Government Pavilion, C/ Padre Herrera s/n
Post Office Box 456
38200, San Cristobal de La Laguna
Santa Cruz de Tenerife - Spain
Switchboard Tel.: (+34) 922 31 90 00
Hours: Mon, 8:00 a.m. to 9:00 p.m.
Statistical Analysis with R. Distribution, communities and populations in Ecology
Statistical Analysis with R. Distribution, communities and populations in Ecology
Overview
This microcredential trains the student to handle the R environment in the analysis of ecological data, including the spatial distribution of species, the analysis of animal and plant populations and the study of communities, providing tools for the interpretation and management of ecological information.
- Managing the R environment for data analysis
- Analysis of the spatial distribution of species
- Analysis of animal and plant species populations – Community analysis
a. Hold an official Spanish university degree or another degree issued by a higher education institution belonging to another Member State of the European Higher Education Area, which qualifies for access to master's level studies in that State.
b. Holding a degree issued by an educational system outside the European Higher Education Area without a validation or declaration of equivalence. In these cases, the academic director will submit a report to the Academic Committee, which will authorize or deny admission. Under no circumstances will authorization imply validation of the foreign degree, nor its recognition for any purpose other than pursuing postgraduate studies at the ULL.
Academic program
Topic I. Introduction to the theory and statistical analysis of biological communities. Description: This course will present the theoretical foundations that explain the patterns and processes that determine biodiversity. The structure and dynamics of biological communities will be contextualized from an ecological and statistical perspective. Methodology: Lectures with real-world examples, supported by basic and current scientific literature.
Topic II. Biological Community Assembly and Diversity Analysis. Description: This course will cover the dimensions of diversity (alpha, beta, and gamma), the main estimators, and methods for representing differences between communities. It will include rarefaction curves, alpha and beta diversity measures, and composition analysis. Methodology: Hands-on practice with R using real data; theory will be combined with parametric and non-parametric statistical analyses.
Topic III. Distance Measures and Clustering Analysis. Description: This course will explore various distance and transformation measures applicable to presence/absence and abundance data. Clustering and classification techniques will be developed to identify structural patterns among communities. Methodology: Practical exercises using R with real data, where comparative analyses will be implemented with different indices (e.g., Bray-Curtis, Jaccard), applying hierarchical and non-hierarchical clustering algorithms.
Topic IV. Multivariate ordination techniques. Description: Indirect (PCA, DCA, NMDS) and direct (RDA, CCA) ordination methods will be explained, along with multivariate analysis of variance. Ecological gradients and relationships between species composition and environmental variables will be interpreted. Methodology: Practical exercises with ordination packages in R (vegan, ade4), with ecological interpretation of the axes and explained variances.
Topic V. Multivariate Analysis of Variance and Indicator Species. Description: The PERMANOVA and ANOSIM methods will be compared to evaluate differences between communities. Indicator species will be identified, and their relationship with specific habitats or conditions will be studied. The interpretation of alpha and beta diversity and its facets (taxonomic, functional, phylogenetic) will be explored in depth. Methodology: Practical sessions applying multivariate significance analysis and indicator species tests (IndVal) with R
MD1. Lectures/expository method: presentation or explanation by the teaching staff.
MD2. Practical classes: activities supervised by the teaching staff in the classroom, laboratories, clinics.
MD7. Assessment: written, oral, practical tests, …
MD8. Tutoring: instruction period in which teachers and students interact with the aim of reviewing and discussing materials and topics presented in class.
SE7. Works, memoirs, internship memoirs, reports and written projects: document prepared on a topic or activity carried out, following the instructions established by the teaching staff.
SE8. Oral presentation and defense of topics, assignments, final degree projects, etc.: oral presentation on a topic related to the course content or on the results of an assignment, exercise, or project, followed by a discussion with the teaching staff. This can be done individually or in a group.
General information
Credits: 4 ECTS
Duration: 06/04/2026-08/05/2026
Teaching modality: In person
Location: Faculty of Sciences, Biology Section
Registration
More information
Short courses available in various formats (in-person, online, or hybrid). Ideal for learning without interrupting your professional life.
Content created and delivered by professionals and experts in the field, designed for immediate application.
Endorsed by the University of La Laguna. You will receive an official ECTS certificate, valid in the European Higher Education Area.
Teaching staff
Tuition
Registration link
Tuition fee
- Tasa de matrícula 200€
