34 research outputs found
RAM Legacy Stock Assessment Database v4.494
No full textRAM Legacy Stock Assessment Database version 4.49
RAM Legacy Stock Assessment Database v4.61
No full textRAM Legacy Stock Assessment Database version 4.6
RAM Legacy Stock Assessment Database v4.46
No full textRAM Legacy Stock Assessment Database version 4.4
RAM Legacy Stock Assessment Database v4.44
No full textRAM Legacy Stock Assessment Database version 4.44.</p
Extended RAM Legacy Stock Assessment Database version 4.61
No full textExtended RAM Legacy Stock Assessment Database version 4.61
Please be aware that this ‘mdl’ ('model fits included') version 4.61 of the RAM Legacy Stock Assessment Database (RAMLDB) additionally includes data not contained in the assessments themselves, but generated from assessment data. Generated data are used to fill in gaps where possible, for example, if stock assessments do not include reference point estimates. Supplemented data include calculations from assessment values, conversions of biomass variables, and reference points estimated post-hoc with surplus production models. The ‘Documents’ folder includes documentation files on the methods used for these calculations, conversions and model fitting. When assessment data are available, they are used preferentially in all cases.
Although we identify data that were supplemented from data that were derived from stock assessments, some collector variables in RAMLDB include both of these data sources (with assessment values preferred). We recommend that the average user does not use this 'mdl' version of RAMLDB because of the additional assumptions and calculations involved. Instead, to avoid confusion between assessment-derived values and supplemented values, we recommend using the ‘asmt’ ('assessment data only') version of RAMLDB version 4.61. This 'asmt' version (10.5281/zenodo.7814638) is also available in our Zenodo repository: https://zenodo.org/communities/rlsadb
Extended RAM Legacy Stock Assessment Database version 4.494
No full textExtended RAM Legacy Stock Assessment Database version 4.494
Please be aware that this ‘mdl’ ('model fits included') version 4.494 of the RAM Legacy Stock Assessment Database (RAMLDB) additionally includes data not contained in the assessments themselves, but generated from assessment data. Generated data are used to fill in gaps where possible, for example, if stock assessments do not include reference point estimates. Supplemented data include calculations from assessment values, conversions of biomass variables, and reference points estimated post-hoc with surplus production models. The ‘Documents’ folder includes documentation files on the methods used for these calculations, conversions and model fitting. When assessment data are available, they are used preferentially in all cases.
Although we identify data that were supplemented from data that were derived from stock assessments, some collector variables in RAMLDB include both of these data sources (with assessment values preferred). We recommend that the average user does not use this 'mdl' version of RAMLDB because of the additional assumptions and calculations involved. Instead, to avoid confusion between assessment-derived values and supplemented values, we recommend using the ‘asmt’ ('assessment data only') version of RAMLDB version 4.494. This 'asmt' version (doi 10.5281/zenodo.4823686) is also available in our Zenodo repository: https://zenodo.org/communities/rlsadb
Extended RAM Legacy Stock Assessment Database version 4.46
No full text<p>Extended RAM Legacy Stock Assessment Database version 4.46</p>
<p>Please be aware that this ‘mdl’ ('model fits included') version 4.46 of the RAM Legacy Stock Assessment Database (RAMLDB) additionally includes data not contained in the assessments themselves, but generated from assessment data. Generated data are used to fill in gaps where possible, for example, if stock assessments do not include reference point estimates. Supplemented data include calculations from assessment values, conversions of biomass variables, and reference points estimated post-hoc with surplus production models. The ‘Documents’ folder includes documentation files on the methods used for these calculations, conversions and model fitting. When assessment data are available, they are used preferentially in all cases.<br>
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Although we identify data that were supplemented from data that were derived from stock assessments, some collector variables in RAMLDB include both of these data sources (with assessment values preferred). We recommend that the average user does not use this 'mdl' version of RAMLDB because of the additional assumptions and calculations involved. Instead, to avoid confusion between assessment-derived values and supplemented values, we recommend using the ‘asmt’ ('assessment data only') version of RAMLDB version 4.46. This 'asmt' version (10.5281/zenodo.3676083) is also available in our Zenodo repository: <a href="https://zenodo.org/communities/rlsadb/">https://zenodo.org/communities/rlsadb/</a></p>
RAM Legacy Stock Assessment Database Geospatial Regions
No full text<p>This data archive describes region definitions for the RAM Legacy Stock Assessment Database. Within the RAM Legacy database, stock assessments are associated with named areas. We approximate coordinates and bounding boxes for each of these areas, using country EEZs and fishing area shapefiles when appropriate. In addition, we develop a simple language to encode the GIS shapes of the areas, along with an interpreter to translate these codes into polygons. The syntax supports using political entities, shapefile regions, circles and rectangles, clipped versions of these, and combinations of these.</p>
<p>The archive contains the following contents:</p>
<p> - syntax.pdf: This document describes the geocoding syntax, and lists all of the geocoding descriptions for the assessment regions.</p>
<p> - results: This folder contains a shapefile of assessment regions (ram.shp) and a summary file of each region's centroid and size.</p>
<p> - sources: This folder contains shapefiles for FAO regions and New Zealand fishing regions, used by the syntax system, and latlon.csv which contains the region descriptions for each assessment region.</p>
<p> - code: load_areas.R contains functions that interpret the geocoding syntax and genshape.R generates the ram.shp shapefile.</p>
The Mediterranean and Black Sea STECF Stock Assessment Database
Get PDFSince 2007, the Scientific Technical Economic Committee for Fisheries (STECF), for which Joint Research Centre (JRC) runs the Secretariat and all the data collection process, started collecting and organizing information on Mediterranean and Black Sea fisheries, and since 2009 performing standardized stock assessments on these fisheries during STECF expert working groups (EWGs).
The stock assessment results have been documented in more than 30 reports STECF EWGs (https://stecf.jrc.ec.europa.eu/reports/medbs).
Stock assessments performed during the STECF EWGs employ different approaches and tools, however, models implemented in the Fisheries Libraries in R (FLR, http://www.flr-project.org) were the most used.
After almost 10 years of stock assessments in the Mediterranean and Black Sea, JRC extracted available stock assessment data from digital repositories of EWGs and compiled a STECF reference database.
From each assessment contained in the STECF reports yearly time series of stock variables such as:Total Catch (total weight of all fish in the stock), Recruitment (total number of individuals entering yearly in the population), Spawning Stock Biomass (total weight of all sexually mature fish in the stock) and Fishing Mortality were extracted.
The assessments data are made available through an online interactive dashboard under the STECF Data dissemination web page (https://stecf.jrc.ec.europa.eu/dd/medbs/ram) that allow readers to compare and contrast several stock assessments variables. Each stock assessment is linked via an URL to the original source of the stock assessment.
According to EU CFP - Common Fisheries Policy (Reg. EU 1380/2013 and Reg. EU812/2015) all EU commercial fish stocks should be fished at a maximum sustainable yield (Fmsy). Biological reference points, Fref (Fmsy or a proxy as F 0.1 ) and were subsequently used to assess if the level of exploitation (F/Fmsy) is in line with the CFP objectives
(F/Fmsy≤1) or not (F/Fmsy >1).
The STECF database is the reference database for the computation of the Common Fisheries Policy monitoring indicators for the Mediterranean and Black Sea
(https://stecf.jrc.ec.europa.eu/documents/43805/2092142/STECF+18-01+adhoc+-+CFP+Monitoring+2018.pdf)
To ensure traceability and foster reproducible scientific research, all the data, code and references part of the compilation process are hosted on GitHub, a well-known version control software platform.
The target audience of the dashboard ranges from governments, fisheries institutes, stakeholders, NGO’s and common citizens that want to check the status of marine fisheries resources evaluated.
A copy of the Mediterranean and Black Sea STECF stock assessment results will be included, for the first time, in the next release of the RAM legacy database: a voluntary contributed worldwide stock assessments database, RAM legacy, (http://ramlegacy.org/).
The RAM Legacy database includes fish stock assessments from all around the world’s oceans, and provides a unique source of information to make comparisons between fisheries and to perform global analysis of stock status.JRC.D.2 - Water and Marine Resource
Modelling the effects of climate change on the distribution and production of marine fishes:Accounting for trophic interactions in a dynamic bioclimate envelope model
Get PDFClimate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment
