A review and tests of validation and sensitivity of geolocation models for marine fish tracking.

Uncertainties in fish tracking studies limit their integration into conservation and fisheries management plans. This is especially true for archival tagging studies that rely on geolocation models to infer fish tracks from recorded environmental variables. Hidden Markov Models (HMMs) are increasingly popular to geolocate marine fish equipped with archival tags; however, true errors and sensitivity of geolocation HMMs are seldom evaluated. In this study, we first review validation methods and implementations of geolocation HMMs to adapt to regional oceanography, fish species and tag data. We then use a case‐study to evaluate strengths and limitations of each validation approach and to illustrate the sensitivity of geolocation HMMs to implementation assumptions. Simulated and fixed tag locations are the most widely implemented methods, but less common methods relying on true fish tracking, that is double‐tagging or distance from recapture experiments, provide more informative estimates of model accuracy and precision. Results showed that model performance can be improved using simple assumptions when pre‐processing tag data rather than using a complex movement behaviour model. In addition, accelerometer show potential to further parameterise geolocation models. Overall, results from our case‐study and previous studies showed that current geolocation HMMs have average errors of ca. 30–50 and 120 km for demersal and large pelagic fish, respectively. We suggest that these errors are acceptable for investigations at the scale of fisheries management units. [ABSTRACT FROM AUTHOR]