Fuzzy logic to address gradual patterns in species distribution and diversity (FLDD01)
11th May 2020 - 14th May 2020£275.00 - £530.00
Live beings are constantly in motion and occur with varying frequency across space. Hence, categorical occurrence maps are always incomplete and oversimplified representations of species’ actual distributions. Analyses that build on such categorical data, such as most diversity, overlap and (dis)similarity indices, overlook important gradations in species occurrence. Fuzzy logic is a valuable tool to formally address the locational uncertainty and gradual variations that characterize biodiversity patterns. This course will show how fuzzy logic can be incorporated in ecological analyses to improve the portrayal, understanding and prediction of species distribution patterns, with implications on (macro)ecological interaction, global change, biodiversity and biotic regionalization studies. We will work with a set of species distribution modelling methods that derive presence probability values (e.g. logistic regression, generalized additive models, tree-based classification and regression methods), which can be mathematically converted to fuzzy membership values. We will then see how these values allow more direct comparisons across species, regions and time periods. Finally, we will see how diversity and (dis)similarity indices, which normally require binary presence-absence data, can be generalized to work with fuzzy (degree of) occurrence data for both species and regions.
The course is aimed at anyone (academic, government or industry) with an interest in analysing occurrence and diversity patterns of species and/or lineages.
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google Map
Availability – 20 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments and welcome meal Monday evening.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, refreshments and welcome dinner Monday evening. Self-catering facilities are available in the accommodation.Accommodation is multiple occupancy (max 4 people) single sex en-suite rooms. Arrival Sunday 10th May (between 17:00-21:00) and departure Thursday 14th May (accommodation must be vacated by 09:15).
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The course will include both theoretical lessons describing the theory and concepts underlying the described procedures; and practical hands-on sessions where students will put these procedures into practice using R. We will use species occurrence data from public sources, but students can also bring their own data, or an idea of which taxa they would like to analyse.
Assumed quantitative knowledge
No previous knowledge required.
Assumed computer background
Basic knowledge of R is desirable but not mandatory. The course has been planned with complete beginners in mind.
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
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Meet at Flat 2/1, 43 Cook Street, Glasgow G5 8JN between 17:00-21:00
Monday 11th – Classes from 09:30 to 17:30
Introduction to species distributions.
Types of distribution data: Presence-only, presence-absence, range maps.
Facing uncertainty in species distributions.
Introduction to modelling species distributions.
Practical: Introduction to the R software and programming language.
Discussion and conclusions.
Tuesday 12th – Classes from 09:30 to 17:30
Presence-only, presence-background and presence-absence modelling methods.
Overview of R packages for modelling species distributions.
fuzzySim introductory practice: Obtaining distance-based fuzzy distribution data.
Species distribution modelling with the favourability function.
fuzzySim modelling practice (with own or provided data).
Discussion and conclusions.
Wednesday 13th – Classes from 09:30 to 17:30
fuzzySim practice: Calculating fuzzy measures of similarity and diversity.
Calculating “quantum” measures of diversity and distributional change.
Practical with own or provided data.
Evaluating the fit and predictive capacity of distribution models.
modEvA practice: Analysing and evaluating fuzzy distribution data.
Discussion and conclusions.
Thursday 14th – Classes from 09:30 to 16:30
Practical with own or provided data (wrap-up).
Short talk preparation.
Students’ short talks.
Students’ short talks (continued).
Final discussion and conclusions.
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)