Climate is changing around the world. This change is impacting species of wild animals. In this project, we will use four decades of bird sightings and climate data to predict the distribution of a bird species in the Scottish Highlands and see how its distribution changed over the years. We will use data from the [Global Biodiversity Information Facility](www.gbif.org) and a subset of the [UKCP09 climate data](https://www.metoffice.gov.uk/climate/uk/data/ukcp09) from the [UK Met Office](https://www.metoffice.gov.uk/).
- 1Tracking a changing climate
- 2Mapping a changing climate
- 3Fieldwork in the digital age – download the data
- 4Sorting out the bad eggs – data cleaning
- 5Nesting the data
- 6Making things spatial - projecting our observations
- 7Extract exactly what we want
- 9Making models - with caret
- 10Prediction probabilities
- 11A map says more than a thousand words
Data Science Manager at Nielsen
Laurens has been using R for over ten years. He holds a PhD from the University of Cambridge where he used geospatial machine learning and modeling to predict the future of the world's fisheries. He has worked in a wide range of domains, from the UN and NGOs over the credit and insurance sector to retail and ad tech. You can find his blog at janlauge.github.io.