Chris Legault¹ and Michael Palmer^1
1Northeast Fisheries Science Center
January 27, 2015

What direction should the fishing mortality target change when natural mortality increases within an assessment?

Traditionally, the natural mortality rate (M) in a stock assessment has been assumed to be constant over years and ages. When M increases within an assessment, as has occurred in a number of Canadian cod stocks, the United States Gulf of Maine cod and Atlantic herring stocks, the question arises how to change the fishing mortality rate target (Ftarget). Yield per recruit considerations lead to an increase in the Ftarget, while maximum sustainable yield considerations often lead to a decrease in the Ftarget. Both approaches are examined using results from recent assessments of Gulf of Maine cod and Georges Bank yellowtail flounder. Problems are found with both the yield per recruit and maximum sustainable yield approaches, leading us to recommend either not allowing M to change within an assessment model or if strong empirical evidence supports a changing M to base the Ftarget on the natural mortality rate considered most appropriate based on the life history traits of the species of interest.

Chantel Wetzel^1
1School of Aquatic and Fishery Science
January 13, 2015

Are we there yet? The impact of reduced composition data on the ability to monitor rebuilding for overfished stocks.

An overfished declaration leads to changes in harvest limits, often dramatic, for the overfished stock. A reduction in catch while the stock is overfished, can lead to a reduction in length and age samples from the fishery. This can be especially problematic when the stock is rarely encountered by fishery independent surveys, with the primary source of composition data coming from the fishery. On the U.S. west coast, several overfished rockfish stocks fall into this category (e.g. yelloweye, canary). The dramatic reductions in catch will inevitably lead to rebuilding of the stock; however, the reduction in available composition data may lead to increased uncertainty about the estimated biomass status. A Management Strategy Evaluation was performed to address the long-term impact of reduced data on the ability to monitor a stock during rebuilding. This work simulates an overfished flatfish and rockfish stock where harvest and the collection of new data are restricted to address two questions; 1) does the increased uncertainty due to limited data impact the ability to correctly detect when an overfished stock is rebuilt, and 2) is there a degradation of ability to detect status correctly with limited data and if so how does this change as the amount of data increases?

Curry Cunningham^1
1School of Aquatic and Fishery Science
December 09, 2014

Methods for Forecasting of Bristol Bay, Alaska Sockeye Salmon Abundance

Bristol Bay, Alaska is home to the largest wild sockeye salmon (Oncorhynchus nerka) fishery in the world, with a total harvest value of $165 million USD in 2010 and supporting an estimated equivalent to 10,000 year-around American jobs. However, returns of sockeye to Bristol Bay are highly variable, with observed returns ranging between less than 10 million and greater than 65 million since 1960. The profitability of the commercial fishery and the ability of the commercial fishing fleet to allocate effort amongst the 5 terminal fishing districts in Bristol Bay depends to some extent on accurate predictions for the number of returning sockeye prior to, and during, the summer fishing season. The Alaska Salmon Program at UW provides inseason forecasts for Bristol Bay sockeye salmon abundance, which are updated on a semi-daily basis throughout the duration of the commercial fishery as new data become available. These inseason forecasts incorporate a wide range of data sources: 1) catch, 2) escapement, 3) age composition, 3) genetic composition of catch, and 4) inseason test fishery catch indices, to inform estimates of run size for Bristol Bay as a whole and for the major fishing districts. I will describe our current forecasting methods for inseason assessment of Bristol Bay sockeye salmon abundance, a retrospective analysis of the efficacy of these forecasting methods, and elicit new ideas for improving these methods in the future.

Dr. André E. Punt¹ and Dr. Jason Cope^2
1School of Aquatic and Fishery Science
²Northwest Fisheries Science Center
November 18, 2014

Simple Stock Synthesis (SSS) and Depletion-Based Stock Reduction Analysis (DB-SRA) are two methods for calculating overfishing limits for data-poor fish stocks. Both methods are Bayesian in that priors are imposed on the parameters of the underlying population dynamics model (although there is no information to update the priors). DSB-SRA is based on a generalized production function which allows independent priors to be imposed on BMSY/B0 and FMSY/B0. However, SSS is based on the Beverton-Holt stock-recruitment relationship so there is a functional relationship between BMSY/B0 and FMSY/B0 as expressed in the steepness parameter (h). We outline two stock-recruitment relationships (the Shepherd and Generalized Ricker) which if incorporated in Stock Synthesis may allow the goal of independent priors to be imposed on BMSY/B0 and FMSY/B0 to be achieved. We show for some example species how well these stock-recruitment relationships achieve this goal and compare DB-SRA and SSS when they are applied to some example rockfish stocks.

Owen Hamel¹, Melissa Haltuch¹, and Jason Cope^1
1Northwest Fisheries Science Center
October 28, 2014

Because growth patterns of many west coast groundfishes limit the informational value of length data, fish ages are very important inputs to our age-structured stock assessments. At the Northwest Fisheries Science Center, we conduct a variety of ageing studies, and we review three recent avenues of research: age validation, alternative ageing methods, and understanding ageing error. Age validation: We developed the first bomb radiocarbon reference chronology for the California Current, using known-age petrale sole (Eopsetta jordani). Petrale sole spend a substantial portion of their first year of life in areas subject to variable upwelling. This variable environment illustrates the importance of using reference curves for age validation that are region- and species-specific, whenever possible. Alternative ageing methods: Traditional age-reading methods are time-consuming for long-lived species. Based on initial success with two groundfishes, we explore the use of otolith weights for rapid age determination of long-lived groundfishes. We also explore the consistency of these relationships over time and space. Ageing error: The Pacific hake (Merluccius productus) stock is characterized by infrequent, strong year-classes, surrounded by average and below-average cohorts. Ageing is conducted annually, such that readers routinely know the year of collection. Ageing error is typically assumed to be largely consistent across years in stock assessments, however, we hypothesized that readers are more likely to assign uncertain hake reads to predominant ages. We conducted a double-blind study wherein previously read otoliths from many years were reread without readers knowing the collection year. Results confirmed that strong year classes experienced less effective ageing error in the regular course of ageing otoliths. Accounting for this tendency improved model fits to age data. Each of these research avenues has improved our understanding and is enabling us to develop more reliable population models and management guidance.

James T. Thorson¹, Andrew O. Shelton¹, Eric J. Ward¹, and Hans Skaug<sup>2

1</sup>Northwest Fisheries Science Center and ²University of Bergen
October 14, 2014

Indices of abundance are the bedrock for stock assessments or empirical management procedures used to manage fishery catches for fish populations worldwide, and are generally obtained by processing catch-rate data. Recent research suggests that geostatistical models can explain a substantial portion of variability in catch rates via the location of samples (i.e., whether located in high- or low-density habitats), and thus use available catch-rate data more efficiently than conventional “design-based” or stratified estimators. However, the generality of this conclusion is currently unknown because geostatistical models are computationally challenging to simulation-test and have not previously been evaluated using multiple species. We develop a new maximum likelihood estimator for geostatistical index standardization, which uses recent improvements in estimation for random fields. We apply the model to data for 28 groundfish species off the U.S. West Coast and compare results to a previous “stratified” index standardization model, which accounts for spatial variation using post-stratification of available data. This demonstrates that the stratified model generates a relative index with 60% larger estimation intervals than the geostatistical model. We also apply both models to simulated data and demonstrate (1) that the geostatistical model has well-calibrated confidence intervals (they include the “true” value at approximately the nominal rate), (2) that neither model on average under- or overestimates changes in abundance, and (3) that the geostatistical model has on average 20% lower estimation errors than a stratified model. We therefore conclude that the geostatistical model uses survey data more efficiently than the stratified model, and therefore provides a more cost-efficient treatment for historical and ongoing fish sampling data.

Eric Ward¹, Mark Scheuerell¹, and Steve Katz^2
1Northwest Fisheries Science Center and ²Washington State University
May 21, 2014

Kelp forest ecosystems (KFEs) occur globally along temperate-zone coast lines, and are some of the most diverse and productive ecosystems of the world. They also provide a wide array of ecosystem services that have sustained coastal human communities for millenia. However, harvest of apex predators and important grazers has had profound effects on KFE structure and services provided. Unfortunately, quantitative tools to quantify the impact of these stressors on ecosystem dynamics have been lacking. Here we present a novel method for analyzing temporal changes in (1) the strength of intra- and inter-species interactions within an ecosystem, and (2) the stability of the ecosystem itself. We applied a Bayesian time-varying vector autoregressive state-space (TVVARSS) model to a 32-year time series of KFE structure at San Nicolas Island, California (USA). Although sea otters were initially absent from the island, they were reintroduced in the late 1980s. We found that the resilience of the KFE has decreased over time concomitant with increased otter density, and that the KFE has also become more reactive to external perturbations such as stron El Niño events.

Vladlena Gertseva
Northwest Fisheries Science Center
April 23, 2014

The second dorsal spine has historically been used for age determination in the spiny dogfish shark. The dorsal spines are located on the external surface of the body and are subjected to natural wear and breakage. Two methods have been developed to account for the worn portion of the spine and extrapolate the lost annuli. We compared the performance of these methods using a large data collection assembled from multiple sources, and evaluated their utility for stock assessment and management of the spiny dogfish shark Squalus suckleyi in the Northeast Pacific Ocean. Our results showed that the two methods produced very different age

Kirsten Holsman
Alaska Fisheries Science Center
March 12, 2014

Climate change is expected to impact marine ecosystems globally, with largest changes anticipated for arctic and sub-arctic ecosystems. The 2°C projected increase in mean summer sea-surface temperature for Alaskan marine ecosystems may alter trophic demand, predator and prey distributions, and overall system productivity. We use multi-species food-web and assessment models to link climate-driven changes in physical and trophodynamic conditions to recruitment and survival to help distinguish fishery impacts from large-scale climate pressures. We first used a Regional Ocean Modeling System (ROMS) model coupled to a Nutrient-Phytoplankton-Zooplankton (NPZ) model to produce detailed hindcasts for the period 1970-2012. These results modulate species interactions in a climate-driven Multispecies Statistical Model (MSM) for three groundfish species from the Bering Sea (walleye pollock, Pacific cod, arrowtooth flounder). We first fit the model to hindcast-extracted time series then used downscaled IPCC scenario-driven ROMS/NPZ model estimates of temperature, circulation, and zooplankton abundance to project MSM forward to 2040. Evaluation of differing climate effects on population projections and predator-prey interactions under various IPCC forecast scenarios, recruitment models, and management strategies will be discussed.

David Sampson
Oregon State University
November 27, 2013

Most population models and stock assessment approaches assume that fish and fishing are uniform in their spatial distribution. In this Think Tank talk we will examine some of the effects that spatial structure can have on selectivity, which refers to the phenomena by which age- or size-classes of fish are not equally vulnerable to fishing. Fishery selection (selectivity) controls how fishing affects the agestructure of a fish stock, which in turn influences a stock’s productivity and ability to sustain harvests. It is possible to analyze selectivity at multiple spatial scales and selectivity can vary at these different scales. For example, the shape of the selection curve at the level of the population will be dome-shaped under a wide range of conditions, even though the gear-selection curve operating in common across all the regions is asymptotic. During this talk we will explore the factors that influence the shape of areas-asfleets selection curves, which are the form of selectivity that results from applying separate regional selection coefficients to the entire stock rather than to the regional sub-populations. Areas-as-fleets selectivity provides a mechanism for modeling spatial catch-at-age in an assessment model that is not spatially explicit. We use a simplified set of survival equations from Sampson and Scott (Can. J. Fish. Aquat. Sci. 68, 1077-1086. 2011), in which there are three distinct spatial regions and the same asymptotic selection curve operating in each region, and show that the overall population-selectivity often will be dome-shaped, but the corresponding areas-as-fleets selection curves will have shapes that differ from each other and from the population-selection and gear-selection curves. Factors that influence how much the selectivity curves differ from each other include the magnitude of the differences in the regional fishing mortality rates, the rates of fish movement and whether the movements are diffusive or directional, and the regional distribution of the recruits. Based on ad hoc explorations with the model it appears that areas-as-fleets selectivity will generally differ from the underlying gear-selectivity, except under the extraordinary conditions of equal recruitment and equal fishing mortality across all spatial regions. The talk will also explore the temporal variations that changes in the regional recruitment or the rates of fishing mortality will induce in population-selection and areas-as-fleets selection curves.