Richard D. Methot

Effects of California El Niiio 1982-1984 on the northern anchovy

El Nitio caused physical and biological changes in the northern anchovy habitat off southern California. Anomalous sea surface temperatures, surface currents, mixed layer depths, and plankton biomass levels began to appear in late 1982 and persisted into 1984. Growth of juvenile and adult anchovy slowed during El Nitio, probably due to reduced availability of zooplankton prey. A decrease in size-at-age in early 1983, with a recovery in late 1984, can be explained by movements of the stock and the latitudinal cline in size-at-age. Spawning range expanded in 1983 due to shifts in sea surface temperature boundaries. Early larval mortality was unusually high in the yolk-sac stage. Fecundity per unit spawning biomass was low in 1983, due primarily to a high proportion of first-year spawners. Size-at-age was very low by spring 1984, but specific fecundity was surprisingly high. Although El Nifio had a variety of significant effects on the northern anchovy, the stock seems to have recovered in 1985.

Stock Assessment: Operational Models in Support of Fisheries Management

Fishery stock assessment models connect ecosystem data to quantitative fishery management. Control rules that calculate annual catch limits and targets from stock assessment results are a common component of US Fishery Management Plans. Ideally, the outcome of such control rules are updated annually on the basis of stock assessment forecasts to track fluctuations in stock abundance. When the stock assessment - fishery management enterprise achieves this level of through- put, they truly are operational models, much as the complex physical models used to routinely update climate forecasts. In reality, many contemporary assessments are closer to an individual scientific investigation than to an operational model. As a result, the review of each stock assessment is extensive and the lag between data acquisition and quota adjustment may extend to several years. If the future stock assessment process is to move towards an operational status, there will need to be changes in three aspects of the process. First, key data streams will themselves need to be made more operational and corporate so that relevant data are immedi- ately available and trusted. Second, stock assessment models need to be made more capable of including diverse relevant data and comprehensively calculating levels of uncertainty, while also being more completely tested, documented, and standard- ized. The class of models called integrated analysis has these characteristics and is described here, with emphasis on the features of the Stock Synthesis model. Areas of future model development, especially to include more ecosystem and environ- mental factors, are explored. Third, increased throughput of assessment updates will require streamlining of the extensive review process now routinely required before stock assessment results can serve as the scientific basis for fishery manage- ment. Emphasizing review of broadly applicable assessment data and methods, rather than each final result, is a logical step in this streamlining, while maintaining public trust in the final results.

A Simulation-Based Method to Determine Model Misspecification: Examples Using Natural Mortality and Population Dynamics Models

Abstract Recent developments in the models used in wildlife and fisheries science have allowed the inclusion of a wider range of data than previously. However, the diagnostics of such complex models have not kept pace. We describe a new diagnostic technique based on simulation analysis. Model misspecification was identified through simulation methods that created a distribution of likely parameter values for a model that was correctly specified. If the actual estimate of that parameter is outside the bounds of the simulated distribution, then the model is probably misspecified. We tested the reliability of the new diagnostic by introducing known-model misspecification into complex fisheries stock assessment models. We then compared the results from this new diagnostic with those of a more tradition fisheries diagnostic, namely, retrospective analysis. The simulation-based diagnostic was shown to identify inisspecification affecting the estimated dynamics more reliably than retrospective analysis.

Drivers and rates of stock assessments in the United States

Fisheries management is most effective when based on scientific estimates of sustainable fishing rates. While some simple approaches allow estimation of harvest limits, more data-intensive stock assessments are generally required to evaluate the stock’s biomass and fishing rates relative to sustainable levels. Here we evaluate how stock characteristics relate to the rate of new assessments in the United States. Using a statistical model based on time-to-event analysis and 569 coastal marine fish and invertebrate stocks landed in commercial fisheries, we quantify the impact of region, habitat, life-history, and economic factors on the annual probability of being assessed. Although the majority of landings come from assessed stocks in all regions, less than half of the regionally-landed species currently have been assessed. As expected, our time-to-event model identified landed tonnage and ex-vessel price as the dominant factors determining increased rates of new assessments. However, we also found that after controlling for landings and price, there has been a consistent bias towards assessing larger-bodied species. A number of vulnerable groups such as rockfishes (Scorpaeniformes) and groundsharks (Carcharhiniformes) have a relatively high annual probability of being assessed after controlling for their relatively small tonnage and low price. Due to relatively low landed tonnage and price of species that are currently unassessed, our model suggests that the number of assessed stocks will increase more slowly in future decades.