The founding charter of the Omic Biodiversity Observation Network (Omic BON).

Omic BON is a thematic Biodiversity Observation Network under the Group on Earth Observations Biodiversity Observation Network (GEO BON), focused on coordinating the observation of biomolecules in organisms and the environment. Our founding partners include representatives from national, regional, and global observing systems; standards organizations; and data and sample management infrastructures. By coordinating observing strategies, methods, and data flows, Omic BON will facilitate the co-creation of a global omics meta-observatory to generate actionable knowledge.

Estimating planktonic diversity through spatial dominance patterns in a model ocean.

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques.

Anthropogenic contaminants in Indo-Pacific humpback and Australian snubfin dolphins from the central and southern Great Barrier Reef.

We present the first evidence of accumulation of organochlorine compounds (DDTs, PCBs, HCB) and polycyclic aromatic hydrocarbons (PAHs) in Indo-Pacific humpback and Australian snubfin dolphins from the central and southern Great Barrier Reef. These dolphins are considered by the Great Barrier Marine Park Authority to be high priority species for management. Analyses of biopsy samples, collected from free ranging individuals, showed PAHs levels comparable to those reported from highly industrialized countries.

Can we detect oceanic biodiversity hotspots from space?

Understanding the variability of marine biodiversity is a central issue in microbiology. Current observational programs are based on in situ studies, but their implementation at the global scale is particularly challenging, owing to the ocean extent, its temporal variability and the heterogeneity of the data sources on which compilations are built. Here, we explore the possibility of identifying phytoplanktonic biodiversity hotspots from satellite.