Improving efficiency of estimating angler effort using low-frequency time-lapse camera data

ABSTRACT Objective Management agencies rely on estimates of angling effort to make many management decisions. Managers frequently use counts of boats, trailers, or anglers alongside traditional interview-based creel methods to inform effort estimates. Use of remote cameras for capturing effort data is increasing, but despite the advances made related to this technology, processing photos from surveys is still very time consuming and limits the implementation of these methods. Additional guidance is needed as to what level of effort is necessary to produce reliable estimates of angler effort while minimizing processing times. Methods In this study, we used images captured at low frequency with time-lapse remote cameras to quantify angling effort based on instantaneous trailer counts at six reservoirs in Arkansas. We determined “true” values of effort based on images taken hourly every day for 3 months. By simulating across a range of sampling frequencies (number of days per month and number of photos per day), we assessed the percent error from the true values. Results We determined that analyzing photos from 12 weekdays and seven weekend days per month at a frequency of one randomly selected photo per day was adequate to produce estimates of effort with less than 20% error 80% of the time (well performing). Counting photos from at least 18 weekdays and eight weekend days per month at a frequency of 2 and 4 photos/d, respectively, produced estimates of effort with less than 10% error 80% of the time (best performing). Conclusions The estimated amount of time required to analyze a month’s worth of photos for the best-performing scenario ranged from 9 min for Jack Nolan Lake to 100 min for Lake Dardanelle. Our work provides guidance to managers on how to most efficiently conduct camera surveys to estimate angler effort.