F— Letter to Analysts
March 19, 1996
Dear [Analysts]:
We are ready to embark on the simulation study discussed at the OSB Stock Assessment Committee meeting in January. The following analysts have agreed to work on the project (names and locations in original letter are deleted here):
Analyst 5, Analyst 2, and Analyst 3—will do two delay-difference models (measurement error, measurement and process error) and a stock synthesis model
Analysts 6 and 7—will do a stock synthesis model and a Bayesian stock synthesis model
Analyst 1—will do a nonequilibrium production model
Analyst 4 will do an ADAPT model. As discussed at the January meeting, Analyst 4 would prefer to do this in a workshop setting with other colleagues… We have no objection to this and hope that NMFS will provide the support to enable this. We request that these teams do their work independently of each other.
Attached please find an Excel spreadsheet that contains data sets from 5 age-structured populations. Each data set contains information on many population parameters such as growth and maturity. There are also statistics from the fishery: reported catch and effort and age composition. A survey was conducted and summarized as a relative index along with survey age composition. Simple random samples of age composition were taken from the catch (n=500) and from the survey (n=200). Ageing error is present and the ageing error matrix is given to you. There are some further details below.
We would like you to analyze each data set in three ways if you can:
[A]: using CPUE as the only measure of relative abundance;
[B]: using only survey information;
[C]: using both CPUE and survey information.
This will allow us to address the question of whether surveys are important. We can label the analyses as 1A, 1B, 1C, 2A,…, 5C. IT IS CRITICAL THAT THE "A" AND "B" ANALYSES BE DONE FIRST AND ARE INDEPENDENT OF THE "C" ANALYSES. (i.e. Do not revise the A and B analyses based on what you come up with in the C analyses.)
As time permits, we would also like to get retrospective analyses of each data set and analysis. Ideally, we would like to get 15 retrospectives per analysis (i.e. years 1-16, … years 1-30). These analyses should be done
independently (i.e., please do not use results from years 1-30 to initialize the parameters for the retrospective analyses). We realize this may be optimistic, but given your time constraints we would like to have at least 5 retrospective analyses for each for the May meeting and more if you can do it.
We would like the results summarized as follows: summarized estimates of model parameters and model structure, estimated exploitable, mature, and total biomasses over time, average fishing mortality and exploitation rate over time, estimated recruitment (youngest age used) if part of the model, and selectivity gives for the fishery and survey. You are welcome to estimate a TAC or ABC; however if you do so, please tell us what approach you will use. As a default, we recommend F40% be calculated for comparison.
Other model features:
- Data from the fishery occurs over 30 years, t = 1,…,30. Age 15 represents a plus group but fish older than 15 are uncommon.
- Natural mortality is unknown, may not be constant, but is in line with species with similar longevity.
- Growth: Mean weight at age follows an allometric von Bertalanffy curve W(a) = Wm [1 - exp(-k(a -t0))]^b. The parameters are given to you.
- The maturity relationship is: m(a) = 1/[1 + a exp(-b a)] with given parameters.
- The generation of recruitment is unknown to you.
- Ageing error was generated with 0 bias at age 1 which increases linearly to -1 at age 15. The variation in ageing error was ~N(0,s^2), with a linear increase from s = 0 for age 1 and s = 2 for age 15.
- For Set 3, a different vessel was used in years t = 16 to 30, which may or may not have altered survey catchability.
- Catch Equation: Fishing occurs continuously throughout the year.
- Reported yield in biomass is determined from landing reports, not as the sum of catch-age times weight-age. Reported catch in numbers is also not affected by age composition.
The survey occurs during a short period of time at the beginning of each year immediately after spawning. We follow the convention that birth-date is assigned at the beginning of each year just prior to spawning.
The ageing error measure is a comparison of the age reader's estimated age of fish to known true age. The comparison results in a misclassification matrix (the age error matrix is provided to the analysts) whose elements are the probability p(i,a), that an individual of true age "i" is said to be estimated age "a".
Sincerely,
Terry Quinn and Rick Deriso
Co-chairs, NRC Committee on Fish Stock Assessment Methods
NOTE: The following analysts agreed to be experimental units to apply the indicated methods: (names deleted)
