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Genomics meets remote sensing in global change studies: monitoring and predicting phenology, evolution and biodiversity


Yamasaki, Eri; Altermatt, Florian; Cavender-Bares, Jeannine; Schuman, Meredith C; Zuppinger-Dingley, Debra; Garonna, Irene; Schneider, Fabian D; Guillén-Escribà, Carla; van Moorsel, Sofia J; Hahl, Terhi; Schmid, Bernhard; Schaepman-Strub, Gabriela; Schaepman, Michael E; Shimizu, Kentaro K (2018). Genomics meets remote sensing in global change studies: monitoring and predicting phenology, evolution and biodiversity. Current Opinion in Environmental Sustainability, 29:177-186.

Abstract

Although the monitoring and prediction of ecosystem dynamics under global change have been extensively assessed, large gaps remain in our knowledge, including a need for concepts in rapid evolution and phenotypic plasticity, and a lack of large-scale and long-term monitoring. Recent genomic studies using the model species Arabidopsis predict that plastic and evolutionary changes in phenology may affect plant reproduction. We propose that three genomic-scale methods would enhance global change studies. First, genome-wide RNA sequencing enables monitoring of diverse functional traits and phenology. Second, sequencing of DNA variants highlights the importance of genetic variation and evolution. Third, DNA metabarcoding provides efficient and unbiased ecosystem monitoring. Integrating these genomic-scale studies with remote sensing will promote the understanding and prediction of biodiversity change.

Abstract

Although the monitoring and prediction of ecosystem dynamics under global change have been extensively assessed, large gaps remain in our knowledge, including a need for concepts in rapid evolution and phenotypic plasticity, and a lack of large-scale and long-term monitoring. Recent genomic studies using the model species Arabidopsis predict that plastic and evolutionary changes in phenology may affect plant reproduction. We propose that three genomic-scale methods would enhance global change studies. First, genome-wide RNA sequencing enables monitoring of diverse functional traits and phenology. Second, sequencing of DNA variants highlights the importance of genetic variation and evolution. Third, DNA metabarcoding provides efficient and unbiased ecosystem monitoring. Integrating these genomic-scale studies with remote sensing will promote the understanding and prediction of biodiversity change.

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Additional indexing

Item Type:Journal Article, refereed, further contribution
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
08 University Research Priority Programs > Global Change and Biodiversity
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Language:English
Date:March 2018
Deposited On:10 Apr 2018 10:12
Last Modified:24 Apr 2018 14:40
Publisher:Elsevier
ISSN:1877-3435
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.cosust.2018.03.005

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