Regional and global observations of biogeochemical cycles, such as ecosystem-atmosphere fluxes or biospheric responses to climate, lead to high dimensional spatiotemporal data matrices. Environmental diagnostics and prognostics under non-stationary climate conditions require insight in the coupling of multiple data streams, posing novel problems to statistics and bioinformatics. Merging the expertise from relevant backgrounds is expected to allow the identification of common goals and open new methodological perspectives.
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