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Physalia courses: Big Data Biogeography

Date & time: February 1st - February 5th

Times (CET):

  • 9:00 - 12:00 Exercises (teachers available for questions via slack)

  • 13:00 - 17:00 Lectures, demonstrations and group work (synchronous)

Location: on-line

Teachers: Alexander Zizka, German Center for Integrative Biodiversity research & Daniele Silvestro, University of Fribourg, Switzerland

Schedule

The course consists of five days with different topics. You can find a detailed schedule in the overview tab for each day.

  • Day 1 - Biodiversity databases. Introduction to different types of large-scale biodiversity data and methods for reproducible data retrieval.

  • Day 2 - Data quality and processing. Understanding common issues with species distribution data from large-scale biodiversity databases and introduction to methods to address them.

  • Day 3 - Historical biogeography

  • Day 4 - Big data conservation assessment

  • Day 5 - Fossil biogeography

Important

We will use Slack for most of the communication before and during the course. Please make sure to check the slack channel regularly.

How the course works

  • We will meet for the first time on Monday 13:00 CET on zoom. Please make sure to have a look at @before_start, so that we can start swiftly.

  • The course will be split into daily live sessions (13:00 - 17:00 CET) and related asynchronous exercise session on which you will work between the live sessions. You can chose the timing of the exercise sessions, and we will be available to answer questions via slack from 9:00 - 12:00 CET every day.

  • During the live session we will consist of lectures where we will present theoretical concepts and a broader context for the exercises of each day and demonstrations where we will briefly present the analysis work-flows for each day and you will then have time to explore them and ask questions. During the asynchronous sessions you will independently address specific exercises following tutorials.

  • Detailed information on the course are available on the course webpage (https://azizka.github.io/big_data_biogeography/) which we will update constantly during the course. On the webpage you will find for each day:

    • the exercises with tutorial
    • a detailed schedule
    • learning objectives and expected outcomes
    • further reading
  • During the course you will work on your own project, applying the methods presented during the course to your own data. To do so please bring a taxonomic group of interest (ideally up to 200 species, and if possible with a phylogeny available), and think of some questions regarding this dataset that you would like to answer. This will give you the opportunity to chose questions and exercises most suitable for your work and get feedback from the teacher. There will be example data for all exercises, in case you do not have your own data yet. At the end of the course you will briefly present your results. You can find more information on the project on the course webpage.

Contact

Course content: Alexander Zizka Organisational: Physalia courses

Physalia courses webpage

Objectives

After this course, students will be able to:

  1. Obtain and prepare large scale species occurrence records from public databases in R (including data mining, data cleaning and exploration)

  2. Apply novel methods for handling and processing ‘big data’ in biogeographic research, including area classification, bioregionalization and automated conservation assessments

  3. Reconstruct species ancestral ranges based on species occurrences and phylogenetic trees, using different evolutionary models

  4. Understand the potential and caveats of fossil based biogeography, and be familiar with novel methods to estimate ancestral ranges and evolutionary rates from ranges of extinct and extant taxa

Background

The public availability of large-scale species distribution data has increased drastically over the last ten years. In particular, due to the aggregation of records from museums and herbaria, and citizen science in public databases such as the Global Biodiversity Information Facility (GBIF). This is leading to a ‘big data’ revolution in biogeography, which holds an enormous but still poorly explored potential for understanding large scale patterns and drivers of biodiversity in space and time.

Course literature

  1. Meyer et al. (2015) Global priorities for an effective information basis of biodiversity distributions. Nature Communications, 8 pp.

  2. Antonelli et al. (2018) Amazonia is the primary source of Neotropical biodiversity. PNAS 115(23): 6034–6039.

  3. One of the following suggestions (depending on your own interests): a. Edler et al. (2017) Infomap Bioregions: Interactive mapping of biogeographical regions from species distributions. Systematic Biology 66(2):197–204.

    b. Zizka et al. (2019) CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases. Methods in Ecology and Evolution 10:744-751.

    d. Price et al. (2019) Big data little help in megafauna mysteries. Nature 558(7):23-25

About

Information and instructions for the Big data Biogeography course 2021. https://azizka.github.io/big_data_biogeography/

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