Assessments run at AFWG provide the scientific basis for the management of cod, haddock, saithe, redfish, Greenland halibut and capelin in subareas 1 and 2. Taking the catch values provided by the Norwegian fisheries ministry for Norwegian catches1 and raising the total landed value to the total catches gives an approximate nominal first-hand landed value for the combined AFWG stocks of ca. 20 billion NOK or ca. 2 billion EUR (2018 estimates).

The purpose of this table is to present the best available abundance estimates for cetacean species in areas of relevance to the work of NAMMCO. It is intended to be used as a starting point for researchers, and the original sources are provided if additional information is required. The Scientific Committee of NAMMCO maintains a Working Group on Abundance Estimates, composed of invited experts in the field as well as some Committee members. This Working Group meets periodically to review new abundance estimates from recent surveys or, in some cases, re-analyses of older data. The reports of the Working Group are brought to the Scientific Committee at their annual meetings, and used to formulate advice on stock status, allowable removals or other matters. In most cases, the Scientific Committee will formally endorse estimates approved by the Working Group, and if so, this is indicated on the Table. Some estimates have been endorsed by the Scientific Committee of the International Whaling Commission (IWC).

This dataset containing traits of marine fish is based on fish taxa observed during international scientific bottom-trawl surveys regularly conducted in the Northeast Atlantic, Northwest Atlantic and the Northeast Pacific. These scientific surveys target primarily demersal (bottom-dwelling) fish species, but pelagic species are also regularly recorded. The overarching aim of this dataset was to collect information on ecological traits for as many fish taxa as possible and to find area-specific trait values to account for intraspecific variation in traits, especially for widely distributed species. We collected traits for species, genera and families. The majority of trait values were sourced from FishBase (Froese and Pauly, 2019), and have been supplemented with values from the primary literature.

Excel file containing CPR data from Standard Areas B4,C3,C4,D3,D4,D5,E4,F4 for the plankton Calanus finmarchicus and helgolandicus, total traverse (small) copepods, total large copepods, Phytoplankton Colour Index and Cnidaria (presence denoted by a 1, absence by a zero). All taxa are from 1980, except Cnidaria which are from 2011. Dataset is in the format of sample level data, with each row being a discrete sample, with a sample being 3m3 filtered seawater, and 10nm of tow. For each row, a sample has the following information, starting at column a: Standard area of sample, sample id, latitude (decimal degrees) of sample mid point, longitude (decimal degrees) of sample midpoint, sample midpoint date and local time, year of sample, month of sample, then plankton abundance values (or PCI index or cnidaria presence/absence). All taxa have been looked for during the period this dataset spans, so zero values represent true absence.

FishStatJ is a Windows and Mac application that anyone can use to access FAO’s Fisheries and Aquaculture statistics. They include datasets on production, trade and consumption. Data can be extracted and aggregated according to different level of details and international standard classifications. It consists of a main application and several workspaces that include the datasets.

We assembled a dataset of 14C-based productivity measurements to understand the critical variables required for accurate assessment of daily depth-integrated phytoplankton carbon fixation (PP(PPeu)u) from measurements of sea surface pigment concentrations (Csat)(Csat). From this dataset, we developed a light-dependent, depth-resolved model for carbon fixation (VGPM) that partitions environmental factors affecting primary production into those that influence the relative vertical distribution of primary production (Pz)z) and those that control the optimal assimilation efficiency of the productivity profile (P(PBopt). The VGPM accounted for 79% of the observed variability in Pz and 86% of the variability in PPeu by using measured values of PBopt. Our results indicate that the accuracy of productivity algorithms in estimating PPeu is dependent primarily upon the ability to accurately represent variability in Pbopt. We developed a temperature-dependent Pbopt model that was used in conjunction with monthly climatological images of Csat sea surface temperature, and cloud-corrected estimates of surface irradiance to calculate a global annual phytoplankton carbon fixation (PPannu) rate of 43.5 Pg C yr‒1. The geographical distribution of PPannu was distinctly different than results from previous models. Our results illustrate the importance of focusing Pbopt model development on temporal and spatial, rather than the vertical, variability.

Stakeholder networks from 32 countries united to collaborate on Ocean Action, Climate Action, addressing pollution from land-based, riverine and marine-based sources and advancing Circular Economy development. International Waste Platform provides international expertise and launches joint initiatives; It supports advancing solutions to mitigate the global waste, plastic pollution & climate crises which are interlinked. Representatives committed themselves to align objectives, to support the implementation of strategies of Ocean Action and Climate Action, as well as to share ideas, best practices, concepts, programs, knowledge and opportunities; including the reduction of plastic debris at the source, before it enters rivers and the coastal environment. Country / regional networks and national marine debris networks make a difference in societal behaviour change and environmental policies by providing input and promoting action which aims at finding solutions to reduce (ocean) plastic pollution. Country and regional networks are instrumental to reach the prevention and reduction of marine pollution, facilitate and foster the establishment of national and international partnerships in a multi-stakeholder approach.

This is the FAO Fishery and Aquaculture Reference Data repository: Codes and reference data for fishing gear, species, currencies, commodities, countries and others.

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 4 to 7 decades. Currently data is available from 1950, split into Climate Data Store entries for 1950-1978 (preliminary back extension) and from 1979 onwards (final release plus timely updates, this page). ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days (monthly means are available around the 6th of each month). In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. So far this has not been the case and when this does occur users will be notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 monthly mean data on single levels from 1979 to present".

The RAM Legacy Stock Assessment Database is a compilation of stock assessment results for commercially exploited marine populations from around the world. The RAM Legacy Stock Assessment Database is grateful to the many stock assessment scientists whose work this database is based upon and the many collaborators who recorded the assessment model results for inclusion in the RAM Legacy Stock Assessment Database. Since 2011 the RAM Legacy Data base has been hosted and managed at the University of Washington with financial assistance from a consortium of Seattle-based seafood companies and organizations, and from the Walton Family Foundation. Initial development of the database from 2006-2010 was supported by the Census of Marine Life, Canadian Foundation for Innovation, NCEAS, NSERC, the Smith Conservation Research Fellowship, New Jersey Sea Grant, and the National Science Foundation.