Stock Assessment of Guam Coral Reef Fish, 2019

This report contains single-species assessments of 12 reef-associated fish stocks around the island of Guam using data from various sources focusing on the 2013–2017 period. Previous management actions have set overfishing limits (OFL) at the family level using either a percentile of historical catches or a catch-MSY approach. Here, we used life history data, fishery-independent and -dependent size composition and abundance data, and total catch estimates to calculate current fishing mortality rates (F), spawning potential ratios (SPR), and SPR-based sustainable fishing rates (F₃₀: F resulting in SPR = 30%). We used the growth-type-group length-based spawning potential ratio model (GTG LBSPR) to obtain both current mortality rates and various stock status metrics. A meta-analytical data-poor approach was used to estimate life history parameters for 6 species with either no or inadequate growth and maturity studies. We used Monte Carlo simulations to incorporate all sources of uncertainty (i.e. life history parameters, size structure, abundance, and catch). Of the 12 assessed species, 4 had median F/F₃₀ ratios greater than 1 and therefore median SPR values below the minimum overfishing limit of 30%. Another 3 species were close to this limit (30% ≤ SPR ≤ 35%). This suggests that 4 assessed species may be experiencing overfishing and 3 others may be close to experiencing overfishing (e.g. 48% risk of overfishing for Monotaxis grandoculis). SPR values among species within any given family varied. Typically, species with low SPR values were the ones with longer lifespans (e.g. Naso unicornis, Scarus rubroviolaceus, and emperors) and/or commonly reported (e.g. Caranx melampygus). Finally, for 5 species for which catch and/or biomass data were deemed of sufficient reliability, catch levels corresponding to F₃₀ (C₃₀) were calculated by combining F₃₀ estimates with current population biomass estimates derived directly from diver surveys or indirectly from the total catch. The overfishing limit (usually defined as the catch level corresponding to a 50% risk of overfishing) was calculated here as the median of the C₃₀ distribution. Overfishing probability distributions for a range of catch limits were generated.