This function lists the general settings of the CMSY++ code (the section "General settings
for the analysis" of CMSY++16.R and the MCMC settings of its JAGS call), their default
values in CMSY++, the values cmsy_run() uses (the defaults, unless changed with its
settings argument), what each one does and which part of CMSY++ it affects.
Usage
cmsy_defaults(settings = list(), lang = NULL)Arguments
- settings
Optional named list of changed settings, e.g.
list(CV.C = 0.2), to show them next to the defaults and check them.- lang
The language of the
descriptioncolumn: "en", "zh" or "both". Default is NULL, the language set withfao_settings().
Value
A data frame with one row per setting: setting, cmsy_default, used, changed,
applies_to and description.
Details
Two settings of the code, sigmaR and ni, are set in CMSY++16.R but used nowhere in it: the
process error of the model is estimated in JAGS with the prior itau2 ~ dgamma(4, 0.01), so
changing sigmaR would not change any result. They are listed as "not used" and cannot be
changed, so that a run is not taken for a sensitivity analysis of the process error.
Settings marked "BSM" only matter when abundance data (CPUE or biomass) are given; FAO data
have none, so with FAO data alone only the settings marked "all" change the results. The chart
and output switches of CMSY++ (mgraphs, kobe.plot, pp.plot, retros, save.plots,
write.output, ...) are set by the plots argument of cmsy_run(), and the file names by
the run itself.
References
Froese, R., Demirel, N., Coro, G. and Winker, H. (2021). User Guide for CMSY++. GEOMAR, Germany, 17 pp. https://oceanrep.geomar.de/id/eprint/52147/
Examples
# All settings with their CMSY++ defaults
cmsy_defaults()
#> setting cmsy_default used changed applies_to
#> 1 CV.C 0.15 0.15 FALSE all
#> 2 CV.cpue 0.2 0.2 FALSE BSM
#> 3 sigmaR 0.1 0.1 FALSE not used
#> 4 cor.log.rk -0.76 -0.76 FALSE charts
#> 5 rk.cor.beta 2.52, 3.37 2.52, 3.37 FALSE all
#> 6 nbk 3 3 FALSE BSM
#> 7 bt4pr FALSE FALSE FALSE BSM
#> 8 ct_MSY.lim 1.21 1.21 FALSE all
#> 9 q.biomass.pr 0.9, 1.1 0.9, 1.1 FALSE BSM
#> 10 n 5000 5000 FALSE charts
#> 11 ni 3 3 FALSE not used
#> 12 nab 3 3 FALSE BSM
#> 13 bw 3 3 FALSE all
#> 14 e.creep.line TRUE TRUE FALSE charts
#> 15 select.yr NA NA FALSE output
#> 16 n.chains 2 2 FALSE all
#> 17 n.iter 60000 60000 FALSE all
#> 18 n.burnin 30000 30000 FALSE all
#> 19 n.thin 10 10 FALSE all
#> description
#> 1 Coefficient of variation of the catch (observation error)
#> 2 Minimum realistic coefficient of variation of CPUE
#> 3 Not used by CMSY++16.R: the code sets it (sigR <- sigmaR) but never uses it; the model estimates its process error with the prior itau2 ~ dgamma(4, 0.01). It cannot be changed
#> 4 Correlation of log r and log k, used only in charts
#> 5 Beta prior of the r-k correlation plus 1
#> 6 Number of B/k priors used by BSM: 1 (first year), 2 (and intermediate year), 3 (and last year)
#> 7 Use the abundance data to set the B/k priors
#> 8 Ratio of catch to the MSY prior above which the B/k prior is kept constant
#> 9 Prior range of q when the abundance data are biomass
#> 10 Number of points of the r-k cloud in the analysis chart
#> 11 Not used by CMSY++16.R: the code sets it but never uses it. It cannot be changed
#> 12 Minimum number of years with abundance data to run BSM
#> 13 Bandwidth of ksmooth() for smoothing the catch
#> 14 Show the CPUE not corrected for effort creep in the biomass chart
#> 15 Year for which B, F, B/Bmsy and F/Fmsy are also reported (NA: none)
#> 16 Number of MCMC chains (JAGS)
#> 17 Number of MCMC iterations per chain (JAGS)
#> 18 Number of burn-in iterations (JAGS)
#> 19 Thinning of the MCMC chains (JAGS)
# Check changed settings before a run: here a larger catch error and longer chains
cmsy_defaults(list(CV.C = 0.2, n.iter = 100000, n.burnin = 50000), lang = "zh")
#> setting cmsy_default used changed applies_to
#> 1 CV.C 0.15 0.2 TRUE all
#> 2 CV.cpue 0.2 0.2 FALSE BSM
#> 3 sigmaR 0.1 0.1 FALSE not used
#> 4 cor.log.rk -0.76 -0.76 FALSE charts
#> 5 rk.cor.beta 2.52, 3.37 2.52, 3.37 FALSE all
#> 6 nbk 3 3 FALSE BSM
#> 7 bt4pr FALSE FALSE FALSE BSM
#> 8 ct_MSY.lim 1.21 1.21 FALSE all
#> 9 q.biomass.pr 0.9, 1.1 0.9, 1.1 FALSE BSM
#> 10 n 5000 5000 FALSE charts
#> 11 ni 3 3 FALSE not used
#> 12 nab 3 3 FALSE BSM
#> 13 bw 3 3 FALSE all
#> 14 e.creep.line TRUE TRUE FALSE charts
#> 15 select.yr NA NA FALSE output
#> 16 n.chains 2 2 FALSE all
#> 17 n.iter 60000 100000 TRUE all
#> 18 n.burnin 30000 50000 TRUE all
#> 19 n.thin 10 10 FALSE all
#> description
#> 1 渔获量观测误差的变异系数
#> 2 CPUE 的最小变异系数
#> 3 CMSY++16.R不使用：代码中有赋值（sigR <- sigmaR），但从未使用；模型的过程误差由先验 itau2 ~ dgamma(4, 0.01) 估计。不能修改
#> 4 log r 与 log k 的相关系数，仅用于作图
#> 5 r-k 相关系数加 1 的 beta 先验
#> 6 BSM 使用的 B/k 先验个数：1（首年）、2（加中间年）、3（再加末年）
#> 7 用丰度数据设定 B/k 先验
#> 8 渔获量与 MSY 先验之比超过此值时，B/k 先验保持不变
#> 9 丰度数据为生物量时 q 的先验范围
#> 10 分析图中 r-k 点云的点数
#> 11 CMSY++16.R不使用：代码中有赋值，但从未使用。不能修改
#> 12 运行 BSM 所需丰度数据的最少年数
#> 13 渔获量平滑（ksmooth()）的带宽
#> 14 在生物量图中显示未按渔效增长（effort creep）校正的 CPUE
#> 15 另外报告该年 B、F、B/Bmsy 和 F/Fmsy 的年份（NA 为不报告）
#> 16 MCMC 链数（JAGS）
#> 17 每条链的 MCMC 迭代次数（JAGS）
#> 18 预烧（burn-in）迭代次数（JAGS）
#> 19 MCMC 抽稀间隔（JAGS）