Objective
Biodiversity underlies ecosystem functioning. To achieve the basis for a sustainable management of natural resources under current environmental change, we thus need a unified theory of the forces structuring vast sets of ecosystems and taxonomical groups on Earth. For the first time, such a synthesis is now within reach, based on a recent revolution in sampling methodology, globally relevant ecological data, and advances in statistical methods for linking immense data to community ecological theory. In LIFEPLAN, we bring together the key expertise needed to generate and interpret Big Ecological Data for a global synthesis of biotic patterning across our planet: world leaders in community ecology, methods for automated species recognition, and Bayesian statistics for immense data. 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 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 spatio-temporal structure of life on Earth. Working together will allow each of us to tackle what we regard as the ultimate challenges in our own fields, while simultaneously collaborating around solutions changing the face of modern biodiversity science. Now is the time for this project, as the big data and big methods emerging today coincide with a great need for global understanding of biodiversity structure and dynamics.
Fields of science
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencesmathematicsapplied mathematicsstatistics and probabilitybayesian statistics
- natural sciencesphysical sciencesastronomyplanetary sciencesplanets
- natural sciencesbiological sciencesecologyecosystems
Programme(s)
Topic(s)
Funding Scheme
ERC-SyG - Synergy grantHost institution
40100 Jyvaskyla
Finland