Ecological niche modelling using R (ENMR01)

Delivered by Dr. Neftali Sillero

http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/

This course will run from 16th – 20th October 2017 at SCENE field station, Loch Lomond national park, Scotland

The course will cover the base theory of ecological niche modelling and its main methodologies. By the end of this 5-day practical course, attendees will have the capacity to perform ecological niche models and understand their results, as well as to choose and apply the correct methodology depending on the aim of their type of study and data.

Ecological niche, species distribution, habitat distribution, or climatic envelope models are different names for similar mechanistic or correlative models, empirical or mathematical approaches to the ecological niche of a species, where different types of ecogeographical variables (environmental, topographical, human) are related with a species physiological data or geographical locations, in order to identify the factors limiting and defining the species' niche. ENMs have become popular due to the need for efficiency in the design and implementation of conservation management.

The course will be mainly practical, with some theoretical lectures. All modelling processes and calculations will be performed with R, the free software environment for statistical computing and graphics (http://www.r-project.org/). Attendees will learn to use modelling algorithms like Maxent, Bioclim, Domain, and logistic regressions, and R packages for computing ENMs like Dismo and Biomod2. Also, students will learn to compare different ecological niche models using the Ecospat package.

Course content is as follows

Monday 16th
Elementary concepts on Ecological Niche Modelling
Module 1: Introduction to ENM theory. Definition of ecological niche model; introduction to species ecological niche theory, types of ecological niches, types of ENM, diagram BAM, ENMs as approximations to species’ niches.
Module 2: Problems and limitations on ENM. Assumptions and uncertainties, equilibrium concept, niche conservatism, autocorrelation and intensity, sample size, correlation of environmental variables, size and form of study area, thresholds, model validation, model projections.
Module 3: Methods on ENM. Mechanistic and correlative models. Overlap Analysis, Biomod, Domain, Habitat, Distance of Mahalanobis, ENFA, GARP, Maxent, Logistic regression, Generalised Linear Models, Generalised Additive Models, Generalised Boosted Regression Models, Random Forest, Support Vector Machines, Artificial Neural Network.
Module 4: Conceptual and practice steps to calculate ENM. How to make an ENM step-by-step.
Module 5: Applications of ENM. Ecological niche identification, Identification of contact zones, Integration with genetical data, Species expansions, Species invasions, Dispersion hypotheses, Species conservation status, Prediction of future conservation problems, Projection to future and past climate change scenarios, Modelling past species, Modelling species richness, Road-kills, Diseases, Windmills, Location of protected areas.

Tuesday 17th
Prepare environmental variables and run ecological niche models with dismo package.
Module 6: Preparing variables. Choosing environmental data sources, Downloading variables, Clipping variables, Aggregating variables, Checking pixel size, Checking raster limits, Checking NoData, Correlating variables.
Module 7: Dismo practice. How to run an ENM using the R package dismo.

Wednesday 18th
Run ecological niche models with Biomod2 package and Maxent.
Module 8: Biomod2 practice. How to run an ENM using the R package Biomod2.
Module 9: Maxent practice. How to run an ENM using the R packages dismo and Biomod2 as well as Maxent software.

Thursday 19th
Compare ecological niche models with ecospat.
Module 10: Ecospat practice. Compare statistically two different ecological niche models using the R package Ecospat.
Module 11: Students’ talks. Attendees will have the opportunity to present their own data and analyse which is the best way to successfully obtain an ENM.

Friday 20th
Run ecological niche models with your own data.
Module 12: Final practical. In this practical, the students will run ENM with their own data or with a new dataset, applying all the methods showed during the previous days.

Please email any inquiries to [log in to unmask] or visit our website www.prstatistics.com

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Our other courses

1.	MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA #MASE
19th – 23rd June, Canada, Prof. Subhash Lele, Dr. Peter Solymos
http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/

2.	TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 #TSME
26th – 30th June, Canada, Dr. Andrew Parnell
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4.	SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R #SPAE
7th – 12th August 2017, Scotland, Prof. Jason Matthiopoulos, Dr. James Grecian
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5.	ECOLOGICAL NICHE MODELLING USING R #ENMR
16th – 20th October 2017, Scotland, Dr. Neftali Sillero
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/

6.	GENETIC DATA ANALYSIS AND EXPLORATION USING R #GDAR
23rd – 27th October, Wales, Dr. Thibaut Jombart, Zhian Kavar
http://www.prstatistics.com/course/genetic-data-analysis-exploration-using-r-gdar03/

7.	STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS USING R #SEMR
23rd – 27th October, Wales, Prof Jarrett Byrnes, Dr. Jon Lefcheck
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8.	LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R #LNDG
6th – 10th November, Wales, Prof. Rodney Dyer
http://www.prstatistics.com/course/landscape-genetic-data-analysis-using-r-lndg02/

9.	APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS #ABME
20th - 25th November 2017, Scotland, Prof. Jason Matthiopoulos, Dr. Matt Denwood
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/

10.	INTRODUCTION REMOTE SENSING AND GIS APPLICATIONS FOR ECOLOGISTS #IRMS
27th Nov – 1st Dec, Wales, Dr Duccio Rocchini, Dr. Luca Delucchi
http://www.prstatistics.com/course/introduction-to-remote-sensing-and-gis-for-ecological-applications-irms01/

11.	ADVANCING IN STATISTICAL MODELLING USING R #ADVR
11th – 15th December 2017, Wales, Dr. Luc Bussiere, Dr. Tom Houslay, Dr. Ane Timenes Laugen,
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12.	INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING #IBHM
29th Jan – 2nd Feb 2018, Scotland, Dr. Andrew Parnell
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/

13.	ANIMAL MOVEMENT ECOLOGY (February 2018) #ANME
19th – 23rd February 2018, Wales, Dr Luca Borger, Dr. John Fieberg

14.	GEOMETRIC MORPHOMETRICS USING R #GMMR
5th – 9th June 2017, Scotland, Prof. Dean Adams, Prof. Michael Collyer, Dr. Antigoni Kaliontzopoulou
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/


15.	FUNCTIONAL ECOLOGY FROM ORGANISM TO ECOSYSTEM: THEORY AND COMPUTATION #FEER
5th – 9th March 2018, Scotland, Dr. Francesco de Bello, Dr. Lars Götzenberger, Dr. Carlos Carmona
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16.	ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA USING R #MVSP
Prof. Pierre Legendre, Dr. Olivier Gauthier - Date and location to be confirmed

17.	STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR #SIMM
Dr. Andrew Parnell, Dr. Andrew Jackson – Date and location to be confirmed

18.	NETWORK ANAYLSIS FOR ECOLOGISTS USING R #NTWA
Dr. Marco Scotti - Date and location to be confirmed

19.	MODEL BASE MULTIVARIATE ANALYSIS OF ABUNDANCE DATA USING R #MBMV0
Prof David Warton - Date and location to be confirmed

20.	PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL
Dr. Emmanuel Paradis – Date and location to be confirmed


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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