Anglers make decisions that have consequences for the fish stocks, ecosystems, and socio-economics with which they interact. Smartphone angling applications (apps) are a potentially less expensive and more comprehensive data source than conventional methods, but their utility has not been evaluated. In this study, I compared results from app and aerial creel survey data from Ontario, Canada. A standard major axis regression found low agreement between effort estimates (n=111, R2=0.20, p=8.2458e-07) and app-based effort was poorly explained by lake characteristics in a random forest analysis (7.66% vs. 29.52% for creels). Explained variation improved when I included more lakes, but province-wide effort prediction did not agree with those based on creel data. I attribute these inconsistent results to low app data volumes and inherent differences between collection and analyses. Until more app data are generated, I recommend using app data to supplement conventional surveys and gain novel insights into angler behavior.
