Assessing a population of stocked muskellunge (Esox masquinongy) using photo-identification and online angler-submitted data

The current methods used to assess recreational fish stocks require substantial time and monetary investment. Constraints become more prevalent in large management zones with numerous waterbodies. The popularity of online angling platforms presents an opportunity for fisheries managers to enhance monitoring effort beyond the scope of what can be achieved in a costly, limited field season. Photo-identification using computer assisted pattern recognition is a cost-effective and non-invasive method of monitoring recreational fisheries from angler submitted images. This technique takes advantage of unique natural skin markings to identify individuals within a population. Currently, only a handful of fishes have demonstrated to be effective candidates for photo-identification, and long-term pattern stability remains uncertain in most species. We examined the effectiveness of this approach by tagging and photographing stocked muskellunge (Esox masquinongy) over the course of two summers in West Watjask Lake, Manitoba. Using the freely available pattern recognition software I3S Spot (Interactive Individual Identification System), we were able to correctly match all images of recaptured fish in our database. We compared out database to angler submitted images of muskellunge occurring over the same period from an existing mobile angling application. Combining our data with angler-submitted detections, we estimated 826 (95% CI: 472–1445) muskellunge were present in the population in 2025. Our results demonstrate the potential for citizen science driven monitoring of recreational fisheries.