TY - JOUR
T1 - Genomics meets remote sensing in global change studies
T2 - monitoring and predicting phenology, evolution and biodiversity
AU - Yamasaki, Eri
AU - Altermatt, Florian
AU - Cavender-Bares, Jeannine
AU - Schuman, Meredith C.
AU - Zuppinger-Dingley, Debra
AU - Garonna, Irene
AU - Schneider, Fabian D.
AU - Guillén-Escribà, Carla
AU - van Moorsel, Sofia J.
AU - Hahl, Terhi
AU - Schmid, Bernhard
AU - Schaepman-Strub, Gabriela
AU - Schaepman, Michael E.
AU - Shimizu, Kentaro K.
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2017/12
Y1 - 2017/12
N2 - 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.
AB - 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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U2 - 10.1016/j.cosust.2018.03.005
DO - 10.1016/j.cosust.2018.03.005
M3 - Review article
AN - SCOPUS:85044941859
SN - 1877-3435
VL - 29
SP - 177
EP - 186
JO - Current Opinion in Environmental Sustainability
JF - Current Opinion in Environmental Sustainability
ER -