Preprints
https://doi.org/10.5194/egusphere-2024-3285
https://doi.org/10.5194/egusphere-2024-3285
04 Nov 2024
 | 04 Nov 2024
Status: this preprint is open for discussion.

Relationships between phytoplankton pigments and DNA- or RNA-based abundances support ecological applications

Robert Lampe, Ariel Rabines, Steffaney Wood, Anne Schulberg, Ralf Goericke, Pratap Venepally, Hong Zheng, Michael Stukel, Michael Landry, Andrew Barton, and Andrew Allen

Abstract. Observations of phytoplankton abundances and community structure are critical towards understanding marine ecosystems. Common approaches to determine group-specific abundances include measuring phytoplankton pigments via high-performance liquid chromatography and DNA-based metabarcoding. Increasingly, mRNA abundances via metatranscriptomics are also employed. As phytoplankton pigments are used to develop and validate remote sensing algorithms, further comparisons between pigments and other metrics are needed to validate the extent to which these measurements agree for group-specific abundances; however, most previous comparisons have been hindered by metabarcoding and metatranscriptomics solely producing relative abundance data. By employing quantitative approaches that express both 18S rDNA and total mRNA as concentrations, we show that these measurements are related for several eukaryotic phytoplankton groups. We further propose that integration of these can be used to examine ecological patterns more deeply. For example, productivity-diversity relationships of both the whole community and individual groups show a dinoflagellate-driven negative trend rather than the commonly-found unimodal pattern. Pigments are also shown to relate to certain harmful algal bloom-forming taxa as well as the expression of sets of genes. Altogether, these results suggest that potential models of pigment concentrations via hyperspectral remote sensing may enable improved assessments of global phytoplankton community structure, including the detection of harmful algal blooms, and support the development of ecosystem models.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Robert Lampe, Ariel Rabines, Steffaney Wood, Anne Schulberg, Ralf Goericke, Pratap Venepally, Hong Zheng, Michael Stukel, Michael Landry, Andrew Barton, and Andrew Allen

Status: open (until 22 Dec 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Robert Lampe, Ariel Rabines, Steffaney Wood, Anne Schulberg, Ralf Goericke, Pratap Venepally, Hong Zheng, Michael Stukel, Michael Landry, Andrew Barton, and Andrew Allen
Robert Lampe, Ariel Rabines, Steffaney Wood, Anne Schulberg, Ralf Goericke, Pratap Venepally, Hong Zheng, Michael Stukel, Michael Landry, Andrew Barton, and Andrew Allen

Viewed

Total article views: 269 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
210 52 7 269 35 3 6
  • HTML: 210
  • PDF: 52
  • XML: 7
  • Total: 269
  • Supplement: 35
  • BibTeX: 3
  • EndNote: 6
Views and downloads (calculated since 04 Nov 2024)
Cumulative views and downloads (calculated since 04 Nov 2024)

Viewed (geographical distribution)

Total article views: 266 (including HTML, PDF, and XML) Thereof 266 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 11 Dec 2024
Download
Short summary
With the likely emergence of satellite-based phytoplankton pigment data, it is increasingly important to examine relationships between phytoplankton pigments and other metrics of phytoplankton community composition. By using quantitative approaches, we show that phytoplankton pigments correlate with DNA- and RNA-based abundances, and examine how integration of these data addresses ecological questions relating to diversity patterns, harmful algal blooms, and inferring cellular activity.