Claire H. Davies

Australian Dust Storm Associated with Extensive Aspergillus sydowii Fungal “Bloom” in Coastal Waters

ABSTRACT A massive central Australian dust storm in September 2009 was associated with abundant fungal spores (150,000/m3) and hyphae in coastal waters between Brisbane (27°S) and Sydney (34°S). These spores were successfully germinated from formalin-preserved samples, and using molecular sequencing of three different genes (the large subunit rRNA gene [LSU], internal transcribed spacer [ITS[, and beta-tubulin gene), they were conclusively identified as Aspergillus sydowii, an organism circumstantially associated with gorgonian coral fan disease in the Caribbean. Surprisingly, no human health or marine ecosystem impacts were associated with this Australian dust storm event. Australian fungal cultures were nontoxic to fish gills and caused a minor reduction in the motility of Alexandrium or Chattonella algal cultures but had their greatest impacts on Symbiodinium dinoflagellate coral symbiont motility, with hyphae being more detrimental than spores. While we have not yet seen any soft coral disease outbreaks on the Australian Great Barrier Reef similar to those observed in the Caribbean and while this particular fungal population was non- or weakly pathogenic, our observations raise the possibility of future marine ecosystem pathogen impacts from similar dust storms harboring more pathogenic strains.

Modeling what we sample and sampling what we model: challenges for zooplankton model assessment

Zooplankton are the intermediate trophic level between phytoplankton and fish, and are an important component of carbon and nutrient cycles, accounting for a large proportion of the energy transfer to pelagic fishes and the deep ocean. Given zooplankton’s importance, models need to adequately represent zooplankton dynamics. A major obstacle, though, is the lack of model assessment. Here we try and stimulate the assessment of zooplankton in models by filling three gaps. The first is that many zooplankton observationalists are unfamiliar with the biogeochemical, ecosystem, and size-based and individual-based models that have zooplankton functional groups, so we describe their primary uses and how each typically represents zooplankton. The second gap is that many modelers are unaware of the zooplankton data that are available, and are unaccustomed to the different zooplankton sampling systems, so we describe the main sampling platforms and discuss their strengths and weaknesses for model assessment. Filling these gaps in our understanding of models and observations provides the necessary context to address the last gap – a blueprint for model assessment of zooplankton. We detail two ways that zooplankton biomass/abundance observations can be used to assess models: data wrangling that transforms observations to be more similar to model output; and observation models that transform model outputs to be more like observations. We hope that this review will encourage greater assessment of zooplankton in models and ultimately improve the representation of their dynamics.

Over 75 years of zooplankton data from Australia

Zooplankton are the key trophic link between primary producers and fish in pelagic ecosystems. Historically, there are few zooplankton time series in Australia, with no data sets longer than two years prior to 2008. Here we compile 98 676 abundance records of more than 1000 zooplankton taxa from unpublished research cruises, student projects, published literature, and the recent Integrated Marine Observing System (IMOS). This data set covers the entire coastal and shelf region of Australia and dates back to 1938. Most records are for copepods, but there are also data for other taxa such as decapods, chaetognaths, thaliaceans, appendicularians, and cladocerans. Metadata are provided for each record, including dates, coordinates, and information on mesh size and sampling methods. To facilitate analysis across the multiple data sets, we have updated the species names according to the World Register of Marine Species (WoRMS) and converted units to abundance per cubic meter. These data will be valuable for studies of biodiversity, biogeography, impacts of climate change, and ecosystem health. We encourage researchers holding additional Australian zooplankton data to contact us and contribute their data to the data set so we can periodically publish updates.

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

There 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.

Systematic, continental scale temporal monitoring of marine pelagic microbiota by the Australian Marine Microbial Biodiversity Initiative

Sustained observations of microbial dynamics are rare, especially in southern hemisphere waters. The Australian Marine Microbial Biodiversity Initiative (AMMBI) provides methodologically standardized, continental scale, temporal phylogenetic amplicon sequencing data describing Bacteria, Archaea and microbial Eukarya assemblages. Sequence data is linked to extensive physical, biological and chemical oceanographic contextual information. Samples are collected monthly to seasonally from multiple depths at seven sites: Darwin Harbour (Northern Territory), Yongala (Queensland), North Stradbroke Island (Queensland), Port Hacking (New South Wales), Maria Island (Tasmania), Kangaroo Island (South Australia), Rottnest Island (Western Australia). These sites span ~30° of latitude and ~38° longitude, range from tropical to cold temperate zones, and are influenced by both local and globally significant oceanographic and climatic features. All sequence datasets are provided in both raw and processed fashion. Currently 952 samples are publically available for bacteria and archaea which include 88,951,761 bacterial (72,435 unique) and 70,463,079 archaeal (24,205 unique) 16 S rRNA v1-3 gene sequences, and 388 samples are available for eukaryotes which include 39,801,050 (78,463 unique) 18 S rRNA v4 gene sequences.

A database of chlorophyll a in Australian waters

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.

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

Claire H. Davies, Alex Coughlan, Gustaaf Hallegraeff, Penelope Ajani, Linda Armbrecht, Natalia Atkins, Prudence Bonham, Steve Brett, Richard Brinkman, Michele Burford, Lesley Clementson, Peter Coad, Frank Coman, Diana Davies, Jocelyn Dela-Cruz, Michelle Devlin, Steven Edgar, Ruth Eriksen, Miles Furnas, Christel Hassler, David Hill, Michael Holmes, Tim Ingleton, Ian Jameson, Sophie C. Leterme, Christian Lønborg, James McLaughlin, Felicity McEnnulty, A. David McKinnon, Margaret Miller, Shauna Murray, Sasi Nayar, Renee Patten, Tim Pritchard, Roger Proctor, Diane Purcell-Meyerink, Eric Raes, David Rissik, Jason Ruszczyk, Anita Slotwinski, Kerrie M. Swadling, Katherine Tattersall, Peter Thompson, Paul Thomson, Mark Tonks, Thomas W. Trull, Julian Uribe-Palomino, Anya M. Waite, Rouna Yauwenas, Anthony Zammit & Anthony J. Richardson