From 1 - 10 / 46
  • Phyto plankton Abundance: Identify the 3 most abundant phytoplankton species in the North Atlantic and calculate a timeseries of their abundance within the basin.

  • Annual resolution time-series of the annual averaged basin average-SST. Calculate the annual average SST on a 1degree grid and then find the area weighted average.

  • The challenge attempts to collect data on landings for the North Atlantic sea basin (i.e. north of the equator, excluding Caribe, Baltic, North Sea and Artic) and to compute: mass and number of discards by species and year. In addition, by-catch of fish, mammals, reptiles and seabirds. Data are presented in an Excel spreadsheet.

  • The aim of the product is to represent areas where all forms of resource extraction are prohibited such as: • fishing • aggregate extraction • hydrocarbon offshore facilities • aids to navigation • habitation The product is specified through the same components as for the first product plus 2 additional ones: • Pipe lines and cables • Military activity

  • We took inspiration from a “Matrix of marine activities” (appropriate for each IUCN management category) extracted from IUCN paper, to achieve the first objective by computing 1 product comprising the following 12 components: Product ATLANTIC_CH02_Product_1 / MPA Atlantic network classified in IUCN classification • Traditional fishing area • Sustainable fishing area (industrial) • Leisure fishing area • Leisure activity area (diving, surfing, tourist beaches) • Shipping area (shipping trajectory, aids navigation) • Scientific activity area • Renewable energy generation facility area (ocean energy facilities, wind farms) • Aquaculture area (finfish production, shellfish production) • Shipping infrastructure area (harbours, dredging area...) • Waste discharge area • Mining area (aggregate extraction, hydrocarbon extraction) • Habitation area (urban area) Each geographic information required for the components was compiled into a layer in grid format. These grids were intersected with the MPAs layer to assign each MPA a IUCN category according to the conditional matrix illustrated below : If the MPA area contains : Habitation area (urban area) The IUCN category is :V If the MPA area contains : Mining area (aggregate extraction, hydrocarbon extraction) The IUCN category is V If the MPA area contains : Waste discharge area The IUCN category is : V If the MPA area contains : Shipping infrastructure area (harbours, dredging area...) The IUCN category is IV If the MPA area contains : Aquaculture area (finfish production, shellfish production) The IUCN category is IV If the MPA area contains : Renewable energy generation facility area (ocean energy facilities, wind farms) The IUCN category is IV If the MPA area contains : Leisure fishing area The IUCN category is IV If the MPA area contains : Sustainable fishing area (industrial) The IUCN category is IV If the MPA area contains : Shipping area (shipping trajectory, aids navigation) The IUCN category is II If the MPA area contains : Leisure activity area (diving, surfing, tourist beaches) The IUCN category is Ib If the MPA area contains : Traditional fishing area The IUCN category is Ib If the MPA area contains : Scientific activity area The IUCN category is Ia

  • Temporal series (annual mean values) with error of estimation and Long Term Average (LTA) with error of estimation of total nitrogen load for each river mouth where in situ data is available. Different sources can be mixed if any.

  • Pentadal (5-year average) resolution time-series of bottom temperature for North Atlantic ocean area deeper than 1000m. Calculate the 5 year average bottom temperature at each point on the grid and then calculate the area weighted average.

  • Temporal series (annual mean values) and Long term Average (LTA) of water discharge for each river mouth where in situ data is available. Different sources can be mixed if any.

  • Temporal series (annual mean values) and Long Term Average (LTA) of sediment load for each river mouth where in situ data is available. Different sources can be mixed if any.

  • Data from a number of different sources have been integrated to provide new perspectives on fishing activities. Vessel Monitoring Systems (VMS) record and transmit the position and speed of fishing vessels at intervals of two hours or less. Fishing time can be calculated from the VMS data and combining this parameter with vessel logbook data, maps of fishing effort and intensity at different spatial and temporal scales can be calculated. The statistical software package “R” is used to extract the required information then re-interrogated to produce maps of fishing effort or intensity per month and year. The use of Automatic Identification System (AIS) data was not considered as combining AIS data with fisheries logbook data would pose issues namely; the ability of the AIS system to be switched off, only mandatory on vessels > 15 meters in length, cost involved to purchase data, and confidentiality.