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. 2018 Feb 20;5:180018. doi: 10.1038/sdata.2018.18

A database of chlorophyll a in Australian waters

Claire H Davies 1,a, Penelope Ajani 2, Linda Armbrecht 3, Natalia Atkins 4, Mark E Baird 1, Jason Beard 5, Pru Bonham 1, Michele Burford 6, Lesley Clementson 1, Peter Coad 7, Christine Crawford 5, Jocelyn Dela-Cruz 8, Martina A Doblin 2, Steven Edgar 9, Ruth Eriksen 1,10, Jason D Everett 11, Miles Furnas 12, Daniel P Harrison 13, Christel Hassler 14, Natasha Henschke 15, Xavier Hoenner 4, Tim Ingleton 8, Ian Jameson 16, John Keesing 17, Sophie C Leterme 18, M James McLaughlin 17, Margaret Miller 9, David Moffatt 19, Andrew Moss 20, Sasi Nayar 21, Nicole L Patten 21, Renee Patten 22, Sarah A Pausina 9,23, Roger Proctor 4, Eric Raes 24,25, Malcolm Robb 26, Peter Rothlisberg 9, Emily A Saeck 6, Peter Scanes 27, Iain M Suthers 11,13, Kerrie M Swadling 5,10, Samantha Talbot 12, Peter Thompson 1, Paul G Thomson 28, Julian Uribe-Palomino 9, Paul van Ruth 21, Anya M Waite 24,25, Simon Wright 29, Anthony J Richardson 9,30
PMCID: PMC5819481  PMID: 29461516

Abstract

Chlorophyll a is the most commonly used indicator of phytoplankton biomass in the marine environment. It is relatively simple and cost effective to measure when compared to phytoplankton abundance and is thus routinely included in many surveys. Here we collate 173, 333 records of chlorophyll a collected since 1965 from Australian waters gathered from researchers on regular coastal monitoring surveys and ocean voyages into a single repository. This dataset includes the chlorophyll a values as measured from samples analysed using spectrophotometry, fluorometry and high performance liquid chromatography (HPLC). The Australian Chlorophyll a database is freely available through the Australian Ocean Data Network portal (https://portal.aodn.org.au/). These data can be used in isolation as an index of phytoplankton biomass or in combination with other data to provide insight into water quality, ecosystem state, and relationships with other trophic levels such as zooplankton or fish.

Subject terms: Physical oceanography, Marine biology, Marine chemistry

Background & Summary

As the pigment chlorophyll a is present in all photosynthetic phytoplankton species1 and is relatively easy and cheap to measure, it has become a standard proxy for estimating phytoplankton biomass2. Samples require minimal processing and storage in the field and are not easily contaminated. Chlorophyll a is cheaper to process using spectrophotometry or fluorometry relative to estimating phytoplankton abundance/biomass using cell counts. Importantly, chlorophyll a measurements also account for the pico and nano plankton in the samples, which are substantially underestimated by phytoplankton analysts using light microscopy. These smaller size classes account for a significant fraction (commonly>70%) of total chlorophyll a biomass3,4.

However, whilst using chlorophyll a as an estimate of phytoplankton biomass is widespread, the relationship between the two variables is complex. Not only does the carbon to chlorophyll ratio of phytoplankton vary with species and morphological characteristics, the chlorophyll a content of a phytoplankton cell per unit of organic matter will vary with light intensity, nutrient availability, temperature and cell age5–8. Despite these complexities chlorophyll a remains useful as a coarse proxy for phytoplankton biomass.

In Australian waters chlorophyll a concentrations are generally lowest in the tropical and subtropical oceanic regions (0.05-0.5 μgL−1) and higher in the Southern Ocean and temperate regions (up to 1.5 μgL−1)2. In coastal zones, the chlorophyll a concentration can fluctuate greatly as phytoplankton blooms develop, peak and crash. The coastal station at Port Hacking, project number P782 in our database, is a good example where chlorophyll a concentrations typically vary between 0.1–8.0 μgL−1 over an annual cycle, with peaks sometimes up to 15 μgL−1 at 20–40 m depth coinciding with phytoplankton blooms9. In inshore estuaries and bays, high chlorophyll a values can also indicate the system is eutrophic with elevated nutrient levels from terrestrial run off. Chlorophyll a is therefore used in several water quality monitoring programs across the country (e.g. project number P1072 Ecosystem Health Monitoring Program in Moreton Bay, Queensland, Australia, http://healthywaterways.org/initatives/monitoring). Concentrations of chlorophyll a also vary throughout the oceans with oceanographic features such as upwelling and fronts which drive nutrients towards surface layers and thus enhance chlorophyll a levels10,11.

Here we collate all available chlorophyll a data from Australian waters, gathered from researchers, students, government bodies, state agencies, councils and databases, along with the associated metadata through the process as detailed in Fig. 1. The chlorophyll a values are as measured and no attempt has been made to synthesise the data across analysis methods. The Australian Chlorophyll a database is available through the Australian Ocean Data Network portal (AODN: https://portal.aodn.org.au/), the main repository for marine data in Australia. The Australian Chlorophyll a Database will be maintained and updated through the CSIRO data centre, with periodic updates sent to the AODN. A snapshot of the Australian Chlorophyll a Database at the time of this publication has been assigned a DOI and will be maintained in perpetuity by the AODN (Data Citation 1).

Figure 1. Flow diagram of data collation, verification and release to AODN.

Figure 1

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Methods

There are three standard methods for determining chlorophyll a concentrations in water samples: spectrophotometry, fluorometry and high performance liquid chromatography (HPLC). Spectrophotometric methods are described fully in Strickland and Parsons (1972)12, fluorometry in Zeng (2015)13, and HPLC in Shoaf (1978)14. A comprehensive discussion of the details of each method and its merits can be found in Manotura et al. (1997) and Roy et al. (2011)15,16.

To measure chlorophyll a, a known volume of water sample is filtered through a glass fibre filter paper, typically 0.45-0.7 μm pore size, under a gentle vacuum. The volume filtered varies depending on the chlorophyll a concentration expected in the sample, with more water filtered at lower concentrations, but the volume should be sufficient to produce a green tinge on the filter paper. Chlorophyll a is extracted from the filter paper with an organic solvent (e.g. acetone). Concentrations are derived from a spectrophotometer to record the light absorbance at particular wavelengths or a fluorometer that transmits an excitation beam of light in the blue range (440–460 nm) and detects the light fluoresced by chlorophyll a in the red wavelength range (650–700 nm). This fluorescence is directly proportional to the concentration of chlorophyll a. For HPLC, the filter paper is similarly extracted with an organic solvent, however pigments are then separated by passing the extract through a chromatographic column and then measured either spectrophotometrically or fluorometrically.

Although HPLC has become the accepted benchmark for the quantification of chlorophyll a the volume of data collated in this database shows that spectrophotometric and fluorometric extraction methods are much more commonly used (Fig. 2). HPLC has the advantages of being more accurate and also quantifies all the other accessory pigments but it does require specialised equipment and technical skills which make it more expensive. Spectrophotometry and fluorometry are simpler and effective, but unlike HPLC they do not differentiate between chlorophyll functional types and accessory pigments. To improve the spectrophotometric and fluorometric methods, an acidifying step (e.g. addition of a small amount of hydrochloric acid) can be added after the extraction to reduce errors associated with chlorophyll degradation products2.

Figure 2. Histogram showing the range of samples over the data set period discriminated by sampling method.

Figure 2

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All three methods require laboratory time and sample preparation, but in-water phytoplankton biomass can also be estimated using in-situ fluorometers. We have excluded such observations from the current dataset because chlorophyll a estimates from in-situ fluorometers are notoriously difficult to calibrate to an absolute standard. Although the accuracy of fluorometers is continually improving they require regular calibration, including against other methods13. The instruments are somewhat unstable and measurements are influenced by the presence of other environmental factors, particularly coloured dissolved organic matter (CDOM), diel, seasonal and regional effects and would also require correction for these factors13. The calibration routines must account for physical factors such as sensor drift, instrument design, biofouling etc. as well as the phytoplankton community composition and physiology in the sample environment, which may vary over space and time.

Data collated for this database have come from many different sources, from long-term monitoring programs run by local governments concerned with water quality to ocean voyages on research vessels. Data have been standardised to μgL−1, and the collection and analysis methods have been included so that inter-project comparisons can be considered. We have collated data from researchers, local and state government agencies and regional databases, e.g. AESOP (The Australian-waters Earth Observation Phytoplankton-type products) database (http://aesop.csiro.au/). The database will be maintained by the CSIRO Data Centre and updates will be available periodically through the AODN.

Data Records

Each data record represents the chlorophyll a measurement taken at a point in space and time and has a unique record identification number, P(project_id)_(sample_id)_(record_id). Each data record belongs to a project, with each project having a unique identification number, Pxxx. A project is defined as a set of data records that have been collected together, usually as a cruise or study, and have the same sampling and analysis methods and the same person analysing the samples. Metadata ascribed to a project relates to all data records within that project. Details to identify each project, along with their associated samples, time and space information (Table 1 (available online only), Fig. 3) allow users to select and download discrete datasets in their area of interest. While each sample within a project has a unique sample_id, there may be more than one chlorophyll a record per sample if multiple replicates or depths were sampled. The sample_id has not been changed from the original data set to maintain traceability. Therefore P(project_id)_(sample_id) may be duplicated within projects, but the chlorophyll a records within that sample, taken at different depths for example, are given a unique record_id.

Table 1. Summary of the project data included in the data set.

Project id Project Name Custodian Acknowledgement Location Project start Project end No records Methods
Where Ae=Acetone Extraction; Me=Methanol Extraction+Ac=Acidified+S=Spectrophotometry; F=Fluorometry                
1072 Estuarine Marine Ecosystem Health Monitoring Program David Moffat (DSITI)   Moreton Bay QLD 2001-03-21 2002-02-20 50140 AeS det lim 0.1 or 0.5 μgL-1
1229 Swan River monitoring Malcolm Robb (DOW) DOW WA Swan River WA 1979-03-21 2017-03-20 44569 AeS det lim 1 to 0.1 μgL-1
1073 Historical ambient chl monitoring Queensland Andrew Moss (DSITI)   QLD 1993-09-14 2013-02-20 22690 AeS det lim 1; 2; or 0.1 μgL-1
1071 Central Queensland ambient Chl Queensland Andrew Moss (DSITI)   Central QLD 2000-10-17 2015-03-16 13524 AeS det lim 0.1 or 0.5 μgL-1
806 CRC Reef project Miles Furnas (AIMS) GBRMPA Great Barrier Reef QLD 1986-02-07 2005-01-14 6532 AeAcSF
1065 Environmental Protection Agency Victoria Renee Patten (EPA VIC) EPA Victoria VIC 2008-02-21 2014-07-22 3879 AeS
1081 NSW Estuaries Chla Peter Scanes (Env NSW)   NSW estuaries 2007-07-16 2016-04-28 3803 AeS or AeF
1122 Coastal Zone Colour Scanner Published literature   Great Barrier Reef QLD 1979-03-06 1981-07-27 3092 AeF
1076 GBR water quality Sam Talbot (AIMS) AIMS Great Barrier Reef QLD 2007-10-03 2015-07-26 3055 AeAcf
969 IDIOTS SAZ_SNARK BROKE SAZ_SENSE BROKEWEST CLIVAR KACTAS Southern Ocean Voyages25 Simon Wright and AADC (AAD)   Southern Ocean 1996-01-20 2007-02-19 1999 HPLC
1051 Huon Estuary Study Huon River sampling Lesley Clementson (CSIRO)   Huon River TAS 1996-07-02 1998-10-05 1799 HPLC
1064 Hornsby Council monitoring Peter Coad (Hornsby Council)   Hornsby NSW 1994-10-06 2015-06-23 1792 AeS det lim 0.2 μgL-1
17 North West Cape23,24 Sam Talbot (AIMS)   North West Cape WA 1997-10-26 2003-04-21 1603 AeAcf
1053 SS2012_T06 SS2010_V05 SS2011_V04 SS2013_V04 SS2012_V04 Southern Surveyor Voyages26–28 Anya Waite (UWA)   West Coast Australia 2010-07-10 2013-07-21 1202 AeAcF; HPLC
7 Scott Reef sampling29 Sam Talbot (AIMS)   Scott Reef WA 2008-06-24 2009-12-04 1134 AeAcf
1084 ASAC project30–37 Simon Wright and AADC (AAD)   Southern Ocean 1987-03-27 1997-11-10 960 HPLC
6 Kimberley sampling38 Sam Talbot (AIMS)   Kimberley WA 2011-01-20 2014-03-22 953 AeAcf
1126 Productivity eastern GAB Paul van Ruth (SARDI)   GAB SA 2004-02-14 2006-03-22 838 MeS
1080 Noctiluca scintillans39,40 Jocelyn Dela-Cruz (UNSW)   Coastal NSW 1998-09-02 1999-03-11 809 AeS det lim 0.3 μgL-1
599 IMOS National Reference Stations22 Anthony Richardson (CSIRO) IMOS Australia 2009-01-15 2016-08-22 789 HPLC
797 Wet dry tropical estuary41 Michele Burford (Griffith University) Tropical Rivers & Coastal Knowledge program Gulf of Carpentaria QLD 2008-10-20 2010-06-03 551 AeAc
1077 Exchanges across the shelf-ocean boundary Sam Talbot (AIMS) AIMS Great Barrier Reef QLD 2011-10-31 2014-06-18 529 AeAcf
1128 Sydney Harbour Daniel Harrison (SIMS)   Sydney Harbour NSW 2012-10-17 2017-02-22 527 AeS
995 SS072003 SS012004 SS032006 SS092004 SS2010_V09 Southern Surveyor Voyages42 Lesley Clementson (CSIRO)   South West Australia 2003-08-23 2010-10-30 490 HPLC
509 Gulf of Carpentaria phytoplankton43–45 Michele Burford (Griffith University) FRDC Gulf of Carpentaria QLD 1986-04-08 2005-03-19 458 AeAcS
1031 Biogeochemical dynamics of an intermittently open estuary46 Jason Everett (UNSW)   Smiths Lake NSW 2002-10-03 2008-10-20 420 AeS
793 SS2010_V01 SS2011_V02 Southern Surveyor Voyages Christel Hassler (UNIGE)   East Coast Australia 2010-01-23 2011-06-01 333 HPLC
4 Darwin Harbour Sam Talbot (AIMS)   Darwin Harbour NT 2002-12-11 2004-12-08 320 AeAcf
1058 Storm Bay monitoring program Kerrie Swadling (IMAS)   Storm Bay TAS 2009-11-09 2015-04-22 311 AeS
782 Port Hacking 100 m station Port Hacking 100 m station10 Penelope Ajani (Macquarie University) IMOS / OEH Port Hacking NSW 1997-04-03 2009-12-07 301 AeS
1082 Ocean Colour validation eReefs Lesley Clementson (CSIRO) IMOS Great Barrier Reef QLD 1999-01-15 2014-12-15 248 HPLC
972 SOOP voyages Lesley Clementson (CSIRO)   Australia 1999-12-01 2000-10-09 226 HPLC
589 Bloom monitoring program Ian Jameson (CSIRO)   Australia 1993-01-14 1995-05-23 220 AeS
1025 Two Rocks SRFME - Ocean colour Lesley Clementson (CSIRO)   Two Rocks WA 2002-02-26 2004-12-17 194 HPLC
1059 Continental Shelf Sophie C. Leterme (Flinders University)   East Coast Australia 2011-01-28 2013-07-31 175 MeS
1074 Mackay estuaries ambient chl monitoring Queensland Andrew Moss (DSITI)   Mackay QLD 2014-10-16 2015-02-10 144 AeS det lim 0.1 μgL-1
988 GBR_Sept2007 GBR Voyages Lesley Clementson (CSIRO)   Great Barrier Reef QLD 2005-08-23 2008-04-23 135 HPLC
796 Phytoplankton abundance off New South Wales Linda Armbrecht (Macquarie University) IMOS / OEH / NSW MPA / NMSC / CSIRO Coffs Harbour NSW 2011-05-27 2012-09-18 128 HPLC
788 SS072005 Southern Surveyor Voyages Peter Thompson (CSIRO)   West Coast Australia 2005-07-21 2005-08-10 125 HPLC
1006 TIP2000 Ocean Colour validation Lesley Clementson (CSIRO)   West Coast Australia 2000-09-11 2000-10-01 118 HPLC
609 Coorong Wetlands and Gulf St Vincent Sophie C. Leterme (Flinders University)   Coorong Wetlands SA 2010-07-01 2013-08-01 110 MeS
1075 WAMSI SW Coastal Biogeography James McLaughlin (CSIRO) WAMSI South Coast WA 2007-02-20 2009-12-18 109 AeS
1130 SS092006 SS10200847,48 Jason Everett (UNSW)   Tasman Sea 2006-09-27 2008-10-18 106 AeS
1007 North West Shelf Lesley Clementson (CSIRO)   North West Shelf WA 1999-01-03 2003-07-17 102 HPLC
1013 FR101997 Franklin Voyages Lesley Clementson (CSIRO)   TAS 1997-12-01 1997-12-07 99 HPLC
1134 SS2012_T03 SS2012_T0749 Martina Doblin (UTS)   Australia 2009-07-26 2013-08-06 99 HPLC
1027 Bunbury_2002_2005 SRFME - Ocean colour Lesley Clementson (CSIRO)   Bunbury WA 2003-03-04 2005-02-02 92 HPLC
980 FRE_feb2008 FREsept2003 FREAug2004 FR200001_PNG FRE_feb05 Ocean Colour validation Lesley Clementson (CSIRO)   Central QLD 2000-01-18 2008-02-09 89 HPLC
971 Sniper voyages S1 to S7 Lesley Clementson (CSIRO)   SE QLD 1999-08-16 2001-01-08 88 HPLC
1063 UWA gliders Paul Thomson (UWA) IMOS WA 2015-01-18 2016-01-27 87 HPLC
1050 SS032010 Southern Surveyor Voyages Peter Thompson (CSIRO)   NW Shelf WA 2010-04-15 2010-05-04 87 HPLC
786 SS042007 Peter Thompson (CSIRO)   West Coast WA 2007-05-16 2007-06-04 83 HPLC
1114 Moreton Bay EHMP Emily Saeck (Griffith Uni) Healthy Waterways Moreton Bay QLD 2009-05-28 2011-03-03 78 HPLC
999 Tasmanian Voyages Lesley Clementson (CSIRO)   TAS 2007-05-21 2008-12-04 78 HPLC
479 Moreton Bay floods spatial 2011 Julian Uribe Palomino (CSIRO)   Moreton Bay QLD 2011-01-19 2011-12-21 77 HPLC
990 Tonka voyages T1 to T8 Lesley Clementson (CSIRO)   SE QLD 1997-07-10 1998-11-09 75 HPLC
1133 FR14/199839,40 Iain Suthers (UNSW)   East Coast Australia 1998-11-16 1998-11-20 68 AeAcS
996 JurienBay_2002_2005 SRFME - Ocean colour Lesley Clementson (CSIRO)   Jurien Bay WA 2003-05-27 2005-02-24 65 HPLC
1060 WAMSI dredging James McLaughlin (CSIRO) WAMSI Kimberley WA 2013-03-09 2015-02-26 61 AeS
1002 Laurina Voyages P1 to P4 Ocean Colour validation Lesley Clementson (CSIRO)   NSW 1997-09-10 1998-04-27 54 HPLC
1055 Bonny and Du Coudeic Canyons Sasi Nayar (SARDI)   Kangaroo Island SA 2008-02-07 2008-02-21 48 AeS
1062 Total Biodiversity Study James McLaughlin (CSIRO) Total Foundation King George River WA 2013-06-06 2013-06-11 47 AeS
1127 Desalination project Paul van Ruth (SARDI)   Adelaide SA 2009-06-12 2011-11-21 42 HPLC
1022 AOCWG_Apr_2003 Ocean Colour validation Lesley Clementson (CSIRO)   West Coast Australia 2003-04-14 2003-04-17 39 HPLC
591 Moreton Bay plankton community dynamics Sarah Pausina (UQ) Healthy Waterways          
ARC LPO883663 Moreton Bay QLD 2009-02-04 2011-09-28 39 AeS      
985 DtreeOct2003 DtreeApr2004 Daintree samples Lesley Clementson (CSIRO)   Daintree QLD 2003-09-29 2004-04-03 34 HPLC
1015 LB3172 Ocean Colour validation Lesley Clementson (CSIRO)   Central QLD 2002-10-21 2002-10-29 34 HPLC
1113 North West Bay Lesley Clementson (CSIRO)   North West Bay TAS 2006-10-02 2006-10-03 31 HPLC
1125 Roles of viruses in coral reef systems Nicole Patten (SARDI)   Heron Island GBR QLD 2005-11-17 2005-11-27 30 AeF
1061 WAMSI Kimberley James McLaughlin (CSIRO) WAMSI Kimberley WA 2014-04-01 2015-04-21 30 AeS
979 Moreton Bay Samples Lesley Clementson (CSIRO)   Moreton Bay QLD 2003-01-28 2003-01-31 27 HPLC
1069 FR051995 Franklin Voyages Peter Thompson (CSIRO)   West Coast Australia 1995-06-14 1995-06-15 24 HPLC
786 SS042007 Southern Surveyor Voyages Peter Thompson (CSIRO)   West Coast Australia 2007-05-16 2007-06-04 24 HPLC
986 Beagle samples legs1;5;6 Lesley Clementson (CSIRO)   South West Australia 2003-08-04 2004-02-17 23 HPLC
993 Townsville_GBR_Jun2002 Ocean Colour validation Lesley Clementson (CSIRO)   Townsville QLD 2002-06-05 2002-06-12 20 HPLC
1024 Elena_Rose_May_1997 Ocean Colour validation Lesley Clementson (CSIRO)   NSW 1997-05-14 1997-05-15 11 HPLC
1020 HImay04 Ocean Colour validation Lesley Clementson (CSIRO)   Central QLD 2004-05-19 2004-05-24 8 HPLC
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Figure 3. Sample locations mapped by analysis type, by HPLC and by spectrophotometry and fluorescence.

Figure 3

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Each data record has been quality controlled. Data with insufficient or unreliable metadata were removed. All depths, times and locations have been validated and are within the boundaries expected for each project.

Technical Validation

The database has been constructed to ensure data extraction is straight forward, although the user needs to be aware of two caveats. First, if chlorophyll b or other pigments are present, then fluorometry may underestimate or spectrophotometry overestimate the chlorophyll a concentration relative to HPLC17–19. When an acidification step is included, the accuracy of chlorophyll a from spectrophotometric and fluorometric methods is improved as effects of chlorophyll degradation products are reduced18. Without further pigment information comparisons between methods need to be carefully considered. This database reports values as measured and does not attempt to compare values across methods, leaving this to the discretion of the user. Second, for the HPLC data we are reporting the sum of the chlorophyll a pigments including the divinyl chlorophyll a components. The user should thus be careful when comparing data across datasets where different analysis methods have been used. Metadata have been provided in as much detail as is available so the user is aware of methodological details specific to the project.

Chlorophyll a values can be reported in micrograms per litre (μgL−1), milligrams per cubic metre (mgm−3) (1 μgL−1=1 mgm−3) or as depth integrated values, i.e. per square metre (mgm−2). In this data set we have standardised to μgL−1. Where depth integrated values were given, the appropriate sample depth from the study was used to convert to μgL−1.

All times have been converted to Coordinated Universal Time, UTC. Dates with no time component remain as reported.

The value −999 has been assigned to values that were below detection limits. The detection limit has also been included, where known, in the sample_method field of the metadata table.

Usage Notes

This dataset and metadata has been made freely available through the AODN (Data Citation 1). The Australian Chlorophyll a database is complementary to the Australian Zooplankton Database20 and the Australian Phytoplankton Database21, both of which provide species-level data and are available through the AODN. Many projects in this data set have corresponding data in these species level databases and can be matched to the project via Project_id and to individual samples, via sample_id, or by using the time and date information. For example, the project 599 has data on zooplankton and phytoplankton composition, included in the aforementioned databases, plus chlorophyll a data in the current data set. Because the three data sets were collected at the same locations and times as part of the Integrated Marine Observing System (IMOS) National Reference Stations (NRS), they can be analysed together to investigate relationships among different trophic levels. These combined data have been used in an analysis of climate-driven variability contrasting the 2010 El Niño with the 2011 La Niña22. Further examples of using chlorophyll data in partnership with species-level phytoplankton and zooplankton data using data are from project 17 in the North West Cape, Western Australia23,24.

Projects 599, 1063, 1064, 1065, 1071, 1072, 1074, 1078 and 1129 are ongoing, and data will continue to be added to the Australian chlorophyll a database; for further information, contact the data custodian as listed in the metadata. The most updated version of P599 IMOS National Reference Stations, is available at: https://portal.aodn.org.au/search?uuid=f48531e2-f182-56ca-e043-08114f8c7f2e.

Additional information

How to cite this article: Davies, C. H. et al. A database of chlorophyll a in Australian waters. Sci. Data 5:180018 doi: 10.1038/sdata.2017.18 (2018).

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Material

sdata201818-isa1.zip (11.1KB, zip)

Acknowledgments

We acknowledge the contributions from all collaborators and their institutions. If data from multiple projects are used, please acknowledge this publication; if individual project data are used, please acknowledge use of data as per the custodian information. We would also encourage data users to enter into collaboration with the researchers involved in the data they use–understanding the history of a project will add value to your research. The relevant acknowledgement data is available from the metadata files attached to the data. If using data from Project 599 the National Reference Stations please use the following acknowledgement: “Data sourced from the Integrated Marine Observing System (IMOS) – IMOS is a national collaborative research infrastructure, supported by the Australian Government. It is operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent.” Similarly, for Project 806, please use the following acknowledgement: “A part of the data included in the database was obtained with support from the Great Barrier Reef Marine Park Authority, through funding from the Australian Government Reef Program and from the Australian Institute of Marine Science”. For Project 1129 the information is supplied on the condition that if used in a study or publication the Department of Water is acknowledged as the source of the information. Citations may take the following form:

• Water INformation (WIN) database - discrete sample data. [10-04-2017]. Department of Water, Water Information section, Perth Western Australia.

Footnotes

The authors declare no competing financial interests.

Data Citations

  1. Davies C. H. 2017. Australian Ocean Data Network. http://dx.doi.org/10.4225/69/586f220c3f708

References

  1. Jeffrey S. W in Primary Productivity in the Sea. ed. (Paul G.Falkowski) 33–58 (Springer: US, 1980). [Google Scholar]
  2. Jeffrey S. W. & Hallegraeff G. M in Biology of marine plants Ch. 14, 310–348 (Longman, 1990). [Google Scholar]
  3. Maranon E. et al. Patterns of phytoplankton size structure and productivity in contrasting open-ocean environments. Marine Ecology Progress Series 216, 43–56 (2001). [Google Scholar]
  4. Buitenhuis E. T. et al. Picophytoplankton biomass distribution in the global ocean. Earth System Science Data 4, 37–46 (2012). [Google Scholar]
  5. Hallegraeff G. M. Comparison of different methods used for quantitative-evaluation of biomass of freshwater phytoplankton. Hydrobiologia 55, 145–165 (1977). [Google Scholar]
  6. Jakobsen H. H. & Markager S. Carbon-to-chlorophyll ratio for phytoplankton in temperate coastal waters: Seasonal patterns and relationship to nutrients. Limnology and Oceanography 61, 1853–1868 (2016). [Google Scholar]
  7. Menden-Deuer S. & Lessard E. J. Carbon to volume relationships for dinoflagellates, diatoms, and other protist plankton. Limnology and Oceanography 45, 569–579 (2000). [Google Scholar]
  8. Roy S., Sathyendranath S. & Platt T. Size-partitioned phytoplankton carbon and carbon-to-chlorophyll ratio from ocean colour by an absorption-based bio-optical algorithm. Remote Sensing of Environment 194, 177–189 (2017). [Google Scholar]
  9. Hallegraeff G. M. Seasonal Study of Phytoplankton Pigments and Species at a Coastal Station off Sydney: Importance of Diatoms and the Nanoplankton. Mar. Biol. 61, 2–3 (1981). [Google Scholar]
  10. Ajani P. et al. Establishing baselines: a review of eighty years of phytoplankton diversity and biomass in southeastern Australia. Oceanography and Marine Biology 54, 387–412 (2016). [Google Scholar]
  11. Armbrecht L. H. et al. Phytoplankton composition under contrasting oceanographic conditions: Upwelling and downwelling (Eastern Australia). Continental Shelf Research 75, 54–67 (2014). [Google Scholar]
  12. Strickland J. D. H. & Parsons T. R. A practical handbook of seawater analysis. 2 edn, 310 (Fisheries Research Board of Canada, 1972). [Google Scholar]
  13. Zeng L. H. & Li D. L. Development of In Situ Sensors for Chlorophyll Concentration Measurement. Journal of Sensors 2015, 16 (1978). [Google Scholar]
  14. Shoaf W. T. Rapid method for separation of chlorophylis-a and chlorophylis-b by high-pressure liquid-chromatography. Journal of Chromatography 152, 247–249 (1978). [Google Scholar]
  15. Mantoura R., Jeffrey S. W., Llewellyn C. A., Claustre H., Morales C. E. in Phytoplankton pigments in oceanography eds (Jeffrey S. W., Mantoura R.F.C. & Wright S.W.) Ch. 14, 361–380 (UNESCO, 1997). [Google Scholar]
  16. Roy S., Llewellyn C. A., Egeland E. S. & Johnsen G. Phytoplankton pigments: characterization, chemotaxonomy and applications in oceanography (Cambridge University Press, 2011). [Google Scholar]
  17. Pinckney J., Papa R. & Zingmark R. Comparison of high-performance liquid-chromatographic, spectrophotometric, and fluorometric methods for determining chlorophyll a concentrations in estuarine sediments. Journal of Microbiological Methods 19, 59–66 (1994). [Google Scholar]
  18. Daemen E. Comparison of methods for the determination of chlorophyll in estuarine sediments. Netherlands Journal of Sea Research 20, 21–28 (1986). [Google Scholar]
  19. Murray A. P., Gibbs C. F., Longmore A. R. & Flett D. J. Determination of chlorophyll in marine waters-intercomparison of a rapid HPLC method with full HPLC, spectrophotometric and fluorometric methods. Marine Chemistry 19, 211–227 (1986). [Google Scholar]
  20. Davies C. H. et al. Over 75 years of zooplankton data from Australia. Ecology 95, 3229–3229 (2014). [Google Scholar]
  21. Davies C. H. et al. A database of marine phytoplankton abundance, biomass and species composition in Australian waters. Scientific Data 3 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Thompson P. A. et al. Climate variability drives plankton community composition changes: the 2010-2011 El Nino to La Nina transition around Australia. Journal of Plankton Research 37, 966–984 (2015). [Google Scholar]
  23. Furnas M. Intra-seasonal and inter-annual variations in phytoplankton biomass, primary production and bacterial production at North West Cape, Western Australia: Links to the 1997-1998 El Nino event. Continental Shelf Research 27, 958–980 (2007). [Google Scholar]
  24. McKinnon A. D., Duggan S., Carleton J. H. & Bottger-Schnack R. Summer planktonic copepod communities of Australia's North West Cape (Indian Ocean) during the 1997-99 El Nino/La Nina. Journal of Plankton Research 30, 839–855 (2008). [Google Scholar]
  25. Wright S. Aurora Australis Voyage 6 (SAZ - Subantarctic Zone) 1997-98 Chlorophyll a Data Australian Antarctic Data Centre - CAASM Metadata https://data.aad.gov.au/metadata/records/SAZ_Chlorophyll (2014).
  26. Raes E. J. et al. Sources of new nitrogen in the Indian Ocean. Global Biogeochemical Cycles 29, 1283–1297 (2015). [Google Scholar]
  27. Raes E. J. et al. Changes in latitude and dominant diazotrophic community alter N-2 fixation. Marine Ecology Progress Series 516, 85–102 (2014). [Google Scholar]
  28. Waite A. M. et al. Cross-shelf transport, oxygen depletion, and nitrate release within a forming mesoscale eddy in the eastern Indian Ocean. Limnology and Oceanography 61, 103–121 (2016). [Google Scholar]
  29. McKinnon A., Duggan S., Böttger-Schnack R., Gusmão L. & O'Leary R. Depth structuring of pelagic copepod biodiversity in waters adjacent to an Eastern Indian Ocean coral reef. Journal of Natural History 47, 639–665 (2013). [Google Scholar]
  30. Wright S. Role of Antarctic marine protists in trophodynamics and global change and impact of UV-B on these organisms - V1 of the Aurora Australis, 1995-96 - HI-HO, HI-HO Australian Antarctic Data Centre - CAASM Metadata https://data.aad.gov.au/metadata/records/ASAC_40_HIHOHIHO (2016).
  31. Wright S. Nella Dan: ADBEX I Cruise - Chlorophyll a data Australian Antarctic Data Centre - CAASM Metadata https://data.aad.gov.au/metadata/records/ADBEX_I_Chlorophyll (2014).
  32. Wright S. Aurora Australis Voyage 2 (ONICE) 1997-98 Chlorophyll a Data Australian Antarctic Data Centre-CAASM Metadata https://data.aad.gov.au/metadata/records/ONICE_Chlorophyll (2014).
  33. Wright S. Aurora Australis Voyage 6 (FISHOG) 1991-92 Heard Island Chlorophyll a Data Australian Antarctic Data Centre - CAASM Metadata https://data.aad.gov.au/metadata/records/AADC-00094 (2014).
  34. Wright S. Aurora Australis Voyage 7 (KROCK) 1992-93 Chlorophyll a Data Australian Antarctic Data Centre - CAASM Metadata https://data.aad.gov.au/metadata/records/AADC-00096 (2014).
  35. Wright S. Chlorophyll a data collected on voyage 4 of the Aurora Australis in the 1991-1992 season Australian Antarctic Data Centre-CAASM Metadata https://data.aad.gov.au/metadata/records/199192040_Chlorophyll (2014).
  36. Wright S. Chlorophyll a data collected on the AAMBER II cruise of the Aurora Australis Australian Antarctic Data Centre - CAASM Metadata https://data.aad.gov.au/metadata/records/AAMBER_II_Chlorophyll (2014).
  37. Wright S. Aurora Australis Voyage 9 (WOES) 1992-93 Chlorophyll a Data Australian Antarctic Data Centre - CAASM Metadata https://data.aad.gov.au/metadata/records/WOES_Chlorophyll (2014).
  38. McKinnon A. D., Duggan S., Holliday D. & Brinkman R. Plankton community structure and connectivity in the Kimberley-Browse region of NW Australia. Estuarine Coastal and Shelf Science 153, 156–167 (2015). [Google Scholar]
  39. Dela-Cruz J., Middleton J. H. & Suthers I. M. The influence of upwelling, coastal currents and water temperature on the distribution of the red tide dinoflagellate, Noctiluca scintillans, along the east coast of Australia. Hydrobiologia 598, 59–75 (2008). [Google Scholar]
  40. Dela-Cruz J., Middleton J. H. & Suthers I. M. Population growth and transport of the red tide dinoflagellate, Noctiluca scintillans, in the coastal waters off Sydney Australia, using cell diameter as a tracer. Limnology and Oceanography 48, 656–674 (2003). [Google Scholar]
  41. Burford M. A. et al. Controls on phytoplankton productivity in a wet-dry tropical estuary. Estuarine Coastal and Shelf Science 113, 141–151 (2012). [Google Scholar]
  42. Everett J. D. & Doblin M. A. Characterising primary productivity measurements across a dynamic western boundary current region. Deep-Sea Research Part I-Oceanographic Research Papers 100, 105–116 (2015). [Google Scholar]
  43. Burford M. A., Rothlisberg P. C. & Wang Y. G. Spatial and temporal distribution of tropical phytoplankton species and biomass in the Gulf of Carpentaria, Australia. Marine Ecology Progress Series 118, 255–266 (1995). [Google Scholar]
  44. Rothlisberg P. et al. Phytoplankton community structure and productivity in relation to the hydrological regime of the Gulf of Carpentaria, Australia, in summer. Marine and Freshwater Research 45, 265–282 (1994). [Google Scholar]
  45. Burford M. & Rothlisberg P. Factors limiting phytoplankton production in a tropical continental shelf ecosystem. Estuarine, Coastal and Shelf Science 48, 541–549 (1999). [Google Scholar]
  46. Everett J. D., Baird M. E. & Suthers I. M. Nutrient and plankton dynamics in an intermittently closed/open lagoon, Smiths Lake, south-eastern Australia: An ecological model. Estuarine Coastal and Shelf Science 72, 690–702 (2007). [Google Scholar]
  47. Henschke N., Everett J. D., Baird M. E., Taylor M. D. & Suthers I. M. Distribution of life-history stages of the salp Thalia democratica in shelf waters during a spring bloom. Marine Ecology Progress Series 430, 49–62 (2011). [Google Scholar]
  48. Henschke N. et al. Demography and interannual variability of salp swarms (Thalia democratica). Marine Biology 161, 149–163 (2014). [Google Scholar]
  49. Robinson C. M. et al. Phytoplankton absorption predicts patterns in primary productivity in Australian coastal shelf waters. Estuarine Coastal and Shelf Science 192, 1–16 (2017). [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Davies C. H. 2017. Australian Ocean Data Network. http://dx.doi.org/10.4225/69/586f220c3f708

Supplementary Materials

sdata201818-isa1.zip (11.1KB, zip)

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