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A century of change in North Sea plankton communities explored through integrating historical datasets
Bedford, J.; Johns, D.; McQuatters-Gollop, A. (2019). A century of change in North Sea plankton communities explored through integrating historical datasets. ICES J. Mar. Sci./J. Cons. int. Explor. Mer 76(1): 104-112. https://dx.doi.org/10.1093/icesjms/fsy148
In: ICES Journal of Marine Science. Academic Press: London. ISSN 1054-3139; e-ISSN 1095-9289, more
Peer reviewed article  

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Keywords
    Aquatic communities > Plankton
    Marine/Coastal
Author keywords
    disparate data; historical ecology; policy assessments; shifting baselines

Authors  Top 
  • Bedford, J.
  • Johns, D., more
  • McQuatters-Gollop, A.

Abstract
    Plankton communities make useful ecosystem indicators, and taking a historical perspective on plankton community composition provides insights into large-scale environmental change. Much of our understanding of long temporal-scale change in plankton communities in the North Sea has been provided by the Continuous Plankton Recorder (CPR) survey, operating since 1931, with consistent time-series data available since 1958. This article further increases the temporal scale of our understanding of community change in the North Sea by combining the CPR dataset with a digitized collection of plankton surveys undertaken by ICES from 1902 to 1912. After steps taken to integrate the two disparate datasets, differences in overall community composition between time periods suggest that the multidecadal changes observed through the CPR survey time period may have occurred from a non-stable baseline that was already on a trajectory of change. Therefore, a stable historical time period in which plankton communities are assessed against for any impact of human pressures may be hard to define for the North Sea and instead underlying variation needs to be encompassed within any baseline chosen. Further evidence for the influence of large-scale changes in sea surface temperature driving change in plankton community composition was found using the extended dataset.

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