Research project

SmartDots for quality assurance of biological data for stock assessment

Transverse section of a western Baltic cod otolith.
Otolith


The Smart4SAM research project will develop a management framework for quality assurance of age and maturity data on fish and the integration of this data into stock assessments. This will improve the output of the biological assessment and scientific advice on the sustainable management of fisheries. 

Background of Smart4SAM

The Common Fisheries Policy (CFP) sets EU quotas and other rules for sustainable fisheries, relying on robust scientific data and accurate scientific advice.

To support stock assessments, biological data are collected in international cooperation under the EU Data Collection Framework (DCF). From the data key parameters like fish growth, mortality, and spawning stock size are estimated.

Age and reproductive maturity, determined from fish otoliths (ear stones) and gonads, are critical but prone to subjective interpretation, introducing uncertainty in the data set.

The SmartDots platform, used for managing age and maturity data, assesses data uncertainty, but does not integrate outputs into stock assessments.

The Smart4SAM project will enhance standardized data collection, quality assurance, and bias reduction, and promote international cooperation via SmartDots to improve assessments and overall fisheries management.

Smart4SAM is an acronym for “SmartDots for monitoring, accuracy and reliable training of essential biological data—quality assurance for stock assessment”.

SmartDots-user-interface
SmartDots user interface showing image of otoliths, annotation tools and associated data.

What is SmartDots?

SmartDots is an online platform and software suite for calibrating, exchanging, and managing biological data, primarily for assessing fish age through otolith (ear stone) image annotation.

SmartDots ensures quality assurance in stock assessments by allowing experts to read and annotate fish samples. The results from SmartDots contribute scientific data for fish stock assessments. 

SmartDots is developed by ILVO (Flanders Research Institute for Agriculture, Fisheries and Food, Belgium) in collaboration with ICES (International Council for the Exploration of the Sea). 

Goals of Smart4SAM

The overall aim of the Smart4SAM research project is to enhance the sustainable exploitation and protection of marine resources under future climate change scenarios.

Smart4SAM will develop a management framework for quality assurance of age and maturity data on fish, and their integration into stock assessments by: 

  • Expanding the ICES SmartDots platform with functionalities for creating Reference Collections, enabling self-training, quality control, and uncertainty quantification. 
  • Adapting and testing Stock Assessment Models with functionalities to integrate data uncertainty from standardized SmartDots outputs. 
  • Advancing Artificial Intelligence applications to support biological data interpretation and integration into SmartDots. 

Smart4SAM will focus on vulnerable stocks and commercially and ecologically important species. 

The tools, protocols and guidelines developed are generic and will be readily transferable across species and regions. 

The project lasts three years and will finalize in autumn 2028.

 

Schematic representation of Smart4SAM contribution
Schematic representation of Smart4SAM’s contribution to the process from sample collection to advice and management.
Laboratory set-up
Laboratory set-up for digital acquisition of otolith images.

Main activities of Smart4SAM

Reference collection
The project will develop a Reference Collection module that enables global compilation, annotation, and approval of otolith and maturity images in SmartDots, creating public reference sets for age and maturity assessment.

Training and quality control
The project will develop a Training and Quality Control module, allowing selection of sets for user training and monitoring temporal consistency, providing R-script reporting of inter- and intra-reader comparisons.

Stock assessment models
The project will adapt stock assessment models, including SAM (State-Space Assessment Model) and other global models, WHAM (Woods Hole Assessment Model), A4A (Assessment for All) and Stock Synthesis, to integrate age reading errors, improving uncertainty estimates and stock status evaluations for sustainable fisheries management. 

AI algorithms
The project will develop and test AI algorithms for age estimation, comparing outputs with expert readings and integrating genetic and biological data to strengthen accuracy, standardization, and applicability across species and regions.

Outputs from Smart4SAM

Partners of Smart4SAM

National Institute of Aquatic Resources, DTU Aqua, Technical University of Denmark

Website: aqua.dtu.dk

Contact: Project Coordinator Karin Hüssy and Julie Olivia Davies 

The Portuguese Institute for Sea and Atmosphere, IPMA, Portugal

Website: ipma.pt

Contact: Patrícia Gonçalves 

Flanders Research Institute for Agriculture, Fisheries and Food, ILVO, Belgium

Website: ilvo.vlaanderen.be

Contact: Karen Bekaert 

International Council for the Exploration of the Sea, ICES

Website: ices.dk

Contact: Carlos Pinto 

Wageningen Marine Research, The Netherlands

Website: wur.nl

Institute of Marine Research, IMR, Norway

Website: hi.no

Government of Canada represented by Fisheries and Oceans Canada, DFO, Canada

Website: dfo-mpo.gc.ca

Funding of Smart4SAM

The Smart4SAM project has received funding (GAP-101241407) from the European Maritime, Fisheries and Aquaculture Fund (EMFAF-2023-PIA-FisheriesScientificAdvice: “Improving scientific knowledge to strengthen the science-basis of management decisions under the Common Fisheries Policy).

Smart4SAM's page on EU's grant portal

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