Using {survdat} for Bottom Trawl Indicators

Bottom Trawl Indicators in NEESP2

This package contains functions for producing bottom trawl indicators from {survdat} data pulls: swept area biomass, stratified mean biomass, species condition, diet, and range. This vignette provides example output data tables and plots using these functions.

For more information on accessing {survdat} data, see vignette “Accessing Bottom Trawl Survey Data”.

Species Condition - Black sea bass

Uses ‘species_condition’ and ‘plot_condition’ functions in R/create_condition_indicator.R and R/plot_condition.R

condition <- species_condition(data = NEesp2::survdat_subset, LWparams = LWparams, species.codes = species.codes)

## Joining with `by = join_by(STRATUM)`
## Joining with `by = join_by(count)`

bsb_condition <- condition %>%
  subset(Species == 'Black sea bass')
head(bsb_condition)

## # A tibble: 6 x 8
##   Species        EPU    YEAR DATA_VALUE nCond     sd variance INDICATOR_NAME
##   <chr>          <chr> <dbl>      <dbl> <int>  <dbl>    <dbl> <chr>         
## 1 Black sea bass GB     1994      0.983     4 0.0330  0.00109 mean condition
## 2 Black sea bass GB     1999      0.960    15 0.0330  0.00109 mean condition
## 3 Black sea bass GB     2000      0.982     4 0.0330  0.00109 mean condition
## 4 Black sea bass GB     2003      0.965     8 0.0330  0.00109 mean condition
## 5 Black sea bass GB     2005      0.944    13 0.0330  0.00109 mean condition
## 6 Black sea bass GB     2007      0.962     7 0.0330  0.00109 mean condition

plot_condition(data = bsb_condition, var = 'Black sea bass')

Species Range - Black sea bass in fall

Uses ‘species_range’ function in R/create_bottomtrawl_indicators.R

range <- species_range(data = NEesp2::survdat_subset, species = NEesp2::species)

## Joining with `by = join_by(SVSPP)`

bsb_range <- range %>%
  subset(SPECIES == 'BLACK SEA BASS') %>%
  subset(SEASON == 'FALL') %>%
  subset(INDICATOR_NAME == c('range_lat','range_lon'))
head(bsb_range)

## # A tibble: 6 x 7
##    YEAR SEASON INDICATOR_NAME DATA_VALUE SPECIES        SVSPP INDICATOR_UNITS
##   <dbl> <chr>  <chr>               <dbl> <chr>          <dbl> <chr>          
## 1  1983 FALL   range_lat            5.33 BLACK SEA BASS   141 degrees        
## 2  1983 FALL   range_lon            5.93 BLACK SEA BASS   141 degrees        
## 3  1984 FALL   range_lat            5.67 BLACK SEA BASS   141 degrees        
## 4  1984 FALL   range_lon            5.2  BLACK SEA BASS   141 degrees        
## 5  1985 FALL   range_lat            6.57 BLACK SEA BASS   141 degrees        
## 6  1985 FALL   range_lon            5.58 BLACK SEA BASS   141 degrees

bsb_range %>%
  ggplot2::ggplot(ggplot2::aes(x = YEAR,
                               y = DATA_VALUE,
                               color = INDICATOR_NAME,
  )) +
  ggplot2::geom_point() +
  ggplot2::geom_path() + 
  ggplot2::theme_bw() +
  ggplot2::labs(title = "Black Sea Bass Range in Fall (Lat + Lon)", 
                x = "Year",
                y = "Range (degrees)") +
  ggplot2::facet_wrap('INDICATOR_NAME')

Swept area biomass - Black sea bass in fall

Uses ‘create_swept_area’ indicator in R/create_bottomtrawl_indicators.R

Modified from ‘calc_swept_area’ in {survdat} package.

bsb_swept_area <- create_swept_area(
  surveyData = NEesp2::survdat_subset,
  areaPolygon = "NEFSC strata",
  areaDescription = "STRATA",
  filterByArea = "all",
  filterBySeason = "FALL",
  groupDescription = "SVSPP",
  filterByGroup = "all",
  mergesexFlag = T,
  tidy = F,
  q = NULL,
  a = 0.0384
) %>%
  dplyr::filter(SVSPP == "141")

## Prepping data ...

## Spherical geometry (s2) switched off

## Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is FALSE

## Filtering data ...

##   [1]  3820  3880  3890  3900  3920  1352     0  3860  3840  3870  1390  1351
##  [13]  1380  3850  1360  1330  1340  3760  3790  3830  3800  3730  3810  1400
##  [25]  3770  3780  3740  3750  3908  3720  3710  1270  1370  1260  3700  1310
##  [37]  1280  3690  3680  3670  3660  3650  3630  3640  3620  1320  1290  1300
##  [49]  1240  1220  1210  3580  3610  3590  3600  1200  3560  1180  1170  1160
##  [61]  3570  1190  1230  1250  3470  3500  3510  3530  3550  3520  3540  3480
##  [73]  3450  3460  1050  1090  1130  3010  3020  3030  1100  3040  3050  1060
##  [85]  3060  3070  3080  1140  1150  1010  3090  3100  3110  3120  3130  3140
##  [97]  1020  1070  1110  1120  3150  3160  3170  1080  1730  1030  1040  3180
## [109]  3190  3200  1740  1750  3220  3230  1760  1690  3240  3250  3260  1700
## [121]  1710  3270  3280  3290  1720  3300  3310  3320  1650  1660  1670  3330
## [133]  1680  3340  3350  3360  3370  3380  3390  3400  3410  1610  1620  1630
## [145]  1640  3420  3430  3440  8510  8520  8530  8500  7500  7510  7520  7540
## [157]  7550 99999  7590  8540  7530  7570  7600  7580  8550  7610  8560  8570
## [169]  7620  7630  7640  8580  7650  7660  7670  8590  8600  8770

## Calculating Stratified Mean  ...

## Calculating Swept Area Estimate  ...

head(bsb_swept_area)

## # A tibble: 6 x 8
##    YEAR SVSPP   variance     se     sd INDICATOR_UNITS INDICATOR_NAME DATA_VALUE
##   <dbl> <dbl>      <dbl>  <dbl>  <dbl> <chr>           <chr>               <dbl>
## 1  1983   141    6.11e 8 2.47e4 1.15e6 numberstow-1    swept_area_bi~    313872.
## 2  1984   141    3.83e 7 6.19e3 1.15e6 numberstow-1    swept_area_bi~   2867870.
## 3  1985   141    1.41e 9 3.76e4 1.15e6 numberstow-1    swept_area_bi~    696770.
## 4  1986   141    2.78e 9 5.27e4 1.15e6 numberstow-1    swept_area_bi~    428373.
## 5  1987   141    4.42e10 2.10e5 1.15e6 numberstow-1    swept_area_bi~    639254.
## 6  1988   141    5.16e 9 7.19e4 1.15e6 numberstow-1    swept_area_bi~    229675.

bsb_swept_area %>%
  ggplot2::ggplot(ggplot2::aes(x = YEAR,
                               y = DATA_VALUE,
  )) +
  ggplot2::geom_point() +
  ggplot2::geom_path() + 
  ggplot2::theme_bw() +
  ggplot2::labs(title = "Black Sea Bass Swept Area Biomass (Fall)", 
                x = "Year",
                y = "Swept Area Biomass")

Stratified mean biomass - Black sea bass in fall

Uses ‘create_stratified_mean’ indicator in R/create_bottomtrawl_indicators.R

Modified from ‘calc_stratified_mean’ in {survdat} package.

bsb_strat_mean <- create_stratified_mean(
  surveyData = survdat_subset,
  areaPolygon = "NEFSC strata",
  areaDescription = "STRATA",
  filterByArea = "all",
  filterBySeason = "FALL",
  groupDescription = "SVSPP",
  filterByGroup = "all",
  mergesexFlag = T,
  tidy = F,
  returnPrepData = F
) %>%
  dplyr::filter(SVSPP == "141")

## Prepping data ...

## Filtering data ...

##   [1]  3820  3880  3890  3900  3920  1352     0  3860  3840  3870  1390  1351
##  [13]  1380  3850  1360  1330  1340  3760  3790  3830  3800  3730  3810  1400
##  [25]  3770  3780  3740  3750  3908  3720  3710  1270  1370  1260  3700  1310
##  [37]  1280  3690  3680  3670  3660  3650  3630  3640  3620  1320  1290  1300
##  [49]  1240  1220  1210  3580  3610  3590  3600  1200  3560  1180  1170  1160
##  [61]  3570  1190  1230  1250  3470  3500  3510  3530  3550  3520  3540  3480
##  [73]  3450  3460  1050  1090  1130  3010  3020  3030  1100  3040  3050  1060
##  [85]  3060  3070  3080  1140  1150  1010  3090  3100  3110  3120  3130  3140
##  [97]  1020  1070  1110  1120  3150  3160  3170  1080  1730  1030  1040  3180
## [109]  3190  3200  1740  1750  3220  3230  1760  1690  3240  3250  3260  1700
## [121]  1710  3270  3280  3290  1720  3300  3310  3320  1650  1660  1670  3330
## [133]  1680  3340  3350  3360  3370  3380  3390  3400  3410  1610  1620  1630
## [145]  1640  3420  3430  3440  8510  8520  8530  8500  7500  7510  7520  7540
## [157]  7550 99999  7590  8540  7530  7570  7600  7580  8550  7610  8560  8570
## [169]  7620  7630  7640  8580  7650  7660  7670  8590  8600  8770

## Calculating Stratified Mean  ...

head(bsb_strat_mean)

## # A tibble: 6 x 9
##    YEAR SEASON SVSPP variance     se    sd INDICATOR_UNITS INDICATOR_NAME    
##   <dbl> <chr>  <dbl>    <dbl>  <dbl> <dbl> <chr>           <chr>             
## 1  1983 FALL     141 0.000850 0.0292 0.845 kgtow-1         strat_mean_biomass
## 2  1984 FALL     141 0.000104 0.0102 0.845 kgtow-1         strat_mean_biomass
## 3  1985 FALL     141 0.00277  0.0527 0.845 kgtow-1         strat_mean_biomass
## 4  1986 FALL     141 0.00119  0.0344 0.845 kgtow-1         strat_mean_biomass
## 5  1987 FALL     141 0.0636   0.252  0.845 kgtow-1         strat_mean_biomass
## 6  1988 FALL     141 0.0233   0.153  0.845 kgtow-1         strat_mean_biomass
## # i 1 more variable: DATA_VALUE <dbl>

bsb_strat_mean %>%
  ggplot2::ggplot(ggplot2::aes(x = YEAR,
                               y = DATA_VALUE,
  )) +
  ggplot2::geom_point() +
  ggplot2::geom_path() + 
  ggplot2::theme_bw() +
  ggplot2::labs(title = "Black Sea Bass Stratified Mean Biomass (Fall)", 
                x = "Year",
                y = "Stratified Mean Biomass")

Stephanie Owen

Bottom Trawl Indicators in NEESP2

Species Condition - Black sea bass

Species Range - Black sea bass in fall

Swept area biomass - Black sea bass in fall

Stratified mean biomass - Black sea bass in fall