Use of Observer Data to Validate a GPS-Based Effort Prediction Model for Southeast U.S. Reef Fish Fisheries

The use of vessel speed alone from Global Positioning Systems (GPS) data to predict effort has worked well for trawl fisheries but proven less successful in stationary fisheries. Five trips on four vessels from a Southeast U.S. vertical hook and line reef fish fishery were used to examine the efficacy of GPS (speed and time) and electronic monitoring (EM) specific sensors (drum and video) to corroborate an observer’s account of effort.  Ninety-five percent and 53% of fishing and non-fishing activity occurred at speeds ≤ 0.4 knots, respectively.  No fishing occurred at night, defined as the seven hours > 2200 and < 0500 hours.  Four nested binary logit models were applied across two conditions: using all combined data (24 hour) and a subset of combined data (17 hour) that sheltered night records from model predictions.  Model classification success ranged from 59% to 93% and performed best when all four variables were used.  The GPS based logit models were effective only when night records were sheltered from model predictions.  Extensive regional observer data suggests the night record exclusion is warranted.  Results indicate that filtered GPS data can be used to provide a detailed account of effort similar to that of an observer.