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Currie, Ashleigh R; Tait, Karen; Parry, Helen E; de Francisco-Mora, Beatriz; Hicks, Natalie; Osborn, A M; Widdicombe, Steve; Stahl, Henrik (2017): Seawater carbonate chemistry and gene abundance and community composition in two contrasting coastal marine sediments [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.890872, Supplement to: Currie, AR et al. (2017): Marine Microbial Gene Abundance and Community Composition in Response to Ocean Acidification and Elevated Temperature in Two Contrasting Coastal Marine Sediments. Frontiers in Microbiology, 8, https://doi.org/10.3389/fmicb.2017.01599

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Abstract:
Marine ecosystems are exposed to a range of human-induced climate stressors, in particular changing carbonate chemistry and elevated sea surface temperatures as a consequence of climate change. More research effort is needed to reduce uncertainties about the effects of global-scale warming and acidification for benthic microbial communities, which drive sedimentary biogeochemical cycles. In this research, mesocosm experiments were set up using muddy and sandy coastal sediments to investigate the independent and interactive effects of elevated carbon dioxide concentrations (750 ppm CO2) and elevated temperature (ambient + 4 °C) on the abundance of taxonomic and functional microbial genes. Specific q-PCR primers were used to target archaeal, bacterial and cyanobacterial/chloroplast 16S rRNA in both sediment types. Nitrogen cycling genes archaeal and bacterial ammonia monooxygenase (amoA) and bacterial nitrite reductase (nirS) were specifically targeted to identify changes in microbial gene abundance and potential impacts on nitrogen cycling. In muddy sediment, microbial gene abundance, including amoA and nirS genes, increased under elevated temperature and reduced under elevated CO2 after 28 days, accompanied by shifts in community composition. In contrast, the combined stressor treatment showed a non-additive effect with lower microbial gene abundance throughout the experiment. The response of microbial communities in the sandy sediment was less pronounced, with the most noticeable response seen in the archaeal gene abundances in response to environmental stressors over time. 16S rRNA genes (amoA and nirS) were lower in abundance in the combined stressor treatments in sandy sediments. Our results indicated that marine benthic microorganisms, especially in muddy sediments, are susceptible to changes in ocean carbonate chemistry and seawater temperature, which ultimately may have an impact upon key benthic biogeochemical cycles.
Keyword(s):
Benthos; Coast and continental shelf; Community composition and diversity; Containers and aquaria (20-1000 L or < 1 m**2); Entire community; Laboratory experiment; North Atlantic; North Atlantic; Soft-bottom community; Temperate; Temperature
Further details:
Gattuso, Jean-Pierre; Epitalon, Jean-Marie; Lavigne, Héloïse; Orr, James C; Gentili, Bernard; Proye, Aurélien; Soetaert, Karline; Rae, James (2016): seacarb: seawater carbonate chemistry with R. R package version 3.1. https://cran.r-project.org/package=seacarb
Coverage:
Median Latitude: 56.365835 * Median Longitude: -2.832360 * South-bound Latitude: 56.365000 * West-bound Longitude: -2.848050 * North-bound Latitude: 56.366670 * East-bound Longitude: -2.816670
Date/Time Start: 2012-03-12T00:00:00 * Date/Time End: 2012-07-23T00:00:00
Event(s):
Eden_Estuary * Latitude: 56.365000 * Longitude: -2.848050 * Date/Time Start: 2012-03-12T00:00:00 * Date/Time End: 2012-07-23T00:00:00 * Method/Device: Experiment (EXP)
West_Sands * Latitude: 56.366670 * Longitude: -2.816670 * Date/Time Start: 2012-03-12T00:00:00 * Date/Time End: 2012-07-23T00:00:00 * Method/Device: Experiment (EXP)
Comment:
In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2016) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2018-05-23.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1Event labelEventHicks, Natalie
2TypeTypeHicks, NatalieStudy
3Experiment durationExp durationdaysHicks, Natalie
4TypeTypeHicks, NatalieSediment
5Depth, descriptionDepth descHicks, Natalie
6CampaignCampaignHicks, Natalie
7IdentificationIDHicks, NatalieFlume
8Day of experimentDOEdayHicks, Natalie
9ReplicateReplHicks, Natalie
10Temperature, waterTemp°CHicks, Natalietreatment
11Partial pressure of carbon dioxide (water) at sea surface temperature (wet air)pCO2water_SST_wetµatmHicks, Natalietreatment
12IdentificationIDHicks, NatalieSample no
13Gene abundanceGA#/gHicks, Natalie16S bacteria
14Gene abundanceGA#/gHicks, Natalie16S archaea
15Gene abundanceGA#/gHicks, Natalie16S cyanobacteria
16Gene abundanceGA#/gHicks, NatalieNirS
17Gene abundanceGA#/gHicks, NatalieamoA bacteria
18Gene abundanceGA#/gHicks, NatalieamoA archaea
19Gene abundanceGA#/gHicks, Nataliehzo
20Species richnessSHicks, Natalie
21Margelf indexMargelf indexHicks, Natalie
22Shannon Diversity IndexH'Hicks, Natalie
23Evenness of speciesEHicks, Natalie
24Sequence abundanceSequence abund%Hicks, NatalieGammaproteobacteria
25Sequence abundance, standard deviationSequence abund std dev±Hicks, NatalieGammaproteobacteria
26Sequence abundanceSequence abund%Hicks, NatalieDeltaproteobacteria
27Sequence abundance, standard deviationSequence abund std dev±Hicks, NatalieDeltaproteobacteria
28Sequence abundanceSequence abund%Hicks, NatalieCytophagia
29Sequence abundance, standard deviationSequence abund std dev±Hicks, NatalieCytophagia
30Sequence abundanceSequence abund%Hicks, NatalieFlavobacteria
31Sequence abundance, standard deviationSequence abund std dev±Hicks, NatalieFlavobacteria
32Sequence abundanceSequence abund%Hicks, NataliePlanctomycetacia
33Sequence abundance, standard deviationSequence abund std dev±Hicks, NataliePlanctomycetacia
34Sequence abundanceSequence abund%Hicks, NatalieActinobacteria
35Sequence abundance, standard deviationSequence abund std dev±Hicks, NatalieActinobacteria
36Sequence abundanceSequence abund%Hicks, NatalieChloroflexi
37Sequence abundance, standard deviationSequence abund std dev±Hicks, NatalieChloroflexi
38Sequence abundanceSequence abund%Hicks, NatalieFirmicutes
39Sequence abundance, standard deviationSequence abund std dev±Hicks, NatalieFirmicutes
40SalinitySalHicks, Natalie
41Alkalinity, totalATµmol/kgHicks, Natalie
42Alkalinity, total, standard deviationAT std dev±Hicks, Natalie
43Carbon, inorganic, dissolvedDICµmol/kgHicks, Natalie
44Carbon, inorganic, dissolved, standard deviationDIC std dev±Hicks, Natalie
45Carbonate system computation flagCSC flagYang, YanCalculated using seacarb after Nisumaa et al. (2010)
46pHpHYang, YanCalculated using seacarb after Nisumaa et al. (2010)total scale
47Carbon dioxideCO2µmol/kgYang, YanCalculated using seacarb after Nisumaa et al. (2010)
48Fugacity of carbon dioxide (water) at sea surface temperature (wet air)fCO2water_SST_wetµatmYang, YanCalculated using seacarb after Nisumaa et al. (2010)
49Partial pressure of carbon dioxide (water) at sea surface temperature (wet air)pCO2water_SST_wetµatmYang, YanCalculated using seacarb after Nisumaa et al. (2010)
50Bicarbonate ion[HCO3]-µmol/kgYang, YanCalculated using seacarb after Nisumaa et al. (2010)
51Carbonate ion[CO3]2-µmol/kgYang, YanCalculated using seacarb after Nisumaa et al. (2010)
52Aragonite saturation stateOmega ArgYang, YanCalculated using seacarb after Nisumaa et al. (2010)
53Calcite saturation stateOmega CalYang, YanCalculated using seacarb after Nisumaa et al. (2010)
54Experiment weekExp weekHicks, Natalie
55Ammonium[NH4]+µmol/lHicks, Natalie
56Ammonium, standard deviation[NH4]+ std dev±Hicks, Natalie
57Nitrate and Nitrite[NO3]- + [NO2]-µmol/lHicks, Natalie
58Nitrate and Nitrite, standard deviation[NO3]- + [NO2]- std dev±Hicks, Natalie
59Phosphate[PO4]3-µmol/lHicks, Natalie
60Phosphate, standard deviation[PO4]3- std dev±Hicks, Natalie
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
16753 data points

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