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ONLINE COURSE – Ecological niche modelling using R (ENMR04) This course will be delivered live
12th December 2022 - 16th December 2022
£460.00
Event Date
Monday, December 12th, 2022
Course Format
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
TIME ZONE – Western European Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).
About This Course
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.
Intended Audiences
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
Course Details
Time Zone – Western European Time
Availability – 24 Places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
Teaching Format
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
Assumed computer background
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
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 oliverhooker@prstatistics.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.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Monday 12th
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 13th
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 14th
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 15th
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 16th
Classes from 09:30 to 17:30
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.
Dr. Neftali Sillero
Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns, from species to populations and individuals. For this, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems, Remote Sensing, Ecological Niche Modelling, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases, ecological modelling of species’ ranges, identification of biogeographical regions and species’ chorotypes, mapping and modelling road-kill hotspots, and spatial analyses of home ranges.
He has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea, where he is the PI of the NA2RE project (www.na2re.ismai.pt), the New Atlas of Amphibians and Reptiles of Europe
Teaches
- Ecological Niche Modelling Using R (ENMR)
- Advanced Ecological Niche Modelling Using R (ANMR)
- GIS And Remote Sensing Analyses With R (GARM)
Teaches
- Ecological Niche Modelling Using R (ENMR)
- Advanced Ecological Niche Modelling Using R (ANMR)
- GIS And Remote Sensing Analyses With R (GARM)