Training: Generalized linear models for community ecology

BIOS² is hosting a workshop about Generalized linear models for community ecology presented by Pr. Pedro Peres-Neto (Concordia) on July 19, 21 and 23, 2021, from 1:00 to 4:00 PM eastern time .

Much as astronomers cannot perform planetary experiments, ecologists cannot easily manipulate the processes underlying biodiversity. How are species selected to occupy certain communities or coexist with particular species? Biodiversity patterns of ecological communities are the result of multiple interacting factors and processes including population demography, species traits (e.g., morphology, behaviour, life history, physiology, resistance to environmental changes), genetics, evolutionary history (phylogeny), species interactions, dispersal, and environmental and landscape spatial heterogeneity. Our ability to understand the roles of different mechanisms and processes underlying biodiversity is challenging because of the possibly complex ways that they may affect community assembly. 

In this workshop we will explore, discuss, and apply generalized linear models to combine information on species distributions, traits, phylogenies, environmental and landscape variation. We will also discuss inference under spatial and phylogenetic autocorrelation under fixed and random effects implementations. We will discuss technical elements and cover implementations using R.

Participants that are interested in these techniques in general or interested in discussing their research are welcomed. We will also set aside time to discuss general quantitative questions that participants may have. The workshop will be in English, and students should feel free to participate in French.

The workshop will be conducted by Pedro Peres-Neto, professor at Concordia University and BIOS2 co-PI specialized in community and quantitative ecology.

Places are limited.
Register here1 by July 16, 2021.


1 Link to form: https://forms.office.com/r/xaFL4p0xcG

Image: http://strijov.com/sources/demo_GLM.php

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