All scientific data collected by the Australian Antarctic program (AAp) are eventually described in the Catalogue of Australian Antarctic and Subantarctic Metadata (CAASM). CAASM can be used to search through AAp data descriptions, and it also provides links to access publicly available datasets, which can either be immediately downloaded or obtained from the Australian Antarctic Data Centre (AADC).

View the full metadata record
Citation
Hancock, A.M., Davidson, A.T., McKinlay, J., McMinn, A., Schulz, K. and van den Enden, R.L. (2019) Ocean acidification changes the structure of an Antarctic coastal protistan community - R Code Analysis, Ver. 1, Australian Antarctic Data Centre - doi:10.26179/5d37b916205e9, Accessed: 2020-01-25
Title
Ocean acidification changes the structure of an Antarctic coastal protistan community - R Code Analysis
Data Centre
Australian Antarctic Data Centre, Australia
DOI
doi:10.26179/5d37b916205e9
Created Date
2017-05-28
Revision Date
2019-07-24
Parent record
AAS_4026_Ocean_Acidification_Marine_Microbes_Parent

Description

An unreplicated, six-level dose-response experiment was conducted using 650 L incubation tanks (minicosms) adjusted to fugacity of carbon dioxide (fCO2) from 343 to 11641 uatm. The minicosms were filled with near-shore water from Prydz Bay, East Antarctica and the protistan composition and abundance was determined by microscopy analysis of samples collected during the 18 day incubation. Abundant taxa with low variance were examined separately, but rare taxa with high variance were combined into functional groups (descriptions below). Cluster analyses and ordinations were performed on Bray-Curtis resemblance matrixes formed from square-root transformated abundance data. This transformation was assessed as appropriate for reducing the influence of abundance species, as judged from a one-to-one relationship between observed dissimilarities and ordination distances (ie. Shepard diagram, not shown). The Bray-Curtis metric was used as it is recommended for ecological data due to its treatment of joint absences (ie. these do not contribute towards similarity), and giving more weight to abundant taxa rather than rare taxa. The data days 1 to 8 and then days 8 to 18 were analysed separately to distinguish community structure in the acclimation period and in the exponential growth phase during the incubation period of the experiment.

Hierarchical agglomerative cluster analyses, based on the Bray-Curtis resemblance matrix, was performed using group-average linkage. Significantly different clusters of samples were determined using SIMPROF (similarity profile permutations method) with an alpha value of 0.05 and based on 1000 permutations. An unconstrained ordination by non-metric multidimensional scaling (nMDS) was performed on the resemblance matrix with a primary (`weak') treatment of ties. This was repeated over 50 random starts to ensure a globally optimal solution according to . Clusters are displayed in the nMDS using colour. Weighted average of sample scores are shown in the nMDS to show the approximate contribution of each species to each sample. The assumption of a linear trend for predictors within the ordination was checked for each covariate, and in all instances was found to be justified.

A constrained canonical analysis of principal coordinates (CAP) was conducted according to the Vegan protocol using the Bray-Curtis resemblance matrix. This analysis was used to assess the significance of the environmental covariates, or constraints, in determining the microbial community structure. Unlike the nMDS ordination, the CAP analysis uses the resemblance matrix to partition the total variance in the community composition into unconstrained and constrained components, with the latter comprising only the variation that can be attributed to the constraining variables, fCO2, Si, P and NOx. Random reassignment of sample resemblance was performed over 199 permutations to compute the pseudo-F statistic as a measure of significance of each environmental constraint in the structural change of the microbial community. A forward selection strategy was used to choose a minimum subset of significant constraints that still account for the majority of the variation within the microbial community.

All analysis were performed using R v1.0.136 and the add-on package vegan v2.4-2.

Protistan taxa and functional group descriptions and abbreviations:
Autotrophic Dinoflagellate (AD) - including Gymnodinium sp., Heterocapsa and other unidentified autotrophic dinoflagellates
Bicosta antennigera (Ba)
Chaetoceros (Cha) - mainly Chaetoceros castracanei and Chaetoceros tortissimus but also other Chaetoceros present including C. aequatorialis var antarcticus, C. cf. criophilus, C. curvisetus, C. dichaeta, C. flexuosus, C. neogracilis, C. simplex
Choanoflagellates (except Bicosta) (Cho) - mainly Diaphanoeca multiannulata but also Parvicorbicula circularis and Parvicorbicula socialis present in low numbers
Ciliates (Cil) - mostly cf. Strombidium but other ciliates also present
Discoid Centric Diatoms greater than 40 microns (DC.l) - unidentified centrics of the genera Thalassiosira, Landeria, Stellarima or similar
Discoid Centric Diatoms 20 to 40 microns (DC.m) - unidentified centrics of the genera Thalassiosira, Landeria, Stellarima or similar
Discoid Centric Diatoms less than 20 microns (DC.s) - unidentified centrics of the genera Thalassiosira
Euglenoid (Eu) - unidentified
Fragilariopsis greater than 20 microns (F.l) - mainly Fragilariopsis cylindrus, some Fragilariopsis kerguelensis and potentially some Fragilariopsis curta present in very low numbers
Fragilariopsis less than 20 microns (F.s) - mainly Fragilariopsis cylindrus, and potentially some Fragilariopsis curta present in very low numbers
Heterotrophic Dinoflagellates (HD) - including Gyrodinium glaciale, Gyrodinium lachryma, other Gyrodinium sp., Protoperidinium cf. antarcticum and other unidentified heterotrophic dinoflagellates
Landeria annulata (La)
Other Centric Diatoms (OC) - Corethronb pennatum, Dactyliosolen tenuijuntus, Eucampia antarctica var recta, Rhizosolenia imbricata and other Rhizosolenia sp.
Odontella (Od) - Odontella weissflogii and Odontella litigiosa
Other Flagellates (OF) - Dictyocha speculum, Chrysochromulina sp., unknown haptophyte, Phaeocystis antarctica (flagellate and gamete forms), Mantoniella sp., Pryaminmonas gelidicola, Triparma columaceae, Triparma laevis subsp ramispina, Geminigera sp., Bodo sp., Leuocryptos sp., Polytoma sp., cf. Protaspis, Telonema antarctica, Thaumatomastix sp. and other unidentified nano- and picoplankton
Other Pennate Diatoms (OP) - Entomonei kjellmanii var kjellmanii, Navicula gelida var parvula, Nitzschia longissima, other Nitzschia sp., Plagiotropus gaussi, Pseudonitzschia prolongatoides, Synedropsis sp.
Phaeocystis antarctica (Pa) - colonial form only
Proboscia truncata (Pro)
Pseudonitzschia subcurvata (Ps)
Pseudonitzschia turgiduloies (Pt)
Stellarima microtrias (Sm)
Thalassiosira antarctica (Ta)
Thalassiosira ritscheri (Tr)
*.se = standard error for mean cell per L estimate ie. Tr.se = standard error for the mean cells per L for Thalassiosira ritscheri based on individual FOV estimates as described in methods above.

Show more...

Purpose

The Southern Ocean is particularly vulnerable to ocean acidification due to its cold temperatures, extensive upwelling and naturally large seasonal fluctuations in pH. Microbes are an important component of these waters through the roles they play in driving productivity, elemental cycles and ocean biogeochemistry, meaning their response to environmental stressors is a key determinant of Southern Ocean feedbacks to global climate change (Arrigo and Thomas, 2004; Arrigo et al., 2008; Kirchman, 2008). Despite their importance, relatively little is known about the sensitivity of Antarctica marine microbes to ocean acidification and this limits our ability to predict the how the Southern Ocean will be impacted in the future, and the feedback this may have on global climate change.
This study will assessed the following questions on a natural microbial community from nearshore East Antarctic waters.
1. Is there a change in protistan community composition and abundance with increased concentration of pCO2? And what pCO2 concentration elicits this change?
2. Does an acclimation period allow the protistan community the cope to increased concentrations of pCO2?
3. Is the effect of increased pCO2 concentration species-specific? And if it is, what are the potential driving mechanisms
behind these responses?
4. Does the results of this minicosm experiment agree with those of previously conducted experiments at this site by Davidson et al. (2016) and Thomson et al. (2016) in the austral summer of 2008-09? Therefore is the response of the protistan community consistent both across a season and between a season at Prydz Bay, East Antarctica?

Quality

This is based on unreplicated data, standard errors are calculated based on microscope field of view pseudoreplicates.
The following functional groups were present in very low numbers and therefore there was high variance between counts resulting in high standard error of mean cells per litre estimates;
Autotrophic and heterotrophic dinoflagellates, ciliates, other flagellates, discoid centric diatoms (greater than 40, 20 to 40 and less than 20 microns), other centric and pennate diatoms.
All other taxa and functional groups have low variance on counts and are statistically viable.

Access

These data are publicly available for download from the provided URL. However, it is recommended that the metadata investigators be contacted before using these data.

Temporal Coverages

Spatial Coverages

Data Resolution

Temporal Resolution:
18 Day(s)

Science Keywords

Additional Keywords

  • Ocean Acidification
  • Minicosm

Locations

  • GEOGRAPHIC REGION > POLAR
  • CONTINENT > ANTARCTICA
  • OCEAN > SOUTHERN OCEAN

Platforms

  • LABORATORY
  • FIELD INVESTIGATION

Instruments

  • SCANNING ELECTRON MICROSCOPES
  • MICROSCOPES

Researchers

  • hancock, alyce (INVESTIGATOR,TECHNICAL CONTACT,DIF AUTHOR)
  • davidson, andrew (INVESTIGATOR)
  • mckinlay, john (INVESTIGATOR)
  • mcminn, andrew (INVESTIGATOR)
  • schulz, kai (INVESTIGATOR)
  • van den enden, derrick (INVESTIGATOR)

Use Constraints

This data set conforms to the CCBY Attribution License (http://creativecommons.org/licenses/by/4.0/).

Please follow instructions listed in the citation reference provided at http://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4026_Microscopy_Multivariate_Statistics_Rcode when using these data.

Creative Commons License