODUCTION TO GEOMETRIC MORPHOMETRICS USING R (June)
Dates still to be confirmed - email for details
oliverhoo...@prstatistics.com
• STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
• 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
3/1
128 Brunswick Street
Glasgow
G1 1TF
+44 (0) 7966500340
www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/
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