Recent activity

Quantitative geographic ecology using R: modelling genomes, niches, and communities (QGER01)

Oliver Hooker, April 5, 2018

Quantitative geographic ecology using R: modelling genomes, niches, and communities (QGER01)

Delivered by Dan Warren and Matt Fitzpatrick, this course will take place in Glasgow city centre from 30th April - 4th May

Full details can be found at

This course is well-suited to anyone working on seabirds at a species or community level

Course Overview: Spatial modelling is increasingly being used in ecology and evolutionary biology for both basic and applied research questions. While emphasis traditionally has been on species-level niche modelling, the increasing availability of genomic and community-level data has increased interest in modelling biodiversity patterns above and below the species level. This 5-day course will provide a thorough introduction to different spatial modelling techniques for quantifying and visualizing patterns of biodiversity across scales of biological organization - from population-level genetic variation, to species ecological niches, to communities. Students will learn about theory, common data types, and statistical techniques used in these different applications. The course will include introductory lectures, guided computer coding in R, and exercises for the participants, with an emphasis on visualization and reproducible workflows. All modelling and data manipulation will be performed with R. Attendees will learn to use niche modelling algorithms including Maxent, GLM, GAM, and others, and will learn both new and existing methods for conducting comparative studies using ENMs in the new ENMTools R package. Generalized Dissimilarity Modelling (GDM) and Gradient Forest (GF) will be taught for modelling genomic and community-level data. The course is intended for intermediate R users with interest in quantitative geographical ecology.

After successfully completing this course students will: 1) Understand the theory underlying ENMs and the critical assumptions necessary to the modelling process. 2) Be able to develop, evaluate, and apply ENMs both in the context of conservation-oriented studies and to study niche evolution. 3) Understand the statistical underpinnings of GDM and GF 4) Be able to develop, evaluate and apply GDM and GF for quantifying and mapping spatial genetic patterns and community-level compositional variation 5) Assess population- and community-level vulnerability to climate change

Check out our sister sites; (Ecology and life sciences) (Bioinformatics and data science) (Behaviour and cognition)

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Other up coming courses below

  1. April 9th – 13th 2018 NETWORK ANAYLSIS FOR ECOLOGISTS USING R (NTWA02 Glasgow, Scotland, Dr. Marco Scotti

  2. April 16th – 20th 2018 INTRODUCTION TO STATISTICAL MODELLING FOR PSYCHOLOGISTS USING R (IPSY01) Glasgow, Scotland, Dr. Dale Barr, Dr Luc Bussierre

  3. April 23rd – 27th 2018 MULTIVARIATE ANALYSIS OF ECOLOGICAL COMMUNITIES USING THE VEGAN PACKAGE (VGNR01) Glasgow, Scotland, Dr. Peter Solymos, Dr. Guillaume Blanchet

  4. April 30th – 4th May 2018 QUANTITATIVE GEOGRAPHIC ECOLOGY: MODELING GENOMES, NICHES, AND COMMUNITIES (QGER01) Glasgow, Scotland, Dr. Dan Warren, Dr. Matt Fitzpatrick

  5. May 7th – 11th 2018 ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA USING R (MVSP02) CANADA (QUEBEC), Prof. Pierre Legendre, Dr. Guillaume Blanchet


  7. May 21st - 25th 2018 INTRODUCTION TO PYTHON FOR BIOLOGISTS (IPYB05) SCENE, Scotland, Dr. Martin Jones

  8. May 21st - 25th 2018 INTRODUCTION TO REMOTE SENISNG AND GIS FOR ECOLOGICAL APPLICATIONS (IRMS01) Glasgow, Scotland, Prof. Duccio Rocchini, Dr. Luca Delucchi

  9. May 28th – 31st 2018 STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR (SIMM04) CANADA (QUEBEC) Dr. Andrew Parnell, Dr. Andrew Jackson

  10. May 28th – June 1st 2018 ADVANCED PYTHON FOR BIOLOGISTS (APYB02) SCENE, Scotland, Dr. Martin Jones

  11. June 12th - 15th 2018 SPECIES DISTRIBUTION MODELLING (DBMR01) Myuna Bay sport and recreation, Australia, Prof. Jane Elith, Dr. Gurutzeta Guillera

  12. June 18th – 22nd 2018 STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS USING R (SEMR02) Myuna Bay sport and recreation, Australia, Dr. Jon Lefcheck

  13. June 25th – 29th 2018 SPECIES DISTRIBUTION/OCCUPANCY MODELLING USING R (OCCU01) Glasgow, Scotland, Dr. Darryl McKenzie

  14. July 2nd - 5th 2018 SOCIAL NETWORK ANALYSIS FOR BEHAVIOURAL SCIENTISTS USING R (SNAR01) Glasgow, Scotland, Prof James Curley

  15. July 8th – 12th 2018 MODEL BASE MULTIVARIATE ANALYSIS OF ABUNDANCE DATA USING R (MBMV02) Glasgow, Scotland, Prof David Warton


  17. July 23rd – 27th 2018 EUKARYOTIC METABARCODING (EUKB01) Glasgow, Scotland, Dr. Owen Wangensteen

  18. October 8th – 12th 2018 INTRODUCTION TO SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (ISAE01) Glasgow, Scotland, Prof. Subhash Lele

  19. October 15th – 19th 2018 APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (ABME Glasgow, Scotland, Dr. Matt Denwood, Emma Howard

  20. October 29th – November 2nd 2018 PHYLOGENETIC COMPARATIVE METHODS FOR STUDYING DIVERSIFICATION AND PHENOTYPIC EVOLUTION (PCME01) Glasgow, Scotland, Prof. Subhash Lele Dr. Antigoni Kaliontzopoulou

  21. November 26th – 30th 2018 FUNCTIONAL ECOLOGY FROM ORGANISM TO ECOSYSTEM: THEORY AND COMPUTATION (FEER Glasgow, Scotland, Dr. Francesco de Bello, Dr. Lars Götzenberger, Dr. Carlos Carmona

  22. February 2018 TBC MOVEMENT ECOLOGY (MOVE02) Margam Discovery Centre, Wales, Dr Luca Borger, Dr Ronny Wilson, Dr Jonathan Potts

Oliver Hooker PhD. PR statistics

2017 publications -

Ecosystem size predicts eco-morphological variability in post-glacial diversification. Ecology and Evolution. In press.

The physiological costs of prey switching reinforce foraging specialization. Journal of animal ecology.

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