This dataset contains (1) outputs of Species Distribution Models (SDMs) for marine fish and (2) estimation of species richness using those outputs. SDMs use correlative algorithms to link presences of species to the environment recorded in place and time of their observation, calculate their environmental niche, estimate the geographical location suitable for them (habitat suitability) and in fine their geographical distribution. Here, we downloaded presences of marine fish from two open source databases, GBIF and OBIS and 13 environmental predictors known to be relevant in fish ecology (list below). We used the CEPHALOPOD pipeline, a framework allowing the user the compute a lot of species at the same time, with comparable methods and a verification of quality of inputs and outputs at every steps (Schickele et al., 2025). 3,642 fish made it to the final step and have the habitat suitability estimated for 12 month + annual mean, 10 bootstrap to quantify uncertainty and x algorithms. Those estimation are available in the “L2_marine_fish_*.nc” files, organized by water column position (bathydemersal, bathypelagic, benthopelagic, demersal, pelagic-neritic, pelagic-oceanic, reef-associated). We then used their annual mean to estimate their actual geographic distribution by applying (1) a bathymetric filtration and (2) a cutting procedure which removes isolated patches of high suitability (i.e., potential distribution) with no recorded presences (i.e., considered to be outside of the species dispersion range). Those geographic distribution were then stacked to estimate global species richness of every fish and each water column position.

Plankton was imaged with the PlanktoScope in different oceanic regions using different nets and protocol of conservation. This dataset aims to serve as reference for taxonomic identification with the PlanktoScope across 256 plankton taxa from 20µm to 300µm. Reference dataset can also serve as learning set for prediction in Ecotaxa (https://ecotaxa.obs-vlfr.fr/prj/15535).  The full images were processed and segmented with the PlanktoScope around each individual. A set of associated features were measured on the objects with skimage.measure. All objects were classified into 256 different classes using the web application EcoTaxa (http://ecotaxa.obs-vlfr.fr). The following dataset corresponds to the 169, 149 objects and their calculated features. The different files provide information about the features of the objects, their taxonomic identification as well as the raw images.   taxa.csv.gz   Table of the classification of each object in the dataset, with columns: - object_id: unique object identifier in EcoTaxa. - annotation_category: taxonomic name corresponding to the last level of hierarchy - annotation_hierarchy: taxonomic lineage to the category  - set: class of the image corresponding to the taxon  - img_file_name: local path of the image corresponding to the taxon, named according to the object id   features_native.csv.gz   Table of morphological features computed by PlanktoScope. All features are computed on the object only, not the background. All area/length measures are in pixels.    - object_id: unique object identifier in Ecotaxa   And 33 features:   - width: width of the smallest rectangle enclosing the object (pixel) - height: height of the smallest rectangle enclosing the object (pixel) - bx: X coordinates of the top left point of the smallest rectangle enclosing the object (pixel) - by: Y coordinates of the top left point of the smallest rectangle enclosing the object (pixel) - circ.: circularity of the object ((4∗π ∗Area)/Perim^2) [0-1] - area_exc: Surface area of the object excluding holes (pixel2) - area: Surface area of the object (pixel2) - %area: Percentage of object’s surface area that is comprised of holes - major: Length of the primary axis of the best fitting ellipse for the object (pixel) - minor: Length of the secondary axis of the best fitting ellipse for the object (pixel) - y: Y position of the center of gravity of the object (pixel) - x: X position of the center of gravity of the object (pixel) - convex_area: The area of the smallest polygon within which all points in the object fit (pixel2) - perim.: The length of the outside boundary of the object (pixel) - elongation: elongation index (major/minor)  - perimareaexc: index of the relative complexity of the perimeter (perim/area_exc) - perimmajor: Index of the relative complexity of the perimeter (perim/major) - circex: Circularity of object excluding white pixels ((4 ∗ π ∗ Area_exc)/perim 2) - angle: Angle between the primary axis and a line parallel to the x-axis of the image - bounding_box_area: Area of the smallest box containing the object (pixel2) - eccentricity: Eccentricity of the ellipse that has the same second-moments as the region. Ratio of the focal distance of the ellipse over the major axis length [0-1] - equivalent_diameter: The diameter of a circle with the same area as the object (pixel) - euler_number: Euler characteristic of the set of non-zero pixels. Computed as number of connected components subtracted by number of holes - extent: Ratio of pixels in the object to pixels in the total bounding box - local_centroid_col: Horizontal coordinate of the center of mass of the object (pixel) - local_centroid_row: Vertical coordinate of the center of mass of the object (pixel) - solidity: Ratio of pixels in the object to pixels of the convex hull image (area / convex_area) - meanhue: Mean base color of the object in hue scale (0-360) - meansaturation: Mean saturation of the object [0-100] - meanvalue: Mean brightness of the object [0-100] - stdhue: Standard deviation of base color - stdsaturation: Standard deviation of saturation  - stdvalue: Standard deviation of brightness   inventory.tsv Tree view of the taxonomy and number of images in each taxon, displayed as text. With columns : - annotation_hierarchy: taxonomic lineage - annotation_category: name of the taxon  - n: number of objects in each taxon group map.png Map of the sampling locations, to give an idea of the diversity sampled in this dataset. imgs Directory containing images of each object, named according to the object id object_id and sorted in subdirectories according to their taxon.