Fine spatial scale seston and plankton size spectra estimates from the Northern California Current

Marco Corrales-Ugalde1, Su Sponaugle1,2, Elena Conser1,2, Moritz Schmid3, Kelly Sutherland4, Christopher Sullivan5, Bing Wang6, Robert K. Cowen1,5 1 Hatfield Marine Science Center, 2030 SE Marine Science Dr., Newport, OR 97365 2 Department of Integrative Biology, 2403 Cordley Hall, Oregon State University, Corvallis, OR 97331 3 Nearshore Ecology Program, Oregon Department of Fish and Wildlife, 2040 SE Marine Science Dr., Newport, OR 97365 4 Oregon Institute of Marine Biology, University of Oregon, 5 College of Earth Ocean and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331 6 Center for Quantitative Life Science, Oregon State University, Corvallis, OR 97331, United States General Description: This dataset is part of the manuscript submission ‘Seston and plankton size spectra variability in a highly productive Eastern Boundary Current System’ to be considered for publication in Progress in Oceanography. VAPP (https://doi.org/10.5281/zenodo.20409846) was used to process raw .avi videos and generate image segments, classification and merge ISIIS environmental data with particle classification. Merged data were then processed by the SPECTRA-NCC size spectrum workflow (https://github.com/MarCorralesU/NCC-SPECTRA_sizeSpectrum_workflow). Details on how the size spectra were estimated can be found on that publication. Briefly, size spectra coefficients (slope and intercept) come from a least-squares linear regression between the log10 transformed normalized biovolume (Normalized biovolume is the biovolume concentration for a size class, divided by the range of the size class) as a function of the log10 transformed biovolume size classes (the mid point of the size range associated to each size class). The size spectrum (calculated for each depth bin and cast) has been thresholded following previously described methods (Dugenne et al., 2024). LISST and ISIIS data were merged following Haëntjens et al. (2022). Thresholding removed in each sample (5 meter depth bins along each cast of the Tow-Yo pattern), abundance data for size classes that (1) were smaller than the size class with the highest abundance value, (2) Particle Count uncertainty (following a Poisson distribution) was >0.2, which implied that abundance of a size class calculated with less than 4 particles were discarded. (3) at the larger end of the spectrum (i.e. largest size classes), data were discarded if they occurred after three consecutive size classes with no data. And finally (4) samples with less than a total of 4 size classes were discarded. Column descriptions for the datasets: group_id: unique identifier of a sample, corresponds to a unique combination of depth_mid and cast_id. time is a unique value of the time spectra coefficients for each group_id depth_mid: depth interval (5 m) in which the particle concentration for each size class and the environmental parameters were averaged for the depth bin time_Pacific: average time or the depth bin Longitude: mean Longitude (decimal degrees) for the depth bin Latitude: mean Latitude (decimal degrees) for the depth bin Salinity: average Salinity (PSU) for the depth bin Temperature: average Temperature (Celsius) for the depth bin chl_a_ug_l: average Chlorophyll-a concentration (micrograms per Liter) for the depth bin biovol_um3_mid: total range of the biovolume size class (max size - min size for each size class), in micrometer cubed NB: Normalized biovolume, result of dividing concentration_um3_m3 by bin_width_um3. This results in units of m^-3 logNB: log10 transformed of NB. Used as the y variable for the size spectra least squares linear regression logSize: log10 transformed of size_class_um3_mid. Used as the x variable for the size spectra least squares linear regression ECD_um_mid: midpoint of the equivalent circular diameter size class range, in micrometers, for each size class count_uncertainty: uncertainty assuming that particle detection (particle_count_L) followed a Poisson distribution (Scheiner et al., 2010). Size classes with an uncertainty >0.2 were discarded intercept: intercept of the least squares linear regression for each group_id slope: slope of the least squares linear regression for each group_id fitted_logNB: calculated NB per biovolume size class using the log linear version of the spectra fit: log10(fitted_logNB) = slope*(log10(biovol_um3_mid)) + log10(intercept) This is used to calculate the integrated total biovolume per group_id Cruise: code for the sampling events:w22 = winter 2022s22 = summer 2022w23 = winter 2023s23 = summer 2023 Transect_ID: identification of the different transects:GH = Grays HarborCR = Columbia RiverCM = Cape MearesNH = Newport LineHH = Heceta HeadRR = Rogue River shelf_loc_200: categorical variable that determines whether the sample (group_id) was on-shelf (<200 m bottom depth) or off-shelf (>200 m bottom depth) based on its relative position to shelf break longitude SPECTRA_ISIIS_NBSS_plankton.csv only taxa: broad plankton taxonomic grouping associated with each particle detection particle_count_L: number of detected plankton particles within each size class concentration_um3_m3: plankton biovolume concentration normalized by sampled water volume SPECTRA_LISST-ISIIS_NBSS_system.csv only instrument: instrument source associated with the spectra estimate (LISST or ISIIS or both) integrated_biovolume: integrated total biovolume estimated from the fitted size spectrum total_biovolume_sum: directly summed observed biovolume across all size classes for the group_id References Dugenne, M., Corrales-Ugalde, M., Luo, J.Y., Kiko, R., O’Brien, T.D., Irisson, J.-O., Lombard, F., Stemmann, L., Stock, C., Anderson, C.R., Babin, M., Bhairy, N., Bonnet, S., Carlotti, F., Cornils, A., Crockford, E.T., Daniel, P., Desnos, C., Drago, L., Elineau, A., Fischer, A., Grandrémy, N., Grondin, P.-L., Guidi, L., Guieu, C., Hauss, H., Hayashi, K., Huggett, J.A., Jalabert, L., Karp-Boss, L., Kenitz, K.M., Kudela, R.M., Lescot, M., Marec, C., McDonnell, A., Mériguet, Z., Niehoff, B., Noyon, M., Panaïotis, T., Peacock, E., Picheral, M., Riquier, E., Roesler, C., Romagnan, J.-B., Sosik, H.M., Spencer, G., Taucher, J., Tilliette, C., Vilain, M., 2024. First release of the Pelagic Size Structure database: global datasets of marine size spectra obtained from plankton imaging devices. Earth System Science Data 16, 2971–2999. https://doi.org/10.5194/essd-16-2971-2024 Haëntjens, N., Boss, E.S., Graff, J.R., Chase, A.P., Karp‐Boss, L., 2022. Phytoplankton size distributions in the western North Atlantic and their seasonal variability. Limnology & Oceanography 67, 1865–1878. https://doi.org/10.1002/lno.12172