642 research outputs found
Jens August Schade
No full textShort presentation of Danish author Jens August Schade and his main work
Jens Christian Grøndahl
No full textThis is a short presentation of the main works of the Danish author Jens Christian Grøndahl
Oxylipin production during a mesocosm bloom of Skeletonema marinoi
No full textNumerous biological activities such as grazer defense and intraspecific signaling have been described for diatom oxylipins, fatty acid derived secondary metabolites produced by some diatom species. As the function and importance of these compounds are still controversial, the production of a subclass of these molecules, nonvolatile oxylipins, was studied during an induced bloom of Skeletonema marinoi (Samo et Zingone) in a mesocosm setup. Reproductive parameters of one of the main grazers, Calanus finmarchicus, were also examined during the bloom. Oxylipins detected during the bloom were the same as those previously described for S. marinoi and were detected predominantly in the mesocosm inoculated with this diatom. Reproductive success of C. finmarchicus remained unaffected during the course of the bloom. This may have been due to a dilution effect by the availability of alternative suitable prey or to the limited exposure of the copepods to the oxylipins generated during the short bloom. Follow up laboratory studies showed that oxylipin composition changed both when the S. marinoi clone used for inoculation was grown in the laboratory and in comparison to the well-studied Adriatic clone of S. marina These results highlight the necessity of quantitatively measuring oxylipin concentrations during diatom blooms at sea to be able to correctly evaluate their ecological significance. (C) 2013 Elsevier B.V. All rights reserved
Correcting for underestimation of microzooplankton grazing in bottle incubation experiments with mesozooplankton
No full textBottle incubation experiments are widely used in mesozooplankton grazing studies.
However, we have shown here that traditional particle removal experiments with Calanus finmarchicus
and C. helgolandicus as grazers on natural plankton may yield low or even statistically significant
(p < 0.05) negative grazing estimates, even though negative grazing rates are impossible.
Low grazing rates are often reported, especially on smaller prey types, despite abundant food and
significant egg production. Microzooplankton, such as ciliates, show higher biomass-specific grazing
rates on algae than do copepods and other mesozooplankton. Instead, copepods often selectively
feed on the microzooplankton. Thus, apparent negative rates would be expected when the release of
microzooplankton grazing pressure outweighs the copepod grazing rates on the same food items in
the incubation bottle. We show that this potentially large bias increases with microzooplankton
community grazing pressure in the control. A simplified general method to correct for this bias is
presented and compared with the original method (Nejstgaard et al. 1997, Mar Ecol Prog Ser
147:197–217). Although complexity and the need for taxonomic accuracy are reduced in the general
method, the results are not significantly different between the 2 methods. Both methods also show a
good fit with ingestion rates estimated from faecal pellet production. We suggest that the general
method be combined with automated sample treatment in future studies. In addition, we argue that
carefully estimated faecal volume production provides a simple and quick overall feeding estimate
with important advantages over the common gut pigment technique, and it may be used as an independent
method in bottle incubation experiments
Long-term phytoplankton community dynamics in Lake Stechlin (NE Germany) under sudden and heavily accelerating eutrophication: data and code
No full textThis upload contains the code and data for the paper Kröger, B. et al., 2023. "Long-term phytoplankton community dynamics in Lake Stechlin (NE Germany) under sudden and heavily accelerating eutrophication", Freshwater Biology, DOI: 10.1111/fwb.14060
Data file "Stechlin_data_2023.RData" contains the data used in the script files. The original data can be downloaded from Kiel et al., (2023), Lentz et al. (2023), and Padisák et al. (2023).
Script files "Stechlin_analysis_I_2023.R", "Stechlin_analysis_IIc_2023.R" , "Stechlin_analysis_III_2023.R" contain the code to reproduce the analysis.
Data files "beta_ewis_b.RData", "beta_ewis_d.RData", "beta_ewis_fg.RData" contain the results from distance decay analysis produced with Stechlin_analysis_IIc_2023.R
The code in brocklehurstscript_m.R is from Brocklehurst & Fröbisch (2018).
References:
Brocklehurst, N., Day, M. O., & Fröbisch, J. (2018). Accounting for differences in species frequency distributions when calculating beta diversity in the fossil record. Methods in Ecology and Evolution, 9(6), 1409-1420. https://doi.org/10.1111/2041-210X.13007
Kiel Christine, Schmidt Silke, Woodhouse Jason, Kasprzak Peter, Wollrab Sabine, Berger Stella A, Beyer Ute, Bodenlos Matthias, Degebrodt Monika, Degebrodt Roman, Gonsiorczyk Thomas, Huth Elfie, Lentz Maren, Mach Elke, Mallok Uta, Nejstgaard Jens C, Papke Monika, Pinnow Solvig, Roßberg Reingard, Sachtleben Michael, Scheffler Adelheid, Scheffler Wolfang, Krienitz Lothar, Casper Peter, Gessner Mark, Grossart Hans-Peter, Koschel Rainer (2023). Lake Stechlin chemistry data (photometry) 1970-2020 . IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-825.1
Marén Lentz, Silke Schmidt, Jason Woodhouse, Peter Kasprzak, Sabine Wollrab, Stella A Berger, Ute Beyer, Matthias Bodenlos, Monika Degebrodt, Roman Degebrodt, Thomas Gonsiorczyk, Elfie Huth, Mallok Uta, Mach Elke, Jens C Nejstgaard, Monika Papke, Solvig Pinnow, Reingard Roßberg, Michael Sachtleben, Adelheid Scheffler, Wolfang Scheffler, Lothar Krienitz, Peter Casper, Mark O Gessner, Hans-Peter Grossart, Rainer Koschel (2023) Lake Stechlin vertical profiles of multiparameter probe data 1970-2020 . IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-823.1
Padisák Judit, Selmeczy Géza B, Papke Monika, Schmidt Silke, Woodhouse Jason, Kasprzak Peter, Wollrab Sabine, Beyer Ute, Bodenlos Matthias, Degebrodt Monika, Degebrodt Roman, Gonsiorczyk Thomas, Huth Elfie, Lentz Maren, Mach Elke, Mallok Uta, Nejstgaard Jens C, Pinnow Solvig, Roßberg Reingard, Sachtleben Michael, Scheffler Adelheid, Scheffler Wolfang, Krienitz Lothar, Casper Peter, Gessner Mark O, Grossart Hans-Peter, Koschel Rainer, Berger Stella A (2023) Lake Stechlin phytoplankton 1994-2020. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-824.
Environmental variability in aquatic ecosystems: Avenues for future multifactorial experiments
No full textThe relevance of considering environmental variability for understanding and predicting biological responses to environmental changes has resulted in a recent surge in variability-focused ecological research. However, integration of findings that emerge across studies and identification of remaining knowledge gaps in aquatic ecosystems remain critical. Here, we address these aspects by: (1) summarizing relevant terms of variability research including the components (characteristics) of variability and key interactions when considering multiple environmental factors; (2) identifying conceptual frameworks for understanding the consequences of environmental variability in single and multifactorial scenarios; (3) highlighting challenges for bridging theoretical and experimental studies involving transitioning from simple to more complex scenarios; (4) proposing improved approaches to overcome current mismatches between theoretical predictions and experimental observations; and (5) providing a guide for designing integrated experiments across multiple scales, degrees of control, and complexity in light of their specific strengths and limitations.Additional authors: Kemal Ali Ger, Silke Langenheder, Jens C. Nejstgaard, Robert Ptacnik, Maren Striebe
Overview about feeding experiment I with <i>A. tonsa</i>.
No full text<p>Copepods were fed for 5 h on non-treated (<b>a</b>, <b>b</b>) <i>O. marina</i> or on TAMRA-N<sub>3</sub> (<b>c</b>, <b>d</b>) loaded <i>O. marina</i> (323 µg C L<sup>−1</sup>) without starvation. Copepods fed for 6 h with TAMRA-PUA (<b>e</b>, <b>f</b>) or TAMRA-SA (<b>g</b>, <b>h</b>) pre-treated <i>O. marina</i> (161 µg C L<sup>−1</sup>) and starved for 40 min still showed gut fluorescence. First line (<b>a</b>, <b>c</b>, <b>e</b>, <b>g</b>): light microscopy images; second line (<b>b</b>, <b>d</b>, <b>f</b>, <b>h</b>): overlay light microscopy and epifluorescence images.</p
Snapshot Surveys for Lake Monitoring, More Than a Shot in the Dark
No full textNo abstract available© 2018 Mantzouki, Beklioǧlu, Brookes, de Senerpont Domis, Dugan, Doubek, Grossart, Nejstgaard, Pollard, Ptacnik, Rose, Sadro, Seelen, Skaff, Teubner, Weyhenmeyer and Ibeling
Synthesis of TAMRA-PUA and TARMA-SA.
No full text<p>A) Synthesis of DDY, conditions: a) KOH, H<sub>2</sub>O, 22% yield; b) 1.2 equ. PPh<sub>3</sub>, 1.2 equ. I<sub>2</sub>, CH<sub>2</sub>Cl<sub>2</sub>, 55% yield; c) 3.2 equ. Mg, C<sub>2</sub>H<sub>4</sub>Br<sub>2</sub>, THF, d) 1.2 equ. ZnBr<sub>2</sub>, THF; e) 0.06 equ. Pd(PPh<sub>3</sub>)<sub>4</sub>, THF, 28 to 30% yield; f) 1.2 equ. TBAF, THF, H<sub>2</sub>O, 30% yield; B) Synthesis of the probes, conditions: g) tris[(1-benzyl-1<i>H</i>-1,2,3-triazol-4-yl)methyl]amine), sodium ascorbate, copper sulfate, 68% and 77% yield. R = 5-N-propylcarbamoyl tetramethylrhodamine. For detailed experimental procedures and product characterization see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112522#pone.0112522.s004" target="_blank">Information S1</a>.</p
Feeding experiment III with <i>A. tonsa</i>.
No full text<p>Copepods were fed for 29 h with TAMRA-N<sub>3</sub> (<b>a</b>, exposure time 1.5 s) or TAMARA-SA (<b>b</b>, <b>b1</b>, <b>b2</b> exposure time 500 ms) pre-treated <i>O. marina</i> (369 µg C L<sup>−1</sup>) and starved for 1 h. The arrow indicates high accumulation of TAMRA-SA in the lipid sac (<b>b2</b>). <b>a, b</b>: overlay light microscopy and epifluorescence images; <b>b1</b>: light microscopy image; <b>b2</b> epifluorescence image.</p
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