PART FUNDED SCHOLARSHIPS FOR SPATIAL ECOLOGY COURSE
‘Spatial analysis of ecological data using R - Funding available'
PR STATISTICS ARE PLEASED TO ANNOUNCE THAT THROUGH THEIR FUNDING SCHEME
THEY CAN CONTRIBUTE TOWARDS TUITION FEES AND ACCOMMODATION WITH A
LIMITED NUMBER OF ‘ALL INCLUSIVE PLACES’ AVAILABLE AT £450.00 (+
VAT) Fees have been subsidised by 40% from £750 (+VAT).
Applications should be sent to [hidden email] and contain
1. Full name
2. Institute name
3. PhD subject title or Post doc research questions
4. Do you hold a funded position
5. 150 words why this course would be relevant to your research or how
it would help.
Monday 21st – Classes from 09:00 to 17:00
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; useful concepts from statistics; Generalised Linear
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
Tuesday 22nd – Classes from 09:00 to 17:00
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
Wednesday 23rd – Classes from 09:00 to 17:00
Module 5: Analysing grid data, Poisson processes, Occupancy models,
Module 6: Analysing telemetry data, Presence-only data, Spatial and
serial autocorrelation, Partitioning variation by mixed effects models.
Thursday 24th – Classes from 09:00 to 17:00
Module 7: Analysing transect data, Detection functions for point and
line transects, Using covariates in transect models. Afternoon for catch
up and/or excursion.
Friday 25th – Classes from 09:00 to 17:00
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.
Saturday 26th – Classes from 09:00 to 16:00
Predictions and applications.
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.
Thank you, Oliver Hooker
1. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (November)
2. ADVANCING IN STATISTICAL MODELLING USING R (December)
3. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R
4. ADVANCED PYTHON FOR BIOLOGISTS (February)
5. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
6. NETWORK ANALYSIS FOR ECOLOGISTS USING R (March)
7. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April)
8. INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS (CHINA, April)
9. ADVANCING IN STATISTICAL MODELLING USING R (CHINA April)
10. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (May)
11. INTRODUCTION TO GEOMETRIC MORPHOMETRICS USING R (June)