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The supplementary material is the complete database extracted from the 40 articles selected for the systematic review. The excel file has two spreadsheets. The spreadsheet named "Articles database" is the complete information extracted from the articles according to the Review Protocol. The spreadsheet named "Bottom-up detailed database" presents the detailed information of the 17 articles classified as "bottom-up" and gives transport-related data type and sources according to the ASIF model

Full data table for Carbon content, Nitrogen content, and biovolume measurements of planktic Rhizaria. This data is associated with the publication: Mansour, J.S., Norlin, A., Llopis Monferrer, N., L'Helguen, S., and Not, F. (2020). Carbon and nitrogen content to biovolume relationships for marine protists of the Rhizaria lineage (Radiolaria and Phaeodaria). Limnol. Oceanogr. doi: 10.1002/lno.11714 Rhizaria are ubiquitous in oceanic waters. They have previously been underestimated due to their fragility, but recent (molecular) studies show that they are major components of the planktic community and contribute greatly to, among others, the carbon and silica flux. This study provides key data on the carbon and nitrogen content of Rhizaria and its relation to cell biovolume. Here presented are the raw data of measured (CN Elemental Analyzer) carbon and nitrogen content of Rhizaria (i.e. specifically Collodaria, Acantharia, Nassellaria, Spumellaria, Aulacantha, Protocystis, and Challengeria), as well as picture-based estimates of biovolume and derived characteristics. The biovolume-to-mass relationship for these protists has allowed the formulation of mass-to-volume equations and ratios that can be used to estimate mass from biovolume. Our data shows that global Rhizaria biomass might have in fact still been underestimated. This will be pivotal information for studies of ocean ecology and for modeling biomass fluxes, whether it is biogeographic or smaller-scale system dynamics.

1.- Data for Tulancingo City, Mexico. Monthly cloudiness calculation for insulation correction in the spatial process. Include the graphic of monthly results. (Excel) 2.- Data exported by ASrcGis and calculation of Indices. (Excel) 3.- Statistics (Excel)