Species distribution models using R (SDMR01)
Deadline for registration is 21/05/2018
This course will be delivered by Prof. Jane Elith, Dr. Gurutzeta Guillera and Jose Square form the 12th - 15th June 2018 at Myuna Bay Sport and Recreation, Wangi Road, Myuna Bay, New South Wales 2264 Australia
Course Overview: The aim of this four-day course is to work towards an understanding of, and practical ability to fit, species distribution models (SDMs). It will be useful if you plan to use SDMs, or if you just want to understand them better.
We will focus on statistical models of species distributions – those that combine observed species records with environmental data.
Using a mixture of lectures, computer exercises and case studies, participants will learn to: 1) identify relevant data, and prepare it for modelling; 2) fit models using several modelling methods (including Maxent, generalized linear models and their extensions, and boosted regression trees); 3) consider how to model species if detection is imperfect; 4) evaluate models and interpret them; 5) understand the range of practical issues that arise in typical applications of SDMs.
Practical sessions will use the free statistical software, R – prior experience (even if some practice before you come) will be useful. Example data will be provided but participants may also bring their own data. Presenters include Jane Elith and Gurutzeta Guillera-Arroita, who are highly experienced in SDMs.
If you have any questions please email email@example.com
Monday 11th Meet at Myuna Bay Sport and |recreation at approx. 18:30
Tuesday 12th – Classes from 09:00 to 17:00 Overview of modelling distributions; niches and theory The modelling process – key concepts Predictor variables Species data Practical: start working with supplied data Methods for presence-absence data; introduction to use of regression models for species modelling
Wednesday 13th – Classes from 09:00 to 17:00 Generalised linear models (GLMs) and GLMMS Practical using GLMs with data How to evaluate models – lecture and practical Occupancy-detection models – lecture and practical
Thursday 14th – Classes from 09:00 to 17:00 What if no absence data? – introduction to presence-only and background data Practical: GLM with background data Relative probabilities, point processes Maxent – lecture and practical Evaluation for presence-background models How to deal with biased data
Friday 15th – Classes from 09:00 to 16:00 Boosted regression trees – lecture and practical Complexity vs simplicity in models Using models for extrapolation Hot topics: where is species modelling heading?
-- Oliver Hooker PhD. PR statistics
2018 publications -
Phenotypic and resource use partitioning amongst sympatric lacustrine brown trout, Salmo trutta. Biological Journal of the Linnean Society. DOI 10.1093/biolinnean/bly032
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