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Tristan Cordier

Tristan Cordier

Senior Researcher

trco@norceresearch.no
+47 56 10 75 13
Jahnebakken 5, 5007 Bergen, Norway

My research aims to better understand the relationships between microbial biodiversity and ecosystems functions and services. To this end, I combine environmental genomics and bioinformatics to address questions spanning the continuum from basic to applied research. My current activity focuses on reconstructing past marine ecosystems functioning using ancient eukaryotic DNA archived in the sediment record. This work aims to deliver DNA-based reconstructions of the past sea ice cover and carbon sequestration in polar regions.

Tristan Cordier

Division

Climate & Environment

Research Groups

Molekylær økologi og paleogenomikk - MEP

More information about Tristan Cordier

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Projects
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Publications
Arctic Paleoceanography Cruise KH21-234 with R/V Kronprins Haakon – NORCE 2022
PaleoEcoGen: Unlocking the power of ancient environmental DNA to understand past ecological trends – Past Global Changes Magazine 2022
Patterns of eukaryotic diversity from the surface to the deep-ocean sediment – Science Advances 2022
Environmental DNA metabarcoding for benthic monitoring: A review of sediment sampling and DNA extraction methods – Science of the Total Environment 2021
Eukaryotic biodiversity and spatial patterns in the Clarion-Clipperton Zone and other abyssal regions: insights from sediment DNA and RNA metabarcoding – Frontiers in Marine Science 2021
Scientific and budgetary tradeoffs between morphological and molecular methods for deep-sea biodiversity assessment – Integrated Environmental Assessment and Management 2021
Microbial community diversity and composition in river sediments contaminated with tetrabromobisphenol A and copper – Chemosphere 2021
Benthic monitoring of oil and gas offshore platforms in the North Sea using environmental DNA metabarcoding – Molecular Ecology 2021
Monitoring the ecological status of rivers with diatom eDNA metabarcoding: a comparison of taxonomic markers and analytical approaches for the inference of molecular diatom index – Molecular Ecology 2021
Supervised machine learning is superior to indicator value inference in monitoring the environmental impacts of salmon aquaculture using eDNA metabarcodes – Molecular Ecology 2021
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News

Insight

A first unified vision of the full ocean eukaryotic biodiversity