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A database of marine phytoplankton abundance, biomass and species composition in Australian waters

Authors: Anthony J. Richardson; Anthony J. Richardson; Jason Ruszczyk; Tim Pritchard; Thomas W. Trull; Thomas W. Trull; Felicity R. McEnnulty; +50 Authors

A database of marine phytoplankton abundance, biomass and species composition in Australian waters

Abstract

AbstractThere have been many individual phytoplankton datasets collected across Australia since the mid 1900s, but most are unavailable to the research community. We have searched archives, contacted researchers, and scanned the primary and grey literature to collate 3,621,847 records of marine phytoplankton species from Australian waters from 1844 to the present. Many of these are small datasets collected for local questions, but combined they provide over 170 years of data on phytoplankton communities in Australian waters. Units and taxonomy have been standardised, obviously erroneous data removed, and all metadata included. We have lodged this dataset with the Australian Ocean Data Network (http://portal.aodn.org.au/) allowing public access. The Australian Phytoplankton Database will be invaluable for global change studies, as it allows analysis of ecological indicators of climate change and eutrophication (e.g., changes in distribution; diatom:dinoflagellate ratios). In addition, the standardised conversion of abundance records to biomass provides modellers with quantifiable data to initialise and validate ecosystem models of lower marine trophic levels.

Countries
Australia, Switzerland, Germany
Keywords

Statistics and Probability, Data Descriptor, Databases, Factual, Climate Change, Library and Information Sciences, 1710 Information Systems, Education, 1706 Computer Science Applications, Community ecology, Biomass, 2613 Statistics and Probability, Ecosystem, Marine biology, 020, Ecology not elsewhere classified, Statistics, Australia, Biodiversity, Eutrophication, Corrigenda, Computer Science Applications, 1804 Statistics, Phytoplankton, phytoplankton, Probability and Uncertainty, 3309 Library and Information Sciences, Information Systems, 3304 Education, ddc: ddc:550

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    29
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%
Green
gold