MSAP/03/# Stock Assessment Analyses on Spanish and King Mackerel Stocks. Prepared for the 2003 Mackerel Stock Assessment Panel Meeting

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1 MSAP/3/# Stock Assessment Analyses on Spanish and King Mackerel Stocks Prepared for the 3 Mackerel Stock Assessment Panel Meeting Not to be distributed without accompanying Panel Report by Sustainable Fisheries Division April 3 National Marine Fisheries Service Southeast Fisheries Science Center Sustainable Fisheries Division 75 Virginia Beach Drive Miami, FL 3349 Sustainable Fisheries Division Contribution SFD/3-8 Since 985 the Mackerel Stock Assessment Panel (MSAP) has met annually to review the status of mackerel and other coastal pelagic stocks within the jurisdiction of the Gulf of Mexico and South Atlantic Fishery Management Councils and to recommend Acceptable Biological Catches (ABC s) for mackerels. The most recent full assessments of the Gulf and Atlantic Spanish mackerel as well the Atlantic king mackerel migratory groups were on March 998 (Legault et al. 998). This document provides: updated baseline analyses considering catch and effort through / fishing year, comparison of evaluation results with the prior assessments, and measures of uncertainty in the results for the MSAP to use in advising the Gulf Council of resource risk for the evaluated mackerel migratory groups under different levels of catch for the 3 management season. The report is organized into sections dealing with discussions of the catch, biological characteristics, indices, and assessment methods and results. Emphasis in the presentation is on changes of data and methodology from those used in 998 stock assessment. Comparison of the 998 and results are presented for discussion. Based on prior history, further exploration by the Mackerel Stock Assessment Panel is expected at the panel meeting in order to build upon the record of MSAP reports and supporting documentation provided since 985. MSAP-3- of 8

2 CATCH Directed Catch U.S. commercial landings, recreational catches, and size-frequency data for calendar years 997, 998, 999,, and * are updated in this assessment. Estimates through the / fishing year (April st to March 3 st for Spanish Atlantic and Gulf stocks, and king Atlantic) are incorporated into these analyses. Table gives the directed catch by the sectors (commercial and recreational) during each fishing year in both numbers and weight of fish landed for Atlantic king mackerel (Fig ), and by sector and state (Table, Fig ). Similarly, catch summary tables are presented for both Atlantic and Gulf Spanish mackerel stocks (Tables 4 to 6, Figs 3 to 6). Shrimp Trawl Bycatch Estimates of annual bycatch of Spanish mackerel in the Gulf of Mexico shrimp trawl fishery were updated using the same general linear model (GLM) as in year 998. The updated GLM analysis not only added two more years of observations but also re-estimated bycatch for all previous years. The updated bycatch estimates were nearly identical to those from the previous assessment (Fig 7, Table 7). The estimation models took into account the use of bycatch reduction devices (BRDs) in the Gulf of Mexico. This was accomplished by adding another level (BRD) in the factor = dataset of the GLM matrix that accounts for bycatch reduction devices used in the commercial fishery. The estimated bycatch rate for those combinations of season, area and depth zone that were required to use BRDs since 997 used the BRD estimates, while the prior years used the commercial estimates. For years 999 to, the area season distribution of BRDs was assumed similar as in 998 (Ortiz ). In prior evaluations, an alternative method to estimate bycatch, the delta lognormal approach, was also considered for sensitivity trials (Legault and Ortiz 998, Legault et al., Ortiz et al. ). In the 998 stock assessment, estimates of shrimp bycatch were presented and evaluated for the South Atlantic king and Spanish mackerel stocks (Vaughan and Nance MSAP 98/4, Harris and Dean MSAP/98/, and Harris and Dean MSAP/98/). However, the MSAP chose not to include bycatch estimates in the final model selected for both Spanish and King mackerel Atlantic stocks, due in part to the large uncertainty of these estimates (MSAP-98). For this evaluation no new data on shrimp bycatch for the South Atlantic were available, therefore no bycatch was included for Atlantic king and Atlantic Spanish stocks following the final model(s) adopted by the MSAP in 998. Size and Age Distribution of the Catches Procedures and protocols used for matching length samples to catch by migratory group, year, month, sector, and gear strata were developed at the 989 MSAP workshop held in Panama City, Florida and have been since discussed in detail (MSAP 997). Briefly, all samples within a catch stratum are combined into a composite sample and then matched to the catches by strata. Document MSAP/3/## (N Cummings) presents a complete description of the data and procedures used for converting catch to catch-at-age for the Spanish Atlantic and Gulf stocks and the King Atlantic stock. The aged catches are maintained at the year, month, area, and gear stratum level so that they can be aggregated to conform to various management schemes in later analyses. * Data for year are provisional NMFS SEFSC Miami MSAP-3- of 8

3 Catch at age for the directed fisheries for Atlantic king, Atlantic Spanish and Gulf Spanish mackerel are presented in Tables 8, 9 and. Figures 8, 9 and show in color schematic the proportion of catch by each age and year for Atlantic king, Atlantic Spanish and Gulf Spanish mackerel stocks, respectively. BIOLOGICAL CHARACTERISTICS Natural Mortality The natural mortality rate (M) used for the analyses in this report were the same as used in previous assessments: 5 for Atlantic king mackerel, and for both Atlantic and Gulf Spanish mackerel. The stochastic analyses allowed the value of M to vary over both years and ages using a random draw from a uniform distribution of to for Atlantic king, and from 5 to 5 for Spanish mackerel stocks. The M point estimates have been selected by the MSAP based upon the longevity and growth rates of the mackerels and by analogy with other species with similar life history characteristics. Fecundity The fecundity at age vectors are the same as used in prior assessments. For Atlantic king mackerel the age specific fecundity values correspond to millions of eggs. The derivation of the egg values came from an age-length relationship (Collins et al. 989), a linear spline fit to maturity at age data (data from Finucane et al. 986), and an eggs-length relationship (Finucane et al. 986). The values of age specific fecundity that reported spawning stock are in trillions ( ) of eggs. For the Spanish mackerel stocks (Gulf and Atlantic), the age specific fecundity was estimated as the biomass of females times the probability of maturity by age (Fable et al 987) times. ABUNDANCE TRENDS FROM INDICES Standardization Methods In prior assessments, the General Linear Modeling (GLM) approach was used to standardize several catch-per-unit-effort (CPUE) series (Legault et al. ). Briefly, the model may be expressed as: Log(CPUE) = a + Σ i b i I i + e where a and the b i are parameters, the I i are categorical variables and e is the error term assumed to be normally distributed with mean and variance v. The categorical variables include year and other factors which contribute to the variation in log(cpue) independently of abundance. However, this model requires modifying values of zero catch (to make the logarithmic transformation). Traditionally a value of or other constant positive value was added to all observations prior to the standardization procedure. In cases where the proportion of zero catch values to the total observations is relatively high, the standardized catch rates may depend largely on the selection of the constant value (Ortiz et al. ). Following, Cooke and Lankester (996) suggestions for alternative statistical models for catch-effort standardization, and Punt et al. () protocols, some of the CPUE indices for king mackerel were MSAP-3-3 of 8

4 standardized using Generalized Linear Models, specifically the delta lognormal model. Briefly, the delta model separates the estimation process into two components: the probability of encountering king mackerel and the density to fish given that at least one fish was encountered. Standardized catch rates for Gulf Spanish mackerel using the delta model have been presented previously to the MSAP working group (Ortiz and Scott ). Indices As in previous mackerel stock assessments conducted since 985, catch per unit of effort (CPUE) data from multiple sources were evaluated as indices of stock abundance. CPUE indices affect assessment results by calibrating estimates of population size to annual trends in CPUE, assuming direct proportionality to abundance. The annual trends in CPUE were assumed to represent age-specific abundance trends. The procedures used to derive annual indices of abundance were similar to those of previous assessments and take into consideration technical decisions made by the Panel during the 996 Panel Review of Gulf king mackerel and the 997, and 998 Panel Reviews of Atlantic king mackerel and Gulf Spanish mackerel stocks (Cummings 996, MSAP 996, MSAP Supplemental 996, MSAP 997, MSAP 998). During those meetings, after consideration by the Panel of the available historical CPUE data for indexing abundance of mackerels, recommendations were made regarding the continued use of specific data sets and the data to be included in the analysis. Emphasis was placed on analyses that accounted for possible biases in the index due impacts of regulations (e.g., bag limits, state trip limits, regulated seasons). For this assessment, each set of CPUE data was analyzed separately using general linear modeling theory as in earlier assessments, and information on area of catch, amount landed, month of capture, vessel, and other available auxiliary information incorporated into the index to adjust for changes in CPUE while applying the rationale specified by the MSAP 996, MSAP 997, and MSAP 998 reviews. Indices updated for this Stock Assessment analyses are described below. All tuning indices available for the VPA analyses of Atlantic king, Atlantic Spanish and Gulf Spanish are listed in Tables, and 3, respectively. In addition, the tables provide information regarding the time of the year when the index was related to abundance, whether the index was compared to estimated numbers or biomass, and the age range used for tuning. ATLANTIC KING MACKEREL A. Florida Fish and Wildlife Conservation Commission (FWC) Marine Fisheries Trip Ticket Program. Following recommendations of the MSAP 997 review, this index included changes due to catch restrictions imposed on the Atlantic migratory group from a State trip limit of 5 fish after 987, separating the landings into areas (north and south of Palm Beach county), and inclusion of catches between April and October when catches were considered to be unrestricted by catch limits. The abundance index was the standard catch (lbs) per trip adjusted for month and county and was applied to ages two through eleven. The standard index was provided by scientists from the FWC Marine Fisheries Division. B. North Carolina Division of Marine Fisheries (NCDENR) Trip Ticket Program. The NCDENR implemented the Trip Ticket Program on 994. For the last assessment in 998, the NCDENR provided a standard index based in their preliminary data collection system (MSAP-98). For this assessment, NCDENR provided Trip Ticket Program data and the standardization was done at the NMFS SEFSC Miami laboratory, there is a supporting document fully describing the standardization process, data restrictions and conclusions (Ortiz and Sabo 3). However, the new index started in 994, while for the 998 stock assessment the prior index started in 984. Because the level of summary and data MSAP-3-4 of 8

5 aggregation differs between the two data collection programs, and as the new index was base on single trip observations, rather than monthly cumulative summarized as the prior one, it was decided to use the trip ticket Program as a separate index. C. NMFS Beaufort Laboratory HeadBoat Survey. CPUE data from the Headboat Survey for the Atlantic king mackerel migratory group covered from North Carolina to the Florida east coast. For the king Atlantic stock in the Florida east coast, the data were restricted to the months of April though October. The index is the standardized numbers of fish caught per trip, adjusted by area, season, and vessel. A detailed report of the standardization procedure was presented in Ortiz (3). The index was applied to ages two through eleven. D. MRFSS Recreational. This index included trips that indicated king mackerel or other likely associated species as primary target for private and charter recreational trips. Data included the North Carolina and Florida east coast with restrictions to the months of April thought December. Index was the total number of fish caught (A+B+B) per angler-trip. A detailed report of protocols was also presented in Ortiz (3). The index was applied to ages two through eleven. E. Southeast Area Monitoring and Assessment Program South Atlantic (SEAMAP-SA). This was a fishery independent survey program conducted by the South Carolina Department of Natural Resources Marine Resources Division (SCDNR-MRD) since 986. The survey used a shallow water trawl that samples coastal habitats from Cape Hatteras (NC) to the Cape Cañaveral area (FL). Survey design and estimation protocols were specified in the appendix A. The index expressed the number of fish per hectare, adjusted for season, and area. Figure presents a comparison of 998 stock assessment and 3 stock assessment standard indices of abundance, for Atlantic king mackerel. Figure summarized all available indices in 3 using a common scale, defined as their respective mean for the overlapping years in all series. ATLANTIC SPANISH MACKEREL A. Florida Fish and Wildlife Conservation Commission (FWC) Marine Fisheries Trip Ticket Program. The analysis of the FWC CPUE index included all trips without landing weight limit, from 985 to, and months January through December. This index was applied to fish age one through six (Table ). B. MRFSS Recreational. This index included trips that indicated Spanish mackerel or other likely associated species as primary target for private and charter recreational trips, or shore sector. Data included the North Carolina and Florida east coast with restrictions to the months of April thought December. Index was the total number of fish caught (A+B+B) per angler-trip. A detailed report of protocols was also presented in Ortiz (3). The index was applied to ages one through six. C. NMFS Beaufort Laboratory HeadBoat Survey. CPUE data from the Headboat Survey for the Atlantic Spanish mackerel migratory group covered from North Carolina to the Florida east coast. For the Spanish Atlantic stock in the Florida east coast, the data was restricted to trips of 4 hours or less. The index was the standardized numbers of fish caught per trip, adjusted by area, season, and vessel. A detailed report of the standardization procedure was presented in Ortiz (3). The index was applied to one through six. MSAP-3-5 of 8

6 D. North Carolina Division of Marine Fisheries Pamlico Sound Survey. This is a fishery independent survey started in 987 with emphasis on sampling of juvenile abundance in the Pamlico Sound, eastern Albemarle Sound and the lower Neuse and Pamlico rivers (See Appendix for further details). Sampling was conducted quarterly for a period of two weeks, with random sampling of 5 fixed stations. Sampling gear was a double rigged demersal mongoose trawls, towed for minutes at.5 knots. Juvenile index was the annual geometric mean (weighted by strata) of the number of individuals per tow for young of the year (YOY). The index was provided by Dr. K. West of the NCDMD, and was the first time that is available for the MSAP evaluation of Atlantic Spanish mackerel stock. E. North Carolina Division of Marine Fisheries (NCDENR) Trip Ticket Program. As previously mention, The NCDENR implemented the Trip Ticket Program on 994. The NCDENR provided Trip commercial catch data for Spanish mackerel and the standardization was done at the NMFS SEFSC Miami laboratory. There was a supporting document fully describing the standardization process, data restrictions and conclusions (Ortiz and Sabo 3). This index started in 994 and was applied to ages one through six. F. Southeast Area Monitoring and Assessment Program South Atlantic (SEAMAP-SA). This is a fishery independent survey program conducted by the South Carolina Department of Natural Resources Marine Resources Division (SCDNR-MRD) since 986. The survey used a shallow water trawl that samples coastal habitats from Cape Hatteras (NC) to the Cape Cañaveral area (FL). Survey design and estimation protocols were specified in the appendix A. The index expressed the number of fish per hectare, adjusted for season, and area. Figure 3 presents a comparison of 998 stock assessment and 3 stock assessment standard indices of abundance, for Atlantic Spanish mackerel. Figure 4 summarized all available indices in 3 using a common scale, defined as their respective mean for the overlapping years in all series. GULF SPANISH MACKEREL A. Florida Fish and Wildlife Conservation Commission (FWC) Marine Fisheries Trip Ticket Program. The analysis of the FWC CPUE index included all trips with landings over 5 lbs, from 985 to, and months July through December. This index was applied to fish age one through seven (Table 3). B. MRFSS Recreational. This index included trips that indicated Spanish mackerel or other likely associated species as primary target for private and charter recreational trips. Data were included from the Gulf of Mexico area with restrictions to the months of March thought December. Index was the total number of fish caught (A+B+B) per angler-trip. A detailed report of protocols was also presented in Ortiz (3). The index was applied to ages one through three. C. Texas Parks and Wildlife Department (TPWD) Recreational Angler Creel Survey. Successful recreational anglers in Texas that caught Spanish mackerel were also used to develop standardized CPUE. The data used included observations between the months of May and October from the private mode, with trips of 4 hours or less. A detailed report of the standardization procedure was presented in Ortiz (3). The index was applied to ages one through three. D. NMFS Beaufort Laboratory HeadBoat Survey. CPUE data from the Headboat Survey for the Gulf Spanish mackerel migratory group covers from the Florida west coast to Texas. For the Spanish Gulf, stock the data was also restricted to trips of 4 hours or less. The index was the standardized MSAP-3-6 of 8

7 numbers of fish caught per trip, adjusted by area, season, and vessel. A detailed report of the standardization procedure was presented in Ortiz (3). The index was applied to one through three. E. Shrimp bycatch index. This index was derived from the estimates of Spanish mackerel bycatch in the Gulf shrimp fishery. The index was estimated as the total number of bycatch fish per year divided by the annual shrimp fishing effort. When estimating total bycatch for use in this tuning index, areas that used BRDs were instead assigned the commercial catch rate in order to have a consistent time series. The bycatch index used for the base case analyses was derived using the GLM method (Nichols et al 987). An alternative model (Delta lognormal approach) was used for sensitivity analyses. The index was applied to ages through two. Age allocation for the partial catch at age of this index used Spanish mackerel length frequency distributions of bycatch samples (MSAP 998). Most of the length data were prior to 996, thus the bycatch age proportions of 996 year was also applied to years 997 through. F. Southeast Area Monitoring and Assessment Program (SEAMAP). This was a fishery independent larval sampling survey Gulf wide (Gledhill and Lyczkowski-Shultz ). The index expressed the percent of occurrence of Spanish mackerel, rather than the estimates of density as per recommendation of the authors. G. Other indices. In prior assessments another index of abundance was included in the tuning of VPA analyses: the Florida Charter Northwest Panhandle area index (MSAP 98/). This index covers from 984 to 99 and was applied to ages one and two. Figure 5 presents a comparison of 998 stock assessment and 3 stock assessment standard indices of abundance, for Gulf Spanish mackerel. Figure 6 summarized all available indices in 3 using a common scale, defined as their respective mean for the overlapping years in all series. METHODS Virtual Population Analysis As in previous mackerel stock assessments, a tuned VPA (Fadapt) method (Powers and Restrepo 99, Restrepo 996) was used to obtain statistical estimates of population parameters. The method is a non-linear least squares (LS) estimation process in which observed indices of abundance are fit by population estimates from cohort analyses for appropriate age groups: min p LS = Σ it [X it - q i Σ j (b ijt N ijt )] where X it is the index i in year t, N ijt is the abundance in year t of the j ages represented in index i and the b ijt are appropriate conversion factors for that index and age (for example conversion from numbers to weight, conversion of the abundance from the beginning of the year to mid-year, or conversion of selectivity by age within the age group). For the index series, there is an option to assign a weight factor that in theory will translate the level of uncertainty of each index into the VPA s fitting procedure. Although in the past the working group suggested the evaluation of alternative weighting for each index, it was concluded that at the present was not possible to assign an equivalent variance estimate among all indices (MSAP, ). In the present analysis, for each index maximum likelihood estimates of variance were estimated, similar as in the 998 stock assessment for all three migratory MSAP-3-7 of 8

8 groups. The scaling parameters q i were computed by maximum likelihood during the minimization process in both situations, they were not estimated directly. Since all indices were scaled to their ownmean, prior to fitting in the VPA, the absolute values of the q i were not meaningful relative to the original data used to create the index. In each analysis, the fishing mortality rates at age in the / fishing year (terminal year) were the parameters estimated. Note that this is analytically equivalent to estimating the population abundance in the next year at the next age but allows estimation for the plus group. An additional assumption made in each analysis was that the fishing mortality rate was the same in the plus group as the previous age class for all years except for the terminal year. As many ages as possible were estimated in each analysis using the positive-defined information matrix solution as the determining factors for a successful solution (Restrepo 996). The VPA algorithms also included a re-start solution process, in order to avoid local minima as solutions. In these analyses, selectivity at age for each index by year was computed based on the partial catch at age associated with the index during that year. The catch at age for a particular index year was first used to find the proportion of total fishing mortality due to that amount of catch as: F y,a,i = F y,a * Catch y,a,i / Catch y,a where y, a and i denote year, age and index, respectively. The selectivity at age is then formed by dividing each F y,a,i by the maximum value over age for that year and index. This use of partial catches to form the selectivity patterns for the tuning indices added stability to the solutions by allowing different indices to tune to the same ages but at differing levels of importance over the ages. Additional assumptions were made in each analysis regarding the fishing mortality rate of the plus group in the terminal year: for Atlantic king the age plus group was Age-+, in the VPA model it was assumed that the terminal F s of ages and + were fixed ratios of the F at age-9 (F /F 9 =., F + F/F 9 =.). For Atlantic Spanish the age plus group was Age-6+, in the VPA model it was assumed that the terminal F 6+ is a fixed ratio of F at age-5 (F 6+ /F 5 =.). For Gulf Spanish, the VPA model estimated F for the plus group (Age-7+) in the terminal year. The fishing mortality rate on the plus group in years before the terminal year is assumed to be equal to the fishing mortality of the next younger age: for Atlantic king F of + is fixed ratios of F at age (F + /F =.); for Atlantic Spanish F 6+ is a fixed ratio of F at age 5 (F 6+ /F 5 =.), and for Gulf Spanish F 7+ is a fixed ratio of F at age 6 (F 7+ /F 6 =.). Characterization of Uncertainty The uncertainty in the assessment estimation was characterized as in the past by both sensitivity analyses on selected components and by mixed Monte Carlo/bootstrap simulations of the tuned VPA. The simulation method repeats the VPA a number of times (5) randomly selecting from ) a uniform distribution of natural mortality rate for each age and year; ) a lognormal distribution of directed catch at age assuming the point estimate represented the mean and the variance was characterized by a CV of 5%; 3) a lognormal distribution of bycatch at age assuming the point estimate represented the mean and the variance was characterized by a CV of 5%; and 4) the observed deviations between the indices of abundance and the predicted population model from the original VPA fit. The results were accumulated and sorted to provide probability statements of relevant statistics. Projections were made using each MSAP-3-8 of 8

9 iteration such that benchmarks, stock trends and ABC could be evaluated on an absolute or relative scale. Probability distributions from these observations were used to construct 8% pseudo-confidence intervals (removing the % lowest and highest observations). The stochastic simulations estimated the same number of parameters as the deterministic case. The final estimates from the deterministic case were used as initial guesses for the terminal year fishing mortality rates at age. Thus, the potential existed for highly different VPA estimates in each simulation, especially given that all the random selections described above were uncorrelated. This use of uncorrelated random selections could be a problem for the catch and index generated from the bycatch data as well as other indices tuning to young ages. Projections Population abundances at age in the terminal year of the VPA (/ fishing year) were projected into the 3/4 fishing year according to the estimated F and M at age values in the terminal year. Recruitment in the projection years came from a stock recruitment model specific within each bootstrap. The point estimate was projected deterministically following this stock recruitment model while the bootstraps used the estimated variability about the model to create a lognormal distribution from which recruitment was randomly chosen. The stock recruitment model was developed during the 998 MSAP meeting according to the following rules. Only years for which both, the stock and recruitment estimated values had tuning index information were used to create the relationship. In the case of Atlantic king mackerel, this means that only years are used. For Atlantic Spanish stock recruitment relationship was estimated from the year 989 to 999, and for Gulf Spanish from the year 985 to 999. The maximum recruitment was set at the average recruitment estimated during these years and declines linearly to the origin when the spawning stock size drops below the Abreak point@. The Abreak point@ was determined by the average of the five lowest spawning stock sizes within the years included (Fig 7). In the present analysis, bycatch mortality was included only for the Gulf Spanish mackerel stock. The bycatch fishing mortality rate for the projection years was computed as the average of the F at age due to bycatch during the period , modified by the expected bycatch reduction due to full implementation of BRDs. The year 998 was not included in this average because BRDs were partially implemented then. The bycatch reduction due to BRDs implementation was estimated as 35% for Gulf Spanish mackerel (S. Nichols, MSAP ), starting in year 998 and beyond. The directed fishing mortality rates at age were assumed separable by sector (commercial and recreational) with the selectivity at age pattern for each sector computed as the average over the last five years and the year multipliers specific to each sector. For the /3 fishing year, the two fishing mortality rate multipliers were estimated simultaneously such that the observed total catch in weight for the commercial sector and the /3 total catch in numbers for the recreational sector was achieved. The total fishing mortality rate at age was computed as the sum of the bycatch F at age, the product of the commercial multiplier and The Atlantic Spanish commercial catch /3 was set to,94,35 lbs. From the Preliminary Landings, Status of Quotas, and daily vessel trip/landing limit report as of April 5, 3. While, the commercial catch for Atlantic king mackerel fishing year /3 was set to the catch of / (,7,56 lbs) and, for Gulf Spanish commercial catch was also set to the catch of / (788,437 lbs) due to incomplete reports for these two stocks. The Atlantic king recreational catch for fishing year /3 was set to 83,99 fish (3,389,565 lbs). For Atlantic Spanish recreational catch of /3 FY was set to,389,84 fish (,37,83 lbs). And, for Gulf Spanish recreational catch of /3 FY was set to,96,759 fish (3,8,437 lbs). From the Preliminary Landings, Status of Quotas, and daily vessel trip/landing limit report as of April 5, 3. MSAP-3-9 of 8

10 selectivity at age, and the product of the recreational multiplier and selectivity at age. The two multipliers were unique values assuming both catches are smaller than the estimated population. The population abundances were then projected into the 3/4 fishing year according to the total fishing mortality rate at age and the natural mortality rate at age. The two fishing mortality rate multipliers (commercial and recreational) for the 3/4 fishing year were estimated simultaneously such that a desired spawning potential ratio (SPR transitional unweighted) was achieved and the ratio of catches in weight by the two sectors equaled the allocation for the specific migratory group. These F multipliers were again unique assuming the SPR could be achieved in that year. The yield resulting from application of the directed fishing mortality rates on the estimated population abundance generated the ABC value. This approach of treating separately the commercial and recreational sectors was used in prior assessments. The recent reauthorization of the Magnuson-Stevens Fishery Management and Conservation Act (MFMCA) requires the use of both biomass and fishing mortality rate limits to classify the status of stocks. Following the decisions made by the MSAP, the recommended proxy for F MSY is F 3%SPR and the proxy for B MSY was the spawning stock that resulted in equilibrium under the F MSY proxy according to the stock recruitment relationship. The default control rule of Restrepo et al (998) was accepted by the MSAP at the last meeting. This default control rule sets the minimum stock size threshold (MSST) to (- M)* B MSY and the maximum fishing mortality threshold (MFMT) to F MSY for SS>MSST and decreasing linearly to the origin for SS<MSST. Risks associated with overfishing, P (F>MFMT), and being overfished, P (SS<MSST), can be calculated from the results of the bootstraps for constant catch projections. RESULTS AND DISCUSSION In the current stock evaluation, the models adopted by the Mackerel Stock Assessment Panel (MSAP) in 998 (last full stock assessment for all three stocks) (MSAP-98) were defined as the base model(s). The models adopted in 998 have been used in projections and for estimation of targets and threshold benchmarks (GMFMC 3, Ortiz, Ortiz and Legault, Legault 999). ATLANTIC KING MACKEREL For Atlantic king mackerel briefly; the 998 MSAP adopted the model with maximum likelihood (ML) estimates option and normal error assumption for all 5 indices of abundance available (with the same age coverage and time of year application as presented in the indices section), not including bycatch estimates, and eliminating the early time series for the SEAMAP index (988 and prior) (MSAP-98). In this model, the VPA-program estimated parameters, i.e. the terminal F s for age- to age-9, and assumed an F ratio of one for F /F 9, and F + /F 9. Thus for the 3 evaluation, the Base model was defined as similar as possible. Initially, the Base model tried to estimate parameters, however the model failed to converge to a successful solution. A successful solution was achieved for the 3 VPA Base model when it estimated eight fishing mortality rates in the last year, corresponding to the age classes through 9, with fixed F ratios for F, F, F and F +. F ratios where defined as: F =.8 of F, F = 76 of F, F =. of F 9 and F + =. of F 9. F ratios for ages and were estimated using separable VPA algorithm (SVPA), with the 997- catch at age as input. Similar process has been done in the past assessments, for example with Gulf king mackerel in stock assessment (Ortiz et al ). The updated NC commercial index was not included in the Base model as it was considered MSAP-3- of 8

11 sufficiently different the data input and standardization procedure compared to the NC commercial index used in 998 SA. Table 4 shows the results of the Base model; stock size at age at the beginning of the year, F at age during the year, parameter estimates with associated variance estimators, and the observed and predicted index results. The alternative VPA model for Atlantic king mackerel or Full Index model simply added the new NC Commercial standard CPUE as a separate index of abundance, with all other settings similar as the Base model. Table 5 shows the results of the Full index model; stock size, F at age, parameter estimates and index results, respectively. A comparison of the results from the Base and Full index models for Atlantic king are shown in figure 8 for the estimated F at age, figure 9 for estimated stock size by age, and figure for the observed vs. predicted indices of abundance. In general, the Base model estimated a higher stock size with lower fishing mortality rates in particular since 99, and for ages 6, 7, 8, and +. However, when the estimated 8% pseudo-confidence intervals were included (Fig ) is clear that both the Base and Full index model provide similar estimates. The confidence intervals were generated by bootstrapping. Overall the VPA indicated a extremely large mortality of older fish (F 7- ) at the beginning of the time series 98, the F increased during the mid 8 s up to mid 9 s in particular for ages to 6, with decreasing trend for the older age classes. In terms of the stock, a large cohort entered in 989, but the overall stock in numbers indicated a downward trend, with the lowest point estimated in the latest year (). The predicted indices of abundance showed similar trends for both models. The largest residuals were observed for the MRFSS index, in particular for the early years of the series (98/83/87). Figure shows a comparison of the 998 stock assessment results and the present one (Full index model). Major departures started in 989 with the estimates of recruits for that year, that can be follow through the time series. In 998-SA the VPA estimated a recruitment of about 5 million fish, while in the 3-SA this recruitment was estimated at about 3 million fish (Age ). Ages 7- differed in the 98 estimates only. In terms of F, the 998 SA estimated a drop in F 3-6 from 5 to.5, this was much less in the 3 SA, and subsequently there was an increase in F 3-6 starting in 995/96. In terms of stock size, the 998 SA estimated a much larger stock biomass for Ages 3-6 with an increasing trend in the period, this was not the case in the 3 SA, instead, the stock biomass remained low during much of the 99 s and increased slightly in the latest years (997-). The impact of each index value on the VPA results can be determined from a jackknife analysis. The jackknife systematically removes each index point and runs the VPA without that one tuning index value. The most influential points for tuning index according to the jackknife analysis is the 98 MRFSS and the 998 NC Commercial indices (Fig 3). The impact of the different scenarios can also be seen in the estimate of spawning potential ratios (SPR). The Base model estimates higher SPR values [Static SPR =6, Transitional unweighted SPR = 8] due to lower estimated F overall relative to the Full Index model [Static SPR =, Transitional unweighted SPR = 3] (Fig 4). The trends from the two models were similar; the transitional SPR trends showed a decrease since 985, with an increase in 997/98 fishing years. The static SPR trends showed an overall decrease since 984, with values below 3% in most of the 8 s and early 9 s, follow by a peak in 993, and increase trend since 997/98. Both models, however indicated that the stock was above the 3% SPR threshold in year /3, either for static or transitional unweighted estimators. As stated in the king mackerel evaluation report (Legault et al. ), in order to determine the stock status under the new rule definitions, the maximum sustainable yield fishing mortality rate and associated spawning stock proxies must first be calculated. These proxies were based upon F 3%SPR and MSAP-3- of 8

12 the two-line model of stock recruitment relationship described previously. These proxies were computed by projecting each bootstrap to the year 7 under constant recruitment and F 3%SPR, both specific to that bootstrap. The same proxies for optimum yield (OY) were computed using F 4%SPR. The median and 8% confidence intervals for these MSY and OY related benchmarks were given in Table 6. The Base model scenario produced slightly higher estimates for all of these benchmarks compared to the Full index model scenario, but the confidence bounds clearly overlapped for both models (Fig 5). Using the bootstrap specific estimates of MFMT and MSST, the probability of being classified as undergoing overfishing or being overfished in fishing year were calculated. For the Base model, 34 of the 5 bootstraps (7%) produced F>MFMT, while 65 of the 5 bootstraps (3%) produced SS<MSST (Fig 6). For the Full Index model, 6 of the 5 bootstraps (%) produced F>MFMT, while 3 of the 5 bootstraps (6%) produced SS<MSST (Fig 7). Since currently, the acceptable resource risk of being overfished or undergoing overfishing is not defined by the Council, no definite statement about stock status can be made. However, the Technical Guidelines (Restrepo et al 998) recommend low risk of exceeding threshold levels, suggesting this value not be greater than -3% and certainly less than 5%. Phase plots for the Atlantic king mackerel stock status in fishing year /3 are shown for both models in Figure 8. The fishing year 3/4 acceptable biological catch (ABC) for the two models have different median values and estimated 8% pseudo confidence interval (Table 7 and Figure 9). ATLANTIC SPANISH MACKEREL For Atlantic Spanish mackerel the 998 MSAP adopted the model with maximum likelihood (ML) estimates option and normal error assumption for all 5 indices of abundance available (with the same age coverage and time of year application as presented in the indices section, with exception of the MRFSS index which was split in two: Florida MRFSS and NC MRFSS 3 ), not including bycatch estimates, and eliminating the early time series for the SEAMAP index (988 and prior) (MSAP-98). In this model, the VPA-program estimated 7 parameters, corresponding to the terminal F s for each age class (Age to Age 6+). Thus for the 3 evaluation, the Base model was defined as similarly as possible. Initially, the Base model tried to estimate all 7 parameters, however the model failed to converge to a successful solution (i.e. a solution with a positive definite information matrix). The 3 VPA Base model estimated 6 fishing mortality rates in the last year, corresponding to the age classes through 5, with fixed F ratio for F 6+, which was defined as: F 6+ =. of F 5. The updated MRFSS index was not split between states, because no particular reason justified such partition, and to avoid giving more weight in the tuning process to a single index source. Table 8 shows the results of the Base model; stock size at age at the beginning of the year, F at age during the year, parameter estimates with associated variance estimators, and the observed and predicted index results. The alternative VPA model for Atlantic Spanish mackerel or Full Index model added two new indices of abundance; the NC Commercial standard CPUE derived from the Trip ticket program (Ortiz and Sabo 3), and the NC Pamlico Sound Survey a fishery independent survey of juvenile fish primarily. All other settings in the Full index model were similar as in the Base model. Table 9 shows the results of the Full index model; stock size, F at age, parameter estimates and index results, 3 The 998 SA MRFSS index was split for the Florida and North Carolina states and used as two different tuning indices in the VPA model, each one with independent q estimates and partial catch at age inputs (MSAP 98/) MSAP-3- of 8

13 respectively. A comparison of the results from the Base and Full index models for Atlantic Spanish are shown in figure 3 for the estimated F at age, figure 3 for estimated stock size by age, and figure 3 for the observed vs. predicted indices of abundance. In general, the Full index model estimated a higher stock size with lower fishing mortality rates through the all time series and for all ages. However, when the estimated 8% pseudo-confidence intervals are included (Fig 33) was clear that both the Base and Full index models provided similar estimates. The confidence intervals were generated by bootstrapping. Overall the VPA indicated a high F mortality rates of ages and 3 (F -3 ) at the beginning of the time series 984, the F increased during the late 8 s up to mid 9 s in particular for ages 3 to 6+, with the highest peak in 993, then it followed a substantial decrease for all age classes in 995. In terms of the stock, the largest cohort entered in 998, but the overall stock in numbers indicated an upward trend, with the highest point estimated in the latest year (). It is particularly notable the increasing trends of older ages (Age 4, 5 and 6+) in the latest 5 years. The predicted indices of abundance showed similar trends for both models. The largest residuals were observed for the Headboat index, in particular for the early years of the series (987/9), the MRFSS index (984/85/93) and the Pamlico Sound index (99). Figure 34 shows a comparison of the 998 stock assessment results and the present one (Full index model). Major departures started in 993 with the estimates of recruits for that year that can be followed through the time series. The 998-SA VPA estimated a recruitment of about 5 million fish for 993, while in the 3-SA this recruitment was estimated at about 8 million fish (Age ). Ages -6+ differed since 99 and forward. In terms of F, the 998 SA estimated lower fishing mortality rates particularly for older ages (F 5-6+ from 99 on). In terms of stock biomass, the 998-SA estimated a much larger stock biomass for Ages -6+ with an increasing trend in the period, this was not the case in the 3 SA, instead, the stock biomass remained low during much of the early 99 s and started increasing by 996 and the latest years. The jackknife analysis indicated that the most influential points for tuning index fitting were the 98 MRFSS and the 998 NC Commercial indices (Fig 35). The results of the different scenarios can also be seen in the estimates of spawning potential ratios (SPR). The Base model [Static SPR =6, Transitional unweighted SPR = 7] and the Full index model [Static SPR =5, Transitional unweighted SPR = 7] estimated similar SPR values (Fig 36). The trends from the two models were similar; the transitional SPR trends show a decrease since 988, with an increase in 995 that continued to the last year (). The static SPR trends showed an overall decrease since 987, with values below 3% in most of the late 8 s and early 9 s, followed by a peak in 995, and an increased trend since then. Both models indicated that the stock was above the 3% SPR threshold in year /3, either for static or transitional unweighted estimators. The proxies for determining the stock status under the new rule definitions were also based upon F 3%SPR and the two-line model of stock recruitment relationship described previously. These proxies were computed by projecting each bootstrap to the year 7 under constant recruitment and F 3%SPR, both specific to that bootstrap. The same proxies for optimum yield (OY) were computed using F 4%SPR. The median and 8% confidence intervals for these MSY and OY related benchmarks are given in Table. The Full index model produced slightly higher estimates for all of these benchmarks compared to the Base model scenario, but the confidence bounds clearly overlapped for both models (Fig 37). Using the bootstrap specific estimates of MFMT and MSST, the probability of being classified as undergoing overfishing or being overfished in fishing year was calculated. For the Base model, 4 of the 5 bootstraps (3%) produced F>MFMT, while of the 5 bootstraps (4%) produced SS<MSST (Fig 38). For the Full Index model, 7 of the 5 bootstraps (3%) produced F>MFMT, while 3 of the 5 bootstraps (6%) produced SS<MSST (Fig 39). Following the Technical Guidelines (Restrepo et al MSAP-3-3 of 8

14 998) recommendations, for Atlantic Spanish there was low risk of exceeding threshold levels (values not greater than -3%). Phase plots for the Atlantic Spanish mackerel stock status in fishing year /3 are shown for both models in Figure 4. The fishing year 3/4 acceptable biological catch (ABC) for the two models had similar median values and estimated 8% pseudo confidence interval (Table and Figure 4). GULF SPANISH MACKEREL For Gulf Spanish mackerel the 998 MSAP adopted the model with maximum likelihood (ML) estimates option and normal error assumption with 5 indices of abundance (with the same age coverage and time of year application as presented in the indices section), including bycatch estimates (GLM shrimp bycatch estimates, Nichols et al 987), and excluding the years from the Florida DEP Trip Ticket Index (MSAP-98). In this model, the VPA-program estimated 8 parameters, corresponding to the terminal F s for each age class (Age to Age 7+). Thus for the 3 evaluation, the Base model was defined as similarly as possible. The 3 VPA Base model estimated 8 fishing mortality rates in the last year, corresponding to the age classes through 7+. And included five indices of abundance (MRFSS, FWC 4, Charter NW FL, Bycatch GLM and Texas PWD). Table shows the results of the Base model; stock size at age at the beginning of the year, F at age during the year, parameter estimates with associated variance estimators, and the observed and predicted index results. The alternative VPA model for Gulf Spanish mackerel or Full Index model added two indices of abundance; the Headboat CPUE derived from the Headboat Survey Program (Ortiz 3), and the SEAMAP index a fishery independent survey of juvenile fish primarily. All other settings in the Full index model were similar as in the Base model. Table 3 shows the results of the Full index model; stock size, F at age, parameter estimates and index results, respectively. A comparison of the results from the Base and Full index models for Gulf Spanish are shown in figure 4 for the estimated F at age, figure 43 for estimated stock size by age, and figure 44 for the observed vs. predicted indices of abundance. In general, both models estimated similar stock sizes; with slightly lower values for the Base model for total stock in the latest years. Accordingly, the Base model estimated slight higher overall F mortality from 998 and forward. However, when the estimated 8% pseudo-confidence intervals were included (Fig 45) it was clear that both the Base and Full index models provided similar estimates. The confidence intervals were generated by bootstrapping. Overall the VPA indicated a high F mortality rates of ages to 4 (F -4 ) at the beginning of the time series 984, the F increased during the late 98 s up to early 99 s in particular for ages to 7+, with the highest peak in 99, then it followed a substantial decreased for all age classes in 993/94. In terms of the stock, the largest cohort entered in 99, with a prior one in 986. The overall stock in numbers dropped to the lowest level in 988, but since 994, the stock (particularly for ages to 7+) showed an increasing trend, with the highest point estimated in the latest year (). It is particularly noteworthy the increasing trends of older ages (Age 5, 6 and 7+) in the latest 5 years. The predicted indices of abundance showed similar trends for both models. The largest residuals were observed for the Headboat index for the early years of the series (987/9), the MRFSS index (988/89/9) and the Texas PWD index (995/96). Figure 46 shows a comparison of the 998 stock assessment results and the present one (Full 4 The Florida FWC index for Gulf Spanish mackerel included standardized indices for the 995 and 996 years, and they were included in the Base model for 3 assessment analysis. MSAP-3-4 of 8

15 index model). Ages -7+ differed since 99 and forward. In terms of F, the 998 SA estimated lower fishing mortality rates particularly for older ages (F 5-7+ from 99 on). In terms of stock biomass, the 998-SA estimated a much larger stock biomass for Ages -7+ with an increasing trend in the period, this was not the case in the 3 SA, instead, the stock biomass remained stable during much of the early 99 s and started increasing by 996 and the latest years. The jackknife analysis indicated that the most influential points for tuning index fitting were the 99 Headboat and the 989 MRFSS (Fig 47). The results of the different scenarios can also be seen in the estimates of spawning potential ratios (SPR). The Base model [Static SPR =4, Transitional unweighted SPR = 4] and the Full index model [Static SPR =, Transitional unweighted SPR = 3] estimated slightly different SPR values (Fig 48). However, the trends from the two models were similar; the transitional SPR trends showed a decrease since 985 with values below 3% SPR for most of the late 98 s and early 99 s, followed by an upward trend since 995, raising the SPR above 3% by 998. The static SPR trends showed an overall decrease since 985, with values below 3% in most of the late 98 s and early 99 s, follow by a peak in 997, and a decrease trend in 998 to, reversing in the latest year. Both models indicated that the stock was above the 3% SPR threshold in year /3, either for static or transitional unweighted estimators. The proxies for determining the stock status under the new rule definitions were also based upon F 3%SPR and the two-line model of stock recruitment relationship described previously. These proxies were computed by projecting each bootstrap to the year 7 under constant recruitment and F 3%SPR, both specific to that bootstrap. The same proxies for optimum yield (OY) were computed using F 4%SPR. The median and 8% confidence intervals for these MSY and OY related benchmarks are given in Table 4. The Base model produces slightly higher estimates for all of these benchmarks compared to the Full Index model scenario, but the confidence bounds clearly overlapped for both models (Fig 49). Using the bootstrap specific estimates of MFMT and MSST, the probability of being classified as undergoing overfishing or being overfished in fishing year was calculated. For the Base model, 44 of the 5 bootstraps (9%) produced F>MFMT, while 5 of the 5 bootstraps (5%) produced SS<MSST (Fig 5). For the Full Index model, 56 of the 5 bootstraps (%) produced F>MFMT, while 7 of the 5 bootstraps (5%) produced SS<MSST (Fig 5). Following the Technical Guidelines (Restrepo et al 998) recommendations, for Gulf Spanish mackerel there was a low risk of exceeding threshold levels (values not greater than -3%). Phase plots for the Gulf Spanish mackerel stock status in fishing year /3 are shown for both models in Figure 5. The fishing year 3/4 acceptable biological catch (ABC) for the two models had similar median values and estimated 8% pseudo confidence interval (Table 5 and Figure 53). SENSITIVITY ANALYSES RETROSPECTIVE ANALYSIS For all three mackerel migratory groups retrospective analyses were performed. The objective was to identify possible patterns in stock size estimation or fishing mortality rates that suggested consistent bias in the VPA tuning results. The retrospective analysis was done by removing the last year data from the CAA and all index series, for the last 5 years (996-), and using the same VPA settings as the Full index models for all three migratory groups. MSAP-3-5 of 8

16 In the case of Atlantic king mackerel, the retrospective analysis was possible only for the 998- years, the model did not converge to a solution for the 996 or 997 years. Figure 54 shows the estimated stock size for the year 998/99// by age and age-groups. Figure 55 shows equivalent results for the estimate F mortality rates. The results did not indicate a strong retrospective pattern either in the stock size or F mortality rates. For Atlantic Spanish mackerel, the retrospective analysis for years 999 and 996 did required to remove the NC Com New index in order to obtain a converging solution of the model, for all other years no modifications were necessary. The retrospective patterns of Atlantic Spanish stock estimates and F mortality rates are shown in figure 56 and 57, respectively. The results did show retrospective patterns for Atlantic Spanish, particularly for fishing mortality rates (F) of ages 4, 5 and 6, and the stock size of the age plus group (Age-6+). The patterns indicated that with more catch and index information the model estimates higher F mortality rates for the older ages especially. Therefore, the stock sizes of older age classes tend to be overestimated. In general, the perception is bias towards a more optimistic stock size in the final years, than the true size if more data were available. For Gulf Spanish the retrospective analysis for 997 year required removing the Charter NWF index in order to get a converging solution. Retrospective patterns of Gulf Spanish stock size and F mortality rates are shown in figures 58 and 59, respectively. The results also indicated retrospective patterns for F mortality rates of ages 5, 6 and 7+. However, the trends were not consistent by years, as more information was available, the trend increased (998-97) or decreased (996). This result may indicate more the effect of particular indices in the overall model fitting, rather than a bias in the VPA model. GULF SPANISH BYCATCH DELTA LOGNORMAL For Gulf of Mexico Spanish mackerel there were alternative estimates of shrimp trawl bycatch based in a delta lognormal model (Ortiz et al ). In prior assessments, the bycatch delta lognormal have been used as sensitivity analyses, and in this evaluation updated estimates as well update index of abundance based on this bycatch estimates were also used as input for a sensitivity analysis for the Gulf Spanish migratory group. The sensitivity evaluation was applied to the Full index model for Gulf Spanish. Figure 6 shows a comparison of the stock size, F mortality rates and stock biomass results from the Bycatch Delta logn and the Full index models. Overall, the main difference is the stock size of Age and Age, and their corresponding F and stock biomass. For older age groups ( and above) there were minor changes, and both models median estimates were between the 8% estimated confidence intervals. Figure 6 presents the estimated SPR trajectories for the Bycatch delta LogN and the Full index models, main differences showed in the period when the stock was below the 3% SPR point. The bycatch delta logn estimated high SPR values compared to the Full model index. However, for the latest years both models estimated similar SPR values either static or transitional unweighted SPR (Fig 6). Figure 6 presents the estimated long term projections of MSY, OY, SS MSY, SS OY F MSY, F OY, from the Bycatch delta logn and the Full Index and Base models for Gulf Spanish. Bycatch delta LogN tend to estimate higher spawning stocks and MYS/OY yields. However, it is important to notice that these estimates included the fixed reduction of bycatch starting in the 3/4 of 35% annually for Gulf Spanish. MSAP-3-6 of 8

17 ATLANTIC KING MACKEREL INDEX REMOVAL An additional sensitivity analysis for Atlantic king mackerel included the removal of complete indices of abundance to evaluate the influence of particular indices in the overall VPA results. In this case, the Full Index model was use as started point, from which each of the six available indices was removed one at the time. In two cases, the model failed to converge to a solution (when the HeadBoat index or the SEAMAP SA index was removed). Further bootstraps were done for those cases when a solution was achieved. Figures 63, 64, 65 and 66 summarized the estimated population trends for Atlantic king when the Florida FWC, MRFSS, North Carolina Commercial New (994-), and North Carolina Commercial Old (98-996) were removed, respectively against the Full Index model. Figure 67 presents the same information but combining all scenarios and removing confidence bounds. From the results, the greatest differences with respect to the Full index model were obtained with the removal of the Florida FWC index. In this case, by removing the FWC index the VPA model estimated larger stock size and stock biomass, particularly for older ages (Age 7-+) in the last years, and corresponding lower fishing mortality rates for the same ages. However, removing the FWC index also increased substantially the estimates of confidence intervals for stock size and stock biomass (Fig 63), in some cases by to 3 times compare to those obtained in the Full index model, and 3%-5% for confidence intervals of F mortality rates. Only in the older age groups (Age7 +) there was a reduction in the confidence intervals of F 7-+. In addition, the removal of the North Carolina Commercial New index increased the confidence bounds estimators for biomass and stock size (Fig 65). On the other hand, by removing the MRFSS index, there were not major changes in the median points estimates, but confidence bounds were much tighter, in some cases by -3 fold decrease compared with the Full Index model confidence intervals. GENERAL DISCUSSION In summary, the 3 stock assessment for the Atlantic king, Atlantic Spanish and Gulf Spanish mackerel migratory groups included the update of catch for five fishing years (997-), update of most indices of abundance present at the 998 assessment, and the inclusion of at least two new indices of abundance. The catch at age (CAA) tables for Atlantic king, Atlantic Spanish and Gulf Spanish did not present changes compare to the CAA inputs of the 998 assessments. Review of the proportions of catch at age for the updated years (997-) indicated that there were some shifts in the average proportions. Atlantic king showed a shift towards older age classes in the 997- period compared to the average, meaning ages -4 decreased in their percent of contribution to the total catch, while the ages 6- + increased their proportion of the total catch, in both the commercial and recreational sectors (Fig 68). No changes were noticed for Atlantic Spanish (Fig 69), while for Gulf Spanish there was also a shift towards older ages showing higher proportion of the total catch compare to the period (Fig 7). For Gulf Spanish, the shift was more obvious in the recreational sector, with ages and 3 being the predominant age classes in the 997- catch, compared to the period when ages and were the predominant classes. MSAP-3-7 of 8

18 Indices of abundance that were available in both the 998 assessment and the 3 assessment were not only updated in terms of year-data but also in the standardization protocols, following recommendations by the Mackerel Stock Assessment Panel (MASP 998). For Atlantic king the Florida FWC was the only index that was updated only in data input, and the trend for the 998 index and 3 index remained very similar (Fig ). In contrast, the MRFSS, HeadBoat, Seamap and North Carolina Commercial indices varied in the standardization protocols and input data. The most prominent changes in the standardization is the inclusion of zero catch records, and the level of aggregation of the data (see Ortiz 3 for further details). These changes required the use of alternative models such the Delta lognormal, that better conformed to the assumptions of the standardization process. In general, these indices showed higher variation in their yearly estimates (Fig ), compared to the prior GLM standardized indices. In the case of Atlantic Spanish, again the Florida FWC index was only updated in terms of year-data. For the Atlantic Spanish MRFSS, Headboat, and Seamap indices the standardization protocols and data were updated (Fig 3). In addition, for Atlantic Spanish two new indices were available; a fishery-independent index from the NC Pamlico Sound Survey, and the fishery dependent North Carolina commercial index. For Gulf Spanish, also the MRFSS and Texas PWD indices were updated in both protocols and data input (Fig 5a). A new index based on the Headboat survey was available for Gulf Spanish. Tuned VPA results show relatively minor differences in terms of stock size and fishing mortality rates between the Base models (only indices used in 998 assessment) and the Full index models for all three mackerel migratory groups. However, compared to the 998 VPA results, the 3 VPA results showed different trends, in particular for the years in the case of Atlantic king (Fig ), for Atlantic Spanish (Fig 34), and for Gulf Spanish (Fig 46). In all cases, the 998 stock assessments estimated higher stock biomass of all three migratory groups for those years compare to similar estimates in the 3 assessments. At least, for Atlantic Spanish there was an indication of retrospective patterns, with tendency to overestimate the stock biomass of older ages in the latest years of the VPA analysis (Fig 56 and 57). Phase plots, on the other hand indicated that all three migratory groups are not either overfished or under overfishing rates (Fig 8, 4, and 5). In the case of Atlantic king, the bootstrapping results indicated a high level of uncertainty, in both the Base and Full index models, the deterministic results diverged from the median of the bootstraps, suggesting a likely bias in the VPA results due to the non-linearity of population model. For Atlantic Spanish and Gulf Spanish, the median estimates from bootstrapping results and deterministic runs were close to each other. The projections of stock status and ranges of ABC for upcoming fishing year (3/4) indicated for all three migratory groups catch targets greater than MSY and OY (Tables 6, and 4). However, it is important to clarify that these ABC estimates (either at F 3%SPR or F 4%SPR ) are NOT sustainable in the long term. These ABC s include a surplus immediately available that will require the reduction of catch after the upcoming years, (if the ABC is fully removed in 3/4 FY). In addition, another important consideration for the Atlantic migratory groups is that the current (as in 998 assessment) estimates do not include bycatch mortality associated with the shrimp fishery. Thus, following a precautionary approach the allocation of catch quotas for the King and Atlantic Spanish stocks should take into account the ignored fishing mortality associated with shrimp bycatch. Following recommendations of the MSAP, the present assessment included a review and reevaluation of the standardization procedures for fishery dependent CPUE data. As discussed in the supporting documents (Ortiz 3, Ortiz and Sabo 3), there is a need to identify and better account for effort directed at mackerels, but with zero catches. This implied a need to revise all the processes from data collection, to selection of data subsets that better reflect a consistent sampling of the stocks. In the case of the Headboat survey, there is a need to account for individual vessel characteristics, as well for improvements of the fleet that may reflect higher fishing power in recent years. Similarly, the MSAP-3-8 of 8

19 commercial catch analysis from the North Carolina trip ticket data, revealed the importance of individual vessels, as consistent units of sampling, and by recognizing those vessels that are transitory or occasional mackerel fishing, a large part of the variability in catch rates can be accounted for. These analyses should also extend to all other indices used in the mackerel stock assessment evaluations. MSAP-3-9 of 8

20 LITERATURE CITED Collins, M.R. D.J. Schmidt, C.W. Waltz and J.L. Pickney Age and growth of king mackerel, Scomberomorus cavalla, from the Atlantic coast of the United States. Fish. Bull. 87():49-6 Cooke, J.G. and K. Lankester Consideration of statistical models for catch-effort indices for use in tuning VPA s. ICCAT Col. Vol. Sci. Pap. 45():5-3. Fable, W.A Jr. A.G. Johnson and L.E. Barger Age and growth of Spanish mackerel, Scomberomorus maculatus, from Florida and the Gulf of Mexico. Fish. Bull. 85(4): Finucane, J.H., L.A. Collins, H.A. Brusher, and C.H. Saloman Reproductive biology of king mackerel, Scomberomorus cavalla, from the Southeastern United States. Fish. Bull. 84: Gledhill, C.T. and J. Lyczkowski-Shultz.. Indices of larval king mackerel (Scomberomorus cavalla) abundance in the Gulf of Mexico for use in population assessments. Fish. Bull. 98: Gulf of Mexico Fishery Management Council (GMFMC). 3. A framework seasonal adjustment of harvest procedures, reference points, and status criteria under the Fishery Management Plan for coastal migratory pelagic resources in the Gulf of Mexico including environmental assessment, regulatory impact review, and initial regulatory flexibility analysis. GMFMC Tampa Florida. Harris, P.J. and J.M. Dean. The potential impact of juvenile king mackerel (Scomberomorus cavalla)and Spanish mackerel (S. maculatus) shrimp trawl bycatch mortality on southeast Atlantic adult populations. MSAP/98/. Harris, P.J. and J.M. Dean. Characterization of the king mackerel and Spanish mackerel bycatch of South Carolina shrimp trawlers. MSAP/98/. Legault, C.M Updated projections for King and Spanish mackerel in the Gulf of Mexico and Atlantic Ocean. NMFS SEFSC Miami Sustainable Fisheries Division contribution SFD-98/ Legault, C.M. and M. Ortiz Delta lognormal estimates of bycatch for Gulf of Mexico king and Spanish mackerel and their impact on stock assessment and allowable biological catch. MSAP/98/. NMFS Sustainable Fisheries Division Contribution SFD-97/98-. Miami, FL. Legault, C.M., N. Cummings and P. Phares Stock assessment analyses on Atlantic migratory group king mackerel, Gulf of Mexico migratory group king mackerel, Atlantic migratory group Spanish mackerel, and Gulf of Mexico migratory group Spanish mackerel. NMFS SEFSC Miami Sustainable Fisheries Division Contribution MIA-97/98-5. Legault, C.M., M. Ortiz, G.P. Scott, N. Cummings and P. Phares.. Stock assessment analyses on Gulf of Mexico king mackerel. MSAP//. NMFS SEFSC Miami Sustainable Fisheries Division Contribution 99/-83. MSAP (Mackerel Stock Assessment Panel) Report of the Mackerel Stock Assessment Panel. Prepared at meeting held March 9 - April, 999. Miami, FL. 5 p. MSAP (Mackerel Stock Assessment Panel) Report of the Mackerel Stock Assessment Panel. Prepared by the MSAP at the Panel Meeting held March 3 6, 998. FL. Gulf of Mexico Fishery Management Council, Tampa FL, and South Atlantic Fishery Management Council, Charleston SC. MSAP (Mackerel Stock Assessment Panel).. Report of the Mackerel Stock Assessment Panel. Prepared by the MSAP at the Panel Meeting held May 6-8,. FL. Gula of Mexico Fishery Management Council, Tampa FL., and South Atlantic Fishery Management Council, Charleston SC. Manooch, C.S. III, S.P. Naughton, C.B. Grimes, and L. Trent Age and growth of king mackerel, Scomberomorus cavalla, from the U.S. Gulf of Mexico. Marine Fisheries Review. 49(): -8. MSAP-3- of 8

21 Nichols, S., A. Shah, G.J. Pellegrin Jr. and K. Mullin Estimates of annual shrimp fleet bycatch for thirteen species in the offshore waters of the Gulf of Mexico. Report to the Gulf of Mexico Fishery Management Council. Ortiz, M.. Even further projections for Gulf and Atlantic King and Spanish mackerel migratory groups. NMFS SEFSC Miami Sustainable Fisheries Division Contribution SFD-/-5. Ortiz, M. 3. Standardized catch rates of king (Scomberomorus cavalla) and Spanish mackerel (S. maculatus) from U.S. Gulf of Mexico and South Atlantic recreational fisheries. NMFS SEFSC Miami Sustainable Fisheries Division Contribution SFD-/3-6. Ortiz, M.. Estimates of Gulf king mackerel bycatch from the U.S. Gulf of Mexico Shrimp Gulf trawl fishery. NMFS SEFSC Miami Sustainable Fisheries Division Contribution SFD-//6. Ortiz, M. and C.M. Legault.. Further projections for Gulf and Atlantic king and Spanish mackerel migratory groups. NMFS SEFSC Miami Sustainable Fisheries Division Contribution SFD-/-. Ortiz, M., C.M. Legault and G. Scott.. Variance component estimation for standardized catch rates for king mackerel (Scomberomorus cavalla) from U.S. Gulf of Mexico recreational fisheries useful for inverse variance weighting techniques. MSAP//3. NMFS Sustainable Fisheries Division Contribution SFD-99/-86. Miami, FL. Ortiz, M., C.M. Legault and N.M. Ehrhardt.. An alternative method for estimating bycatch from the U.S. shrimp trawl fishery in the Gulf of Mexico, Fish. Bull. 98: Ortiz, M. and P. Phares.. Standardized catch rates of king mackerel (Scomberomorus cavalla) from U.S. Gulf of Mexico and South Atlantic recreational fisheries. MSAP--##. NMFS SEFSC Miami Sustainable Fisheries Division Contribution /-55. Ortiz, M., G.P. Scott, N. Cummings and P.L. Phares.. Stock assessment analyses on Gulf of Mexico King Mackerel. NMFS SEFSC Miami Sustainable Fisheries Division Contribution SFD-/- 6. Ortiz, M. and G.P. Scott.. Standardized catch rates of king (Scomberomorus cavalla) and Spanish (S. maculatus) mackerel from U.S. Gulf of Mexico and South Atlantic recreational fisheries. MSAP--. NMFS SEFSC Miami Sustainable Fisheries Division Contribution /-5. Ortiz, M. and L. Sabo. 3. Standardized catch rates of Spanish and king mackerel (Scomberomorus maculatus and S. cavalla) from the North Carolina Commercial Fisheries. NMFS SEFSC Miami Sustainable Fisheries Division Contribution SFD-/3-5. Powers, J.E. and V.R. Restrepo. 99. Additional options for age-sequenced analysis. ICCAT Coll. Vol. Sci. Pap. 39: Punt, A.E., T.I. Walker, B.L. Taylor and F. Pribac.. Standardization of catch and effort data in a spatially-structured shark fishery. Fisheries Research 45:9-45. Restrepo, V.R FADAPT 3. A Guide. University of Miami, Cooperative Unit for Fisheries Research and Education (CUFER). Restrepo, V.R., G.G. Thompson, P.M. Mace, W.L. Gabriel, L.L. Low, A.D. MacCall, R.D. Methot, J.E. Powers, B.L. Taylor, P.R. Wade and J.F. Witzig Technical guidance on the use of precautionary approaches to implementing National Standard of the Magnuson-Stevens Fishery Conservation and Management Act. NOAA Technical Memorandum NMFS-F/SPO-##. 54 pp. Shepherd, J.G Deconvolution of length compositions. ICES Methods Working Group. Working paper 7 pp. Vaughan, D.S. and J.M. Nance Estimates of bycatch of mackerel and cobia in U.S. South Atlantic shrimp trawls. MSAP/98/4. MSAP-3- of 8

22 Table. Atlantic king mackerel stock catch summary by sector. Commercial Recreational Total Fishing Year Num fish Weight Num fish Weight Num Wgt 98/ / / / / / / / / / / / / / / / / / / / / Table. Atlantic king mackerel stock catch summary by sector and state. Commercial Recreational Fishing Year FLE FLW N_NC NC SCGA Total Com FLE FLW N_NC NC SCGA Total Rec 98/ / / / / / / / / / / / / / / / / / / / / MSAP-3- of 8

23 Table 3. Atlantic Spanish mackerel stock catch summary by sector Commercial Recreational Total Fishing Year Num fish Weight Num fish Weight Num Wgt 984/ / / / / / / / / / / / / / / / / / Table 4. Atlantic Spanish mackerel stock catch summary by sector and state. Commercial Recreational Fishing Year FLE N_NC NC SCGA Total Com FLE N_NC NC SCGA Total Rec 984/ / / / / / / / / / / / / / / / / / MSAP-3-3 of 8

24 Table 5. Gulf Spanish mackerel stock catch summary by sector. Commercial Recreational Total Fishing Year Num fish Weight Num fish Weight Num Wgt 984/ / / / / / / / / / / / / / / / / / Table 6. Gulf Spanish mackerel stock catch summary by sector and state. Commercial Recreational Fishing Year AL-MS FLW LA TX Total Com AL-MS FLW LA TX Total Rec 984/ / / / / / / / / / / / / / / / / / MSAP-3-4 of 8

25 Table 7. Gulf Spanish mackerel shrimp bycatch estimates from two methods, GLM and Delta lognormal models. Fishing Year GLM Delta LogN 984/ / / / / / / / / / / / / / / / / / Table 8. Atlantic king mackerel catch at age (CAA) directed fisheries. YEAR Age Age Age Age 3 Age 4 Age 5 Age 6 Age 7 Age 8 Age 9 Age Age + 98/ ,854 4,335 55,954 54,3 3,6,579 34,7 5,5 7,985,95 7,68 98/83,89 5,59 5,75,653 7,35 7,69 68,34 63,5 54,633 7,8,97 9,87 983/84 3,693 9,87 6,59,54 7,4 38,44 7,8 8,89 37,35 68,94 3, 64, /85,75 4,65,79 9,65, 35,6 9,35 43,957 54,5 67,9 57,85 79,6 985/86,7 86,459 6,498 5,568 64,835 98,86 33,34 68,9,33 59,33 8,48 67,9 986/87,44 8,93,97 5,697 4,44 63,7 6,9 9,87 56,98 7,873 6,756 57, /88 6,5 97,89, 39,893 95,7 73,755 4,87 33,794 3,4 3,9,9 43, /89,757 9,394 7,48 9,579 3,4 6,4 6,993 6,595,46 46,998,8 77,8 989/ ,84,676 37,946 98,88 69,87 45,3 3,75 6,74 9,8 4,949 4,376 99/ ,83 6,794 78,594 9,87 8,53 6,87 6,54 5,597 7,8 4,47 56, 99/ ,988 3,48 3,736 7,365 99,8 83,573 45,99 3,85,985 8,84 6,5 99/ ,386 59,453 79,93 7,9 43,7 5,4 46,67 8,954 8,36,9 6,4 993/94,8 48,764 85,49 9,63,448 3,38 34,36 34,6 4,3 8,569 7,947 45,97 994/95 3 9,443 4,7 64,85 75,89 88,968 4,433 5,378,874 3,98 3,3 3, /96 59,77 49,7 88,8 5,38 6,3 75,64,364 8,56,78 8,85 6,64 996/ ,539 84,57 36,549 93,9 6,6 34,6 63,735 5,35 3,65 5,95 4,44 997/98,87 93,357 8,753 34,56 83,879 5,738 9,568 4,47 4,788 6,5 5,6 6, /99 7,54 58,59 77,637 8,958,693 63,645 35,6 9,778 7,48 6,66 6,96,73 999/,479 8,3 4,99 39,6 7,86 57,8 9,67,68,58 7,66 5,539,377 / 888 7,6 78,58 99,655 6,877 88,43 38,838 3,537 9,96 9,399 7,9 36,69 / - 6,448 94,5 34,37 65,79 85,686 45,85 9, 8,596 5,596 7,65 4,99 MSAP-3-5 of 8

26 Table 9. Atlantic Spanish mackerel catch at age (CAA) directed fisheries. YEAR Age Age Age Age 3 Age 4 Age 5 Age 6+ 98/ ,8,896,7 88,85 7,935 34,47 6,646 98/83,89 8,9,88,593 57,54 34,749,94 93,4 983/84 5,56,96,39,65,685,7 9,35 46,339 4,87 984/85 3,7,3,39 653,76 6,53 3,35 66,886 5,3 985/86 34,77,3,346,55, 96,87 3,698 4,75 6, /87 5,53,3,996 6,76 599,84 44,5 3,864, /88 349,5,44,54 83,785 4,4 5,783 4,98 7,63 988/89 338,47,3,969 88,4 43,78 95,458 63,893 98,35 989/9 66,6,538,548 97,6 47,78 7,874,374 4,75 99/9 56,83,,94 899,38 645,88 76,774,677 53,5 99/9 3,73,954,47 998,95 65,56 333,483 49,348 6,3 99/93 43,84 934,79 56,756 36,88 9,366 9,8,56 993/94 73,33,36,67 84,3 5,44 39,55 5,784 3,63 994/95 46,585,8,6 949,45 498,,5 58,39 59,66 995/96 465,473 8,66 833,4 49,5,3 9,93 84, /97 67,398,4, ,5 94,56 58,7 7,8 73,77 997/98 7,594,46,37,5,7 47,734 39,646 84,895 97,58 998/99 69,65 8,784,5, ,696 87,753 44,9 7,96 Table. Gulf Spanish mackerel catch at age (CAA) directed fisheries. YEAR Age Age Age Age 3 Age 4 Age 5 Age 6 Age / ,378,598,94 578,5 9,7 3,65 583,58 985/ ,47,37, ,43 77,57,587,53 3, /87 5,8 4,643,85,34,86 33,69 68,846 67,364 33,68,54 987/88 43,794,36,7,3, ,69 435,375 8,5 66,475 39,75 988/89 36,6,48,983,334,348 56,5 445, 73,356 5,38 54, /9 99,59 833, ,659 39,58 63,756 8,83 36,46 7,88 99/9 67,79,, ,37 363,79 9,438 3,863 46,49,638 99/9 5,36,36,33,398,3 677,836 35,765 49,98 67,895 67,93 99/93 3,97 94,93,587,49 84,34 97,56 94,6 8,988 6,93 993/94 56,87 65,5,8,43 99,3 373,987 7,43,575 34,8 994/95 4,65 975,363 66,9 6,47 3,7 66,67 4,73 5, /96 339,4 389,469 74,3 98,63 3,93 4,9 8,338 7, /97 77,7 55,44 348,97 4,758 94,56 49,786 7,83 8,95 997/98 9,68 439,637 66,489 8,7 7,3 5,957,93 998/99 6,383 5,88 734,95 634,89 9,47 7,68 7,69, / 8, ,45 588,5 654,75 6,68 54,48,9 4,6 / 86,44 956,8 666,83 39, 3,785 8,33 7,64 / 89,39,559,554 87,59 65,787 7,985 8,535 4,84 MSAP-3-6 of 8

27 Table. Tuning indices for Atlantic king mackerel VPA analyses. Time of comparison between observed and predicted values is either mid-year (MID) or at the start of the year (BEG), and the stock is measured in biomass or numbers. INDICES OF ABUNDANCE North Carolina Fishing Year HeadBoat MRFSS Florida FWC Comm New SEAMAP SA North Carolina Comm Old 98/ / / / / / / / / / / / / / / / / / / / / / Time MID MID BEG MID MID MID Stock Number Number Biomass Biomass Number Biomass Ages Table. Tuning indices available for Atlantic Spanish mackerel VPA analyses. INDICES OF ABUNDANCE North Carolina Fishing Year HeadBoat MRFSS Florida FWC Pamlico North Carolina Comm SEAMAP SA 984/ / / / / / / / / / / / / / / / / / / Time MID MID MID MID MID MID Stock Number Number Biomass Number Biomass Freq occurrence Ages MSAP-3-7 of 8

28 Table 3. Tuning indices available for Gulf Spanish mackerel VPA analyses. Fishing Year HeadBoat MRFSS Texas PWD Florida FWC INDICES OF ABUNDANCE Shrimp Bycatch GLM Shrimp Bycatch Delta LogN SEAMAP SA Charter NW Florida 984/ #N/A / / / / / / / / / / / / / / / / / / Time MID BEG BEG BEG BEG BEG BEG BEG Stock Number Number Number Biomass Number Number Number Number Ages MSAP-3-8 of 8

29 Table 4. Atlantic king mackerel tuned VPA results for model Base, Stock at Age at beginning of year F at Age during year MSAP-3-9 of 8

30 Parameter Estimates Atlantic King Base Model Update of FADAPT Version 3 (Feb 96) by V. Restrepo Input DATA file: AtlKng3a.inp Input CONTROL file: AtlKng3B.inp Output Stock Size file: AtlKng.naa Output Fishing Mortality file: AtlKng.faa Ouput Fitted Indices file: AtlKng.ind Output Diagnostics (this) file: AtlKng.par Run name: Atl_King-3 Base[wo_NCCommNew] No. index values: 87 Parameters: 8 Mean Squared Error (rss/df) = 7474E+ Rsquared =.364 Loglikelihood = -5E+ res from indices = res from curvature =.E+ Program termination OK More details of the run can be found in file FADAPT5.RUN Parameter Estimate S.E. % C.V. F age F age F age F age F age F age F age F age Variances of terminal yr F and survivors Age, SE(F,) CV(F) SE(N,) CV(N) 9E E E E E E E E E E E E E E E E E Obs. and pred. indices in objective function 667E+ 643E+.9993E+ 9E+ 837E+ 778E+.7543E+ 6E+.958E+ 583E+ E+ 3834E+ 384E+ 5654E+ 693E+ 3487E+.9894E+.795E+ 836E+ 977E+ 77E+ 8E+ 3648E+ 4E+ 556E+ 44E+ 949E+ 97E+.768E+ 89E+.9578E+ 778E+ 3E+ 989E+ 5E+ 9E+ 3E+ 67E+ 793E+ 38E+ 377E+ 63E+ 3E+ 965E E+ 898E+ 8477E+ 33E+ 9433E+ 956E+ 779E+ 766E+ 359E+ 953E+ 337E+.96E+ 396E+ 74E+.9584E+.9363E+.9976E+.9447E+ 6676E+.9484E+ 9678E+ 634E+.9657E+ 89E+ 475E E+ 666E+.764E+.9475E+ 88E+ 479E+ 76E+.7585E+ 75E+ 547E+ 388E+ 9453E+ 986E+.7546E+ 989E+ 393E E+ 967E+ 4755E+ 64E+ 7E+ 3939E+ 3876E+ 9E+ 3839E+.774E+ 35E+ 399E+.949E+ 898E+ 9478E+.777E+.955E+.7977E+.9836E+ E+ 83E+ 6987E+.993E+ 58E+ 373E+ 4686E+ 499E+ 8559E E+ 85E+ 495E+ 549E+ 679E+.7883E+ 46E+ 698E+ 786E+ 549E+ 354E+ 66E+ 56E+.9663E+.7534E+ 9698E+ 5579E+ 4799E+ 933E+ 4E+ 7E+ 5E+.775E+ 73E+ 364E+.7693E+.9563E E E+.958E+ 47E+ 57E+ 53E+ 3376E+ 565E+ 88E+ 7E+ 556E+ 3446E+ 635E+.734E+ 4337E+.73E+ 443E+ 5543E+ 588E+.999E+ 44E+ 58E+ 964E+ 836E+ 636E E+ 3E+ 34E+ 6997E+.7468E E+ 55E+ 8478E+ 9749E-6 MSAP-3-3 of 8

31 INDEX RESULTS Maximum likelihood weighting for indices Fit results for index = NC Com Old Index Fitted to Mid-Year Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 8/ / / / / / / / / / / / / / / / Index ML estimate of the variance:.75 (S.E.: 74) ML estimate of catchability: 6E-7 Pearsons (parametric) correlation: 5 P=. Kendalls (nonparametric) Tau: P=.55 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / Fit results for index = FWC Index Fitted to Beginning Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 85/ / / / / / / / / / / / / / / / / Index ML estimate of the variance:.37 (S.E.: 78) ML estimate of catchability: 389E-7 Pearsons (parametric) correlation: P=.3 Kendalls (nonparametric) Tau: 8 P=.7 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / Fit results for index = MRFSS Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 8/ / / / / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 358 (S.E.: 794) ML estimate of catchability: 48E-6 Pearsons (parametric) correlation: 5 P= 86 Kendalls (nonparametric) Tau:.76 P= 496 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / / / / Fit results for index = Headboat Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 8/ / / / / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 97 (S.E.: 46) ML estimate of catchability: 6959E-6 Pearsons (parametric) correlation: 8 P=.8 Kendalls (nonparametric) Tau: P=.46 Selectivity at age from Partial Catches year MSAP-3-3 of 8

32 8/ / / / / / / / / / / / / / / / / / / / / Fit results for index = Seamap SA Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 9/ / / / / / / / / / / / Index ML estimate of the variance: 8 (S.E.: 56) ML estimate of catchability:.75346e-6 Pearsons (parametric) correlation:.75 P=. Kendalls (nonparametric) Tau: 94 P=.83 Selectivities set to. year 9/9. 9/9. 9/93. 93/94. 94/95. 95/96. 96/97. 97/98. 98/99. 99/. /. /. MSAP-3-3 of 8

33 Table 5. Atlantic king mackerel tuned VPA results for Full Index Model. Stock at Age at beginning of year F at Age during year MSAP-3-33 of 8

34 Parameter Estimates Atlantic King Model Full Index Update of FADAPT Version 3 (Feb 96) by V. Restrepo Input DATA file: AtlKng3.inp Input CONTROL file: AtlKng3B.inp Output Stock Size file: AtlKng.naa Output Fishing Mortality file: AtlKng.faa Ouput Fitted Indices file: AtlKng.ind Output Diagnostics (this) file: AtlKng.par Run name: Atl_King-3 Full_Index No. index values: 95 Parameters: 8 Mean Squared Error (rss/df) = 556E+ Rsquared =.78 Loglikelihood = -76E+ res from indices = res from curvature =.E+ Program termination OK More details of the run can be found in file FADAPT5.RUN Parameter Estimate S.E. % C.V. F age F age F age F age F age F age F age F age Variances of terminal yr F and survivors Age, SE(F,) CV(F) SE(N,) CV(N) 55E E E E E E E E E E E E E E E E Obs. and pred. indices in objective function 667E+.7357E+.9993E+ 496E+ 837E+.96E+.7543E+ 57E+.958E+ 6796E+ E+ 469E+ 384E+ 578E+ 693E+ 446E+.9894E+.79E+ 836E+ 979E+ 77E+ 3E+ 3648E+ 99E+ 556E+ 3376E+ 949E+ 335E+.768E+ 746E+.9578E+ 3353E+ 69E+ 54E+ 644E+.957E+.969E+ 88E+ 463E+ 564E+ 8E+ 6E+ 74E+.957E+ 434E+.98E+.7456E+.7957E+ 3E+ 45E+ 5E+ 597E+ 3E+ E+ 793E+ 3556E+ 377E+ 39E+ 3E+.7464E E+ 99E+ 8477E+ 3E+ 9433E+ 634E+ 779E+ 898E+ 359E+ 573E+ 337E+ 564E+ 396E+.9985E+.9584E+.7936E+.9976E+ 579E+ 6676E+.964E+ 9678E+ 553E+.9657E+ 4666E+ 475E+ 793E+ 666E+.7749E+.9475E+ 65E+ 479E+ 648E+.7585E+ 36E+ 547E+ 4639E+ 9453E+ 7E+.7546E+ 643E+ 393E+ 838E+ 967E+ 4945E+ 64E+ 359E+ 3939E+ 36E+ 9E+ 6E+.774E+ E+ 399E+ 7345E+ 898E+ 46E+.777E+.787E+.7977E+ 595E+ E+ 44E+ 6987E+.76E+ 58E+ 546E+ 4686E+ 33E+ 8559E+.7687E+ 85E+ 796E+ 549E+ 8587E+.7883E+ 5E+ 698E+ 6E+ 549E+ 386E+ 66E+ 68E+.9663E+.766E+ 9698E+ 5573E+ 4799E+ 76E+ 4E+ 448E+ 5E+.7673E+ 73E+.797E+.7693E+ 5674E E+ 5377E+.958E+ 675E+ 57E+ 59E+ 3376E+ 37E+ 88E+ 343E+ 556E+ 37E+ 635E+ 946E+ 4337E+.736E+ 443E+ 455E+ 588E E+ 44E+ 5733E+ 964E+ 3658E+ 636E+.7668E+ 3E+ 58E+ 6997E+.7467E E+ 43E+ 8478E+ 9439E-6 MSAP-3-34 of 8

35 INDEX RESULTS Maximum likelihood weighting for indices Fit results for index = NC Com Old Index Fitted to Mid-Year Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 8/ / / / / / / / / / / / / / / / Index ML estimate of the variance:.87 (S.E.: 84) ML estimate of catchability: 895E-7 Pearsons (parametric) correlation: 99 P=.9 Kendalls (nonparametric) Tau: 7 P=. Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / Fit results for index = NC Com New Index Fitted to Mid-Year Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 94/ / / / / / / / Index ML estimate of the variance:.8 (S.E.: 444) ML estimate of catchability: 464E-6 Pearsons (parametric) correlation:.77 P=. Kendalls (nonparametric) Tau: 4 P= 78 Selectivity at age from Partial Catches year / / / / / / / / Fit results for index = FWC Index Fitted to Beginning Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 85/ / / / / / / / / / / / / / / / / Index ML estimate of the variance:.357 (S.E.: 889) ML estimate of catchability: 6884E-7 Pearsons (parametric) correlation: 44 P=.4 Kendalls (nonparametric) Tau: 4 P=.73 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / Fit results for index = MRFSS Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 8/ / / / / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 69 (S.E.: 54) ML estimate of catchability: 83E-6 Pearsons (parametric) correlation: 6 P=.7 Kendalls (nonparametric) Tau: 4 P= 6 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / / / / MSAP-3-35 of 8

36 Fit results for index = Headboat Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 8/ / / / / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 63 (S.E.: 554) ML estimate of catchability: 98E-6 Pearsons (parametric) correlation: 59 P=.5 Kendalls (nonparametric) Tau: 33 P= 639 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / / / / Fit results for index = Seamap SA Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 9/ / / / / / / / / / / / Index ML estimate of the variance: 98 (S.E.: 449) ML estimate of catchability: 4E-6 Pearsons (parametric) correlation:.79 P=. Kendalls (nonparametric) Tau: 4 P=.47 Selectivities set to. year 9/9. 9/9. 9/93. 93/94. 94/95. 95/96. 96/97. 97/98. 98/99. 99/. /. /. MSAP-3-36 of 8

37 Table 6. Maximum sustainable yield (MSY) and optimum yield (OY) related values from the Base model and the Full index model for Atlantic king mackerel 3 stock evaluation. SS is spawning stock biomass in trillions of yolked eggs, F values are associated with the fully selected age, and yields are given in millions of pounds. 8% confidence intervals generated from 5 bootstrap projections. MODEL BASE SS MSY F MSY MSY SS OY F OY OY Median low 8% upp 8% Deterministic MODEL Full Index SS MSY F MSY MSY SS OY F OY OY Median low 8% upp 8% Deterministic Table 7. Estimated acceptable biological catch (ABC) in millions of pounds for the Atlantic king mackerel 3/4 fishing year under a projected F of F 3%SPR or F 4%SPR from the Base and Full index models evaluated. Probability denotes the likelihood of exceeding the desired F mortality rates. Base Model Full Index Model Probability F 3%SPR F 4%SPR F 3%SPR F 4%SPR 5% Median % lower CI % upper CI MSAP-3-37 of 8

38 Table 8. Atlantic Spanish mackerel tuned VPA results for Base Model. Stock at Age at beginning of year F at age during year MSAP-3-38 of 8

39 Parameter Estimates Atlantic Spanish Base Model Update of FADAPT Version 3 (Feb 96) by V. Restrepo Input DATA file: AtlSpn3A.inp Input CONTROL file: AtlSpn3A.inp Output Stock Size file: AtlSPa.naa Output Fishing Mortality file: AtlSPa.faa Ouput Fitted Indices file: AtlSPa.ind Output Diagnostics (this) file: AtlSPa.par Run name: Atl Spanish 3 NoByc NoSeaMap early No. index values: 65 Parameters: 6 Mean Squared Error (rss/df) = 348E+ Rsquared = -373 Loglikelihood = -356E+ res from indices = res from curvature =.E+ Program termination OK More details of the run can be found in file FADAPT5.RUN Parameter Estimate S.E. % C.V. F age F age F age F age F age F age E+ 795E+ 489E+ 37E+ 56E+ 83E+ 39E+ 4E+ 43E+ 858E+ 4993E+ 399E+ 497E+ 7E+ 386E+ 78E+ 397E+ 865E+ 6685E+ 376E+ 473E+ 5E+ 37E+ 6E E+.9856E+ 4684E E+.7957E E+ 597E+ 98E+ 333E+ 94E+ 939E+.7944E+ 99E+.76E+ 7E+ E+ 69E E+ 6E+ 685E+.9846E+ 3784E+ 379E+ 35E+.948E+ 9E+ 55E+.936E+ 47E+.944E+ 57E+.7733E+ 868E+ 534E E+.945E+.9663E E+.7383E+ 496E+ 34E+.7789E+ 635E+ 74E+.967E+ 65E+ 335E+ 335E+ 3849E+ 3849E+ Variances of terminal yr F and survivors Age, SE(F,) CV(F) SE(N,) CV(N) 5E E E E E E E E E E E E+6.3 Obs. and pred. indices in objective function 383E+ 666E+ 36E E+ 635E+ 9677E+ 875E+ 3669E E+.755E+ 649E+.9953E+ 899E+ 345E+ 56E+.7656E+ 97E+ 5797E+.9477E+ 343E+ 6956E+.7869E+ 4689E+ 54E+ 445E+ 335E+ 666E+ 3E+ 5354E+ 69E+ 653E+ 55E+ 94E+ 4849E+ 5345E+ 6867E+.776E+ 7883E- 943E+.738E+ 477E+ 57E+ 653E+.763E+ 487E+ 8364E+ 553E+ 86E+ 45E+ 5E+ 686E+ 8E+ 848E+ E+.7957E+ 6659E+ MSAP-3-39 of 8

40 INDEX RESULTS Maximum likelihood weighting for indices Fit results for index = FDEP Index Fitted to Mid-Year Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 85/ / / / / / / / / / / / / / / / / Index ML estimate of the variance: 58 (S.E.: 53) ML estimate of catchability: 7E-6 Pearsons (parametric) correlation:.75 P=. Kendalls (nonparametric) Tau: P=.8 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / Fit results for index = Headboat Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 849 (S.E.: 338) ML estimate of catchability: 6356E-6 Pearsons (parametric) correlation: 5 P= 63 Kendalls (nonparametric) Tau:.98 P= 98 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / Fit results for index = MRFSS Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 33 (S.E.: 83) ML estimate of catchability: 488E-6 Pearsons (parametric) correlation: -84 P= 965 Kendalls (nonparametric) Tau: -63 P= 76 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / Fit results for index = SeaMap SA Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 9/ / / / / / / / / / / / Index ML estimate of the variance:.73 (S.E.: 76) ML estimate of catchability:.7988e-7 Pearsons (parametric) correlation: 95 P=.77 Kendalls (nonparametric) Tau: 64 P=.4 Selectivities set to. year 9/9.. 9/9.. 9/ / / / / / / /.. /.. /.. MSAP-3-4 of 8

41 Table 9. Atlantic Spanish mackerel tuned VPA results for Full Index Model. Stock at Age at beginning of year F at age during year MSAP-3-4 of 8

42 Parameter Estimates Atlantic Spanish Full Index Model Update of FADAPT Version 3 (Feb 96) by V. Restrepo Input DATA file: AtlSpn3B.inp Input CONTROL file: AtlSpn3B.inp Output Stock Size file: AtlSPa.naa Output Fishing Mortality file: AtlSPa.faa Ouput Fitted Indices file: AtlSPa.ind Output Diagnostics (this) file: AtlSPa.par Run name: Atl Spanish 3 Full index No. index values: 87 Parameters: 6 Mean Squared Error (rss/df) = 568E+ Rsquared = -687 Loglikelihood = -83E+ res from indices = res from curvature =.E+ Program termination OK More details of the run can be found in filefadapt5.run Parameter Estimate S.E. % C.V. F age F age F age F age F age F age Variances of terminal yr F and survivors Age, SE(F,) CV(F) SE(N,) CV(N) 77E E E E E E E E E E E E E Obs. and pred. indices in objective function 383E+ 55E+ 36E+.759E+ 635E+.745E+ 875E+ 388E E+.7446E+ 649E E+ 899E+ 38E+ 56E+.7595E+ 97E+ 683E+.9477E+ 4939E+ 6956E+ 598E+ 4689E+ 63E+ 445E+ 3834E+ 666E+ 8E+ 5354E+ 654E+ 653E+ 5743E+ 94E+ 485E+ 5345E+ 483E+.776E+ 978E- 943E+.7468E+ 477E+ 749E+ 653E+.7585E+ 487E+ 843E+ 553E+ 846E+ 45E+ 95E+ 686E+ E+ 848E+ 357E+.7957E+ 8784E+ 96E+ 675E+ 489E+ 6E+ 56E+ 899E+ 39E E+ 43E+ 786E+ 4993E+ 379E+ 497E+ 789E+ 386E+ 963E+ 397E+ 979E+ 6685E+ 3786E+ 473E+ 98E+ 37E+ 336E E+.9447E+ 4684E+.955E+.7957E E+ 597E+ 953E+ 333E+ 47E+ 939E+ 658E+ 99E E+ 7E+ 55E+ 69E+ 65E+ 6E+ 733E+.9846E+ 375E+ 379E+ 33E+.948E+ 9E+ 55E+ 938E+ 47E+.988E+ 57E+.7766E+ 868E+ 6464E E E+.9663E E+.7383E+ 5964E+ 34E+.7977E+ 635E+ 6E+.967E+ 876E+ 335E+ 788E+ 3849E+ 349E+ 44E+ 37E+ 4E E+ 86E+ 655E+ 39E+.985E+ 944E E+ 869E+ 793E+ 43E+.9436E+ 68E+.93E+ 869E+ 477E+ 5E E+ 5E+ 374E+ 7E+ 95E+ 694E+ 44E+ 477E+ 9E+ 4E+.788E+ 348E+ 8549E+.797E+ 8E+ 49E+.9556E+.743E+ 99E+ 8434E+ 76E+ 43E+ 864E+ 795E+ 44E+ MSAP-3-4 of 8

43 INDEX RESULTS Maximum likelihood weighting for indices Fit results for index = FWC Index Fitted to Mid-Year Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 85/ / / / / / / / / / / / / / / / / Index ML estimate of the variance:.988 (S.E.: 43) ML estimate of catchability: 364E-6 Pearsons (parametric) correlation:.77 P=. Kendalls (nonparametric) Tau: P=.8 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / Fit results for index = Headboat Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 83 (S.E.: 3) ML estimate of catchability: 469E-6 Pearsons (parametric) correlation: 4 P= 89 Kendalls (nonparametric) Tau:.85 P= 438 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / Fit results for index = MRFSS Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 9 (S.E.: 786) ML estimate of catchability: 69E-6 Pearsons (parametric) correlation: -84 P= 957 Kendalls (nonparametric) Tau: -63 P= 76 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / Fit results for index = SeaMap SA Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 9/ / / / / / / / / / / / Index ML estimate of the variance:.79 (S.E.: 8) ML estimate of catchability:.73543e-7 Pearsons (parametric) correlation: 3 P=.7 Kendalls (nonparametric) Tau: 3 P=.37 Selectivities set to. year 9/9.. 9/9.. 9/ / / / /97.. MSAP-3-43 of 8

44 97/ / /.. /.. /.. Fit results for index = NCPamlicoSS Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 88/ / / / / / / / / / / / / / Index ML estimate of the variance: 3 (S.E.:.788) ML estimate of catchability: 767E-7 Pearsons (parametric) correlation: -86 P=.67 Kendalls (nonparametric) Tau: - P=.44 Selectivities set to. year 88/ /9.. 9/9.. 9/9.. 9/ / / / / / / /.. /.. /.. Fit results for index = NC Comm Index Fitted to Mid-Year Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 94/ / / / / / / / Index ML estimate of the variance:.445 (S.E.: ) ML estimate of catchability: 858E-7 Pearsons (parametric) correlation: 4 P=.64 Kendalls (nonparametric) Tau: 86 P= 43 Selectivity at age from Partial Catches year / / / / / / / / MSAP-3-44 of 8

45 Table. Maximum sustainable yield (MSY) and optimum yield (OY) related values from the Base model and the Full index model for Atlantic Spanish mackerel 3 stock evaluation. SS is spawning stock biomass in weight of mature females (million pounds), F values are associated with the fully selected age, and yields are given in millions of pounds. 8% confidence intervals generated from 5 bootstrap projections. MODEL BASE SS MSY F MSY MSY SS OY F OY OY Median low 8% upp 8% Deterministic MODEL Full Index SS MSY F MSY MSY SS OY F OY OY Median low 8% upp 8% Deterministic Table. Estimated acceptable biological catch (ABC) in millions of pounds for the Atlantic Spanish mackerel 3/4 fishing year under a projected F of F 3%SPR or F 4%SPR from the Base and Full index models evaluated. Probability denotes the likelihood of exceeding the desired F mortality rates. Base Model Full Index Model Probability F 3%SPR F 4%SPR F 3%SPR F 4%SPR 5% Median % lower CI % upper CI MSAP-3-45 of 8

46 Table. Gulf Spanish mackerel tuned VPA results for Base Model. Stock at Age at beginning of year F at age during year MSAP-3-46 of 8

47 Parameter Estimates Gulf Spanish Base Model Update of FADAPT Version 3 (Feb 96) by V. Restrepo Input DATA file: glfspn3a.inp Input CONTROL file: glfspn3a.inp Output Stock Size file: GlfSPA.naa Output Fishing Mortality file: GlfSPA.faa Ouput Fitted Indices file: GlfSPA.ind Output Diagnostics (this) file: GlfSPA.par Run name: Gulf Spanish-3 Base No. index values: 77 Parameters: 8 Mean Squared Error (rss/df) = 57E+ Rsquared = -648 Loglikelihood = -753E+ res from indices = res from curvature =.E+ Program termination OK More details of the run can be found in filefadapt5.run Parameter Estimate S.E. % C.V. F age F age F age F age F age F age F age F age Variances of terminal yr F and survivors Age, SE(F,) CV(F) SE(N,) CV(N) 995E E E E E E E E E E E Obs. and pred. indices in objective function 5333E+ 5364E+ 44E+ 446E+ 6367E+ 97E+ 838E+ 86E+ 69E+.9954E+.9866E+ 388E+ 388E+.79E+ 38E+ 869E+ 98E+ 75E+ 57E+ 99E+ 858E+.9948E+ 556E+ E+ 43E+ 969E+ 57E+ 755E+ 976E+.9699E+ 985E+ 78E+ 8E+ 679E+ 578E+ 683E+ 443E+ 986E+ 53E+ 39E+ 564E+ 5385E+ 6555E+.7666E+ 9699E+ 347E+ 589E+ 87E+ 73E+.9886E+ 88E+ 95E+ 8746E+ 53E+.93E+ 3789E+ 8953E+.774E+ 66E+ 69E+ 897E+.773E+ 8E+ 84E+.999E+ 76E+ 5796E+.7656E+ 3E+ 757E+ 693E+ 6E+ 836E+ 3546E+ 76E+ 586E+ 8739E+.7634E+ 64E+ 938E+ 77E+ 73E+.9865E+ 889E E+ 4E+.7945E+ 387E+ 577E+.7936E+ 97E+ 88E+ 69E+ 9687E+ 5E+ 4673E+ 63E+.998E+ 33E+.9974E+ 4636E E+.9645E+.985E+.9496E+.753E+ 7774E+ 55E+ 64E+ 98E+ 56E+ 477E+ 75E+ 76E+ 365E+ 37E E E+ 6758E+ 348E+ 958E+.7848E+ 7459E+ 4E+ 66E+ 97E+ 574E+ 95E+ 368E+ 4876E+.9737E+ 853E+ 539E+.987E+.9638E+ 598E E+ 45E+ 443E+ 4577E+ 6E+.9499E+ 877E+ 566E+ 76E+ 3645E+.786E+ 6668E+ 836E+ 939E+ 7E+.9848E+ 497E+ 4564E+ MSAP-3-47 of 8

48 INDEX RESULTS Maximum likelihood weighting for indices Fit results for index = FWC Index Fitted to Beginning Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 85/ / / / / / / / / / / / / / / / / Index ML estimate of the variance: 455 (S.E.: 84) ML estimate of catchability: 97E-6 Pearsons (parametric) correlation:.6 P= 5 Kendalls (nonparametric) Tau: -.44 P= 38 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / Fit results for index = MRFSS Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 5 (S.E.: 97) ML estimate of catchability: 343E-6 Pearsons (parametric) correlation: 36 P= 7 Kendalls (nonparametric) Tau: - P= 563 Selectivity at age from Partial Catches year 3 84/ / / / / / / / / / / / / / / / /.3 6. / Fit results for index = Chart NWF Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / Index ML estimate of the variance:.46 (S.E.: 4) ML estimate of catchability: 34E-6 Pearsons (parametric) correlation:.94 P=. Kendalls (nonparametric) Tau: P=.9 Selectivity at age from Partial Catches year 84/ / / / / /9 7. Fit results for index = Bycatch GLM Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance:.685 (S.E.: 67) ML estimate of catchability: 837E-7 Pearsons (parametric) correlation: 7 P= 757 Kendalls (nonparametric) Tau: 37 P= 843 Selectivity at age from Partial Catches year 84/ / / / / / / / / / / / / / / / / / Fit results for index = TPWD Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / MSAP-3-48 of 8

49 9/ / / / / / / / / / / / Index ML estimate of the variance: 57 (S.E.: 7) ML estimate of catchability: 695E-6 Pearsons (parametric) correlation: -7 P= Kendalls (nonparametric) Tau: -.7 P= 99 Selectivity at age from Partial Catches year 3 84/ / / / / / / / / / / / / / / / /.9 4. / MSAP-3-49 of 8

50 Table 3. Gulf Spanish mackerel tuned VPA results for Full Index Model. Stock at Age at beginning of year F at age during year MSAP-3-5 of 8

51 Parameter Estimates Gulf Spanish Full Index Model Update of FADAPT Version 3 (Feb 96) by V. Restrepo Input DATA file: glfspn3.inp Input CONTROL file: glfspn3.inp Output Stock Size file: GlfSPA.naa Output Fishing Mortality file: GlfSPA.faa Ouput Fitted Indices file: GlfSPA.ind Output Diagnostics (this) file: GlfSPA.par Run name: Gulf Spanish-3 Full Index No. index values: Parameters: 8 Mean Squared Error (rss/df) = 53E+ Rsquared = -45 Loglikelihood = -89E+ res from indices = res from curvature =.E+ Program termination OK More details of the run can be found in filefadapt5.run Parameter Estimate S.E. % C.V. F age F age F age F age F age F age F age F age Variances of terminal yr F and survivors Age, SE(F,) CV(F) SE(N,) CV(N) 858E E E E E E E E E E E E E Obs. and pred. indices in objective function 5333E+ 3E+ 44E+ 387E+ 6367E+ 6695E+ 838E+.793E+ 69E+.9778E+.9866E+ 75E+ 388E+.7738E+ 38E+ 6797E+ 98E+ 64E+ 57E+ 988E+ 858E+.9984E+ 556E+ 3E+ 43E+ 4E+ 57E+.963E+ 976E+ 373E+ 985E+ 939E+ 8E+ 56E+ 578E+ 634E+ 443E+ 93E+ 53E+ 3E+ 564E+ 4763E+ 6555E+.7694E+ 9699E+ 35E+ 589E+ 765E+ 73E+.9836E+ 88E+ 9E+ 8746E+ 363E+.93E+ 435E+ 8953E+.786E+ 66E+ 883E+ 897E+.796E+ 8E+ 486E+.999E+ 938E+ 5796E+ 6688E+ 3E+ 9E+ 693E+ 53E+ 836E+ 355E+ 76E+ 574E+ 8739E+.763E+ 64E+ 934E+ 77E+ 758E+.9865E+ 794E E+ 39E+.7945E+ 95E+ 577E E+ 97E+ 57E+ 69E+ 976E+ 5E+ 469E+ 63E+.9754E+ 33E E+ 4636E+ 5E+.9645E+.9943E+.9496E+.773E+ 7774E+.7896E+ 64E+ 7594E+ 56E+.765E+ 75E+.945E+ 365E+ 365E E E+ 6758E+ 39E+ 958E+.7879E+ 7459E+ 66E+ 66E+ 56E+ 574E+ 68E+ 368E+ 455E+.9737E+ 7334E+ 539E+.954E+.9638E+ 5463E E+ 487E+ 443E+ 475E+ 6E+.964E+ 877E+ 6593E+ 76E+ 39E+.786E+ 965E+ 836E+.7579E+ 7E+ 97E+ 497E+ 698E+ 3934E+ 97E+ 5E+ 873E+.756E+ 838E+ 9E+ 636E+ 77E+.7483E+ 53E+ 375E+ 84E+ 56E+ 668E+.796E+ 8E+ 87E+ 94E+ 3689E+.7479E+ 4E+ 95E+.7547E+ 9833E+.7454E+ 4E+.968E+ 648E E+.997E+.9447E+ 6733E+ 47E+ 788E+ 99E+.9356E+ 44E+ 78E+ 67E+ 75E+ 875E+ 497E+ 3E+.9398E+ 99E+ 3E+ 864E+ 975E+ 4736E+ 6587E+ 778E+ 478E+ 657E+ 953E+ 4E+ 483E+ 65E E+ 495E+ 486E+.978E+ 93E+ 399E+ 6749E+.7439E+ 367E+.9386E+ MSAP-3-5 of 8

52 INDEX RESULTS Maximum likelihood weighting for indices Fit results for index = FWC Index Fitted to Beginning Stock Size in BIOMASS Scaled Obj.Function Predicted Residual Scaled resid 85/ / / / / / / / / / / / / / / / / Index ML estimate of the variance: 55 (S.E.: 95) ML estimate of catchability: 68E-6 Pearsons (parametric) correlation: -.83 P= 5 Kendalls (nonparametric) Tau: -.88 P= 46 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / Fit results for index = MRFSS Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 55 (S.E.: 98) ML estimate of catchability: 394E-6 Pearsons (parametric) correlation: 7 P= 495 Kendalls (nonparametric) Tau: -76 P= 47 Selectivity at age from Partial Catches year 3 84/ / / / / / / / / / / / / / / / / /.5 4. Fit results for index = Chart NWF Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / Index ML estimate of the variance:.45 (S.E.: 37) ML estimate of catchability: 3389E-6 Pearsons (parametric) correlation:.943 P=. Kendalls (nonparametric) Tau: P=.9 Selectivity at age from Partial Catches year 84/ / / / / /9 7. Fit results for index = Bycatch GLM Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / Index ML estimate of the variance:.66 (S.E.: 57) ML estimate of catchability: 767E-7 Pearsons (parametric) correlation: P= 646 Kendalls (nonparametric) Tau:.98 P= 98 Selectivity at age from Partial Catches year 84/ / / / / / / / / / / / / / / / / / Fit results for index = TPWD Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / MSAP-3-5 of 8

53 9/ / / / / / / / / / / / Index ML estimate of the variance: 55 (S.E.: 5) ML estimate of catchability: 6553E-6 Pearsons (parametric) correlation: -45 P= 788 Kendalls (nonparametric) Tau: -.85 P= 438 Selectivity at age from Partial Catches year 3 84/ / / / / / / / / / / / / / / / /.9 9. / Fit results for index = SEAMAP Index Fitted to Beginning Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / / / / / / / / / / / / / / / / / / / / / / / / / / / Index ML estimate of the variance: 5 (S.E.:.746) ML estimate of catchability: 7788E-6 Pearsons (parametric) correlation: -66 P= 37 Kendalls (nonparametric) Tau: -.46 P= 4 Selectivity at age from Partial Catches year / / / / / / / / / / / / / / / / / / Index ML estimate of the variance:.688 (S.E.: 63) ML estimate of catchability:.7476e-7 Pearsons (parametric) correlation: 49 P=.35 Kendalls (nonparametric) Tau: 83 P= 4 Selectivities set to. year 84/85. 85/86. 86/87. 87/88. 88/89. 89/9. 9/9. 9/9. 9/93. 93/94. 94/95. 95/96. 96/97. 97/98. 98/99. 99/. Fit results for index = HeadBoat Index Fitted to Mid-Year Stock Size in NUMBERS Scaled Obj.Function Predicted Residual Scaled resid 84/ / / / MSAP-3-53 of 8

54 Table 4. Maximum sustainable yield (MSY) and optimum yield (OY) related values from the Base model and the Full index model for Gulf Spanish mackerel 3 stock evaluation. SS is spawning stock biomass in weight of mature females (million pounds), F values are associated with the fully selected age, and yields are given in millions of pounds. 8% confidence intervals generated from 5 bootstrap projections. MODEL BASE SS MSY F MSY MSY SS OY F OY OY Median low 8% upp 8% Deterministic MODEL Full Index SS MSY F MSY MSY SS OY F OY OY Median low 8% upp 8% Deterministic Table 5. Estimated acceptable biological catch (ABC) in millions of pounds for the Gulf Spanish mackerel 3/4 fishing year under a projected F of F 3%SPR or F 4%SPR from the Base and Full index models evaluated. Probability denotes the likelihood of exceeding the desired F mortality rates. Base Model Full Index Model Probability F 3%SPR F 4%SPR F 3%SPR F 4%SPR 5% Median % lower CI % upper CI MSAP-3-54 of 8

55 Atlantic King Catch by sector and year Atlantic King Yield by sector and year. Commercial Recreational... million fish M Million lbs M Commercial Recreational Figure. Atlantic king mackerel catch and yield by fishing year and sector from 98 through. Atlantic Spanish Catch by sector and year Atlantic Spanish Yield by sector and year million fish M Commercial Recreational Million lbs M Commercial Recreational Figure. Atlantic Spanish mackerel catch and yield by fishing year and sector from 984 through Gulf Spanish Catch by sector and year Gulf Spanish Yield by sector and year million fish Commercial Recreational Million lbs.. Commercial Recreational Figure 3. Gulf Spanish mackerel catch and yield by fishing year and sector from 984 through MSAP-3-55 of 8

56 5 Million fish 5.5 Million fish FLE NC SCGA FLW N_NC FLE NC SCGA FLW N_NC Figure 4. Atlantic king mackerel catch by state, fishing year and sector: commercial (left) and recreational (right) from 98 through. Million fish FLE NC N_NC SCGA Million fish NC FLE N_NC SCGA Figure 5. Atlantic Spanish mackerel catch by state, fishing year and sector: commercial (left) and recreational (right) from 984 through Million fish FLW ALMS TX LA Million fish FLW ALMS TX LA Figure 6. Gulf Spanish mackerel catch by state, fishing year and sector: commercial (left) and recreational (right) from 984 through MSAP-3-56 of 8

57 Gulf Spanish mackerel shrimp bycatch estimates 6 Million fish 8 4 Dta lgn 3 GLM 3 Dta lgn 98 GLM Figure 7 Comparison of 998 and 3 estimates of Spanish mackerel bycatch in the shrimp trawl fishery of the US Gulf of Mexico. Estimates from the GLM (base) and delta lognormal models Atlantic King Catch by Age Percent Distribution Age Age Age Age 3 Age 4 Age 5 Age 6 Age 7 Age 8 Age 9 Age Age + % % 4% 6% 8% % Figure 8. Proportion of total catch by age and year for Atlantic king mackerel from 98 through fishing year. MSAP-3-57 of 8

58 Atlantic Spanish Catch by Age Percent Distribution Age Age Age Age 3 Age 4 Age 5 Age 6 % % 4% 6% 8% % Figure 9. Proportion of total catch by age and year for Atlantic Spanish mackerel from 984 through fishing year. Gulf Spanish Catch by Age Percent Distribution Age Age Age Age 3 Age 4 Age 5 Age 6 Age 7+ % % 4% 6% 8% % Figure. Proportion of total catch by age and year for Gulf Spanish mackerel from 984 through fishing year. MSAP-3-58 of 8

59 NC Commercial FL WC.8.6 Scaled CPUE mean overlap years.6.4. Index 3 Index 998 Scaled CPUE mean overlap years.4. Index 3 Index MRFSS HeadBoat 3.5 Scaled CPUE mean overlap years.5.5 Index 3 Index 998 Scaled CPUE mean overlap years.5 Index 3 Index SEAMAP.5 Scaled CPUE mean overlap years.5 Index 3 Index Figure. Comparison of standardized indices of abundance for the Atlantic king mackerel used in 998 stock assessments and correspondent ones available for 3 analysis. MSAP-3-59 of 8

60 King Mackerel Atlantic stock INDEX SCALED TO MEAN OVERLAP YEARS HeadBoat MRFSS FloridaWC NC Com SEAMAP NC ComOld Figure. Standard indices of abundance of Atlantic king mackerel available for VPA tuning analysis in 3. Indices are scaled to their mean for the overlapping years. MSAP-3-6 of 8

61 FL WC HeadBoat Scaled CPUE mean overlap years 3 Index 3.5 Index Scaled CPUE mean overlap years Index 3 Index FL MRFSS NC MRFSS.8.8 Scaled CPUE mean overlap years.6.4. Index 3 Index Scaled CPUE mean overlap years.6.4. Index 3 Index SEAMAP Scaled CPUE mean overlap years.6.4. Index 3 Index Figure 3. Comparison of standardized indices of abundance for the Atlantic Spanish mackerel used in 998 stock assessments and correspondent ones available for 3 analysis. MSAP-3-6 of 8

62 Spanish mackerel Atlantic Stock HeadBoat MRFSS FloridaWC () 3.5 NCPamlico NC Com SEAMAP Index scaled to mean overlap years Figure 4. Standard indices of abundance of Atlantic Spanish mackerel available for VPA tuning analysis in 3. Indices are scaled to their mean for the overlapping years. MSAP-3-6 of 8

63 Gulf Spanish Shrimp bycatch lenght frequency distributions by year Fork length (mm) Gulf Spanish Shrimp bycatch lenght frequency distributions by quarter Apr-Jun Jan-Mar Jul-Sep Oct-Dec Fork length (mm) Figure 5. Size frequency distribution of Spanish mackerel bycatch from the US Gulf shrimp fishery by year and season (Data provided by NMFS SEFSC Galveston lab). MSAP-3-63 of 8

64 FL WC MRFSS.8.6 Index 3.8 Index 3 Scaled CPUE mean overlap yrs.4. Index 998 Scaled CPUE mean overlap yrs.6.4. Index CHART NWFL BYCATCH.5.6 Scaled CPUE mean overlap yrs.5 Index 3 Index 998 Scaled CPUE mean overlap yrs.4. Index 3 Index Tx PWD Scaled CPUE mean overlap yrs Index 3 Index Figure 5a. Comparison of standardized indices of abundance for the Gulf Spanish mackerel used in 998 stock assessments and correspondent ones available for 3 analysis. MSAP-3-64 of 8

65 Spanish mackerel Gulf Stock Headboat MRFSS TxPWD FloridaWC 3.5 Bycatch GLM Bycatch Delta SEAMAP ChartNWF Index scaled to mean overlap years Figure 6. Standard indices of abundance of Gulf Spanish mackerel available for VPA tuning analysis in 3. Indices are scaled to their mean for the overlapping years. MSAP-3-65 of 8

66 Atl_King-3 Stock Recruitment Relationship Million of recruits (Age ) Trillions of eggs Not used Used Atl Spanish Stock Recruitment Relationship Million of recruits (Age ) Mature females biomass (million lbs) Used Not used Gulf Spanish-3 Stock Recruitment Relationship Million of recruits (Age ) Mature females biomass (million lbs) Used Not used Figure 7. Deterministic stock recruitment relationship under the two line model for Atlantic king, Spanish king and Gulf king mackerel. MSAP-3-66 of 8

67 F at Age F at Age F at Age F at Age F at Age F at Age F at Age F at Age F at Age F at Age F at Age F at Age Overall F 3 Base 3 Full Index Figure 8. Atlantic king mackerel estimates of F mortality by age from the Base and Full index models. MSAP-3-67 of 8

68 N Age N Age N Age Millions fish Millions fish Millions fish N Age 3 N Age 4 N Age 5 Millions fish Millions fish Millions fish N Age 6 N Age 7 N Age 8 Millions fish Millions fish Millions fish N Age 9 N Age N Age Millions fish.5 Millions fish 5 Millions fish Stock Size 4 3 Base 3 Full Index Millions fish Figure 9. Atlantic king mackerel estimates of stock size by age from the Base and Full index models MSAP-3-68 of 8

69 NC Com Old Base Model 3.8 Full Index Model NC Com New.6.4. Full Index Model FWC MRFSS Headboat Seamap SA Figure. Atlantic king mackerel predicted (solid lines) and standard index (diamonds) from the tuned VPA Base and Full index models. MSAP-3-69 of 8

70 Stock N Age - Stock N Age - Stock N Age 3-6 Million fish Million fish Million fish Stock N Age 7- Stock N Age - Average F Age 3-6 Million fish Million fish Average F Age 7- Average F Age - Stock Biomass Age Million pounds Stock Biomass Age 3-6 Stock Biomass Age 7- Million pounds Million pounds Figure. Comparison of Atlantic king mackerel population trends estimated by the Base model (solid lines) with 8% confidence intervals and the Full model index (open square line). MSAP-3-7 of 8

71 Stock N Age - Stock N Age - Stock N Age 3-6 Million fish Million fish Million fish Stock N Age 7- Stock N Age - Average F Age Million fish 3 Million fish Average F Age 7- Average F Age - Stock Biomass Age Million pounds Stock Biomass Age 3-6 Stock Biomass Age 7- Million pounds Million pounds Figure. Atlantic king mackerel population trends with 8% confidence intervals from the Full Index model (solid lines). For comparison, results from the 998 SA are also show (square marker line) MSAP-3-7 of 8

72 NC Com Old NC Com New Ln(liklhd) Ln(liklhd) FWC MRFSS Ln(liklhd) Ln(liklhd) Headboat Seamap SA Ln(liklhd) Ln(liklhd) Figure 3. Jacknife estimates for tuned VPA Full index model fit Atlantic king mackerel. MSAP-3-7 of 8

73 BASE MODEL Static SPR BASE MODEL Unweighted SPR FULL INDEX MODEL Static SPR FULL INDEX M ODEL Unweighted SPR Figure 4. Comparison of static and transitional un-weighted SPR from the VPA Base model and the VPA Full index model for Atlantic king mackerel 3 stock evaluation. Comparison bench marks Atlantic King 3 Comparison bench marks Atlantic King Spawning stock (trillion eggs) SS MSY Base SS MSY Full Index SS OY Base SS OY Full Index Million lbs MSY Base MSY Full Index OY Base OY Full Index Comparison bench marks Atlantic King 3 5 F Multiplier 5 5 F MSY Base F MSY Full Index F OY Base F OY Full Index Figure 5. Atlantic king mackerel benchmarks 3 assessment. Spawning stock (SS) biomass, MSY, OY, and correspondent fishing mortality rates from the two models. MSAP-3-73 of 8

74 5 Histrogram of F/Fmsy ratio distributions Histrogram of SS/SS msy ratio distributions MODEL BASE More Figure 6. Frequency distribution of Atlantic king F /F MSY and SS /SS MSY ratios of 5 boostraps for the Base model. 5 Histrogram of F/Fmsy ratio distributions Histrogram of SS/SS msy ratio distributions MODEL Full Index More Figure 7. Frequency distribution of Atlantic king F /F MSY and SS /SS MSY ratios of 5 bootstraps for the Full Index model. King Atlantic F year ratio MODEL BASE King Atlantic F year ratio MODEL Full Index F / F msy. F / F msy SS / SS msy SS / SS msy Figure 8. Phase plots of 5 bootstraps for the Base and Full index models. The upper solid line denotes the MFMT, the vertical dashed line denotes MSST, and the lower solid line denotes the OY control rule. The deterministic run corresponds to the larger diamond marker. MSAP-3-74 of 8

75 Atlantic King Group Base pdf of Yield in 3 Cumulative probability.9.7 F 3%SPR F 4%SPR 5 5 Yield (millions of lbs) in 3 Atlantic King Group Full Index pdf of Yield in 3 Cumulative probability.9.7 F 3%SPR F 4%SPR 5 5 Yield (millions of lbs) in 3 Figure 9. Frequency distribution of 5 bootstraps range of ABC based on probability of F exceeding F3%SPR and F4%SPR in the 3/4 fishing year for Atlantic king mackerel under the two models. Vertical solid lines represent percentile; dashed lines represent and.9 percentiles of the cumulative distributions. MSAP-3-75 of 8

76 F at Age F at Age F at Age F F F F at Age 3 F at Age 4 F at Age F F F F at Age 6 Total Fishing mortality. 5 5 F F multiplier Full Index 3 Base Figure 3. Atlantic Spanish mackerel estimates of F mortality by age from the Base and Full index models. MSAP-3-76 of 8

77 N Age N Age N Age Millions of fish Millions of fish Millions of fish N Age 3 N Age 4 N Age 5 Millions of fish Millions of fish Millions of fish N Age 6 Stock Size estimated Millions of fish Millions of fish Full index 3 Base Figure 3. Atlantic Spanish mackerel estimates of stock size by age from the Base and Full index models. MSAP-3-77 of 8

78 FWC Headboat.5.5 Base Full Index MRFSS SeaMap SA NCPamlicoSS NC Comm Figure 3. Atlantic Spanish mackerel predicted (solid lines) and standard index (diamonds) from the tuned VPA Base and Full index models. MSAP-3-78 of 8

79 Stock size age:- Stock size age:- Stock size age:-4 Millions fish Millions fish Millions fish Stock size age:-6 Stock size age:5-6 Average F age: Millions fish Millions fish.5 F Average F age:-4 Average F age:5-6 Average F age: F Stock Biomass age:- F Stock Biomass age:-6 F Annual Change Stock Biomass -6 Millions lbs Millions lbs Millions lbs Figure 33. Comparison of Atlantic Spanish mackerel population trends estimated by the Base model (solid lines) with 8% confidence intervals and by the Full model index (open square line). MSAP-3-79 of 8

80 Stock size age:- Stock size age:- Stock size age:-4 Millions fish Millions fish Millions fish Stock size age: Stock size age: Average F age: Average F age:-6 Average F age:5-6 Average F age: Stock Biomass age: Stock Biomass age: Annual Change Stock Biomass -6 Millions lbs Millions lbs Millions lbs Figure 34. Atlantic Spanish mackerel population trends with 8% confidence intervals from the Full Index model (solid lines). For comparison, results from the 998 SA are also shown (square marker line). MSAP-3-8 of 8

81 FWC Headboat Ln(liklhd) Ln(liklhd) MRFSS SeaMap Ln(liklhd) Ln(liklhd) NCPamlicoSS NC Comm Ln(liklhd) Ln(liklhd) Figure 35. Jacknife estimates for tuned VPA Full index model fit Atlantic Spanish mackerel. MSAP-3-8 of 8

82 Static SPR Unweighted SPR % SPR % SPR BASE MODEL BASE MODEL Static SPR Unweighted SPR % SPR % SPR FULL INDEX MODEL FULL INDEX MODEL Figure 36. Comparison of static and transitional un-weighted SPR from the VPA Base model and the VPA Full index model for Atlantic Spanish mackerel 3 stock evaluation. Comparison benchmarks Atlantic Spanish 3 Comparison benchmarks Atlantic Spanish Female biomass million lbs SS MSY Base SS MSY Full Index SS OY Base SS OY Full Index Million lbs MSY Base MSY Full Index OY Base OY Full Index Comparison benchmarks Atlantic Spanish 3 5 F Multiplier 5 5 F MSY Base F MSY Full Index F OY Base F OY Full Index Figure 37 Atlantic Spanish mackerel benchmarks 3 assessment. Spawning stock (SS) biomass, MSY, OY, and correspondent fishing mortality rates from the two models evaluated. MSAP-3-8 of 8

83 8 Histrogram of F/Fmsy ratio distributions Histrogram of SS/SS msy ratio distributions MODEL BASE Figure 38. Frequency distribution of Atlantic Spanish F /F MSY and SS /SS MSY ratios of 5 bootstraps for the Base model. 8 Histrogram of F/Fmsy ratio MODEL Full Index Histrogram of SS/SSmsy ratio distributions MODEL Full Index Figure 39. Frequency distribution of Atlantic Spanish F /F MSY and SS /SS MSY ratios of 5 bootstraps for the Full Index model. Atlantic Spanish F year ratio MODEL BASE Atlantic Spanish F year ratio MODEL Full Index.5.5 F / F msy.5 F / F msy SS / SS msy.5.5 SS / SS msy 3 Figure 4. Phase plots of 5 bootstraps for the Base and Full index models. The upper solid line denotes the MFMT, the vertical dashed line denotes MSST, and the lower solid line denotes the OY control rule. The deterministic run corresponds to the larger diamond marker. MSAP-3-83 of 8

84 Atlantic Spanish Base pdf of Yield in 3 Cumulative probability.9.7 F 3%SPR F 4%SPR 5 5 Yield (millions of lbs) in 3 Atlantic Spanish Full Index Model pdf of Yield in 3 Cumulative probability.9.7 F 3%SPR F 4%SPR 5 5 Yield (millions of lbs) in 3 Figure 4. Frequency distribution of 5 bootstraps range of ABC based on probability of F exceeding F 3%SPR and F 4%SPR in the 3/4 fishing year for Atlantic Spanish mackerel under the two models. Vertical solid lines represent percentile; dashed lines represent and.9 percentiles of the cumulative distributions. MSAP-3-84 of 8

85 F at Age F at Age F at Age F F F F at Age 3 F at Age 4 F at Age F F F F at Age 6 F at Age F F Total Fishing mortality.75 5 Full Index Model 3 Base Model 5 F multiplier Figure 4. Gulf Spanish mackerel estimates of F mortality by age from the Base and Full index models. MSAP-3-85 of 8

86 N Age N Age N Age Millions of fish Millions of fish Millions of fish N Age 3 N Age 4 N Age Millions of fish Millions of fish..5. Millions of fish N Age 6 N Age 7+ Millions of fish Millions of fish Stock Size estimated Millions of fish 6 6 Full Index 3 3 BASE Figure 43. Gulf Spanish mackerel estimates of stock size by age from the Base and Full index models. MSAP-3-86 of 8

87 FWC MRFSS Full Index Base Model Chart NWF Bycatch GLM TPWD SEAMAP HeadBoat Figure 44. Gulf Spanish mackerel predicted (solid lines) and standard index (diamonds) form the tuned VPA Base and Full index models. MSAP-3-87 of 8

88 Stock size age:- Stock size age:- Stock size age: Millions fish 5 Millions fish 8 6 Millions fish Stock size age:5-7 Stock size age:-7 Average F age: Millions fish Average F age:-4 Millions fish Average F age:5-7 F Average F age: F F F Stock Biomass age:- Stock Biomass age:-7 Annual Change Stock Biomass -7 Millions lbs Millions lbs Millions lbs Figure 45. Comparison of Gulf Spanish mackerel population trends estimated by the Base model (solid lines) with 8% confidence intervals and the Full index model (open square line). MSAP-3-88 of 8

89 Stock size age:- Stock size age:- Stock size age: Millions fish 5 Millions fish 8 6 Millions fish Full Index SA Model Stock size age:5-7 Stock size age:-7 Average F age: Average F age:-4 Average F age:5-7 Average F age: Millions lbs Stock Biomass age: Millions lbs Stock Biomass age: Millions lbs Annual Change Stock Biomass Figure 46. Gulf Spanish mackerel population trends with 8% confidence intervals from the Full Index model (solid lines). For comparison, results from the 998 SA are also shown (square marker line). MSAP-3-89 of 8

90 FWC MRFSS Ln(liklhd) Ln(liklhd) Chart NWF Bycatch GLM Ln(liklhd) Ln(liklhd) TPWD SEAM AP Ln(liklhd) Ln(liklhd) HeadBoat 6 58 Ln(liklhd) Figure 47. Jacknife estimates for tuned VPA Full index model fit Gulf Spanish mackerel. MSAP-3-9 of 8

91 Gulf Spanish Base Static SPR Gulf Spanish Base Unweighted SPR Gulf Spanish Full Index Static SPR Gulf Spanish Full Index Unweighted SPR.7 FULL INDEX MODEL FULL INDEX MODEL Figure 48. Comparison of static and transitional unweighted SPR from the VPA Base model and the VPA Full Index model for Gulf Spanish mackerel 3 stock evaluation. Comparison bench marks Gulf Spanish 3 Comparison bench marks Gulf Spanish Matured females (million lbs) SS MSY Base SS MSY Full Index SS OY Base SS OY Full Index Million lbs MSY Base MSY Full Index OY Base OY Full Index Comparison bench marks Gulf Spanish F Multiplier F MSY Base F MSY Full Index F OY Base F OY Full Index Figure 49. Gulf Spanish mackerel benchmarks 3 assessment. Spawning stock (SS) biomass, MSY, OY, and correspondent fishing mortality rates from the two models. MSAP-3-9 of 8

92 6 Histrogram of F/Fmsy ratio distributions Histrogram of SS/SS msy ratio distributions MODEL BASE Figure 5. Frequency distribution of Gulf Spanish F /F MSY and SS /SS MSY ratios of 5 bootstraps for the Base model. 5 Histrogram of F/Fmsy ratio MODEL Full Index Histrogram of SS/SSmsy ratio distributions MODEL Full Index Figure 5. Frequency distribution of Gulf Spanish F /F MSY and SS /SS MSY ratios of 5 bootstraps for the Full Index model. Gulf Spanish MODEL BASE Gulf Spanish MODEL Full Index F / F msy. F / F msy SS / SS msy SS / SS msy Figure 5. Phase plots of 5 bootstraps for the Base and Full Index models. The upper solid line denotes the MFMT, the vertical dashed line denotes MSST, and the lower solid line denotes the OY control rule. The deterministic run corresponds to the large diamond marker. MSAP-3-9 of 8

93 Gulf Spanish Group Base pdf of Yield in 3 Cumulative probability.9.7 F 3%SPR F 4%SPR 5 5 Yield (millions of lbs) in 3 Gulf Spanish Full Index Model pdf of Yield in 3 Cumulative probability.9.7 F 3%SPR F 4%SPR 5 5 Yield (millions of lbs) Figure 53. Frequency distribution of 5 bootstraps range of ABC based on probability of F exceeding F3%SPR and F4%SPR in the 3/4 fishing year for Gulf Spanish mackerel under the two models. Vertical solid lines represent percentile; dashed lines represent and.9 percentiles of the cumulative distributions. MSAP-3-93 of 8

94 Atlantic King Stock Age Atlantic King Stock Age Atlantic King Stock Age Millions Millions Millions Atlantic King Stock Age 3 Atlantic King Stock Age 4 Atlantic King Stock Age 5 Millions Millions Millions Atlantic King Stock Age 6 Atlantic King Stock Age 7 Atlantic King Stock Age 8 Millions Millions Millions Millions Atlantic King Stock Age Millions Atlantic King Stock Age Millions Atlantic King Stock Age Atlantic King Stock Age - 3 Atlantic King Stock Age 4-8 Atlantic King Stock Age 9+ Millions Millions Figure 54. Atlantic king retrospective analysis stock size estimation. Millions MSAP-3-94 of 8

95 Atlantic King F Age Atlantic King F Age Atlantic King F Age Atlantic King F Age 3 Atlantic King F Age 4 Atlantic King F Age Atlantic King F Age Atlantic King F Age Atlantic King F Age Atlantic King F Age Atlantic King F Age Atlantic King F Age Atlantic King F Age -+ Atlantic King F Age - 3 Atlantic King F Age Figure 55. Atlantic king retrospective analysis F mortalities by age estimation. MSAP-3-95 of 8

96 Millions Stock Age Spanish Atlantic Millions Stock Age Spanish Atlantic Millions Stock Age Spanish Atlantic Millions Stock Age 3 Spanish Atlantic Millions Stock Age 4 Spanish Atlantic Millions Stock Age 6+ Spanish Atlantic Millions Stock Age -4 Spanish Atlantic Millions Stock Age -6+ Spanish Atlantic Millions Stock Age 4-6+ Spanish Atlantic Stock Age 5 Spanish Atlantic Millions Figure 56. Atlantic Spanish retrospective analysis stock size estimation by sequentially removing the last year of data from the 984- catch at age and indices of abundance. The retrospective period covers 996- years. MSAP-3-96 of 8

97 F Age Spanish Atlantic F Age Spanish Atlantic F Age Spanish Atlantic F Age 3 Spanish Atlantic. F Age 4 Spanish Atlantic. F Age 5 Spanish Atlantic F Age 6+ Spanish Atlantic F Age -4 Spanish Atlantic F Age -6+ Spanish Atlantic F Age 4-6+ Spanish Atlantic Figure 57. Atlantic Spanish retrospective analysis F mortality rates by age estimation. MSAP-3-97 of 8

98 Gulf Spanish Stock Age Gulf Spanish Stock Age Gulf Spanish Stock Age Millions 5 Millions 8 6 Millions Gulf Spanish Stock Age 3 Gulf Spanish Stock Age 4 Gulf Spanish Stock Age 5 Millions Millions Millions Gulf Spanish Stock Age 7 Gulf Spanish Stock Age Millions Millions Gulf Spanish Stock Age 4-7+ Gulf Spanish Stock Age -4 Gulf Spanish Stock Age - 7+ Millions Millions Millions Figure 58. Gulf Spanish retrospective analysis stock size estimation. MSAP-3-98 of 8

99 Gulf Spanish F Age Gulf Spanish F Age Gulf Spanish F Age Gulf Spanish F Age 3 Gulf Spanish F Age 4 Gulf Spanish F Age Gulf Spanish F Age 6 Gulf Spanish F Age Gulf Spanish F Age 4-7+ Gulf Spanish F Age -4 Gulf Spanish F Age Figure 59. Gulf Spanish retrospective analysis F mortality rates by age estimation. MSAP-3-99 of 8

100 Stock size age:- Stock size age:- Stock size age:-4 Millions fish Millions fish Millions fish Stock size age:5-7 Stock size age:-7 Average F age: Average F age:-4 Average F age:5-7 Average F age: Millions lbs Stock Biomass age: Millions lbs Stock Biomass age: Millions lbs Annual Change Stock Biomass Figure 6. Gulf Spanish sensitivity analysis: Comparison of population trends estimated by the Bycatch Delta logn models (solid lines) with 8% confidence intervals and the Full index model (open square line). MSAP-3- of 8

101 Gulf Spanish Byc Delta Unweighted SPR Gulf Spanish Byc Delta Static SPR 5 BYC DELTA LOGN BYC DELTA LOGN Figure 6. Static and transitional unweighted SPR from the VPA Bycatch Delta logn model for Gulf Spanish mackerel 3 stock evaluation (solid lines). For comparison, equivalent values are plotted for the Full Index model (open square line). Comparison bench marks Gulf Spanish 3 Comparison bench marks Gulf Spanish Matured females (million lbs) SS MSY Bas e SS MSY Full Index SS MSY Byc Delta LogN SS OY Bas e SS OY Full Index SS OY Byc Delta LogN Million lbs MSY Base MSY Full Index MSY Byc De lta LogN OY Base OY Full Index OY Byc Delta LogN Comparison bench marks Gulf Spanish F Multiplier F MSY Base F MSY Full Index F MSY Byc F OY Base Delta LogN F OY Full Index F OY Byc Delta LogN Figure 6. Gulf Spanish mackerel benchmarks 3 SA. Comparison of estimates from the Base model, Full index model and the Bycatch Delta logn model reference points. MSAP-3- of 8

102 Stock N Age - Stock N Age - Stock N Age 3-6 Million fish Million fish Million fish Stock N Age 7- Stock N Age - Average F Age 3-6 Million fish Million fish Average F Age 7- Average F Age - Stock Biomass Age Million pounds Stock Biomass Age 3-6 Stock Biomass Age 7- Million pounds Million pounds Figure 63. Sensitivity Analysis Atlantic king mackerel. Comparison of population trend estimates from the Full index model (open square line) and the model without the Florida FWC index of abundance (solid lines) with 8% confidence intervals. MSAP-3- of 8

103 Stock N Age - Stock N Age - Stock N Age 3-6 Million fish Million fish Million fish Stock N Age 7- Stock N Age - Average F Age 3-6 Million fish Million fish Average F Age 7- Average F Age - Stock Biomass Age Million pounds Stock Biomass Age 3-6 Stock Biomass Age 7- Million pounds Million pounds Figure 64. Sensitivity Analysis Atlantic king mackerel. Comparison of population trend estimates from the Full index model (open square line) and the model without the MRFSS index of abundance (solid lines) with 8% confidence intervals. MSAP-3-3 of 8

104 Stock N Age - Stock N Age - Stock N Age 3-6 Million fish Million fish Million fish Stock N Age 7- Stock N Age - Average F Age 3-6 Million fish Million fish Average F Age 7- Average F Age - Stock Biomass Age Million pounds Stock Biomass Age 3-6 Stock Biomass Age 7- Million pounds Million pounds Figure 65. Sensitivity Analysis Atlantic king mackerel. Comparison of population trend estimates from the Full index model (open square line) and the model without the North Carolina Commercial (New) index of abundance (solid lines) with 8% confidence intervals. MSAP-3-4 of 8

105 Stock N Age - Stock N Age - Stock N Age 3-6 Million fish Million fish Million fish Stock N Age 7- Stock N Age - Average F Age 3-6 Million fish Million fish Average F Age 7- Average F Age - Stock Biomass Age Million pounds Stock Biomass Age 3-6 Stock Biomass Age 7- Million pounds Million pounds Figure 66. Sensitivity Analysis Atlantic king mackerel. Comparison of population trend estimates from the Full index model (open square line) and the model without the North Carolina Commercial (Old) index of abundance (solid lines) with 8% confidence intervals. MSAP-3-5 of 8

106 Stock N Age - Stock N Age - Stock Biomass Age Millions 5 remfwc remmrfss remnccomnew remnccomold Full Index Stock N Age 3-6 Average F Age 3-6 Stock Biomass Age Millions remfwc remmrfss remnccomnew remnccomold 5 Full Index Stock N Age 7- Average F Age 7- Stock Biomass Age Millions remfwc remmrfss remnccomnew 5 remnccomold Full Index Stock N Age - Average F Age Figure 67. Sensitivity Atlantic king mackerel. Population trend estimators from the Full index model (solid line) and the models with the removal of a complete indices of abundance. MSAP-3-6 of 8

107 Catch Prop by age-year Commercial Catch Prop by age-year Recreational All 5 5 Percent Avg 8-96 Avg 97- Percent Avg 8-96 Avg Catch Prop by age-year Recreational No Headboat Catch Prop by age-year HeadBoat 5 5 Percent Avg 8-96 Avg 97- Percent Avg 8-96 Avg Figure 68. Atlantic King mackerel comparison of directed catch distribution by age and sector. Solid lines represent average of years (blue) and average of 997- year (red). Catch Prop by age-year Commercial Catch Prop by age-year Rec All percent percent Prop by age-year Rec No HeadBoat Prop by age-year HeadBoat.7 percent percent Figure 69. Atlantic Spanish mackerel comparison of directed catch distribution by age and sector. Solid lines represent average of years (blue) and average of 997- year (red). MSAP-3-7 of 8

108 Prop by age-year Commercial Prop by age-year Recreational all.7 Percent Percent Prop by age-year Recreational no HeadB Prop by age-year HeadBoat.7 Percent Percent Figure 7. Gulf Spanish mackerel comparison of directed catch distribution by age and sector. Solid lines represent average of years (blue) and average of 997- year (red). MSAP-3-8 of 8

109 NMFS SEFSC Miami SFD/3-8 Appendix Appendix A. General Description of SEAMAP Plankton Surveys and Methods: Ichthyoplankton samples have been collected annually since 98 during Southeast Area Monitoring and Assessment Program (SEAMAP) surveys conducted by the National Marine Fisheries Service in cooperation with the states of Florida, Alabama, Mississippi, and Louisiana. Samples are taken during two, dedicated plankton surveys, one in the open Gulf in spring (mid April to early June) and the other over the continental shelf in late summer and early fall (late August to mid October). Plankton samples are also taken ( piggybacked ) during summer and fall shrimp/groundfish surveys in June/July and October/November. In addition to the standard SEAMAP time series of plankton collections there have been collections taken during winter surveys of open Gulf waters; surveys conducted by individual states (Louisiana Seasonal Trawl survey); and special projects associated with specific habitats and species such as the Reef Fish and Squid/Butterfish surveys (Table i.e. mackereleffort.xls). Plankton samples are taken following standard SEAMAP collection procedures (see SEAMAP Field Methods Manual). The water column is sampled with oblique tows from near bottom (or a maximum depth of m) to the surface using a 6-cm bongo net with 33 (35) mm mesh nets. The upper m of the water column is sampled with a X single or double neuston net frame with.947 (.95) mm mesh net(s) towed at the surface for minutes. Non-standard gear has been used to collect plankton samples from smaller vessels operated by the states and are coded as such in the database. Most standard SEAMAP survey stations are located 3 nautical miles apart in a fixed grid and sampled at all times of day or night. Samples have been taken at stations that do not conform to the standard 3 mile grid and these are not as yet coded as such in the database. Catches of larvae from bongo nets are standardized to account for sampling effort and expressed as number of larvae under m of sea surface. This is accomplished by dividing the number of larvae of each taxon caught in a sample by the volume of water filtered during the tow; and than multiplying the resultant by the maximum depth (m) of the tow and the factor. Catches of larvae from neuston nets are standardized to account for sampling effort and expressed as number of larvae per min tow. General description of king and Spanish mackerel datasets: Annual mean abundance and occurrence of mackerel larvae are calculated only from the catches in 6-cm bongo net samples taken during the two sampling periods that encompass the king and Spanish mackerel spawning season in the Gulf of Mexico: June and July, and late-august to mid-october (Table ). Samples used in annual estimates are collected on both state and federal cruises. Since 98 the number of samples taken each year during SEAMAP summer shrimp/groundfish surveys has typically ranged from 3 to 76 samples. In 998 only samples were collected due to vessel breakdowns and severe weather. The summer survey area includes the continental shelf and coastal waters west of 88 W longitude; although in the earliest years of the time series (98 to 988) sampling was conducted further east off northwest Florida. Samples from late August to mid-october are taken during the SEAMAP fall plankton survey which only became a Gulfwide survey of continental shelf and coastal waters between Brownsville, Texas and south Florida in 986. This survey has produced from 8 to 5 samples per year since 986; however, 4 plankton samples taken during the Louisiana seasonal trawl survey in September 985 are included in the estimate of mean abundance and occurrence for that year. In 998 only 35 samples were collected during this timeframe due to vessel breakdowns and severe weather. Mesh size change in database does not represent an actual change in gear but only a change in the accuracy at which plankton mesh aperture size can be measured by the manufacturer.

110 Appendix NMFS SEFSC Miami SFD/3-8 Appendix Biological Program Documentation Program 95 Pamlico Sound Survey Masterfile: NER.NMA.NMA-.JUVENILE Biologist: Tina Moore

111 I. General Description A. Overview Program 95 Narrative Pamlico Sound Survey Prepared by: Tina Moore NMFS SEFSC Miami SFD/3-8 Appendix The survey was initially designed to provide a long term fishery-independent database for the waters of the Pamlico Sound, eastern Albemarle Sound and the lower Neuse and Pamlico rivers. However, in 99 the Albemarle Sound sampling in March and December was eliminated, and sampling occurs only in the Pamlico Sound and associated rivers and bays in June and September (Figure ). The survey is now called the Pamlico Sound Survey. Division of Marine Fisheries Biological Program Documentation F:\Shared\DMF\Bio_Pgms\Drafts\PGM_95 4/3/3 Page 3

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