eDNA metabarcoding as a new surveillance approach for coastal Arctic biodiversity.
eDNA metabarcoding as a new surveillance approach for coastal Arctic biodiversity.
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DOI:
10.1002/ece3.4213
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发表时间:
2018-08
影响因子:
2.6
通讯作者:
Bernatchez L
中科院分区:
文献类型:
--
作者:
Lacoursière-Roussel A;Howland K;Normandeau E;Grey EK;Archambault P;Deiner K;Lodge DM;Hernandez C;Leduc N;Bernatchez L
Because significant global changes are currently underway in the Arctic, creating a large‐scale standardized database for Arctic marine biodiversity is particularly pressing. This study evaluates the potential of aquatic environmental DNA (eDNA) metabarcoding to detect Arctic coastal biodiversity changes and characterizes the local spatio‐temporal distribution of eDNA in two locations. We extracted and amplified eDNA using two COI primer pairs from ~80 water samples that were collected across two Canadian Arctic ports, Churchill and Iqaluit, based on optimized sampling and preservation methods for remote regions surveys. Results demonstrate that aquatic eDNA surveys have the potential to document large‐scale Arctic biodiversity change by providing a rapid overview of coastal metazoan biodiversity, detecting nonindigenous species, and allowing sampling in both open water and under the ice cover by local northern‐based communities. We show that DNA sequences of ~50% of known Canadian Arctic species and potential invaders are currently present in public databases. A similar proportion of operational taxonomic units was identified at the species level with eDNA metabarcoding, for a total of 181 species identified at both sites. Despite the cold and well‐mixed coastal environment, species composition was vertically heterogeneous, in part due to river inflow in the estuarine ecosystem, and differed between the water column and tide pools. Thus, COI‐based eDNA metabarcoding may quickly improve large‐scale Arctic biomonitoring using eDNA, but we caution that aquatic eDNA sampling needs to be standardized over space and time to accurately evaluate community structure changes.
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影响因子:
4.6
作者:
Eguíluz VM;Fernández-Gracia J;Irigoien X;Duarte CM
通讯作者:
Duarte CM
影响因子:
3.7
作者:
Foote AD;Thomsen PF;Sveegaard S;Wahlberg M;Kielgast J;Kyhn LA;Salling AB;Galatius A;Orlando L;Gilbert MT
通讯作者:
Gilbert MT
DOI:
10.1139/cjfas-2014-0473
发表时间:
2015-08-01
影响因子:
2.4
作者:
Chan, Farrah T.;MacIsaac, Hugh J.;Bailey, Sarah A.
通讯作者:
Bailey, Sarah A.
影响因子:
3.7
作者:
Elbrecht V;Leese F
通讯作者:
Leese F
影响因子:
7.7
作者:
Geller, J.;Meyer, C.;Hawk, H.
通讯作者:
Hawk, H.