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To determine the effect of the rate of temperature increase (acute vs. gradual) and magnitude as well as the timing of nutrient addition on a natural marine phytoplankton community, a bottle incubation experiment has been conducted at the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Wilhelmshaven, Germany. The community was collected at the Helgoland Roads long-term time series site in the German part of the North Sea (https://deims.org/1e96ef9b-0915-4661-849f-b3a72f5aa9b1) on the 6ᵗʰ of March 2022. The surface water containing the phytoplankton community was collected from the RV HEINCKE with a pipe covered with a 200 µm net attached to a diaphragm pump. In the first experimental run, the community was exposed to either gradual or acute temperature increase (from 6 to either 12 or 18°C) with 25 different N:P supply ratios added as a batch at the beginning of the bottle incubation. Simultaneously, the same community was gradually acclimated to their experimental temperatures under ambient nutrients and was used in a second experimental run in which it received the same 25 different N:P supply ratios after temperature acclimation. The light conditions were set to 175 µmol s-1 m-2 and a day-night cycle of 12h:12h which corresponds to the natural conditions at that time of the year. With this, it was possible to test the effect of a gradual vs. acute temperature increase and the timing of nutrient addition i.e., before or after the temperature change. This experimental set-up summed up to 400 units (8 temperature treatments x 5 nitrogen levels x 5 phosphorus levels x 2 replicates). Each experimental run was ended after 12 days. Fluorescence (395/680 Exc./Em.) was measured every second day using a SYNERGY H1 microplate reader (BioTek®) to determine phototrophic growth over time. At the end of each experiment, one replicate was filtered onto pre-combusted acid-washed glass microfiber filters (WHATMAN® GF/C) for intracellular carbon (POC), nitrogen (PON), and phosphorus (POP) content. The POP filters were pre-combusted and then analysed by molybdate reaction after digestion with a potassium peroxydisulfate solution (Wetzel and Likens 2003). The POC and PON filters were dried at 60°C before they were measured in an elemental analyser (Flash EA 1112, Thermo Scientific, Walthman, MA, USA).
To investigate the effect of temperature on a North Sea spring bloom community, we performed an incubation experiment in the mesocosm facility of the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Wilhelmshaven. The plankton community was sampled from the long-term ecological research station Helgoland Roads (https://deims.org/1e96ef9b-0915-4661-849f-b3a72f5aa9b1) on the 6ᵗʰ of March, 2022. Collection of the surface community was conducted from the RV Heincke with a pipe covered with a 200 µm net that was attached to a diaphragm pump. The month-long incubation was started on the 7ᵗʰ of March in twelve indoor mesocosms, the Planktotrons (Gall et al., 2017). We chose three temperatures along the ascending part of the thermal performance curve (TPC) of the in situ community: the minimum temperature for positive growth (6°C, also the field temperature), the middle between the minimum and the optimum temperature (12 °C), and the optimum temperature for growth (18 °C). Ramping up the temperatures was conducted by 1 °C per day until the treatment temperatures were reached, resulting in a ramp phase (first twelve days) and a constant temperature phase. This dataset comprises all data collected within the experiment. Temperature, oxygen, pH, salinity, and in vivo fluorescence were measured daily at 10 am. Samples for dissolved nutrients (nitrate, nitrite, phosphate, silicate), chlorophyll a, DNA, particulate nutrients (biogenic silica, particulate organic carbon/nitrogen/phosphorus), as well as flow cytometric counts of bacteria (stained) and the unstained community were sampled every third day at the same time. The mesocosm water was generally filtered over a 200 µm mesh before sampling to exclude mesozooplankton. However, due to the appearance of large Phaeocystis colonies, additional samples without pre-filtration were taken for particulate organic carbon, nitrogen, phosphorus, and chlorophyll a starting on incubation day 15. PAR, total nitrogen and phosphorus as well as total alkalinity were measured at the start, in the middle, and at the end of the incubation. Samples for Mesozooplankton enumeration were taken and plankton species identified at the end of the experiment. All analysis scripts can be found on github (https://github.com/AntoniaAhme/TopTrons22MesocosmIncubation). The sequence data are available at the European Nucleotide Archive (ENA).
Ecosystem models often use wet weights to parameterise biota disregarding their water content. This may be especially erroneous for gelatinous plankton, such as salps and pyrosomes, with high, compared to crustaceans, water content. Poorly quantified residual water should also be corrected when using dry weights for parameterisation. We estimated the residual water content (as well as elemental and organic contents) for seven tunicate species, one pyrosome and six salps (N = 107). Specimens were collected during several research expeditions in the Southern Ocean, the Northeast Pacific, east of New Zealand, and around Hawaii between 2004 and 2021. The residual water content of tunicates was analyzed for inter- and intraspecific variability. The H-surplus method (Madin et al. 1981) was applied for the residual water content calculation. The dataset contains information about the life cycle stage (blastozooid versus oozooid), tissue type (tunic versus whole organism), drying method (oven versus freeze-drying), size, and the elemental and organic contents of the samples. The methods and results of the study are described in detail in Lüskow et al. (submitted).
Changes in silicon to nitrogen (Si:N) ratios are known to affect phytoplankton community composition, as silicon is an essential nutrient for diatoms but not for most other phytoplankton. Less is known if and how this ratio affects biochemical composition and stoichiometry of seston. This is of importance, as changes in seston chemistry can have implications on the quality of food available for zooplankton. We applied a range of Si:N ratios and two levels of copepod grazing on a natural Baltic sea plankton community pre-filtered with 125um mesh size filter. Si:N ratios were achieved by adding silicate (at target concentrations of 10, 16, 22, 28 and 34 μmol L−1) and nitrate solutions (at target nitrogen concentration of 40 µmol L-1) to the experimental units at the start of the experiment. Copepod grazing was manipulated by adding 30 individuals of adult Eurytemora affinis copepods per liter to high copepod treatments once phytoplankton bloom has established (day 6 of the experiment). The mesocosm experiment was carried out in summer 2016 and lasted 20 days. The response of particulate carbon, nitrogen, phosphorus was followed by sampling three times per week and fatty acid samples were taken at the end of the experiment. Our data reveals that increasing Si:N ratios result in an increase of particulate carbon, phosphorus, nitrogen and total fatty acid concentrations. Carbon to nitrogen (C:N) and carbon to phosphorus (C:P) ratios increased with increasing Si:N ratios as well as the concentrations of individual essential fatty acids such as DHA and EPA per seston carbon. Enhanced copepod grazing affected C:N, C:P and DHA and ALA concentrations negatively. Consequently, this data illustrates the importance of bottom up effects such as changes in Si:N ratio and top-down controls like copepod grazing in shaping particulate nutrient and fatty acid composition of marine seston.
Changes in silicon to nitrogen (Si:N) ratios are known to affect phytoplankton community composition, as silicon is an essential nutrient for diatoms but not for most other phytoplankton. Less is known if and how this ratio affects biochemical composition and stoichiometry of seston. This is of importance, as changes in seston chemistry can have implications on the quality of food available for zooplankton. We applied a range of Si:N ratios and two levels of copepod grazing on a natural Baltic sea plankton community pre-filtered with 125um mesh size filter. Si:N ratios were achieved by adding silicate (at target concentrations of 10, 16, 22, 28 and 34 μmol L−1) and nitrate solutions (at target nitrogen concentration of 40 µmol L-1) to the experimental units at the start of the experiment. Copepod grazing was manipulated by adding 30 individuals of adult Eurytemora affinis copepods per liter to high copepod treatments once phytoplankton bloom has established (day 6 of the experiment). The mesocosm experiment was carried out in summer 2016 and lasted 20 days. The response of particulate carbon, nitrogen, phosphorus was followed by sampling three times per week and fatty acid samples were taken at the end of the experiment. Our data reveals that increasing Si:N ratios result in an increase of particulate carbon, phosphorus, nitrogen and total fatty acid concentrations. Carbon to nitrogen (C:N) and carbon to phosphorus (C:P) ratios increased with increasing Si:N ratios as well as the concentrations of individual essential fatty acids such as DHA and EPA per seston carbon. Enhanced copepod grazing affected C:N, C:P and DHA and ALA concentrations negatively. Consequently, this data illustrates the importance of bottom up effects such as changes in Si:N ratio and top-down controls like copepod grazing in shaping particulate nutrient and fatty acid composition of marine seston.
Phytoplankton, microzooplankton, copepod and dissolved nutrient data from a mesocosm experiment, which took place in summer 2016. A range of Si:N ratios and two levels of copepod grazing pressure were manipulated on a natural plankton community in Kiel Bay, Southern Baltic Sea, Germany.
The present dataset contains measurements of vertical particle fluxes (export) and their elemental composition. Data was collected with sediment traps in several in situ mesocosm experiments on ocean acidification. Study locations were the Kongsfjord in Svalbard (2010), the Raunefjord in Norway (2011), Storfjärden in Finland (2012), the Gullmar Fjord in Sweden (2013), and Gando Bay in Gran Canaria, Spain (2014). The dataset was to investigate the impact of ocean acidification on vertical particle fluxes and their elemental composition (stoichiometry of Si, C, and N).
The GEOROC database includes helpful compilations of mineral compositions aggregated from measurements reported in decades worth of publications, but it can be challenging to consistently filter mislabeled, inaccurate, or incomplete mineral compositions. MIST (Mineral Identification by Stoichiometry) is a stoichiometry-based computational algorithm that identifies geochemical observations with normalized elemental ratios matching natural minerals. The stoichiometric filters that were manually coded in MIST for over 240 mineral species are based on reported mineral formulas and well-documented examples of mineral chemistry reported in RRUFF and associated databases, typically including a ~5-10% tolerance in stoichiometric ratios based on measurement errors, vacancies, and substitutions. The MIST model can therefore efficiently filter the GEOROC mineral compilation files to recognize compositions whose normalized oxides match the labeled mineral stoichiometry. Furthermore, the MIST output includes results of intermediate data manipulation steps, a detailed stoichiometric formula for each input composition, and consistently calculated mineral endmembers such as Fo, En, Ws, and Fs. MIST is agnostic to the instrument used to collect oxide data. Because MIST uses normalized oxides, it cannot distinguish between some mineral species, where applicable, they are reported as a group (e.g., gypsum/bassanite/anhydrite). MIST can only recognize minerals encoded in the algorithm, so other real but less common minerals will not be recognized. The full list of minerals MIST can recognize, along with more details of the algorithm and results pages, are published in Siebach et al. (https://doi.org/10.1016/j.cageo.2025.106021). This dataset includes fifteen of the Compiled Mineral files published by GEOROC in 12-2024 including the MIST results (whether or not a species was confirmed by MIST). Prior to running the data through MIST, all files were filtered to only include mineral compositions that included major oxides (e.g., silicate mineral compositions where SiO2 > 0 wt%). Furthermore, all variations of reported Fe were collapsed into a single column representing FeOT. Metadata is preserved from the original compiled GEOROC files, so users may add additional filters as appropriate for different purposes. Results have not been filtered for reported sum of total oxides, but doing so can help identify particular mineral species (e.g., separate gypsum from bassanite). An additional file preserves the full reference information for each mineral compilation. We suggest using the compositions that MIST identifies as stoichiometrically consistent with a mineral species as a standardized filter on the GEOROC datasets prior to utilizing the data in machine learning models or similar applications. These may also be helpful any time a user would like standardized formulas or mineral endmember information for these mineral compilations.
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