Estimating a population’s growth rate and year-to-year variance is a key component of population viability analysis (PVA). However, standard PVA methods require time series of counts obtained using consistent survey methods over many years. The authors of this study used REEF data along with two other fisheries datasets to evaluate the long-term trends of rockfish in Puget Sound, Washington State. The time-series analysis was performed with a multivariate autoregressive state-space (MARSS) model. The authors show that using a MARSS modeling approach can provide a rigorous statistical framework for solving some of the challenges associated with using multiple, sometimes inconsistent datasets, and can reduce the proportion of fisheries assessment cases that are assigned a designation of “data deficient.”
The analysis of the paper was part of the 5-year review of the Endangered Species Act (ESA) listing of Puget Sound populations of three rockfish species (Bocaccio, Canary Rockfish, and Yelloweye Rockfish), and was conducted by scientists at the National Marine Fisheries Service and Washington Department of Fish and Wildlife. The three sources of data included in the study were: (1) recreational catch data, (2) scuba surveys conducted by REEF surveyors, and (3) a fishery-independent trawl survey. Because there were too few observations of the three species of rockfish in the data sources to analyze these species directly, the MARSS analysis estimated the abundance of all rockfish. Because Bocaccio, Canary, and Yelloweye are deep water species, they are not often seen by REEF surveyors. The other two data sets showed that these rockfishes declined as a proportion of recreational catch between the 1970s and 2010s. The REEF data suggest that other species like Copper and Quillback rockfish have experienced population growth in shallower depths.