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SpatialAnalysisOfEcologicalDataUsingR_JasonMatthiopoulos_UK_7th-12thAug

Oliver Hooker
Spatial analysis of ecological data using R

Delivered by Prof. Jason Matthiopoulos, Dr. James Grecian

http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/

This course will run from 7th – 12th August 2017 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. 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 [hidden email] or visit our
website www.prstatistics.com

Please feel free to distribute this material anywhere you feel is
suitable


1. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/

2. 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/

3. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/

4. 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/

5. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/

6. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/

7. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/

8. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE
http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/

9. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME)

10. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/

11. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/

12. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/

13. INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL
http://www.prstatistics.com/course/introduction-to-bioinformatics-using-linux-ibul02/

14. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY
BIOLOGISTS (October 2017) #SEMR

15. GENETIC DATA ANALYSIS USING R (October 2017 TBC) #GDAR

16. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November 2017
TBC) #LNDG
http://www.prstatistics.com/course/landscape-genetic-data-analysis-using-r-lndg02/

17. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017) #ABME
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/

18. INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS

19. INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB
http://www.prstatistics.com/course/introduction-to-python-for-biologists-ipyb04/

20. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017)
#DVMP
http://www.prstatistics.com/course/data-visualisation-and-manipulation-using-python-dvmp01/

21. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr07/

22. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (January 2018) #IBHM
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/

23. PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL

Oliver Hooker PhD.
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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