A new synthesis built on big data combined with novel statistical methods.
Our objectives are to generate a new understanding of biodiversity patterns and dynamics by developing fundamentally new methods for big data statistics. To this end, we will generate fully standardized, global big data on a range of species groups, thus allowing quantification of variation in ecological communities at spatial scales covering six orders of magnitude (from 0.1 km to 10000 km), across tens of thousands of species. The resulting data motivate the development of transformative big data statistics, in particular highly scalable algorithms for spatio-temporal and network-structured data, as well as methods for automated species identification from DNA, audio and image samples. As a key deliverable, we will develop global joint species distribution models describing the spatiotemporal structure of life on Earth.
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