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

The impact of fishing on benthic habitats has previously been investigated however; a conclusive classification of potentially sensitive habitats per gear type does not exist. Currently only qualitative estimates of fishery impact using Broad-scale habitat maps are possible. Here a sensitivity matrix using both fishing pressure (fishing Intensity) and habitat sensitivity is employed to define habitat disturbance categories. The predominant fishing activities associated with physical abrasion of the seafloor area are from bottom contacting towed fishing gear. The swept area of the aforementioned gear in contact with the seabed is generally considered a function of gear width, vessel speed and fishing effort (ICES. 2015). The varying characteristics of fishing gear, their interaction with the sea floor and species being targeted; provide scope for differing interactions with subsurface (infaunal) and surface (epifaunal) dwelling communities. An evaluation of the abrasion pressure and habitat sensitivity split into surface and subsurface pressure allows greater insight to the ecological effects. Fishing intensity was calculated annually and based on the area of sea floor being swept (or swept area ratio SAR) by gear type. Calculations are based on SAR’s of gear types per area, per year. Fishing pressure ranks and habitat sensitivity ranks obtained from WGSFD working group (01 WGSFD - Report of the Working Group on Spatial Fisheries Data 2015) can be incorporated within a GIS environment to existing ICES fisheries data to provide habitat disturbance maps (fishing pressure maps+ habitat sensitivity maps) ICES. 2015. Report of the Working Group on Spatial Fisheries Data (WGSFD), 8–12 June 2015, ICES Headquarters, Copenhagen, Denmark. ICES CM 2015/SSGEPI:18. 150 pp.

Annual time series of salmon recruitement biomass (2005-2014): • Time series of atlantic salmon recruitment • Location and Long Term Average (LTA) of atlantic salmon recruitment per Management Unit, that could be a river, basin district, a region or a whole country.

Map at 1 degree resolution of 50-year linear trend in sea water temperature at 3 levels: surface, 500m, bottom.

North Atlantic basin average at Pentadal (5-year) resolution time-series of the ocean heat storage (upper 700m) and kinetic energy. Use gridded information to calculate the local heat storage and average kinetic energy as a 5 year average and then calculate the basin average.

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.

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.

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

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.

Map the occurrence of ice at 1-degree resolution over different periods of the last century (1915-2014, 1965-2014, 2005-2014, 2009-2014). For each entire period (100, 50, 10, 5 years) find and map all cells of the 1 degree grid that experience ice conditions in at least 1 month.