This dataset contains all the data we analysed for our work on the phenology of the toxic dinoflagellate genus Dinophysis in European coastal waters. To get a good understanding of this dataset, we suggest looking at the R scripts we used in our analysis, available in this public github repository:  https://github.com/vpochic/DinophysisPhenology The dataset contains data of various natures that come from different sources: - Geolocalised Dinophysis presence/absence data from long-term monitoring survey of the Continuous Plankton Recorder in North-Atlantic waters  - Geolocalised phytoplankton count data and hydrological measurements data from the REPHY (French monitoring network for phytoplankton and hydrology in coastal waters) - Geolocalised data from oceanographic (GAMAR, doi:10.1016/j.jmarsys.2025.104068) and atmospheric (ERA5, doi:10.1002/qj.3803) models - Reflectance data from pixels in Sentinel-2 MSI (ESA) satellite images - A compilation of eDNA data (metabarcoding) collected from plankton samples at 2 sampling sites in coastal France in a previous research program (doi:10.12770/53dfe316-a6d4-426f-8983-56f2b37a5e8a) - Data from lab experiments conducted on phytoplankton cultures between 2016 and 2024: phytoplankton cell counts, fluorescence microscopy images and videos. Additionnaly, it also contains a shapefile reprensenting european rivers (source: https://www.hydrosheds.org/products/gloric via https://milospopovic.net/map-rivers-with-sf-and-ggplot2-in-r/) used for visualisation purposes, and ouputs from statistical models applied on the time-series data described above (generated with the R scripts in the github repository, see above). The dataset contains several empty folders (with only a README.md file) whose purpose is to welcome data files generated by the R scripts in the aforementioned github repository (https://github.com/vpochic/DinophysisPhenology). This way, we hope our work is easily reproducible by downloading this dataset and putting the "Data" folder in the same folder as the R scripts/R project, so that the scripts can call data files and store generated ones properly. In the github repository, you will find a map that explains which data file is called by which script, and what is generated by each script as a result.