The SDC_GLO_CLIM_Dens product contains global monthly climatological estimates of in situ density using Temperature and Salinity from profiling floats contained in the World Ocean Data 18 (WOD18) database. The profiles were first quality controlled with a Nonlinear Quality control procedure. The climatology considers observations from surface to 2000 m for the time period 2003-2017. Density profiles are computed using UNESCO 1983 (EOS 80) equation from in situ temperature, salinity and pressure measurements by the PFL. Only profiles with both T,S values were used. The gridded fields are computed using DIVAnd (Data Interpolating Variational Analysis) version 2.3.1.

The SDC_GLO_CLIM_TS_V2 product is an improved version of SDC_GLO_CLIM_TS_V1 and contains two different monthly climatologies for temperature and salinity from the World Ocean Data 2018 (WOD-18) database. Along with the basic quality control flags from the WOD-18, an additional quality Control named Nonlinear Quality Control (NQC) is applied. The first climatology, V2_1, considers temperature and salinity profiles from Conductivity Depth Temperature (CTD), Ocean station data (OSD) and Moored buoy data (MRB) along with Profiling Floats (PFL) from 1900 to 2017. The second climatology, V2_2, utilizes only PFL data from 2003 to 2017. V2_1 considers 44 layers from surface to 6000 m while V2_2 only 34 from 0 to 2000 m. The gridded fields are computed using DIVAnd (Data Interpolating Variational Analysis) version 2.3.1. For data access, please register at http://www.marine-id.org/.

Animal movements are typically influenced by multiple environmental factors simultaneously and individuals vary in their response to this environmental heterogeneity. Therefore, understanding how environmental aspects, including biotic, abiotic and anthropogenic factors, influence the movements of wild animals is an important focus of wildlife research and conservation. We apply exponential random graph models (ERGMs) to analyse movement networks of a bull shark population in a network of acoustic receivers and identify the effects of environmental, social or other types of covariates on their movements. We found that intra- and interspecific factors often had stronger effects on movements than environmental variables. ERGMs proved to be a potentially useful tool for studying animal movement network data especially in the context of spatial attribute heterogeneity.

The SDC_GLO_CLIM_O2_AOU product contains two different monthly climatology for dissolved Oxygen and Apparent Oxygen Utilization, SDC_GLO_CLIM_O2 and SDC_GLO_CLIM_AOU respectively from the World Ocean Data (WOD) database. Only basic quality control flags from the WOD are used. The first climatology, SDC_GLO_CLIM_O2, considers Dissolved Oxygen profiles casted together with temperature and salinity from CTD, Profiling Floats (PFL) and Ocean Station Data (OSD) for time duration 2003 to 2017. The second climatology, SDC_GLO_CLIM_AOU, apparent Oxygen utilization, is computed as a difference of dissolved oxygen and saturation O2 profiles. The gridded fields are computed using DIVAnd (Data Interpolating Variational Analysis) version 2.3.1.

This dataset was collected by an Unmanned Aerial Vehicle in Hermitage, Réunion - 2023-12-01. Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps. Survey information - Camera: Hasselblad L1D-20c - Number of images: 119 - Total size : 1.04 Gb - Flight start: 2023:12:01 15:07:31 - Flight end: 2023:12:01 15:13:31 - Flight duration: 0h 6min 0sec - Median height: 79.9 m - Area covered: 3.93 ha Generic folder structure YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number ├── DCIM : folder to store videos and photos depending on the media collected. ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. │ ├── BASE : files coming from rtk station or any static positioning instrument. │ └── DEVICE : files coming from the device. ├── METADATA : folder with general information files about the session. ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. │ ├── IA : destination folder for image recognition predictions. │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). Software All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!

This visualization product displays the density of floating micro-litter per net normalized per km² per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. Densities were calculated for each net using the following calculation: Density (number of particles per km²) = Micro-litter count / (Sampling effort (km) * Net opening (cm) * 0.00001) When the number of microlitters or the net opening was not filled, the density could not be calculated. Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area.

This visualization product displays the density of floating micro-litter per net normalized per km² per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. Densities were calculated for each net using the following calculation: Density (number of particles per km²) = Micro-litter count / (Sampling effort (km) * Net opening (cm) * 0.00001) When the number of microlitters or the net opening was not filled, it was not possible to calculate the density. Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. Warning: the absence of data on the map does no't necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area.