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Live Online Course – 2nd Edition

Evolutionary Macroecology in R: Exploring Biodiversity Patterns at Large Scales

June 8th-12th, 2026

Course Evolutionary Macroecology in R

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You can also use this form to request this as an in-house course for your group.

Course Overview

This course provides a primer on Macroecology, focusing on geographic patterns of biodiversity and how those patterns are affected by species evolution and adaptation over time. It combines historical components of geographic patterns, phylogenies, and ecology to provide a comprehensive overview of evolutionary macroecology.

The course has a strong practical component in R. Students will learn to manipulate large geographic databases in R, grid-map biodiversity in various forms, conduct analyses of biogeographic regionalization incorporating evolutionary history, and estimate phylogenetic turnover and historical dispersal in geographic space. The practical sessions also cover common metrics in community phylogenetics and diversification, focusing on large geographic scales.

At the end of this course, participants will be able to:

  • Generate geographic maps of biodiversity (species diversity, trait diversity, etc.).
  • Use phylogenies to incorporate evolution into geographic patterns of diversity.
  • Construct biogeographic regions while accounting for the evolutionary relationship of species.
  • Map historical patterns of diversification, historical dispersal, and phylogenetic turnover.
  • Calculate and map in-situ diversification, the age of assemblages, and new tip-based metrics of trait evolution.
  • Associate geographic patterns of biodiversity with ecological predictors.
  • Integrate tools of macroevolutionary dynamics, such as estimating ancestral areas and ancestral traits, with community phylogenetic metrics.

Several datasets will be provided to illustrate the application of these methods. Participants are encouraged to bring their own datasets to analyze and discuss with the instructor.

Places are limited to 16 participants.

Programme

Introduction to Macroecology & Mapping Biodiversity

Theory

  • Origin and fundamentals of Macroecology.
  • Species range maps.
  • Geographic gradients of diversity.

Practice

  • Manipulating large geographic datasets in R.
  • The presence-absence matrix.
  • Geographic coordinates and different map projections.
  • Mapping species diversity and other geographic gradients of diversity.

Phylogenies in Macroecology I

Theory

  • Incorporating phylogenies into Macroecology I.
  • Evolutionary metrics of central tendency using the assemblage-based approach.

Practice:

  • Estimating the phylogenetic and specific components of trait variation over geographic space.
  • Assessing the contribution of phylogenetic composition to trait geographic variation.
  • Incorporating environmental and evolutionary predictors into ecological analyses of biodiversity.

Phylogenies in Macroecology II

Theory

  • Incorporating phylogenies into Macroecology II.
  • Diversity and rates of species and trait diversification across geographic space.
  • Evolutionary metrics of diversity and historical dispersal using the assemblage-based approach.

Practice:

  • Introduction to alculating and mapping phylogenetic and trait diversity
  • Rates of evolution in geographic space.

Biogeographic Regionalization & Evolutionary History

Theory

  • Biogeographic regionalization and estimation of ancestral evolutionary arenas.

Practice

  • Estimating biogeographic regions incorporating phylogenies (evoregions).
  • Accounting for uncertainty in biogeographic regionalization.
  • Mapping shifts in phylogenetic turnover.
  • Calculating the age of assemblages.

Integrated Analyses & Herodotools

Theory

  • Integrating macroecology, macroevolution, and community ecology.
  • Exploring the capabilities of the Herodotools R package.

Practice

  • Estimating macroevolutionary metrics of in-situ diversification and historical dispersal.
  • Incorporating in-situ diversification into common community phylogenetic metrics.
  • Calculating and mapping trait tip-based metrics of transition rates, stasis time, and last transition time.

Assumed Background

basic to intermediate level of R knowledge is required. Students must be able to load and save data, understand the functionality of packages, manipulate vectors and data frames, and use basic functions.

Keyboard Keyboard

Software

All participants must have a personal computer with current versions of R and R Studio.

Dates & Schedule

Online live sessions from June 8th-12th, 2026.

From 13:00-17:30 (Madrid time zone).

Total course hours: 32.5 (22.5 hours of online live lessons, plus 10 hours of participants working on their own between the live sessions).

This course is equivalent to 1 ECTS (European Credit Transfer System). The recognition of ECTS by other institutions depends on each university or school.

Format

In the live sessions, we will combine online lectures with hands-on computational exercises in R, to provide both theoretical understanding and practical skills.

Live sessions will be recorded. However, attendance to the live sessions is required to obtain the course certificate.

This course will be delivered in English.

Instructor

Renan Mestri instructor for Transmitting Science

Dr. Renan Maestri

Universidade Federal do Rio Grande do Sul
Brazil

Registration Fees

  • Course Fee
  • Early bird (until April 30th, 2026):
  • 426 €
    (340.80 € for Ambassador Institutions)
  • Regular (after April 30th, 2026):
  • 520 €
    (416 € for Ambassador Institutions)
  • Prices include VAT.
    After registration you will receive confirmation of your acceptance on the course.
    Payment is not required during registration. Check discounts here.