diff --git a/doc/data/figcapold.csv b/doc/data/figcapold.csv deleted file mode 100644 index 0a427c1..0000000 --- a/doc/data/figcapold.csv +++ /dev/null @@ -1,75 +0,0 @@ -name,no,label,cap,Alt,Filename -catch.ppdf,1,catch,Pollock catch estimates (t) from the Eastern Bering Sea by season and region. The A-season is defined as from Jan-May and B-season from June-October.,Cumulative catch by year and season and area, -catch_sex.pdf,2,catch_sex,Estimate of EBS pollock catch numbers by sex for the A season (January-May) and B seasons (June-October) and total.,, -catch_distn_a.png,3,catch_distn_a,"EBS pollock catch distribution during A-season, 2017--2019. Column height is proportional to total catch.",, -cpue_aseason.png,4,aseas_cpue,A-season EBS fleet-wide nominal pollock catch (kg) per hour of fishing recorded by NMFS scientific observers.,, -catchp.png,5,prop_a_season,"Proportion of the annual EBS pollock TAC by month during the A-season, 2000--2019. The higher value observed since 2017 was due to Amendment 110 of the FMP to allow greater flexibility to avoid Chinook salmon.",, -catch_distn_b.png,6,catch_distn_b,"EBS pollock catch distribution during B-season, 2017--2019. Column height is proportional to total catch. Note that directed fishery for pollock generally is finished prior to October; the labels are indicative full-year catches.",, -cpue_bseason.png,7,bseas_cpue,B-season EBS fleet-wide nominal pollock catch (kg) per hour of fishing recorded by NMFS scientific observers.,, -roe.pdf,8,roe,"EBS pollock roe production in A and B seasons , 2000-2019.",, -fleet_dispersal.png,9,fleet_dispersal,"Estimated mean daily distance between operations, 2000-2019.",, -catage.png,10,catage,EBS pollock fishery estimated catch-at-age data (in number) for 1992--2018. Age 10 represents pollock age 10 and older. The 2008 year-class is shaded in green.,, -bts_biom.pdf,11,bts_biom,Bottom-trawl survey biomass estimates with error bars representing 1 standard deviation (for design-based and density-dependent correction method) for EBS pollock. ,, -bts_temp.pdf,12,bts_temp,Bottom and surface temperatures for the Bering Sea from the NMFS summer bottom-trawl surveys (1982--2018). Dashed lines represent mean values. ,, -bts_temp_cpue.pdf,13,bts_temp_cpue,EBS pollock CPUE (shades = relative kg/hectare) and bottom temperature isotherms in degrees C; from the bottom trawl survey data 2011--2018. ,, -bts_3d.png,14,bts_3d,Bottom trawl survey pollock catch in kg per hectare for 2017 - 2019. Height of vertical lines are proportional to station-specific pollock densities by weight (kg per hectare) with constant scales for all years (red stars indicate tows where pollock were absent from the catch). ,, -bts_age_comp.png,15,bts_age,"Pollock abundance levels by age and year as estimated directly from the NMFS bottom-trawl surveys (1990--2019). The 2006,2008, and 2012 year-classes are shaded differently.",, -at_age.png,16,at_age,Pollock abundance at age estimates from the AT survey comparing the estimates based primarily on BTS age data used last year and the updates for this year's assessment.,, -vastage.png,17,vastage,Pollock abundance levels by age and year as estimated directly from the NMFS bottom-trawl surveys (1990--2019) using standard 'design-based' (DB) and VAST approaches.,, -fsh_wtage_comb.pdf,20,fsh_wtage_comb,"Recent fishery average weight-at-age anomaly (relative to mean) by strata for ages 3--10, 2014--2018. Vertical shape reflects uncertainty in the data (wider shapes being more precise), colors are consistent with cohorts.",, -fsh_wtage_strata,21,fsh_wtage_strata,"Fishery average weight-at-age anomaly (relative to mean) across strata and combined for all ages (3--10), and available years (1991--2017). Vertical shape reflects uncertainty in the data (wider shapes being more precise), colors are consistent with cohorts.",, -,22,fsh_wtage_strata_yr,"Recent fishery average weight-at-age anomaly (relative to mean) by strata for ages 3--10, 2014--2018. Vertical shape reflects uncertainty in the data (wider shapes being more precise), colors are consistent with cohorts.",, -,23,fsh_lw_month,EBS pollock fishery body mass (given length) anomaly (standardized by overall mean body mass at each length) by month based on some over 700 thousand fish measurements from 1991--2018.,, -,24,fsh_lw_str_yr_box,"EBS pollock fishery body mass (given length) anomaly (standardized by overall mean body mass at each length) by year and season/area strata, 1991--2018.",, -,25,fsh_lw_str_box,"EBS pollock body mass (given length) anomaly (standardized by overall mean body mass at each length) by year and season/area strata, 1991--2018, aggregated by strata.",, -,26,fsh_lw_str_yr_mean,"EBS pollock body mass (given length) anomaly (standardized by overall mean body mass at each length) by year and season/area strata shown as mean values with a fitted loess smooth trend, 1991--2018.",, and the fishery (bottom) for EBS pollock. -cole1.png,27,cole1,"Estimated log-density (color) of pollock for three select years (rows) for the base case combined model. Columns represent the density available to the gear types, which for the ATS is the sum of strata 2 and 3, and for the BTS is the sum of strata 1 and 2, while the total is the sum of all three. ",, -cole2.png,28,cole2,"Estimated availability (i.e., fraction of pollock available to a survey gear type) for three select years (rows) for the bottom (BT) and acoustic (AT) trawl surveys (columns) from the combined base case model.",, -mod_data.pdf,30,mod_data,"Model runs comparing last year's assessment with the impact of sequentially addint new data (first 2018 catch and 2017 fishery catch-at-age, then the acoustic trawl survey (ATS), bottom trawl survey (BTS) and the acoustic AVO data for model 16.1.",, -fsh_wtage.pdf,31,mod_eval0a,EBS pollock model evaluation results of female spawning biomass comparing model results with different data treatments.,, -,32,mod_eval0b,EBS pollock model evaluation results of recruitment comparing last year's model with this year.,, -fsh_lw_month.png,33,mod_bts_biom,"EBS pollock model fit to the BTS biomass data (density dependence corrected estimates), 1982--2019.",, -fsh_lw_str_yr_box.pdf,34,mod_ats_biom,"EBS pollock model fit to the ATS biomass data, 1994--2018; green points to the right of vertical grey line are a preliminary treatment of applying a VAST model to the acoustic trawl survey data.",, -xxx,35,mod_mean_age,EBS pollock model fits to observed mean age for the Acoustic trawl survey (top),, -fsh_lw_str_yr_mean.pdf,36,mod_fsh_sel,Selectivity at age estimates for the EBS pollock fishery.,, -layer1.png,37,mod_fsh_age,Model fit (dots) to the EBS pollock fishery proportion-at-age data (columns; 1964--2018). The 2018 data are new to this year's assessment. Colors coincide with cohorts progressing through time. ,, -layer2.png,38,mod_cpue_fit,EBS pollock model fits to the Japanese fishery CPUE.,, -mod_data.pdf,39,mod_avo_fit,Model results of predicted and observed AVO index. Error bars represent assumed 95\% confidence bounds of the input series. ,, -mod_eval0c.pdf,40,mod_bts_sel,"Model estimates of bottom-trawl survey selectivity, 1982--2019.",, -mod_eval0a.pdf,41,mod_bts_age,Model fit (dots) to the bottom trawl survey proportion-at-age composition data (columns) for EBS pollock. Colors correspond to cohorts over time. Data new to this assessment are from 2018.,, -mod_eval0b.pdf,42,mod_ats_ones,Estimates of AT survey numbers (lower panel) and selectivity-at-age (with mean value equal to 1.0) over time (upper panel) for EBS pollock age 2 and older.,, -(,43,mod_ats_age,Model fit (dots) to the acoustic-trawl survey proportion-at-age composition data (columns) for EBS pollock. Colors correspond to cohorts over time (for years with consecutive surveys).,, -mod_cpue_fit.pdf,44,mod_ser,Estimated spawning exploitation rate (defined as the percent removal of egg production in a given spawning year).,, -mod_avo_fit.pdf,45,mod_F,Estimated instantaneous age-specific fishing mortality rates for EBS pollock.,, -mod_bts_biom.pdf,46,mod_hist,Comparison of the current assessment results with past assessments of begin-year EBS age-3+ pollock biomass.,, -mod_ats_biom.pdf,47,mod_phase,Estimated spawning biomass relative to annually estimated $F_{MSY}$ values and fishing mortality rates for EBS pollock. Most recent two years are shaded in yellow,, -mod_mean_age.pdf,48,mod_rec,Recruitment estimates (age-1 recruits) for EBS pollock for all years since 1964 (1963--2017 year classes) for Model 16.1. Error bars reflect 90\% credible intervals based on model estimates of uncertainty. ,, -mod_fsh_sel.pdf,49,mod_srr,Stock-recruitment estimates (shaded represnts structural uncertainty) and age-1 EBS pollock estimates labeled by year-classes,, -mod_fsh_age.pdf,50,mod_rs,"EBS pollock productivity as measured by logged recruits per spawning biomass, log(R\/S), as a function of spawning biomass with a linear fit (bottom) and over time, 1964--2018 (top).",, -mod_bts_sel.pdf,51,bts_biom,,, -mod_bts_age.pdf,52,mod_retro,Retrospective patterns for EBS pollock spawning biomass showing the point estimates relative to the terminal year (top panel) and approximate confidence bounds on absolute scale (+2 standard deviations).,, -,53,tier3_proj,Projected EBS Tier 3 pollock yield (top) and female spawning biomass (bottom) relative to the long-term expected values under $F_{35\%}$ and $F_{40\%}$ (horizontal lines). $B_{40\%}$ is computed from average recruitment from 1978--2017. Future harvest rates follow the guidelines specified under Tier 3 Scenario 1. ,, -,54,proj_const_catch,"Projected fishing mortality and spawning biomass relative to 2018 values under constant catch of 1.35 million t, 2019--2023.",, -mcmc_pairs.pdf,55,mcmc_pairs,"Pairwise plot of selected EBS pollock parameters and output from 3 million MCMC iterations thinned such that 5 thousand draws were saved as an approximation to the multivariate posterior distribution. Note that the figures on the diagonal represent the marginal posterior distributions. Key: lnR0 is the parameter that scales the stock-recruit relationship, B_Bmsy is estimated $B_{2017}/B_{MSY}$, DynB0 is the ratio of spawning biomass estimated for in 2018 over the value estimated that would occur if there had been no fishing, B18 is the spawning biomass in 2018, and B_Bmean is $B_{2018}/\bar{B}$.",, -mcmc_marg.pdf,56,mcmc_marg,Integrated marginal posterior density (based on MCMC results) for the 2018 EBS pollock female spawning biomass compared to the point estimate (dashed red line). The mean of the posterior is shown in green (under the dashed line).,, -,57,vast_idx,"Pollock index values for the standard survey region, the NBS, and combined based on the VAST application to density-dependent corrected CPUE values from the BTS data, 1982--2019. The different lines are smoothed trends for with and without including the cold-pool extent as a covariate.",, -,58,,,, -mod_ser.pdf,59,mod_eval0c,EBS pollock model evaluation results of three model fits to different treatment of bottom trawl survey sampling.,, -mod_F.pdf,60,bholt_ricker,EBS pollock model evaluation results comparing model 16.1 (which assumes a Ricker stock-recruitment relationship) with that where a prior mean steepness of 0.67 and CV of 15% applied to a Beverton-Holt stock recruit relationship.,, -mod_hist.pdf,61,,EBS pollock model evaluation results comparing model 16.1 (which assumes a Ricker stock-recruitment relationship) with that where a prior mean steepness of 0.67 and CV of 15% applied to a Beverton-Holt stock recruit relationship.,, -mod_phase.pdf,62,fsh_wtage_comb,"Fishery average weight-at-age anomaly (relative to mean) across strata and combined for all ages (3--10), and available years (1991--2017). Vertical shape reflects uncertainty in the data (wider shapes being more precise), colors are consistent with cohorts.",, -mod_srr.pdf,63,age_diversity,"For the mature component of the EBS pollock stock, time series of estimated average age and diversity of ages (using the Shannon-Wiener H statistic), 1980--2018. ",, -mod_rs.pdf,64,N_comp,Numbers-at-age estimates for 2019 (top) and 2020 (bottom) cmpared to the mean values since 1991.,, -mod_retro.pdf,65,cum_N_wt,Numbers-at-age multiplied by weights-at-age estimates for 2020 (top) and accumulated (bottom).,, -tier3_proj.pdf,66,sel_comp_vast,Comparison of the selectivity estimates between Model 16.1 and the implementation with the VAST treatment of the survey (including the NBS).,, -future_F.pdf,67,,,, -diversity.pdf,68,mod_data,"Model runs comparing last year's assessment with the impact of sequentially addint new data (first 2018 catch and 2017 fishery catch-at-age, then the acoustic trawl survey (ATS), bottom trawl survey (BTS) and the acoustic AVO data for model 16.1.",, -poll_cod_rec.png,69,poll_cod,Plot of age-1 abundance for walleye pollock (orange; in millions) and Pacific cod (blue; in 1000s) as estimated in the 2018 stock assessments (Ianelli et al. 2018; Thompson 2018).,, -,70,bts_data_by_yr,"Locations of stations used for the VAST moldel, 1982--2018.",, -,71,,,, -,72,,,, -,,,,, -,,,,, -,,,,, -,,,,, -mod_ats_age.pdf,,,,, diff --git a/doc/data/lf.csv b/doc/data/lf.csv index 27ffd8b..25c1647 100644 --- a/doc/data/lf.csv +++ b/doc/data/lf.csv @@ -32,3 +32,4 @@ year,F_A Season,F_B Season NW,F_B Season SE,M_A Season,M_B Season NW,M_B Season 2021,59580,30833,61208,75561,27641,53205,127,82,404 2022,93686,36012,94900,114918,33622,86598,184,36,210 2023,54056,37101,42259,73284,38222,38537,105,33,26 +2024,60398,29581,41855,71834,29604,36811,91,46,9 diff --git a/doc/figs/fmsy_sel.pdf b/doc/figs/fmsy_sel.pdf index 72dc36b..931a340 100644 Binary files a/doc/figs/fmsy_sel.pdf and b/doc/figs/fmsy_sel.pdf differ diff --git a/doc/figs/fsh_lenfreq.pdf b/doc/figs/fsh_lenfreq.pdf index 574116b..a3df013 100644 Binary files a/doc/figs/fsh_lenfreq.pdf and b/doc/figs/fsh_lenfreq.pdf differ diff --git a/doc/figs/fsh_wtage_comb.pdf b/doc/figs/fsh_wtage_comb.pdf index 9c7d0b1..3ac3953 100644 Binary files a/doc/figs/fsh_wtage_comb.pdf and b/doc/figs/fsh_wtage_comb.pdf differ diff --git a/doc/figs/mod_bts_biom.pdf b/doc/figs/mod_bts_biom.pdf deleted file mode 100644 index ad03891..0000000 Binary files a/doc/figs/mod_bts_biom.pdf and /dev/null differ diff --git a/doc/figs/mod_phase.pdf b/doc/figs/mod_phase.pdf index 2eeb5a7..bb72213 100644 Binary files a/doc/figs/mod_phase.pdf and b/doc/figs/mod_phase.pdf differ diff --git a/docs/doc/figs/fsh_lenfreq.png b/docs/doc/figs/fsh_lenfreq.png index 30f0185..c46664f 100644 Binary files a/docs/doc/figs/fsh_lenfreq.png and b/docs/doc/figs/fsh_lenfreq.png differ diff --git a/docs/doc/figs/mod_phase.png b/docs/doc/figs/mod_phase.png index 81e249d..349f249 100644 Binary files a/docs/doc/figs/mod_phase.png and b/docs/doc/figs/mod_phase.png differ diff --git a/docs/ebswp.pdf b/docs/ebswp.pdf index c602058..a4b7f8e 100644 Binary files a/docs/ebswp.pdf and b/docs/ebswp.pdf differ diff --git a/ebswp.qmd b/ebswp.qmd index 7e9d946..353b6ca 100644 --- a/ebswp.qmd +++ b/ebswp.qmd @@ -142,7 +142,7 @@ Islands region (Chapter 1A) and the Bogoslof Island area (Chapter 1B) are presented separately. A multi-species stock assessment is provided separately. A list of this -document contents, including tables and figures is provided in +document's contents, including tables and figures is provided in @sec-contents. ### Summary of changes in assessment inputs @@ -150,13 +150,14 @@ document contents, including tables and figures is provided in Relative to last year's BSAI SAFE report, the following substantive changes have been made in the EBS pollock stock assessment. This includes the `r thisyr` NMFS bottom-trawl survey (BTS) covering the EBS -and NBS. As before, these data were treated with a spatio temporal model -for index standardization. Age data from this survey effort was compiled +(but no new data from the NBS). As before, these data were treated with a spatio temporal model +for index standardization (and extended into the NBS). +Age data from this survey effort were compiled and included (also with an extensive spatio-temporal model treatment). -The NMFS acoustic-trawl survey (ATS) age composition data was revised -from the preliminary estimates developed in 2022. The BTS chartered -boats also collected acoustic data and the series was updated this year -(AVO). Explorations were presented in @ianelli2023. +Preliminary estimates of the 2024 NMFS acoustic-trawl survey (ATS) age composition data +was developed using the age-length key from the BTS survey. +The BTS-chartered boats also collected acoustic data and the series was updated this year +(AVO). #### Changes in the data @@ -205,7 +206,7 @@ reclassified Tier 3 table. We provide these as options to guide the SSC in their decisions. We also recall the work presented at their October 2024 meeting which indicated the very high value of $F_{MSY}$ estimates when alternative (i.e., less prior influence) assumptions about the stock-recruitment relationship were examined -@ianellisept. +(@ianellisept). @@ -294,7 +295,7 @@ less prior influence) assumptions about the stock-recruitment relationship were applied each year rather than an ad hoc choice of selectivity based on a previous year. - *As with past assessments, we document how we chose a selectivity to assume for - projection purposes and provide more rationale and objectives in making this choice.* + projection purposes and provide more rationale and objectives in making this choice (see @sec-selex).* # Introduction @@ -383,7 +384,7 @@ increasing proportion of shore-based catcher vessels have adopted electronic monitoring devices. This has replaced at-sea observers on these boats. However, the biological sampling continues to occur at about the same rate as previously but with samples obtained during the -offloading. Work continues on linking the log-book data withe the EM +offloading. Work continues on linking the log-book data with the EM data so that tow-by-tow estimates can be obtained. Historical catch estimates used in the assessment, along with management measures (i.e., OFLs, ABCs and TACs) are shown in (\cref{tbl:abctac}). @@ -560,7 +561,7 @@ quite high again in the A-season (68%). The higher values in recent years were likely due to good fishing conditions close to the main port. The recent transition from at-sea observer sampling of many catcher vessels to a combination of at-sea electronic monitoring and shore-based -observer sampling has resulted in a temporary hiatus in to associate +observer sampling has resulted in a temporary hiatus in our ability to associate catches with specific areas. Work has progressed to link the position information to offloads so that haul records could be used to evaluate fishing patterns. @@ -713,7 +714,7 @@ characteristic of the stock. In 2020, an unusual presence of age-2 pollock appeared in the catch, along with some from the 2014 year-class while the 2012 year-class was a smaller part of the catch (@fig-catage). By 2021 and 2022, the predominance of 3- and 4-year olds in the catch -confirms the abundance year-class from 2018. We note that the center of +confirms the abundant year-class from 2018. We note that the center of locations of the 2018 year-class, as plotted based on the locales of samples from that cohort, appears to be more oriented to the south east (by age) when compared to another abundant year-class (the 2008; @@ -812,8 +813,8 @@ more abundant in 2024. The size compositions were consistent with the age data Observed fluctuations in survey estimates may be attributed to a variety of sources including unaccounted-for variability in natural mortality, -survey catchability, and **horizontal** migrations and **vertical -availability** (@monnahan2021; @oleary2022). As an example, some strong +survey catchability, and horizontal migrations and vertical +availability (@monnahan2021; @oleary2022). As an example, some strong year classes appear in the surveys over several ages (e.g., the 1989 year class) while others appear only at older ages (e.g., the 1992 and 2008 year class). Sometimes, initially strong year classes appear to @@ -843,7 +844,7 @@ to weight using sex-specific length-weight parameters that were estimated from data prior to 1999. In reconsidering this approach, data on weight-at-age from intervening years have become available and some new methods applied including those corrected by spatio-temporal -modeling (@indivero2023). This work was adopted in 2022 and values used +modeling (see @indivero2023 for details). This work was adopted in 2022 and values used are shown in \cref{tbl:wtbts}. The time series of BTS survey indices is shown in \cref{tbl:btsabund}. @@ -904,16 +905,15 @@ contributed to loss of sea days. After the survey area coverage was completed at 40 nmi transect resolution, there was sufficient time to add transects on the northwestern shelf where historically most juveniles have been observed. This resulted in transects at 20 nmi -spacing between 172° W and the US-Russia maritime boundary." The areas +spacing between 172° W and the US-Russia maritime boundary." The area east of 170°W was surveyed from 11-22 June and west of 170°W was surveyed from the 23rd of June through July 17. -The estimated amount of pollock in the core survey area in 2024 was 11.4 -billion fish with a biomass of 2.87 million metric tons (t), a 25% -decrease from the estimate of 9.67 billion fish with a biomass of 3.8 -million t in 2022. This was a 20% decrease from the 3.617 million t -estimated in 2020 by the acoustics-only Saildrone survey, and 10% below -the survey mean of 3.2 million tons for all surveys from 1994-2022. +The survey estimate of pollock for 2024 was 11.4 +billion fish with a biomass of 2.87 million t. This represents a 25% +decrease in biomass from the 2022 estimate of 3.8 million t (with the +abundance estimate at 9.67 billion fish). The 2024 biomass estimate is +10% below the survey mean of 3.2 million tons for all surveys from 1994-2022. Preliminary population age estimates from 2024 using the length compositions applied to the BTS age-length key (\cref{tbl:atsage}). Six-year-old pollock (2018 year class) dominated the estimated @@ -1078,8 +1078,8 @@ Sample sizes for age-composition data were re-evaluated in @ianelli2023 and found to be consistent with the relative variability allowed for selectivities and with the observation errors specified for the indices. Principally, this work resulted in tuning the recent era (1991-present -year) to an average sample sizes of 350 for the fishery and then using -estimated values for the period 1978-1990 and as earlier +year) to an average sample size of 350 for the fishery and then using +estimated values for the period 1978-1990 and earlier (\cref{tbl:inputn}). As rationalized in earlier assessments, we found that assuming average values of 100 and 50 for the BTS and ATS data, respectively resulted in consistent model fits and were (relatively) @@ -1343,7 +1343,7 @@ associated with earlier diapause of copepods (@thorson2020b), such that a fall (but not spring) survey of copepod densities is also associated with cold conditions and elevated recruitment (@eisner2020). -### Fishery selectivity for projections +### Fishery selectivity for projections {#sec-selex} The SSC requested a clear development on the assumptions of what selectivity estimates should be used for projections. The model estimates vary by @@ -1371,13 +1371,14 @@ and compare the projected $F_{35\%}$ rate with the annual estimates in later years. For example, in the terminal (retrospective) year 2015 we have estimates of $F_{35\%}$ based on the 2016 expected selectivity (using the above scenarios). We can then compare the "final" estimate of the 2016 -selectivity as estimated this year (2024) and go back and compute the $F_{35\%}$ +selectivity as estimated this year (2024) and go back and compute the $F_{35\%}$ using that year's selectivity. We do that for each retrospective projection $\sum (F_{35\%}^{proj,i}-F_{35\%}^{full,i})^2$ given each of the five scenarios outlined above. [calculations so far incomplete...]{bg-colour="#FFFF00" } + # Results The input sample size (as tuned in 2016 using "Francis Weights") can be @@ -1418,7 +1419,7 @@ posterior density) with the mean of the posterior marginal distribution of the `r thisyr` spawning biomass. This showed that the point estimate was similar to the mean of the marginal posterior distribution (@fig-mcmc_marg). As an additional part of the Tier 1 consideration, we -evaluated the posterior density of $F_{MSY}$ and is provided in +evaluated the posterior density of $F_{MSY}$ and it is provided in @fig-mcmc_marg_fmsy for reference. We added code for producing posterior predictive distributions (e.g., @@ -1438,8 +1439,11 @@ year's spawning biomass (@fig-ssb_v_2018). In the [September 2024 assessment evaluation](https://afsc-assessments.github.io/ebs_pollock_safe/doc/sept.html) a detailed set of sensitivities were presented regarding assumptions -about the stock-recruitment relationship (SRR), an alternative natural -mortality-at-age and year matrix (from the CEATTLE model results), +about the stock-recruitment relationship (SRR). Additionally, an alternative natural +mortality-at-age and year matrix (from the CEATTLE model results) was tested along +with some preliminary model applications using alternative software platforms +and a numbe of SSC requests. Please refer to that work and that from 2023 for +recent sensitivities. A sequential sensitivity of available new data showed that adding the new data from 2024 had very minor changes and impact on the spawning @@ -1673,7 +1677,6 @@ the 2018 year class, the impact of the recent warm conditions suggest that the recent period (2000-present) is similar to the mean since 1977. # Harvest recommendations - ## Status summary The estimate of $B_{MSY}$ is `r M$bmsys` kt (with a CV of @@ -1900,10 +1903,10 @@ is defined as $B_{35\%}$). For the purposes of these projections, we present results based on selecting the $F_{40\%}$ harvest rate as the $F_{ABC}$ value and use $F_{35\%}$ as a proxy for $F_{MSY}$. Scenarios 1 through 7 were -projected 14 years from `r thisyr` (\cref{tbl:tier3SSB} for Model +projected 14 years from `r thisyr+1` (\cref{tbl:tier3SSB} for Model 23.0--including the 1978 year-class as is convention for Tier 3 estimates). Under catches set to Tier 3 ABC estimates, the expected -spawning biomass is well above $B_{35\%}$ and is expected to be drop +spawning biomass is well above $B_{35\%}$ and is expected to drop below $B_{40\%}$ by 2026 (given mean recruitment; @fig-tier3_proj and assuming catches \>2 million t in 2025). @@ -1980,7 +1983,6 @@ suggests that it would be the biggest year-class on record Given the same estimated aggregate fishing effort as in 2024, the stock trend would be stable and yield about 1.3 million t (Table 34). - ### Should the ABC be reduced below the maximum permissible ABC? The SSC in its September 2018 minutes recommended that assessment @@ -1998,8 +2000,8 @@ procedure evaluation can be undertaken. \hline &\multicolumn{4}{c}{\textbf{Considerations}} \\ \hline - &\textbf{Assessment-related} & \textbf{ Population dynamics} & \textbf - {Environmental \& ecosystem } & Fishery performance \\ + &\textbf{Assessment-related} & \textbf{ Population dynamics} & \textbf + {Environmental \& ecosystem } & \textbf{Fishery performance} \\ \hline Level 1 No concern & Typical to moderately increased uncertainty \& minor unresolved issues in assessment @@ -2902,6 +2904,42 @@ Year & Males & Females & Males & Females & Males & Females 1986 & 689 & 794 & 518 & 501 & 286 & 286 & 3,074 \\ 1987 & 1,351 & 1,466 & 25 & 33 & 72 & 63 & 3,010 \\ - & -- & -- & -- & -- & -- & -- & -- \\ +1991 & 155,876 & 143,625 & 148,385 & 132,539 & 123,516 & 122,241 & 826,182 \\ +1992 & 152,566 & 148,024 & 150,829 & 152,003 & 93,073 & 94,701 & 791,196 \\ +1993 & 136,211 & 126,635 & 145,280 & 137,384 & 24,797 & 26,057 & 596,364 \\ +1994 & 138,179 & 146,067 & 154,311 & 148,497 & 26,431 & 26,380 & 639,865 \\ +1995 & 128,719 & 125,847 & 175,115 & 150,323 & 16,142 & 16,327 & 612,473 \\ +1996 & 147,992 & 139,905 & 193,493 & 149,814 & 18,101 & 18,288 & 667,593 \\ +1997 & 123,454 & 102,619 & 114,846 & 106,001 & 58,492 & 51,498 & 556,910 \\ +1998 & 135,136 & 109,119 & 205,282 & 174,676 & 31,968 & 39,475 & 695,656 \\ +1999 & 36,035 & 32,407 & 38,229 & 35,084 & 16,258 & 18,321 & 176,334 \\ +2000 & 64,430 & 58,030 & 63,746 & 41,027 & 40,839 & 39,105 & 307,177 \\ +2001 & 79,190 & 75,491 & 54,037 & 51,179 & 44,232 & 45,766 & 349,895 \\ +2002 & 71,502 & 69,467 & 65,299 & 64,243 & 37,661 & 39,285 & 347,457 \\ +2003 & 74,902 & 77,533 & 49,307 & 52,899 & 51,764 & 53,435 & 359,840 \\ +2004 & 75,208 & 75,811 & 63,146 & 61,957 & 47,261 & 44,220 & 367,603 \\ +2005 & 75,784 & 68,665 & 43,271 & 33,917 & 68,831 & 63,022 & 353,490 \\ +2006 & 72,543 & 63,349 & 35,378 & 27,939 & 77,620 & 67,219 & 344,048 \\ +2007 & 66,533 & 63,969 & 38,104 & 29,558 & 76,755 & 70,504 & 345,423 \\ +2008 & 51,303 & 46,296 & 23,467 & 20,462 & 64,126 & 60,678 & 266,332 \\ +2009 & 43,476 & 41,540 & 17,343 & 16,148 & 45,418 & 47,926 & 211,851 \\ +2010 & 41,019 & 39,495 & 20,577 & 19,194 & 40,914 & 40,449 & 201,648 \\ +2011 & 62,295 & 58,481 & 65,057 & 60,208 & 48,055 & 50,927 & 345,023 \\ +2012 & 57,946 & 53,557 & 46,942 & 45,024 & 53,243 & 49,968 & 306,680 \\ +2013 & 62,148 & 51,984 & 44,582 & 37,307 & 49,649 & 49,161 & 294,831 \\ +2014 & 58,066 & 55,954 & 51,743 & 46,568 & 46,067 & 46,642 & 305,040 \\ +2015 & 56,419 & 55,646 & 43,601 & 46,853 & 41,183 & 45,117 & 288,819 \\ +2016 & 58,915 & 57,478 & 69,654 & 72,973 & 9,015 & 10,264 & 278,299 \\ +2017 & 64,693 & 55,965 & 65,982 & 70,285 & 14,125 & 15,871 & 286,921 \\ +2018 & 64,628 & 57,156 & 49,653 & 56,243 & 32,796 & 35,811 & 296,287 \\ +2019 & 64,665 & 49,191 & 54,927 & 59,416 & 27,753 & 34,955 & 290,907 \\ +2020 & 65,609 & 60,018 & 47,791 & 53,161 & 48,459 & 53,985 & 329,023 \\ +2021 & 75,561 & 59,580 & 53,205 & 61,208 & 27,641 & 30,833 & 308,028 \\ +2022 & 114,918 & 93,686 & 86,598 & 94,900 & 33,622 & 36,012 & 459,736 \\ +2023 & 73,284 & 54,056 & 38,537 & 42,259 & 38,222 & 37,101 & 283,459 \\ +2024 & 71,834 & 60,398 & 36,811 & 41,855 & 29,604 & 29,581 & 270,083 \\ + + 1991 & 2,893 & 2,791 & 1,209 & 1,116 & 2,536 & 2,408 & 12,953 \\ 1992 & 1,605 & 1,537 & 556 & 600 & 2,003 & 1,940 & 8,241 \\ 1993 & 1,278 & 1,205 & 451 & 437 & 1,412 & 1,459 & 6,242 \\ @@ -2933,8 +2971,8 @@ Year & Males & Females & Males & Females & Males & Females 2019 & 4,513 & 6,086 & 3,594 & 2,953 & 5,809 & 5,499 & 28,454 \\ 2020 & 6,116 & 6,846 & 5,325 & 4,815 & 5,376 & 4,900 & 33,378 \\ 2021 & 5,852 & 7,368 & 6,247 & 5,468 & 2,886 & 2,698 & 30,519 \\ -2022 & 4,862 & 5,817 & 2,240 & 1,858 & 531 & 506 & 15,814 \\ -2023 & xxxxx & 5,817 & 2,240 & 1,858 & 531 & 506 & 15,814 \\ +2022 & 4,890 & 5,847 & 1,705 & 1,566 & 4,899 & 4,364 & 23,271 \\ +2023 & 10,676 & 14,487 & 6,171 & 6,173 & 5,911 & 5,436 & 48,854 \\ \hline \end{tabular} } @@ -2994,8 +3032,8 @@ Year & Males & Females & Males & Females & Males & Females 2019 & 552 & 778 & 387 & 332 & 558 & 531 & 3,138 \\ 2020 & 757 & 899 & 405 & 420 & 450 & 408 & 3,339 \\ 2021 & 760 & 910 & 588 & 542 & 270 & 256 & 3,326 \\ -2022 & 608 & 776 & 616 & 558 & 209 & 211 & 2,978 \\ -2023 & xxx & 776 & 616 & 558 & 209 & 211 & 2,978 \\ +2022 & 609 & 777 & 209 & 212 & 616 & 563 & 2,986 \\ +2023 & 452 & 633 & 350 & 313 & 399 & 342 & 2,489 \\ \hline \end{tabular} } @@ -4144,8 +4182,8 @@ printfig("AVO_Series_change.png", 99) printfig("avo_map_yr.png", 16) printfig("fsh_lw_month.png", 23) printfig("fsh_lw_anom_str_yr_box.png", 24) -printfig("fsh_lw_anom_yr_box.png", 25) -printfig("fsh_wtage_comb.png", 20) +printfig("fsh_lw_anom_yr_box.pdf", 25) +printfig("fsh_wtage_comb.pdf", 20) printfig("fsh_wtage_data_pred.png", 88) printfig("fsh_wtage_strata.png", 21) printfig("fsh_wtage_strata_yr.png", 22) diff --git a/tools/do-phase.R b/tools/do-phase.R index fd03290..0ece6e4 100644 --- a/tools/do-phase.R +++ b/tools/do-phase.R @@ -22,11 +22,11 @@ df <- read_table(paste0(.MODELDIR[thismod],"F40_t.rep")) #,header=TRUE) SSB=M$future_SSB[5,2:3], B.Bmsy= M$future_SSB[5,2:3]/bmsy) #%>% - mutate(Yr=substr(as.character(Year),3,4), - Fmsy=c(fmsy,fmsy)) #, - Fmsy=rep(fmsy,2), - F.Fmsy=F/Fmsy, - Bmsy=rep(bmsy,2), + #mutate(Yr=substr(as.character(Year),3,4), + #Fmsy=c(fmsy,fmsy)) #, + #Fmsy=rep(fmsy,2), + #F.Fmsy=F/Fmsy, + #Bmsy=rep(bmsy,2), df2 pt pt2 @@ -41,11 +41,12 @@ df <- read_table(paste0(.MODELDIR[thismod],"F40_t.rep")) #,header=TRUE) geom_hline(size=.5,yintercept=1) + geom_vline(size=0.5,linetype="dashed",xintercept=.2) + geom_vline(size=.5,xintercept=1) + geom_path(size=.4) + guides(size=FALSE,fill=FALSE,alpha=FALSE,col=FALSE) ;p1 ggsave("doc/figs/mod_phase.pdf",plot=p1,width=7.2,height=5.7,units="in") + ggsave("doc/figs/mod_phase.png",plot=p1,width=7.2,height=5.7,units="in") -sdf <- tibble(data.frame(year=1964:2024,rbind(M$sel_fsh,M$sel_fut))) +sdf <- tibble(data.frame(year=1964:2025,rbind(M$sel_fsh,M$sel_fut))) tail(sdf) names(sdf) <- c("Year",1:15) -wtdf <- tibble(data.frame(year=1964:2023,rbind(M$wt_fsh,M$wt_fut))) +wtdf <- tibble(data.frame(year=1964:2025,rbind(M$wt_fsh,M$wt_fut))) names(wtdf) <- c("Year",1:15) #sdf[,2:16] <- wtdf[,2:16]*sdf[,2:16] sdfm <- sdf %>% pivot_longer(cols=2:16,names_to="age",values_to="Selectivity") %>% @@ -66,12 +67,13 @@ wtdf # plot of selected age vs Fmsy p1 <- df %>% select(Year,Fmsy,AM_fmsyr,F35) %>% left_join(sdfm) %>% filter(age<11,Year>2000)%>% mutate( Year=substr(as.character(Year),3,4)) %>% group_by(Year) %>% - summarise(Fmsy=mean(Fmsy),mnage=sum(Selectivity*age)/sum(Selectivity)) %>% + summarise(F35=mean(F35), Fmsy=mean(Fmsy),mnage=sum(Selectivity*age)/sum(Selectivity)) %>% + #ggplot(aes(y=F35,x=mnage,label=Year)) + geom_text() + ggplot(aes(y=Fmsy,x=mnage,label=Year)) + geom_text() + theme_few() + geom_path(size=.2,color="grey") + xlab( "Mean age selected") #+ geom_smooth();p1 p1 ggsave("doc/figs/fmsy_sel.pdf",plot=p1,width=5.2,height=4.0,units="in") -ndf <- tibble(data.frame(year=1964:2023,rbind(M$N))) +ndf <- tibble(data.frame(year=1964:2024,rbind(M$N))) names(ndf) <- c("Year",1:15) ndfm <- ndf %>% pivot_longer(cols=2:16,names_to="age",values_to="Numbers") %>% mutate( age=as.numeric(age), @@ -85,7 +87,8 @@ sdfm mnagesel=sum(Selectivity*age)/sum(Selectivity), mnage=sum(Numbers*age)/sum(Numbers)) %>% ggplot(aes(y=mnagesel,x=mnage,label=Year)) + geom_text() + ylab("Mean age selected") + - theme_few() + geom_path(size=.2,color="grey") + xlab( "Mean age in stock") + geom_smooth(method='lm');p1 + theme_few() + geom_path(size=.2,color="grey") + xlab( "Mean age in stock") + + geom_smooth(method='lm');p1 ggsave("figs/xxxfmsy_sel.pdf",plot=p1,width=7.2,height=5.7,units="in")