4-8 November 2019
Freie Universität Berlin; Otto-von-Simson-Straße 26, 14195 Berlin
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.
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
Students and researchers working with biodiversity data and biogeography, including large species occurrence data in biogeography or biodiversity research. The course is in English. Example data will be available for all excises, but students are encouraged to bring their own datasets. During the course, there will be time to work with the students data.
Two weeks before the start, participants will be provided with five articles as pdfs, to be read prior to the workshop.
Monday- 09:30- 17:30
Morning: Introduction, Lecture Potential of big data in biogeography
Afternoon: Lecture and hands on “Common public biogeographic databases and how to obtain data from them”
COURSE + REFRESHMENTS
COURSE + REFRESHMENTS + LUNCH and ACCOMMODATION
Registration deadline: 4th October 2019
> 30 days before the start date = 30% cancellation fee
< 30 days before the start date= No Refund.
Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.