Category Archives: Fisheries Think Tank

Summiting the steepness mountain: Current and alternative approaches in determining steepness for West Coast rockfish stocks

Chantel Wetzel1
1NWFSC
October 2, 2018 9:00 (PST): FSH 203

Summiting the steepness mountain: Current and alternative approaches in determining steepness for West Coast rockfish stocks

Productivity, termed steepness, in West Coast rockfish stocks has historically been difficult to estimate within stock assessment models. Since 2007, West Coast Estimating the rockfish assessments have used a regional meta-analysis prior to estimate or fix the steepness parameter. However, the information about the steepness parameter has varied among assessments for the same species over time and the number of species included in the meta-analysis has varied since 2007 resulting in variability in the prior mean for steepness being applied in assessments for rockfish species for each West Coast groundfish assessment cycle. The assumption regarding steepness is highly influential in the assessment model and the majority of assessments for rockfish species have been unable to estimate steepness resulting in the parameter being fixed at the prior mean. This was a major issue in the 2017 Pacific ocean perch assessment where the model results were deemed implausible when steepness was fixed at the prior mean. The steepness value applied in the final model was determined using a new approach for West Coast rockfish stocks where a model-ensemble approach with alternative values of steepness were equally weighted. This presentation will examine the approach that was used in the Pacific ocean perch assessment, explore the results of this approach being applied to other rockfish stocks, and the potential challenges to this approach.

Ideas on evaluating the value of monitoring data and the vulnerability of management advice to data degradation on the US West Coast

Kristin Marshall1
1NWFSC
May 29th, 2018 9:00 (PST): FSH 105

Ideas on evaluating the value of monitoring data and the vulnerability of management advice to data degradation on the US West Coast

The costs and values of monitoring is an important consideration for natural resource management. For example, fishery independent surveys are financially demanding. Yet, sound advice for fisheries management relies on high quality survey data. On the West Coast, most stock assessment models use indices of abundance and age composition data from surveys to estimate biomass available to fisheries and inform decisions about harvest levels. Static or declining federal budgets translate to fewer dollars available to conduct fishery independent surveys. NWFSC currently faces difficult decisions about allocation of resources among surveys. In order to minimize the impact of potential reductions in survey funding and make better decisions about allocating funding, understanding the consequences of reduced survey data on assessment models is a key challenge. Recent work by the NWFSC assessment team investigated retrospective scenarios that reduced survey data by 50%, which, among other impacts, could have led to triggering the “40-10” control rule for several rockfish species. Using that study as motivation, in this talk, I will discuss (and solicit) ideas for expanding on that work with potential approaches to 1) identify target species whose management is likely vulnerable to changes in survey effort, 2) better demonstrate the costs and values of fisheries independent surveys, and 3) provide advice on how to lessen the effects of reduced budgets for monitoring.

Characterizing sources of uncertainty in future projections of the Eastern Bering Sea food web using a multi species-size spectrum model

Jonathan Reum1
1NWFSC
May 08, 2018 9:00 (PST): FSH 105

Characterizing sources of uncertainty in future projections of the Eastern Bering Sea food web using a multi species-size spectrum model

In this talk I’ll give an overview of my ongoing efforts to (1) calibrate and validate a multi-species size spectrum model of the Eastern Bering Sea and (2) generate future projections of the EBS food web using 11 different downscaled global climate model (GCM) projections. The size spectrum model can represent different hypothesized pathways through which climate may influence system dynamics. Specifically, temperature can influence predator feeding rates and natural morality and the productivity of low trophic level groups can also be modified in accordance with down-scaled estimates for the EBS using each GCM. While there are several potential sources of structural and parameter uncertainty that may influence the projection envelope, I focus on how projection uncertainty is apportioned according to GCM, climate impact hypothesis, and fishing mortality scenario over time. In a preliminary simulation experiment, near-term projection uncertainty (2020 – 2050) of biomass for some species (e.g., forage fish, snow crab, pollock) was dominated by uncertainty related to fishing mortality scenario. However, uncertainty stemming from GCMs and the specific climate hypothesis was more important for long-term (2075-2100) projection uncertainty. The reverse pattern was observed for other species (e.g., Pacific cod, Pacific halibut). I’ll discuss how this information can be useful for prioritizing future research and and developing ensemble projections. This modeling work is part of the Alaska Climate Integrated Modeling Project (ACLIM).

Detecting mortality variation to enhance forage fish population assessments

Nis S Jacobsen1, Jim Thorson1 and Tim E Essington2
1NWFSC
2SAFS
April 17th, 2018 9:00 (PST): FSH 105

Detecting mortality variation to enhance forage fish population assessments

Contemporary stock assessment models used by fisheries management often assume that natural mortality rates are constant over time for exploited fish stocks. This assumption results in biased estimates of fishing mortality and reference points when mortality changes over time. However, it is difficult to distinguish changes in natural mortality from changes in fishing mortality, selectivity and recruitment. Because changes in size structure can be indicate changes in mortality, one potential solution is to use population size-structure and fisheries catch data to simultaneously estimate time-varying natural and fishing mortality. Here we test that hypothesis by simulating the ability to accurate estimate natural and fishing mortality from size structure and catch data and compare performance among four alternative estimation models. We show that it is possible to estimate time-varying natural mortality in a size-based model, even when fishing mortality, recruitment, and selectivity are changing over time. Finally, we apply the model to North Sea sprat, and show that estimates of recruitment and natural mortality are similar to estimates from an alternative multispecies population model fitted to additional data sources. We recommend considering diagnostic tools such as ours within forage fish stock assessment to explore potential trends in natural mortality.

Ensemble models for data-poor assessment: the value of life-history information

Dr. Merrill Rudd1
1NOAA
April 03, 2018 9:00 (PST): FSH 105

Ensemble models for data-poor assessment: the value of life-history information

Scientists and resource managers need to understand a population’s biological parameters, such as mortality and individual growth rates, to successfully manage exploitation and other risks. In the absence of age data, growth rate estimates come from direct observation, proxies, or patterns in the length data while natural mortality rate estimates are often assumed based on empirical relationships with the growth rate estimates. Length composition of the catch can inform recruitment and fishing mortality, but parameter estimates depend on accurate growth and natural mortality rates. Uncertain or unreliable mortality and growth rates propagate high uncertainty in stock status estimates when relying on length data to inform vital stock assessment parameters. This study uses predictive stacking as a method of model averaging across a distribution of values for growth and mortality. We used the R package FishLife to develop distributions of life history parameters based on a multivariate model with taxonomic structure, drawing combinations of points from these distributions to integrate uncertainty in life history parameters into a data-limited, length-based stock assessment. Through simulation we demonstrate that predictive stacking leads to better assessment performance than assuming the parameter means from FishLife when the true values of life history parameters are unknown. We then applied the predictive stacking method for a U.S. Caribbean stock previously lacking accepted management advice due to debilitating uncertainty in life history parameters. This method will be applicable for stock assessments concerned with properly accounting for uncertainty in biological parameters, ranging from life-history-based to length-or age-based stock assessments.

“Progress and Challenges in Implementing Ecosystem Drivers of Recruitment in West Coast Sablefish Stock Assessments” AND “Assessing the effects of climate change on U.S. West Coast sablefish productivity and on the performance of alternative management strategies”

Melissa Haltuch1 Teresa A’mar2 Juan Valero3 Owen Hamel1 Nicholas Bond4
1NWFSC
2Fred Hutchinson Cancer Research Center
3CAPAM
4JISAO
March 06, 2018 9:00 (PST): FSH 203

“Progress and Challenges in Implementing Ecosystem Drivers of Recruitment in West Coast Sablefish Stock Assessments” and “Assessing the effects of climate change on U.S. West Coast sablefish productivity and on the performance of alternative management strategies”

U.S. West Coast sablefish is one of the most commercially valuable species targeted by the groundfish fishery. Research on ecosystem drivers of sablefish recruitment has a long history, the results of which have been a topic of ongoing debates during the scientific review of stock assessment products for management. This review extends from the published peer review literature on the topic to the most recent implementation of the sablefish stock assessment accepted for management by the Pacific Fishery Management Council. We discuss technical and implementation challenges, as well as lessons learned along the way.

AND

U.S. west coast sablefish are commercially valuable, making assessing and understanding the impact of climate change on the California Current (CC) stock a priority for (1) forecasting future stock productivity, and (2) testing the robustness of management strategies to climate variability and change. The horizontal-advection bottom-up forcing paradigm describes large-scale climate forcing that drives regional changes in alongshore and cross-shelf ocean transport and directly impacts the transport of water masses, nutrients, and organisms. This concept describes a mechanistic framework through which climate variability and change alter sea level (SL), zooplankton community structure, and sablefish recruitment, all of which have been shown to be regionally correlated. This study forecasts potential future trends in sablefish productivity using SL from Global Climate Models (GCMs) as well as explores the robustness of harvest control rules (HCRs) to climate driven changes in recruitment by conducting a management strategy evaluation (MSE) of the currently implemented 40-10 HCR as well as an alternative Dynamic Unfished Biomass 40-10 HCR. A majority of the GCMs suggest that after about 2040 there will be a slight trend towards generally lower SLs relative to the global mean, with an increasing frequency of low SLs outside of the range of the historical observations, suggesting favorable conditions for sablefish in the northern CC by 2060. Projected SLs from the GCMs suggest that future sablefish recruitment is likely to fall within the range of past observations but may be less variable and is likely to exhibit decadal trends that result in recruitments that persist at lower levels (through about 2040) followed by somewhat higher levels (from about 2040 through 2060). Although this MSE suggests that spawning biomass and catches will decline, and then stabilize, into the future under both HCRs, the sablefish stock is not projected to fall below the stock size that would lead to a fishery closure during the period analyzed (through 2060). However, the 40-10 HCR triggers stock rebuilding plans more frequently than the alternative Dynamic Unfished Biomass 40-10 HCR (based on the concept of a dynamic, rather than static, baseline stock size), suggesting that the alternative HCR is more robust to potential future climate driven changes in sablefish productivity.

Architectural principles of harvest control rules based on dynamic equilibrium analysis

Josh Nowlis1
1ECS (in service of NWFSC)
February 27, 2018 9:00 (PST): FSH 203

Architectural principles of harvest control rules based on dynamic equilibrium analysis

Harvest control rules (HCRs) translate measures of fish stock status into management action. They are a staple tool in achieving performance objectives, like optimum yield, from fisheries. Despite recent improvements, we have lacked a fundamental understanding of how design details of HCRs translate into performance. This lack of understanding is especially problematic because of the multiple competing objectives that exist for fisheries, including income/profits, conservation, predictability of income and food supply, and sustainability. Using dynamic equilibrium analysis, this paper provides fundamental architectural principles. It demonstrates how to design HCRs to achieve common objectives, illustrates constraints on performance outcomes; and identifies trade-offs among objectives. In doing so, it provides critical insight into how to achieve various performance outcomes through the design of HCRs.

An individual-based bioenergetics model to predict the response of Alaskan snow crab (Chionoecetes opilio) to ocean change: model development and calibration.

Christine Stawitz1
1SAFS
February 06, 2018 9:00 (PST): FSH 203

An individual-based bioenergetics model to predict the response of Alaskan snow crab (Chionoecetes opilio) to ocean change: model development and calibration.

Ocean change is forecasted to have the largest and most rapid effects at the earth’s poles. The Alaskan snow crab (Chionoecetes opilio), a highly valuable target species, inhabits northern Alaskan waters and has a narrow thermal tolerance. However, spatial distribution and thermal tolerance of this species vary across life stage, making cumulative effects of environmental change difficult to predict. Here, we integrate physiological data with an individual-based model for snow crab to predict population response to ocean change. Future ocean conditions are forecasted across the Northern Bering, Chukchi, and Beaufort Seas using a regional ocean model forced by global climate model (GCM) projections. Snow crab are modeled across three larval and six adult life stages. The DisMELS (Dispersal Model for Early Life Stages) framework predicts larval dispersal and settlement. Temperature-dependent growth and starvation rates are parameterized using physiological data within a bioenergetics framework. Here, I will discuss the model development and calibration with hindcast climate data.

Development of a size-structured spatiotemporal population model for invertebrates: individual growth, size-transitions, and natural and fishing mortality

Jie Cao1
1SAFS
January 23rd, 2018 9:00 (PST): FSH 203

Development of a size-structured spatiotemporal population model for invertebrates: individual growth, size-transitions, and natural and fishing mortality

Population dynamics and stock assessment models have historically modeled populations by tracking total abundance (often structured by age, size, and/or sex) across the entire stock. This practice implicitly assumes that individuals are equally mixed within each stratum, and overlooks the fact that marine populations are spatially patchy and locally structured. In this study, we apply spatiotemporal approach to population models by combining theory and methods from population dynamics and geostatistics. Specifically, spatiotemporal population models define population variables (density) as varying continuously across space, while estimating spatial variation as a random effect. Size-structured population models are convenient for populations where ageing information is unavailable or inaccurate, and such models are commonly used for assessment of crustacean species worldwide, e.g. crab, shrimp, and lobster. This proposed size-structured spatiotemporal model allows external specification of survival, growth, and size transition rates, and assumes that recruitment can be approximated as varying around a constant mean that varies spatially. Spatially-explicit catch data from fisheries are used for estimating annual fishing mortality across space. We use simulation approach to demonstrate that the spatiotemporal population model provides (1) accurate and precise estimates of spatial variation in population density and fishing mortality of each size class over years, (2) unbiased estimates of total abundance and model parameters, such as fishery selectivity. We apply this model to eastern Bering Sea snow crab, where spatially-explicit fishery-dependent and fishery-independent data are directly used.

New features for spatio-temporal analysis using FishStats: An improved model for biomass sampling data, spatial expansion of age/length compositions, and short-term forecasts for distribution shift

James Thorson1 and Melissa Haltuch1
1NWFSC
January 9th, 2018 9:00 (PST): FSH 203

New features for spatio-temporal analysis using FishStats: An improved model for biomass sampling data, spatial expansion of age/length compositions, and short-term forecasts for distribution shift

In this talk, we quickly summarize the FishStats spatio-temporal toolbox (www.FishStats.org), including the spatio-temporal approach to index standardization. We then highlight three research topics since my last Think Tank in Nov. 2016. First, we highlight a new “Poisson-link delta model” (PLDM) that is more biological interpretable and parsimonious than the conventional delta-model that is widely used in fisheries science. We also discuss how this PLDM is interpreted as a computationally efficient approximation to a compound-Poisson-gamma model. Second, we discuss ongoing research using a vector autoregressive spatio-temporal (VAST) model to expand age and length composition samples, including a calculation for input sample size based on estimation variance. A simulation experiment shows that the VAST model has 20-30% lower errors than the design-based estimator, but a case-study application involving lingcod shows that small differences in composition expansion can result in a large difference in scale when used in an assessment model. Finally, we discuss ongoing research regarding short (1-3 year) forecasts of distribution shift using a climate-envelope or spatio-temporal model using retrospective skill testing. This shows that autoregressive spatio-temporal errors are important to generate unbiased forecasts with good forecast interval coverage. We therefore conclude by recommending increased use of the Poisson-link delta model, particularly for forecasting future distribution shifts, but further research regarding spatio-temporal expansion of composition data.