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ONLINE COURSE – Ecological niche modelling using R (ENMR04) This course will be delivered live
25th May 2020 - 29th May 2020£460.00
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak.
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – Western European Summer Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email firstname.lastname@example.org for full details or to discuss how we can accommodate you).
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.
This course is orientated to PhD and MSc students, as well as persons in researcher or industry working on biogeography, spatial ecology, or related disciplines.
Venue – Delivered remotely
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3ECT’s
Language – English
PLEASE READ – CANCELLATION POLICY: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
Introductory lectures on the concepts and applications of ENM. Practical lectures on most used ENM methods. Presentations and round-table discussions about the analysis requirements of attendees (option for them to bring their own data). Data sets for computer practicals will be provided by the instructor, but participants are welcome to bring their own data
Assumed quantitative knowledge
Basic knowledge in Geographical Information Systems and spatial analyses.
Assumed computer background
Familiarity with GIS software like QGIS. Ability to visualise shapefiles and raster files. Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots.
Equipment and software requirements
A laptop/personal computer with a working version or R and RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Monday 25th – Classes from 09:30 to 17:30
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 26th – Classes from 09:30 to 17:30
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 27th – Classes from 09:30 to 17:30
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 28th – Classes from 09:30 to 17:30
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 29th – Classes from 09:30 to 16:00
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.
“PR-statistics offers a variety of courses, but ‘Introduction to Ecological Niche Modelling’ taught by an esteemed researcher of the field, Dr. Neftali Sillero, is definitely (either in their early in career or more experienced) a course any ecologist should attend.
The course started with a smooth and gentle introduction to the underlying principles of ecological niche modelling and provided a solid basis of how to build, test and evaluate an ecological niche model from start to finish. The instructor also took special care to point out which are the caveats you need to take care of when dealing with this kind of analysis. Dr. Sillero was always keen to answer our questions and attend to our needs and he even had time to discuss the problems we were facing with our own data (which ranged from plant/animal ecology to disease mapping).
It is an ideal course for anyone interested in species distribution modelling, either experienced or not, since it constitutes an extremely thorough and detailed step-by-step guide of how to approach the ever-growing ENM field. At least for me, it clarified a lot of concepts and I now feel confident about my modelling methodology.
Finally, Dr. Oliver Hooker, the heart and soul of PR-statistics, ensured that our stay in the Scottish Centre of Ecology and the Natural Environment (SCENE) would be as nice as possible and that we only had to worry about attending the lectures and nothing else. It was a memorable and fulfilling experience participating in the ENM course and I strongly recommend attending it.”
Kostas Kougioumoutzis, Ecologist
(Attended ENMR course)