CAMBON, Marine; TRILLAT, Marine; LESUR‐KUPIN, Isabelle; BURLETT, Régis; CHANCEREL, Emilie; GUICHOUX, Erwan; PIOUCEAU, Lucie; CASTAGNEYROL, Bastien; LE PROVOST, Grégoire; ROBIN, Stéphane; RITTER, Yves; VAN HALDER, Inge; DELZON, Sylvain; BOHAN, David; VACHER, Corinne

doi:10.1111/mec.17149

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CAMBON, Marine
Biodiversité, Gènes & Communautés [BioGeCo]

TRILLAT, Marine
Biodiversité, Gènes & Communautés [BioGeCo]

LESUR‐KUPIN, Isabelle
Biodiversité, Gènes & Communautés [BioGeCo]
HelixVenture

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Article de revue

Este ítem está publicado en

Molecular Ecology. 2023-10-10, vol. 32, n° 22, p. 5944-5958

Wiley

Resumen en inglés

Next-generation biomonitoring proposes to combine machine-learning algorithms with environmental DNA data to automate the monitoring of the Earth's major ecosystems. In the present study, we searched for molecular biomarkers of tree water status to develop next-generation biomonitoring of forest ecosystems. Because phyllosphere microbial communities respond to both tree physiology and climate change, we investigated whether environmental DNA data from tree phyllosphere could be used as molecular biomarkers of tree water status in forest ecosystems. Using an amplicon sequencing approach, we analysed phyllosphere microbial communities of four tree species (Quercus ilex, Quercus robur, Pinus pinaster and Betula pendula) in a forest< Leer menos

Palabras clave en inglés

environmental DNA data

machine-learning algorithms

molecular biomarkers

next-generation biomonitoring

phyllosphere microbial communities

water stress

DOI

http://dx.doi.org/10.1111/mec.17149

Proyecto ANR

Biosurveillance Next-Gen des changements dans la structure et le fonctionnement des écosystèmes
Diversité et Productivité des forêTs impactées par le Changement Climatique

Orígen

Importado de Hal

Centros de investigación

BioGeCo (Biodiversité Gènes & Communautés) - UMR 1202