Gallantries Grant - Intellectual Output 4 - Data analysis and modelling for evidence and hypothesis generation and knowledge discovery

Comment: What is a Learning Pathway?
A graphic depicting a winding path from a start symbol to a trophy, with tutorials along the way
We recommend you follow the tutorials in the order presented on this page. They have been selected to fit together and build up your knowledge step by step. If a lesson has both slides and a tutorial, we recommend you start with the slides, then proceed with the tutorial.

This Learning Pathway collects the results of Intellectual Output 4 in the Gallantries Project

Success Criteria:

Year 1: Biodiversity data handling and visualisation

learners will understand how to handle biodiversity data and analyse it, as well as elements of visualisation, identifying the optimal visualisation for a dataset. [SC1.1,SC1.4, SC2.1, SC2.3, SC4.1-3]

Lesson Slides Hands-on Recordings
Compute and analyze biodiversity metrics with PAMPA toolsuite
Regional GAM
Biodiversity data exploration
Cleaning GBIF data for the use in Ecology

Year 2: Metabarcoding and environmental DNA data analysis

analysis of environmental DNA samples requires integrative analysis of highly diversified samples, and new techniques to scale with the data [SC1.4, SC1.5, SC2.1, SC3.1, SC4.1-4]

Lesson Slides Hands-on Recordings
Metabarcoding/eDNA through Obitools

Year 3: Species distribution modeling

As an application of data modeling, we will use species migration and biodiversity to teach learners how to build models for complex data and visualise the results. [SC1.1, SC2.4, SC4.1-4]

Lesson Slides Hands-on Recordings
Species distribution modeling

Editorial Board

This material is reviewed by our Editorial Board:

orcid logoYvan Le Bras avatar Yvan Le Brasorcid logoBérénice Batut avatar Bérénice Batut


These individuals or organisations provided funding support for the development of this resource