Dr. Owen Hamel^1
1NWFSC
February 02, 2016 9:00 (PST): FSH 213

Investigating measures of fishing impact for use in informing management

NOTE THE ROOM CHANGE == FSH 213

Coauthors: Christopher M. Legault, Grant G. Thompson and Richard D. Methot, Jr.

Fishery management is informed by measures of the impacts of fishing on fish stocks. However, while a number of these measures have been proposed and used, none is able to capture all the short- and long-term impacts of fishing on fish stocks. One set of such measures are fishing intensity metrics, which under one definition are invariant to changing population structure, but because of that very attribute may poorly reflect the impact of fishing on a stock in any one year. Other common fishing intensity metrics are either inconsistent measures given changes in fishery selectivity (e.g. apical fishing rate F or exploitation rate U) or reflect only long term equilibrium effects (e.g. Spawning Potential Ratio (SPR) or Equilibrium Stock Depletion (ESD)). Other measures, which we call “fishing impact metrics”, may better reflect the short-term impacts of fishing or the impacts of short-term fishing. This may be especially important in certain situations, such as when fisheries target strong cohorts, and therefore fishing intensity metrics that are independent of the beginning of year numbers-at-age may underestimate both short- and long-term impacts. We will discuss a number of alternative fishing intensity and impact metrics with the goal of finding metrics which reflect short-term impacts under a variety of fishing strategies, as well as to allow for comparison across stocks and across alternative stock assessment methodologies.

Dr. Darcy Webber^1,2
1QUANTIFISH
²SAFS, UW
January 19, 2016 9:00 (PST): FSH 213

Exploring Bayesian state-space age-structured fisheries population dynamics models

Fisheries stock assessment models use incomplete observational data and knowledge of the system we are modeling to provide estimates of key management parameters, and require that we assume that the resulting uncertainty is properly reflected in the outputs. Current models typically follow a ‘deterministic’ approach. They are deterministic in the sense that the population follows sets of equations that deterministically define the population state from a previous state, without stochastic error.
State-space models provide an alternative approach to implementing fisheries assessment models. They can incorporate both observation uncertainty and the uncertainty that arises from modelling a simplification of reality — usually referred to as process error. Specifically, state-space models relate observations to unobserved states (e.g. numbers of fish in this context) through stochastic observation equations. Stochastic transition equations define how the unobserved states are assumed to evolve over time. Because state-space models incorporate both observation and process error explicitly, they may be able to help us better quantify the uncertainty of parameters of interest for management.
Until recently, state-space models have not been more frequently applied because they have been technically difficult to implement. However as computational methods in general and Bayesian methods in particular, become more sophisticated, the approach is becoming increasingly tractable.

Michelle Jones^1
1Simon Fraser University
January 05, 2016 9:00 (PST): FSH 203

Maturing estimates of maturity – probabilistic maturation reaction norms for British Columbia sablefish (Anoplopoma fimbria)

Predicting the size and age at which fish will mature is a key factor in estimating stock productivity. In fisheries stock assessment, this relationship is usually defined by estimating maturity ogives, which describe the proportion of the stock mature at a given age or length. However, length is a function of growth. Thus, differences in growth rates among years may cause apparent changes in maturation rates. While consistent spatial variation is expected in maturity ogives, in the case of sablefish (Anoplopoma fimbria), significant temporal variation in maturity ogives is unexpected and is large enough to cause substantial concern to stock assessment modeling. Here, we examine Probabilistic Maturation Reaction Norms (PMRNs) as an alternative for estimating sablefish maturity schedules. PMRNs condition the probability an individual will mature over a set time interval given its age, size, and survival, which may reduce confounding among each of these parameters, providing a temporally-stable model. If PMRNs can provide a stable relationship to estimate sablefish maturity schedules, then uncertainty in stock assessment models may be significantly reduced.

Dr. James Ianelli^1
1AKFSC
November 24, 2015 9:00 (PST): FSH 203

Data [un]limited assessments? Minding the gaps…

A critical and seemingly less emphasized component of fisheries research involves sampling design and efficiency. Also, understanding how sampling designs and effort has changed over time is an important element for specifying scale parameters (e.g., variances or sample sizes) for stock assessment modeling. In this discussion session we’ll illustrate some big-data tools (i.e., some rudimentary Hadleyisms) and approaches used to estimate variability from sampling to achieve process error estimates so they can be evaluated relative to risk-averse control rules. Examples include novel approaches to modeling fishery weight-at-age for Bering Sea pollock and growth increments related to bottom temperature for yellowfin sole from the same region.

Caitlin I Allen Akselrud^1
1SAFS
November 10, 2015 9:00 (PST): FSH 203

Application of an age-length structured population dynamics model to data for Eastern Bering Sea Tanner crab (Chionoecetes bairdi)

Fishery stock assessments are frequently based on either age-structured population dynamics or length-structured dynamics. We have developed and implemented a model to account for both age and length dynamics for an individual fishery. An age-length assessment model is unique in its ability to capture the dynamics of fishing mortality and natural mortality on fish populations, which are functions of both length and age. By accounting for both factors, the age-length model should reduce estimation bias present in models that only account for age (or length) dynamics, and assist managers in achieving statutory goals for fishery management.
Simulation studies have showed that the age-length models can provide essentially unbiased estimates of biomass trajectories and have low sensitivity to the precision of the data. Here we evaluate these models using the actual data for the Eastern Bering Sea Tanner crab (Chionoecetes bairdi) fishery. The data include catches, fishing effort, and survey index, as well as length-composition and conditional age-at-length. Survey and fishery data (including several fleets) are available for each stock.

Dr. Allan Hicks^1
1NWFSC
October 27, 2015 9:00 (PST): FSH 203

A management strategy evaluation for Pacific Hake: the past and future

Management strategy evaluation (MSE) is a tool that can be used to investigate data collection, assessment assumptions, and harvest rules for a fishery. A condition of the Marine Stewardship Council (MSC) certification for the Pacific Hake (Merluccius productus) fishery was to use MSE to investigate the harvest rule defined by an International Agreement between the U.S. and Canada. This started a more expansive MSE in 2012 for the Pacific Hake fishery that attempted to define fishery and management objectives as well as investigate data collection, the assessment model, and the harvest rule. This process has been a learning experience with incremental changes made along the way. I will describe this learning process along with an explanation of how the closed-loop simulation, a part of the larger MSE process, was implemented. Some results of our analysis and how they have influenced the assessment and management of Pacific Hake will be presented, followed by a vision of how this MSE may continue to evolve in the future.

Presentation