Bioactive trace metal time series during Austral summer in Ryder Bay, Western Antarctic Peninsula

Bown, J.; Laan, Patrick; Ossebaar, Sharyn; Bakker, Karel; Rozema, Patrick D.; Baar, H. J. W. de

doi:10.1016/j.dsr2.2016.07.004

Cited by 35 publications

(50 citation statements)

References 64 publications

(125 reference statements)

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“…Classical features of the sea ice environment were the sole dominance of diatoms and depleted silicate stocks, the latter unexpected given the coastal nature of the site and never documented prior to the 2013-2104 summer Annett et al, 2017;Bown et al, 2017;Cassarino et al, 2017;Rozema et al, 2017b). Even though macronutrient concentrations in the water column during this period were low and uptake by phytoplankton was likely hampered, nutrients could still have been available through high bacterial remineralization, sloppy grazing, and/or viral lysis which peaks after the end of the bloom (Ducklow et al, 2012b;Brum et al, 2015).…”

Section: Influence Of Presence/absence Of Sea Ice On Phytoplankton Dymentioning

confidence: 99%

“…The major benefits of using such a tool over more traditional (mostly linear) models are: Regression trees allow for (1) non-linear relationships between input and output variables, (2) non-additive interactions between predictor and response variables and (3) correlations between different input variables (Breiman, 2001;Shi and Horvath, 2006). The relevant variables included were phytoplankton biomass, macronutrients, MLD, temperature, salinity, total irradiance and the relative abundance of the three most important phytoplankton groups, namely diatoms, haptophytes and cryptophytes (Behrenfeld and Falkowski, 1997;Arrigo et al, 1999;Dierssen and Smith, 2000;Vernet et al, 2008Vernet et al, , 2012Montes-Hugo et al, 2009;Piquet et al, 2011;Venables et al, 2013;Williams et al, 2016;Bown et al, 2017;Rozema et al, 2017a,b).…”

Section: Constructing and Evaluate Modelsmentioning

confidence: 99%

“…This dendrogram suggested binning of the samples collected at 0-7, 8-49, and 50-75 m bins and the smallest bin size was 40. The initial ratios were as used previously with the RaTS data (Supplementary Table 1; Bown et al, 2017;Rozema et al, 2017a). Neoxanthin and prasinoxanthin were excluded for the 50-75 m bin.…”

Section: Phytoplankton Pigmentsmentioning

confidence: 99%

“…Subsamples (2 × 5 mL) for macronutrient analysis were filtered (prefilter: 0.8 µm, membrane: 0.2 µm, Acrodisc Supor PF, Pall, US) and stored in the dark at −20 • C (nitrate, nitrite, and phosphate) or 4 • C (silicate). Analyses for samples collected using both collection methods were conducted using a Technicon TRAACS 800 Autoanalyzer at the Royal Netherlands Institute for Sea Research, The Netherlands (Bown et al, 2017). Nitrite and nitrate were summed and are presented as N Tot .…”

Section: Macronutrientsmentioning

confidence: 99%

“…Nutrient samples were collected as described earlier (Bown et al, 2017) or as described below. A cross comparison of these two different collection methods during the 2012-2013 season did not yield major differences.…”

Section: Macronutrientsmentioning

confidence: 99%

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Assessing Drivers of Coastal Primary Production in Northern Marguerite Bay, Antarctica

Rozema

Kulk

Veldhuis³

et al. 2017

Front. Mar. Sci.

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The coastal ocean of the climatically-sensitive west Antarctic Peninsula is experiencing changes in the physical and (photo)chemical properties that strongly affect the phytoplankton. Consequently, a shift from diatoms, pivotal in the Antarctic food web, to more mobile and smaller flagellates has been observed. We seek to identify the main drivers behind primary production (PP) without any assumptions beforehand to obtain the best possible model of PP. We employed a combination of field measurements and modeling to discern and quantify the influences of variability in physical, (photo)chemical, and biological parameters on PP in northern Marguerite Bay. Field data of high-temporal resolution (November 2013-March 2014) collected at a long-term monitoring site here were combined with estimates of PP derived from photosynthesis-irradiance incubations and modeled using mechanistic and statistical models. Daily PP varied greatly and averaged 1,764 mg C m −2 d −1 with a maximum of 6,908 mg C m −2 d −1 after the melting of sea ice and the likely release of diatoms concentrated therein. A non-assumptive random forest model (RF) with all possibly relevant parameters (M RFmax ) showed that variability in PP was best explained by light availability and chlorophyll a followed by physical (temperature, mixed layer depth, and salinity) and chemical (phosphate, total nitrogen, and silicate) water column properties. The predictive power from the relative abundances of diatoms, cryptophytes, and haptophytes (as determined by pigment fingerprinting) to PP was minimal. However, the variability in PP due to changes in species composition was most likely underestimated due to the contrasting strategies of these phytoplankton groups as we observed significant negative relations between PP and the relative abundance of flagellates groups. Our reduced model (M RFmin ) showed how light availability, chlorophyll a, and total nitrogen concentrations can be used to obtain the best estimate of PP (R 2 = 0.93). The resulting estimates from our models suggest summer PP to have been between 214.4 and 176.1 g C m −2 . Through the employment of a modeling technique without any assumptions apart from a representative sampling strategy, we showed and estimated how PP in this climatically sensitive and changing region can best be predicted and described.

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Section: Influence Of Presence/absence Of Sea Ice On Phytoplankton Dymentioning

confidence: 99%

Section: Constructing and Evaluate Modelsmentioning

confidence: 99%

Section: Phytoplankton Pigmentsmentioning

confidence: 99%

Section: Macronutrientsmentioning

confidence: 99%

Section: Macronutrientsmentioning

confidence: 99%

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Assessing Drivers of Coastal Primary Production in Northern Marguerite Bay, Antarctica

Rozema

Kulk

Veldhuis³

et al. 2017

Front. Mar. Sci.

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Investigating the fate of copper in a laboratory‐based toxicity test with embryos of Mytilus galloprovincialis: Copper mass balance of a closed bioassay

Zitoun

Hassler²,

Clearwater

et al. 2019

Enviro Toxic and Chemistry

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The production of accurate and reliable data on metal toxicity during ecotoxicological bioassays is important for credible environmental risk assessments and management in aquatic environments. Actual measurements and reporting of contaminant concentrations in bioassays are, however, often disregarded; and potential contaminant loss attributable to adsorption processes (e.g., wall adsorption) in bioassays is widely omitted, which can have detrimental effects on calculated metal toxicity thresholds. In the present we assessed copper (Cu) mass balance during a standard 48‐h bioassay test with blue mussel (Mytilus galloprovincialis) embryos to evaluate effects on calculated toxicity endpoints. We demonstrated that measured Cu concentrations at the test conclusion need to be used to quantify the risk of Cu toxicity because nominal Cu and initial Cu concentrations underestimate overall Cu toxicity by up to 1.5‐fold, owing to Cu loss in solution attributable to adsorption and bioaccumulation processes. For the first time we provide evidence that extracellular adsorption to the biological surface of the embryos is the most important sink for total dissolved Cu in a bioassay. We also established that adsorbed extracellular Cu accumulation reduces Cu toxicity to embryos, potentially by inhibiting Cu from entering the cell of the mussel embryo. Environmental factors (e.g., salinity and dissolved organic carbon) did not influence the partitioning of Cu within the laboratory‐based bioassay. The present results 1) demonstrate the importance of differentiating extra‐ and intracellular Cu pools to improve our understanding of Cu toxicity and associated processes, 2) reveal the potential for bias with respect to calculated Cu toxicity thresholds when results are based on nominal and initial Cu concentrations, and 3) point out the need to follow current guidelines for the testing of chemicals to standardize toxicity tests and data reporting. Environ Toxicol Chem 2019;38:561–574. © 2019 SETAC

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Interannual variability in phytoplankton biomass and species composition in northern Marguerite Bay (West Antarctic Peninsula) is governed by both winter sea ice cover and summer stratification

Rozema

Venables

Poll

et al. 2016

Limnology & Oceanography

107

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The rapid warming of the West Antarctic Peninsula region has led to reduced sea ice cover and enhanced glacial melt water input. This has potential implications for marine ecosystems, notably phytoplankton growth, biomass, and composition. Fifteen years (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) of year-round size fractionated chlorophyll a (Chl a), phytoplankton pigment fingerprinting and environmental data were analyzed to identify the relationship between sea ice cover, water column stability and phytoplankton dynamics in northern Marguerite Bay, Antarctica. Over the investigated period, both summer (December-February) and winter biomass declined significantly, 38.5% and 33.3% respectively. Winter phytoplankton biomass was low (< 0.25 lg Chl a L 21) and consisted on average of 69% diatoms, 5% cryptophytes, and 20% haptophytes. Summers following winters with low (< 65 days) sea ice cover were characterized by decreased stratification strength and relatively low (median < 4.4 lg Chl a L 21) phytoplankton biomass, as compared to summers preceded by high winter sea ice cover. In addition, the summertime microphytoplankton (> 20 lm) fraction was strongly decreased in the low biomass years, from 92% to 39%, coinciding with a smaller diatom fraction in favor of nanophytoplankton (< 20 lm), represented by cryptophytes and haptophytes. In contrast, diatoms dominated (> 95%) during summers with average-to-high biomass. We advance a conceptual model whereby low winter sea ice cover leads to low phytoplankton biomass and enhanced proportions of nanophytoplankton, when this coincides with reduced stratification during summer. These changes are likely to have a strong effect on the entire Antarctic marine food web, including krill biomass, and distribution.Climate change strongly affects the physical environment in many different regions of our planet. One of the regions most profoundly affected is the West Antarctic Peninsula (WAP). Annual mean air temperatures over the WAP have increased by 2-38C over the past 50 years (Turner et al. 2005), whilst summertime sea surface temperatures increased by more than 18C (Meredith and King 2005). The increase in temperatures in the WAP region is associated with a shortening of the sea ice season and an increase in glacial ice discharge (Depoorter et al. 2013;Rignot et al. 2013). These large-scale changes are strongly affecting the physical and chemical properties of the water column and may thereby affect marine food webs as well (Constable et al. 2014). Pronounced changes in sea ice cover have been observed in the coastal WAP region (Vaughan et al. 2003;Meredith and King 2005;Harangozo 2006). Sea ice duration has decreased by almost 90 days in the 1979-2004 period. This decrease contrasts with the general trend of modestly increasing sea ice extent around Antarctica as a whole, which is driven in particular by major advances in the Ross Sea with much slower rates of change elsewhere (Stammerjohn et al. 2008b;Montes-Hugo ...

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Bioactive trace metal time series during Austral summer in Ryder Bay, Western Antarctic Peninsula

Cited by 35 publications

References 64 publications

Assessing Drivers of Coastal Primary Production in Northern Marguerite Bay, Antarctica

Assessing Drivers of Coastal Primary Production in Northern Marguerite Bay, Antarctica

Investigating the fate of copper in a laboratory‐based toxicity test with embryos of Mytilus galloprovincialis: Copper mass balance of a closed bioassay

Interannual variability in phytoplankton biomass and species composition in northern Marguerite Bay (West Antarctic Peninsula) is governed by both winter sea ice cover and summer stratification

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