Computing PSD and Relative Weight Metrics in FSA
2026-01-09
Source:vignettes/articles/Computing_PSDs_and_RelativeWeights.qmd
Introduction
Other vignettes introduced using FSA to compute proportional size distribution (PSD) and relative weight (i.e., condition) metrics. Both of those vignettes mentioned some peculiarities in their methodology related to when PSDs and relative weights were computed concurrently on the same data that contained some “issues.” These peculiarities and issues are explained further and how to handle them are illustrated here. I urge you to explore those other vignettes before continuing here.
The following packages are used herein. Note that the FSA functions described here were modified after version 0.9.6 and are thus specific to FSA >v0.9.6.
Data
The hypothetical PSDWRtest data.frame distributed with FSA was created to purposely provide data for a variety of species that were realistic but created some issues for the psdAdd() and wrAdd() functions described in the other vignettes.
peek(PSDWRtest,n=20)
#> species location len wt sex
#> 1 Bluegill Sunfish Bass Lake 107 25.8 <NA>
#> 53 Bluegill Sunfish Bass Lake 116 34.8 <NA>
#> 107 Bluegill Sunfish Bass Lake 191 138.3 <NA>
#> 160 Brook Trout Trout Lake 291 NA <NA>
#> 214 Brown Trout Trout Lake 151 45.4 <NA>
#> 267 Brown Trout Trout Lake 190 86.3 <NA>
#> 321 Brown Trout Brushy Creek 318 198.4 M
#> 374 Brown Trout Brushy Creek 446 533.4 F
#> 428 Largemouth Bass Bass Lake 199 70.1 <NA>
#> 481 Largemouth Bass Bass Lake 306 311.9 <NA>
#> 535 Lean Lake Trout Trout Lake 529 1480.0 F
#> 588 Lean Lake Trout Trout Lake 809 5448.1 F
#> 642 Muskellunge Long Lake 1097 11376.4 U
#> 695 Walleye Bass Lake 72 3.5 <NA>
#> 749 Walleye Bass Lake 307 273.6 M
#> 802 Walleye Bass Lake 345 429.8 F
#> 856 Yellow Perch Bass Lake 165 59.4 F
#> 909 Yellow Perch Bass Lake 150 40.2 F
#> 963 Yellow Perch Bass Lake 241 187.9 F
#> 1016 Yellow Perch Bass Lake 322 520.0 FUltimately it is best that you have a full understanding of the issues that may arise with your data by carefully examining your data and understanding the Gabelhouse (GH) length categories and relative weight equations for the species in your data. There are several “issues” that need to be addressed with the PSDWRtest data.
First, Bluegill and Lake Trout exist in PSDlit and WSlit but appear as “Bluegill Sunfish” and “Lean Lake Trout” in PSDWRtest.
Second, Brook Trout were sampled from a lotic (“Trout Lake”) system and Brown Trout were sampled from a lotic (“Trout Lake”) and a lentic (“Brush Creek”) system. There are separate GH length categories and standard weight equations for these sub-groups for each species.
Third, Muskellunge and Walleye provide a challenge because standard weight equations differ among sub-groups for each of these species, but the GH length categories do not differ among sub-groups. Walleye use separate standard weight equations depending on whether the individual’s total length is less than 150 mm or not. Muskellunge have a sex-specific standard weight equation for when sex is known, but an overall equation for when sex is unknown. As will be seen, a new species variable will be created that incorporates the subgroup name into the “species name” for calculating standard weights (as was illustrated in this vignette). Because the GH length categories don’t differ by sub-group for either of these species, these new names are not needed when finding the GH length categories. However, for simplicity (as illustrated further below), these GH length categories have been duplicated for the sub-groups of each species and labelled with the combined species and sub-group name. This is illustrated below for muskellunge.
wsVal("Muskellunge (overall)") # different from next two
#> species measure units ref method min.TL int slope
#> 138 Muskellunge (overall) TL metric 75 RLP 380 -6.066 3.325
#> source
#> 138 Neumann and Willis (1994)
wsVal("Muskellunge (female)")
#> species measure units ref method min.TL int slope
#> 134 Muskellunge (female) TL metric 75 RLP 380 -6.105 3.34
#> source
#> 134 Neumann and Willis (1994)
wsVal("Muskellunge (male)")
#> species measure units ref method min.TL int slope
#> 136 Muskellunge (male) TL metric 75 RLP 380 -5.823 3.245
#> source
#> 136 Neumann and Willis (1994)
psdVal("Muskellunge (overall)") # exact same as next two
#> substock stock quality preferred memorable trophy
#> 0 510 760 970 1070 1270
psdVal("Muskellunge (female)")
#> substock stock quality preferred memorable trophy
#> 0 510 760 970 1070 1270
psdVal("Muskellunge (male)")
#> substock stock quality preferred memorable trophy
#> 0 510 760 970 1070 1270Fourth, Ruffe for which the reference quantile of the standard weight equation must be specified.
Adding GH Length Category and Wr Variables
The easiest way to deal with all of these “issues” except for the one related to Ruffe is to create a new “species” variable (i.e., species2 below) that appends the specific sub-groups in parentheses to the species name. There are a variety of ways to do this and which way (is best or works) may depend on the specifics of the situation. Here, we use case_when() from dplyr with a series of statements that begin with a “condition” to the left of the ~ and new species “name” for that condition to the right of the ~. The .default=species at the end puts the name from species into species2 for all situations where none of the conditions above it are met (e.g., if species is “Yellow Perch” then species2 will be “Yellow Perch”).
PSDWRtest <- PSDWRtest |>
mutate(species2=case_when(
species=="Bluegill Sunfish" ~ "Bluegill",
species=="Lean Lake Trout" ~ "Lake Trout",
species=="Brown Trout" & location=="Trout Lake" ~ "Brown Trout (lotic)",
species=="Brown Trout" & location=="Brushy Creek" ~ "Brown Trout (lentic)",
species=="Brook Trout" & location=="Trout Lake" ~ "Brook Trout (lotic)",
species=="Muskellunge" & sex=="M" ~ "Muskellunge (male)",
species=="Muskellunge" & sex=="F" ~ "Muskellunge (female)",
species=="Muskellunge" & sex=="U" ~ "Muskellunge (overall)",
species=="Muskellunge" & is.na(sex) ~ "Muskellunge (overall)",
species=="Walleye" & len>=150 ~ "Walleye (overall)",
species=="Walleye" & len<150 ~ "Walleye (30-149 mm)",
.default=species
))
peek(PSDWRtest,n=20)
#> species location len wt sex species2
#> 1 Bluegill Sunfish Bass Lake 107 25.8 <NA> Bluegill
#> 53 Bluegill Sunfish Bass Lake 116 34.8 <NA> Bluegill
#> 107 Bluegill Sunfish Bass Lake 191 138.3 <NA> Bluegill
#> 160 Brook Trout Trout Lake 291 NA <NA> Brook Trout (lotic)
#> 214 Brown Trout Trout Lake 151 45.4 <NA> Brown Trout (lotic)
#> 267 Brown Trout Trout Lake 190 86.3 <NA> Brown Trout (lotic)
#> 321 Brown Trout Brushy Creek 318 198.4 M Brown Trout (lentic)
#> 374 Brown Trout Brushy Creek 446 533.4 F Brown Trout (lentic)
#> 428 Largemouth Bass Bass Lake 199 70.1 <NA> Largemouth Bass
#> 481 Largemouth Bass Bass Lake 306 311.9 <NA> Largemouth Bass
#> 535 Lean Lake Trout Trout Lake 529 1480.0 F Lake Trout
#> 588 Lean Lake Trout Trout Lake 809 5448.1 F Lake Trout
#> 642 Muskellunge Long Lake 1097 11376.4 U Muskellunge (overall)
#> 695 Walleye Bass Lake 72 3.5 <NA> Walleye (30-149 mm)
#> 749 Walleye Bass Lake 307 273.6 M Walleye (overall)
#> 802 Walleye Bass Lake 345 429.8 F Walleye (overall)
#> 856 Yellow Perch Bass Lake 165 59.4 F Yellow Perch
#> 909 Yellow Perch Bass Lake 150 40.2 F Yellow Perch
#> 963 Yellow Perch Bass Lake 241 187.9 F Yellow Perch
#> 1016 Yellow Perch Bass Lake 322 520.0 F Yellow PerchThe GH length categories and relative weights for each fish (for species with standard weight equations) is added to this data.drame with psdAdd() and wrAdd() as described in the other vignettes, specifically noting the use of the “new” species variable species2. Further note the use of wsOpts= to define which reference quantile to use for the Ruffe standard weight equation.
PSDWRtest$psd <- psdAdd(len~species2,data=PSDWRtest)
#> Species in the data with no Gabelhouse (PSD) lengths in `PSDlit`: "Iowa
#> Darter".
PSDWRtest$wr <- wrAdd(wt~len+species2,data=PSDWRtest,
WsOpts=list(Ruffe=list(ref=75)))
peek(PSDWRtest,n=20)
#> species location len wt sex species2
#> 1 Bluegill Sunfish Bass Lake 107 25.8 <NA> Bluegill
#> 53 Bluegill Sunfish Bass Lake 116 34.8 <NA> Bluegill
#> 107 Bluegill Sunfish Bass Lake 191 138.3 <NA> Bluegill
#> 160 Brook Trout Trout Lake 291 NA <NA> Brook Trout (lotic)
#> 214 Brown Trout Trout Lake 151 45.4 <NA> Brown Trout (lotic)
#> 267 Brown Trout Trout Lake 190 86.3 <NA> Brown Trout (lotic)
#> 321 Brown Trout Brushy Creek 318 198.4 M Brown Trout (lentic)
#> 374 Brown Trout Brushy Creek 446 533.4 F Brown Trout (lentic)
#> 428 Largemouth Bass Bass Lake 199 70.1 <NA> Largemouth Bass
#> 481 Largemouth Bass Bass Lake 306 311.9 <NA> Largemouth Bass
#> 535 Lean Lake Trout Trout Lake 529 1480.0 F Lake Trout
#> 588 Lean Lake Trout Trout Lake 809 5448.1 F Lake Trout
#> 642 Muskellunge Long Lake 1097 11376.4 U Muskellunge (overall)
#> 695 Walleye Bass Lake 72 3.5 <NA> Walleye (30-149 mm)
#> 749 Walleye Bass Lake 307 273.6 M Walleye (overall)
#> 802 Walleye Bass Lake 345 429.8 F Walleye (overall)
#> 856 Yellow Perch Bass Lake 165 59.4 F Yellow Perch
#> 909 Yellow Perch Bass Lake 150 40.2 F Yellow Perch
#> 963 Yellow Perch Bass Lake 241 187.9 F Yellow Perch
#> 1016 Yellow Perch Bass Lake 322 520.0 F Yellow Perch
#> psd wr
#> 1 stock 113.81070
#> 53 stock 117.44555
#> 107 quality 89.31318
#> 160 quality NA
#> 214 stock 118.65447
#> 267 stock 114.26156
#> 321 quality 53.30764
#> 374 preferred 48.64940
#> 428 substock 70.72483
#> 481 quality 76.95718
#> 535 quality 102.54739
#> 588 memorable 95.07015
#> 642 memorable 103.11404
#> 695 substock 104.56374
#> 749 stock 95.72295
#> 802 stock 103.75325
#> 856 stock 99.38328
#> 909 stock 91.50636
#> 963 quality 92.47232
#> 1016 memorable 100.37577