NWFSC California Current

# Get rid of memory limits -----------------------------------------------------
options(future.globals.maxSize = 1 * 1024^4) # Allow up to 1 TB for globals

# Install Libraries ------------------------------------------------------------

# Here we list all the packages we will need for this whole process
# We'll also use this in our works cited page.
PKG <- c(
  "surveyresamplr",
  "dplyr",
  "tidyr",
  "purrr",
  "ggplot2",
  "future.callr",
  "flextable", 
  "sdmTMB"
)

pkg_install <- function(p) {
  if (!require(p, character.only = TRUE)) {
    install.packages(p)
  }
  require(p, character.only = TRUE)
}
base::lapply(unique(PKG), pkg_install)
#> Loading required package: surveyresamplr
#> Loading required package: dplyr
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
#> Loading required package: tidyr
#> Loading required package: purrr
#> Loading required package: ggplot2
#> Loading required package: future.callr
#> Loading required package: future
#> Loading required package: flextable
#> 
#> Attaching package: 'flextable'
#> The following object is masked from 'package:purrr':
#> 
#>     compose
#> Loading required package: sdmTMB
#> [[1]]
#> [1] TRUE
#> 
#> [[2]]
#> [1] TRUE
#> 
#> [[3]]
#> [1] TRUE
#> 
#> [[4]]
#> [1] TRUE
#> 
#> [[5]]
#> [1] TRUE
#> 
#> [[6]]
#> [1] TRUE
#> 
#> [[7]]
#> [1] TRUE
#> 
#> [[8]]
#> [1] TRUE

# Set directories --------------------------------------------------------------
wd <- paste0(here::here(), "/vignettes/")
dir_out <- paste0(wd, "output/")
dir_final <- paste0(dir_out, "CA_0results/")

Run scenarios 


### Define study species -------------------------------------------------------

spp_list <- data.frame(
  srvy = c(
    "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA",
    "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA"
  ),
  common_name = c(
    "arrowtooth flounder", "bocaccio", "canary rockfish", "darkblotched rockfish",
    "Dover sole", "lingcod", "lingcod", "longnose skate",
    "Pacific ocean perch", "Pacific spiny dogfish",
    "petrale sole", "rex sole", "sablefish",
    "shortspine thornyhead", "yellowtail rockfish", "widow rockfish"
  ),
  file_name = c(
    "arrowtooth_flounder", "bocaccio", "canary_rockfish", "darkblotched_rockfish",
    "dover_sole", "lingcod_N", "lingcod_S", "longnose_skate",
    "pacific_ocean_perch", "pacific_spiny_dogfish", "petrale_sole", "rex_sole",
    "sabefish", "shortspine_thornyhead", "yellowtail_rockfish", "widow_rockfish"
  ),
  filter_lat_gt = c(34, NA, NA, 335, NA, 35, NA, NA, 35, NA, NA, NA, NA, NA, 35.5, 33.5),
  filter_lat_lt = c(NA, NA, NA, NA, NA, NA, 35, NA, NA, NA, NA, NA, NA, NA, NA, NA),
  filter_depth = c(NA, 500, 275, 675, NA, 450, 450, NA, 500, 700, 675, 700, NA, NA, 425, 675),
  model_fn = c(
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass + depth_m + (depth_m^2)",
    "total_catch_wt_kg ~ 0 + factor(year) + pass",
    "total_catch_wt_kg ~ 0 + factor(year) + pass"
  ),
  # model_fn = c( # name of funcion for sdm. Will build in specificity for this later
  # "species_sdm_fn", "species_sdm_fn", "canary_sdm_fn", "darkblotched_sdm_fn",
  # "species_sdm_fn", "species_sdm_fn", "species_sdm_fn", "species_sdm_fn",
  # "species_sdm_fn", "species_sdm_fn",
  # "species_sdm_lognormal_fn", "species_sdm_fn", "species_sdm_lognormal_fn"),
  # "shortspine_sdm_fn", "species_sdm_fn", "widow_sdm_fn"
  model_family = c(
    "delta_gamma", "delta_gamma", "delta_lognormal", "delta_lognormal",
    "delta_gamma", "delta_gamma", "delta_gamma", "delta_gamma",
    "delta_gamma", "delta_gamma",
    "delta_lognormal", "delta_gamma", "delta_lognormal",
    "delta_gamma", "delta_gamma", "delta_gamma"
  ),
  model_anisotropy = c(
    TRUE, TRUE, FALSE, TRUE,
    TRUE, TRUE, TRUE, TRUE,
    TRUE, TRUE,
    TRUE, TRUE, TRUE,
    TRUE, TRUE, TRUE
  ),
  model_spatiotemporal = c(
    "iid, iid",
    "iid, iid",
    "iid, off",
    "off, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "iid, iid",
    "off, off"
  )
)


### Load survey data -----------------------------------------------------------

# source(paste0(wd, "code/data_dl_nw.r"))
catch <- surveyresamplr::noaa_nwfsc_catch # pulled data again to get 2024
bio <- surveyresamplr::noaa_nwfsc_bio

### Load grid data -------------------------------------------------------------

grid_yrs <- sdmTMB::replicate_df(
  dat = surveyresamplr::noaa_nwfsc_pred_grid_depth,
  time_name = "year",
  time_values = unique(catch$year)
)

### Variables ------------------------------------------------------------------

srvy <- "CA"
seq_from <- 0.1
seq_to <- 1
seq_by <- 0.1
tot_dataframes <- 91
replicate_num <- 10

### Run ------------------------------------------------------------------------

purrr::map(
  1:nrow(spp_list),
  ~ clean_and_resample(spp_list[.x, ],
    catch,
    seq_from,
    seq_to,
    seq_by,
    tot_dataframes,
    replicate_num,
    grid_yrs,
    dir_out,
    n_knots = 500,
    bio = bio
  )
)

### Plot indices ---------------------------------------------------------------

out <- plot_results(srvy = srvy, dir_out = dir_out, dir_final = dir_final)
out$plots
#> $index_boxplot_log_biomass

#> 
#> $index_boxplot_log_biomass_SE

#> 
#> $index_boxplot_biomass

#> 
#> $index_timeseries_biomass

Parameter output:

i <- 1
print(names(out$tables)[i])
#> [1] "fit_df"
head(out$tables[i][[1]]) |>
  flextable::flextable()

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X

srvy

common_name

file_name

filter_lat_gt

filter_lat_lt

filter_depth

model_fn

model_family

model_anisotropy

model_spatiotemporal

effort

term

estimate

std.error

conf.low

conf.high

1

1

1

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1

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1

1

1

1

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

factor(year)2003

-5.971292

1.867024

-9.630592

-2.311992

2

2

2

2

2

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2

2

2

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

factor(year)2004

-5.904872

1.899050

-9.626941

-2.182802

3

3

3

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

factor(year)2005

-5.339547

1.865157

-8.995187

-1.683906

4

4

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

factor(year)2006

-6.836383

1.877666

-10.516540

-3.156226

5

5

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

factor(year)2007

-6.603194

1.855753

-10.240403

-2.965985

6

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

factor(year)2008

-5.410851

1.835831

-9.009014

-1.812688

 
i <- 1 + i
print(names(out$tables)[i])
#> [1] "fit_pars"
head(out$tables[i][[1]]) |>
  flextable::flextable()

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X

srvy

common_name

file_name

filter_lat_gt

filter_lat_lt

filter_depth

model_fn

model_family

model_anisotropy

model_spatiotemporal

effort

term

estimate

std.error

conf.low

conf.high

1

1

1

1

1

1

1

1

1

1

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1

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

range

1.2135798963

0.3045316

0.7421143

1.984568

2

2

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

sigma_O

5.2587608445

1.0082172

3.6115185

7.657324

3

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

sigma_E

0.0001432170

0.1140497

0.0000000

Inf

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_10

range

1.3802719552

0.3917700

0.7913408

2.407497

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_10

sigma_O

6.1013538266

1.3015058

4.0165463

9.268291

6

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CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_10

sigma_E

0.0003374822

0.1539537

0.0000000

Inf

 
i <- 1 + i
print(names(out$tables)[i])
#> [1] "fit_check"
head(out$tables[i][[1]]) |>
  flextable::flextable()

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X.76

X.75

X.74

X.73

X.72

X.71

X.70

X.69

X.68

X.67

X.66

X.65

X.64

X.63

X.62

X.61

X.60

X.59

X.58

X.57

X.56

X.55

X.54

X.53

X.52

X.51

X.50

X.49

X.48

X.47

X.46

X.45

X.44

X.43

X.42

X.41

X.40

X.39

X.38

X.37

X.36

X.35

X.34

X.33

X.32

X.31

X.30

X.29

X.28

X.27

X.26

X.25

X.24

X.23

X.22

X.21

X.20

X.19

X.18

X.17

X.16

X.15

X.14

X.13

X.12

X.11

X.10

X.9

X.8

X.7

X.6

X.5

X.4

X.3

X.2

X.1

X

srvy

common_name

file_name

filter_lat_gt

filter_lat_lt

filter_depth

model_fn

model_family

model_anisotropy

model_spatiotemporal

effort

hessian_ok

eigen_values_ok

nlminb_ok

range_ok

gradients_ok

se_magnitude_ok

se_na_ok

sigmas_ok

all_ok

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

TRUE

TRUE

TRUE

TRUE

TRUE

FALSE

TRUE

FALSE

FALSE

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_10

TRUE

TRUE

TRUE

TRUE

TRUE

FALSE

TRUE

FALSE

FALSE

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_2

TRUE

TRUE

TRUE

TRUE

TRUE

FALSE

TRUE

FALSE

FALSE

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_3

TRUE

TRUE

TRUE

TRUE

TRUE

FALSE

TRUE

FALSE

FALSE

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_4

TRUE

TRUE

TRUE

TRUE

TRUE

FALSE

TRUE

FALSE

FALSE

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_5

TRUE

TRUE

TRUE

TRUE

TRUE

FALSE

TRUE

FALSE

FALSE

 
i <- 1 + i
print(names(out$tables)[i])
#> [1] "index"
head(out$tables[i][[1]]) |>
  flextable::flextable()

X.90

X.89

X.88

X.87

X.86

X.85

X.84

X.83

X.82

X.81

X.80

X.79

X.78

X.77

X.76

X.75

X.74

X.73

X.72

X.71

X.70

X.69

X.68

X.67

X.66

X.65

X.64

X.63

X.62

X.61

X.60

X.59

X.58

X.57

X.56

X.55

X.54

X.53

X.52

X.51

X.50

X.49

X.48

X.47

X.46

X.45

X.44

X.43

X.42

X.41

X.40

X.39

X.38

X.37

X.36

X.35

X.34

X.33

X.32

X.31

X.30

X.29

X.28

X.27

X.26

X.25

X.24

X.23

X.22

X.21

X.20

X.19

X.18

X.17

X.16

X.15

X.14

X.13

X.12

X.11

X.10

X.9

X.8

X.7

X.6

X.5

X.4

X.3

X.2

X.1

X

srvy

common_name

file_name

filter_lat_gt

filter_lat_lt

filter_depth

model_fn

model_family

model_anisotropy

model_spatiotemporal

effort

year

est

lwr

upr

log_est

se

type

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

2,003

203,332.1

98,387.88

420,213.6

12.22260

0.3703756

index

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

2

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

2,004

590,686.0

251,897.01

1,385,129.4

13.28904

0.4348367

index

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

3

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

2,005

412,734.6

201,444.43

845,641.8

12.93056

0.3659716

index

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

4

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

2,006

362,858.6

153,677.67

856,769.8

12.80177

0.4383529

index

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

5

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

2,007

356,351.7

180,235.05

704,560.9

12.78367

0.3477903

index

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

CA

arrowtooth flounder

arrowtooth_flounder

34

total_catch_wt_kg ~ 0 + factor(year) + pass

delta_gamma

TRUE

iid, iid

01_1

2,008

359,187.2

184,946.73

697,581.6

12.79160

0.3386674

index