kkougiou / Using_biodiversity_data_for_biogeography

Information, scripts, exercises and example data for the Workshop 'Using biodiversity data in biogeography'. Please scroll down for more information.

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Workshop: Using spatial biodiveristy data for biogeography

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presented by Alexandre Antonelli & Alexander Zizka from the Antonelli lab, University of Gothenburg and Gothenburg Global Biodiversity Centre

This folder contains scripts and example data for the 'Using spatial biodiveristy data for biogeography' workshop.

BEFORE THE WORKSHOP: For the hands-on exercise please install R and Rstudio, and run the script '00_package_setup'(see above, just copy the text of the script into you R console to install dependencies).

Please do not hesitate to contact us if you have any questions.

Objectives

  1. Provide an overview on new tools (speciesgeocodeR, Infomap bioregions and sampBias) for using ‘big data’ occurrence data in biogeography and biodiversity science
  2. Provide the participants with a workflow to use large scale species occurrence data for biodiversity analyses (including both point localities and range maps)
  3. Provide an overview of how to use R for analysing large datasets of species occurrences (including data mining, visualisation, exploration, cleaning and applications)

Schedule

15:00 Lecture by Alexandre Antonelli setting the scene: where do we stand now in terms of biodiversity data? What are some of the main questions in ecology, evolution and biogeography that such data can be used to address? What are the main challenges, prospects and limitations?

15:45 Discussion of the lecture and a short break

16:00 Lecture by Alexander Zizka, "Caveats when using large scale spatial biodiversity data for biogeography and new Software to deal with them. speciesgeocodeR, Infomap Bioregions and SampBias.

16:20 Short break

16:30 Short presentation of all participants and there interest in spatial biodiversity data

16:45 Software demonstration: specsgeocodeR, Infomap bioregions and sampBias

17:00 hands-on software exercises with time to discuss participants’ individual data and questions (depending on the number of participants)

18:45 Wrap up

after 19:00 Informal joint dinner at a close-by location for those interested.

Exercises

The folder contains the below exercises for the participants to choose, depending on their skill level and interest. Each exercise includes an example dataset, some questions and a “solution script” so participants can use them later on their own data.

  1. Downloading geographic occurrence data from GBIF (R)
  2. Geographic cleaning of occurrence data from errors common to biological databases (R & Graphical User Interface)
  3. Species richness maps and range size estimation from point occurrences (R)
  4. Using point occurrences for taxon-specific bioregionalization (GUI)
  5. Classifying species into descrete areas for historical biogeography (R)
  6. Quantifying collection bias related to accessibility (R & GUI)

Background

The public availability of large-scale species distribution data has increased drastically over the last ten years. In particular, the digitalization of collections from museums and herbaria, the input from human and machine observations, and the aggregation of information in public databases such as the Global Biodiversity Information Facility (GBIF) have contributed significantly to this development. This is leading to a ‘big data’ revolution in biogeography, which holds enormous potential for understanding large scale patterns and drivers of biodiversity. In this workshop, we will present some examples of how biodiversity data can be used to address key evolutionary and ecological questions, we will then familiarize with some of the tools available to use large species distribution data for analysing biodiversity, and we will address how to deal with common concerns such as data quality and sampling biases.

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Information, scripts, exercises and example data for the Workshop 'Using biodiversity data in biogeography'. Please scroll down for more information.


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