Work

Pathways toward modernizing fisheries-independent surveys

Year: 2026
Type: article
Abstract: Fisheries-independent survey(s) (FIS(s)) are conducted worldwide to study the status of marine populations and ecosystems and provide consistent time-series data for use in stock assessments, ecosystem assessments, ecological studies, and forecasting. These time series allow researchers to track changes in populations and ecosystem responses to environmental variation over time and can be used to reveal trends and patterns that single observations cannot capture. However, the consistency and continuity of a FIS time series may be impacted by natural forces (e.g. changes in environment, stock distribution, and weather) or anthropogenic actions (e.g. funding, vessel availability, new sampling objectives, new technology, and reduction of sampling area due to spatial closures or restrictions). These issues, and others, are increasingly common due to changes in marine ecosystems, increased human activities in and around FIS areas, and the evolution of FIS technologies and statistical methods. We review drivers that are triggering changes in FISs and propose pathways for adapting existing FISs to these changes while ensuring consistency in the information provided by FIS time series. We show that there is potential for advanced technologies (e.g. autonomous vehicles, remotely operated vehicles, and eDNA) to improve information collected from traditional FIS methods (e.g. trawls, longlines, acoustics, and pots). The modernization of FISs is best achieved through incremental incorporation and calibration of new technologies to existing FIS designs and operations, rather than a wholesale replacement of existing methods that would disrupt the historical baseline of a time series. These transitions of FISs in a changing world can be aided by developing methods to collect FIS data using multiple types of equipment and/or from multiple FIS platforms.
Language: English
Subfield: Aquatic Science
Open Access status: gold
Estimated APC paid: $3,686
OpenAlex ID: W7168842691
FWCI: 4.362
Cites: 109
Cited by: 1
Related to: 10