A Pelagic Size Structure database (PSSdb) to support biogeochemical modeling: third update to first release of PSSdb-bulk
Creators
- 1. Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefranche, Villefranche-sur-mer, France
- 2. Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA
- 3. NOAA Fisheries - Office of Science & Technology - Marine Ecosystems Division, Silver Spring, Maryland, USA
- 4. NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
- 5. Department Ocean Ecosystems Biology, GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Description
This dataset represents the third update to the first release of the Pelagic Size Structure database (PSSdb, https://pssdb.net) scientific project, investigating the global particle size distributions measured from multiple pelagicǂ imaging systems. These devices include the Imaging Flow Cytobot (Olson and Sosik 2007), benchtop scanners like the ZooScan (Gorsky et al. 2010), and the Underwater Vision Profiler (Picheral et al. 2010). The data sources originate from Ecotaxa (https://ecotaxa.obs-vlfr.fr/), Ecopart (https://ecopart.obs-vlfr.fr/), and Imaging FlowCytobot dashboards (https://ifcb.caloos.org/dashboard and https://ifcb-data.whoi.edu/dashboard). Links to the PSSdb code and documentation are available on the PSSdb webpage (https://pssdb.net).
This updated version includes the following changes:
● Duplicate data entries and NaN values have been removed.
● Data products now include Normalized Biomass Size Spectra (NBSS), and Particle Size Distribution (PSD), two widely used methods to represent plankton and particles size distribution in marine ecology and biogeochemistry (Jonasz and Fournier 1996, San Martin et al. 2006).
● Linear regressions are now performed with log10 transformations of the normalized biovolume/abundance and the size classes.
● Inclusion of UVP6 and other benchtop plankton Scanner datasets from net tows, which expand the temporal and spatial coverage of the data products.
● Unbiased portion of the size spectra is selected by a new thresholding method that accounts for both uncertainties on particle sizes, limited by the camera resolution, and particle count (Schartau et al. 2010), so that only size classes with less than 20% uncertainty are retained, in addition to gaps in the size spectra.
Added in this version (March, 2024):
● An error in the thresholding function (scripts/funcs_NBS.py) was corrected.
● A quality control function was implemented (scripts/funcs_NBS.py) to flag size spectra calculations in products 1a and 1b.
Added in this version (April, 2024):
● An error in the size classes defined in the ecopart_size_bins.tsv used by the size binning function (scripts/funcs_NBS.py) was corrected, the size ratio between consecutive size bins is the same across all the size ranges now.
This PSSdb dataset is composed of two products, specific to each imaging device:
- Product 1a includes the size distribution , computed from normalized biovolume, for NBSS, and normalized abundance, for PSD, of plankton and particles within a set of pre-defined size classes (expressed in both biovolume and equivalent circular diameter), averaged by year and month, and in 1-degree longitude/latitude grid cells.
- Product 1b includes the results of NBSS and PSD regression fit parameters, slopes, intercept, and coefficient of determination (R2), averaged by year and month, and in 1-degree longitude/latitude grid cells. The regression parameters are defined using ordinary least squares linear regressions applied to a log10 transformed normalized biovolume/normalized abundance and biovolume/ diameter size class values.
Size spectra parameters were averaged over a maximum of 16 spatial and temporal subsets (0.5°x0.5°x1 week) to avoid over-representation of repeated sampling events (e.g., time-series datasets) within a grid cell. Linear regressions were performed on the linear portion of the log10-transformed NBSS and PSD estimates, between the size classes with a size measurement or particle count uncertainty greater than 20% (Schartau et al. 2010) , and where the maximum NB/PSD is observed and the largest size class before three empty consecutive size classes.
For additional information, please see the PDF documentation available below ...
Files
Documentation_PSSdb_v2024-04.pdf
Files
(1.1 MB)
Name | Size | Download all |
---|---|---|
md5:82db7f6144dda77471da9cd290950975
|
183.6 kB | Preview Download |
md5:9b10e4f7d251ea5a9897bc7257160b1d
|
883.9 kB | Preview Download |
Additional details
Related works
- Is new version of
- Dataset: 10.5281/zenodo.7998800 (DOI)