Making the Most of Available Data: A Case Study of Converging Analyses to Model an Emerging Fishery for Jonah Crab (Cancer borealis)

Abstract

Targeted fishing of Jonah crabs (Cancer borealis) has greatly intensified in recent decades as lobster populations have declined, forcing fishermen to shift their focus to Jonah and other crab species. Effective management of this developing fishery is limited, however, by a lack of information on their life history traits, abundance and distribution. The long‐term sustainability of the fishery depends upon near‐term efforts to maximise the value of existing data sources to assess species abundance and inform management. We applied three distinct modelling approaches—traditional linear regression, generalised additive models and empirical dynamic modelling—to data from the Maine–New Hampshire Inshore Trawl Survey to validate hypotheses about Jonah crab distribution and migration earlier derived from interviews with fishermen. There was strong agreement between the information reported by fishermen and the survey data, including depth preferences, seasonal inshore–offshore movements and sex‐specific migration patterns. This study demonstrates that rather than simply deploying a multi‐modal approach with model selection or averaging, employing a complement of statistical methods convergently and interfacing with engaged social science can better capitalise on limited fishery‐independent data to support the development of sustainable management frameworks for emerging fisheries.