Back-calculates length at previous ages from a data.frame that was primarily created from combineData and digitizeRadii. One of several back-calculation models, described in bcFuns and Vigliola and Meekan (2009), can be used. Parameter estimates from various models of fish length on structure radius or structure radius on fish length are computed internally and used in the back-calculations. This function is intended to make back-calculation of fish length at previous ages as streamlined as possible.
backCalc(
dat,
lencap,
BCM,
inFormat,
outFormat = inFormat,
a = NULL,
L0p = NULL,
R0p = NULL,
L0 = NULL,
R0 = NULL,
deletePlusGrowth = TRUE,
digits = getOption("digits")
)A data.frame created with combineData that MUST have at least the length-at-capture appended as a variable. See Details.
The unquoted name of the length-at-capture variable.
A single numeric between 1 and 22 or a string that indicates which model to use (based on numbers and names in Vigliola and Meekan (2009)). See Details in bcFuns for the list of available models.
The format of the data in dat. The two choices are "long" with one radial measurement per line (and all radial measurements for a fish in separate rows) and "wide" with one fish per line (and all radial measurements in separate variables). Defaults to "long".
The format for the returned data.frame. Choices are as described for inFormat. Defaults to be the same as inFormat.
The fish length when the structure first forms as used in the Fraser-Lee model (i.e., BCM=1 or BCM="FRALE"). If this is missing then a will be estimated as the intercept from the fish length on structure radius linear regression.
The length at the “Biological Intercept” point. Only used in the “Biological Intercept” (BCM=3), “Watanabe and Kuroki” (BCM=12), and “Modified Fry” (BCM=14) models.
The structure radius at the “Biological Intercept” point. Only used in the “Biological Intercept” (BCM=3), “Watanabe and Kuroki” (BCM=12), and “Modified Fry” (BCM=14) models.
The length at the arbitrarily selected point in the “Fry” (BCM=13) model.
The structure radius at the arbitrarily selected point in the “Fry” (BCM=13) model.
A logical that indicates whether the radial measurement that corresponds to “plus-growth” on the structure should be deleted (TRUE; Default) or not (FALSE).
Number of digits to which the back-calculated lengths should be rounded. Defaults to the value returned by getOptions("digits"), which is generally 7 digits.
A data.frame similar to dat but with the radial measurements replaced by back-calculated lengths at previous ages.
## Get some data
data(SMBassWB1,package="RFishBC") ## fish data
data(SMBassWB2,package="RFishBC") ## rad data
# Simplify to 3 fish so we can see what is going on
tmp1 <- subset(SMBassWB1,id %in% c(377,378,379))
tmp2 <- subset(SMBassWB2,id %in% c(377,378,379))
# Combine data frames to form a wide data frame (i.e., a left join)
wdat1 <- merge(tmp1,tmp2,by="id",all.x=TRUE)
wdat1
#> id species lake gear yearcap lencap reading agecap radcap rad1 rad2
#> 1 377 SMB WB E 1990 244 DHO 7 7.32901 1.14855 2.40505
#> 2 378 SMB WB E 1990 205 DHO 6 5.68903 1.44620 2.30517
#> 3 379 SMB WB E 1990 117 DHO 2 3.05503 1.59628 3.05503
#> rad3 rad4 rad5 rad6 rad7 rad8 rad9
#> 1 3.43185 4.32332 5.25482 6.36840 7.32901 NA NA
#> 2 3.24254 4.23761 4.91082 5.68903 NA NA NA
#> 3 NA NA NA NA NA NA NA
# Make a long data frame for examples (remove annuli with NA rads)
ldat1 <- tidyr::pivot_longer(wdat1,rad1:rad9,names_to="ann",names_prefix="rad",
values_to="rad")
ldat1 <- subset(ldat1,!is.na(rad))
ldat1 <- as.data.frame(ldat1)
ldat1
#> id species lake gear yearcap lencap reading agecap radcap ann rad
#> 1 377 SMB WB E 1990 244 DHO 7 7.32901 1 1.14855
#> 2 377 SMB WB E 1990 244 DHO 7 7.32901 2 2.40505
#> 3 377 SMB WB E 1990 244 DHO 7 7.32901 3 3.43185
#> 4 377 SMB WB E 1990 244 DHO 7 7.32901 4 4.32332
#> 5 377 SMB WB E 1990 244 DHO 7 7.32901 5 5.25482
#> 6 377 SMB WB E 1990 244 DHO 7 7.32901 6 6.36840
#> 7 377 SMB WB E 1990 244 DHO 7 7.32901 7 7.32901
#> 8 378 SMB WB E 1990 205 DHO 6 5.68903 1 1.44620
#> 9 378 SMB WB E 1990 205 DHO 6 5.68903 2 2.30517
#> 10 378 SMB WB E 1990 205 DHO 6 5.68903 3 3.24254
#> 11 378 SMB WB E 1990 205 DHO 6 5.68903 4 4.23761
#> 12 378 SMB WB E 1990 205 DHO 6 5.68903 5 4.91082
#> 13 378 SMB WB E 1990 205 DHO 6 5.68903 6 5.68903
#> 14 379 SMB WB E 1990 117 DHO 2 3.05503 1 1.59628
#> 15 379 SMB WB E 1990 117 DHO 2 3.05503 2 3.05503
## Back-calculate using Dahl-Lea method
# wide in and wide out
wwres1 <- backCalc(wdat1,lencap,BCM="DALE",inFormat="wide",digits=0)
#> ✔ Using the Dahl-Lea model.
wwres1
#> # A tibble: 3 × 15
#> id species lake gear yearcap lencap reading agecap len1 len2 len3
#> <dbl> <fct> <fct> <fct> <int> <int> <chr> <int> <dbl> <dbl> <dbl>
#> 1 377 SMB WB E 1990 244 DHO 7 38 80 114
#> 2 378 SMB WB E 1990 205 DHO 6 52 83 117
#> 3 379 SMB WB E 1990 117 DHO 2 61 117 NA
#> # ℹ 4 more variables: len4 <dbl>, len5 <dbl>, len6 <dbl>, len7 <dbl>
# wide in and long out
wlres1 <- backCalc(wdat1,lencap,BCM="DALE",inFormat="wide",
outFormat="long",digits=0)
#> ✔ Using the Dahl-Lea model.
wlres1
#> # A tibble: 15 × 10
#> id species lake gear yearcap lencap reading agecap ann bclen
#> <dbl> <fct> <fct> <fct> <int> <int> <chr> <int> <dbl> <dbl>
#> 1 377 SMB WB E 1990 244 DHO 7 1 38
#> 2 377 SMB WB E 1990 244 DHO 7 2 80
#> 3 377 SMB WB E 1990 244 DHO 7 3 114
#> 4 377 SMB WB E 1990 244 DHO 7 4 144
#> 5 377 SMB WB E 1990 244 DHO 7 5 175
#> 6 377 SMB WB E 1990 244 DHO 7 6 212
#> 7 377 SMB WB E 1990 244 DHO 7 7 244
#> 8 378 SMB WB E 1990 205 DHO 6 1 52
#> 9 378 SMB WB E 1990 205 DHO 6 2 83
#> 10 378 SMB WB E 1990 205 DHO 6 3 117
#> 11 378 SMB WB E 1990 205 DHO 6 4 153
#> 12 378 SMB WB E 1990 205 DHO 6 5 177
#> 13 378 SMB WB E 1990 205 DHO 6 6 205
#> 14 379 SMB WB E 1990 117 DHO 2 1 61
#> 15 379 SMB WB E 1990 117 DHO 2 2 117
# long in and wide out
lwres1 <- backCalc(ldat1,lencap,BCM="DALE",inFormat="long",digits=0)
#> ✔ Using the Dahl-Lea model.
lwres1
#> id species lake gear yearcap lencap reading agecap ann bclen
#> 1 377 SMB WB E 1990 244 DHO 7 1 38
#> 2 377 SMB WB E 1990 244 DHO 7 2 80
#> 3 377 SMB WB E 1990 244 DHO 7 3 114
#> 4 377 SMB WB E 1990 244 DHO 7 4 144
#> 5 377 SMB WB E 1990 244 DHO 7 5 175
#> 6 377 SMB WB E 1990 244 DHO 7 6 212
#> 7 377 SMB WB E 1990 244 DHO 7 7 244
#> 8 378 SMB WB E 1990 205 DHO 6 1 52
#> 9 378 SMB WB E 1990 205 DHO 6 2 83
#> 10 378 SMB WB E 1990 205 DHO 6 3 117
#> 11 378 SMB WB E 1990 205 DHO 6 4 153
#> 12 378 SMB WB E 1990 205 DHO 6 5 177
#> 13 378 SMB WB E 1990 205 DHO 6 6 205
#> 14 379 SMB WB E 1990 117 DHO 2 1 61
#> 15 379 SMB WB E 1990 117 DHO 2 2 117
# wide in and long out
llres1 <- backCalc(ldat1,lencap,BCM="DALE",inFormat="long",
outFormat="long",digits=0)
#> ✔ Using the Dahl-Lea model.
llres1
#> id species lake gear yearcap lencap reading agecap ann bclen
#> 1 377 SMB WB E 1990 244 DHO 7 1 38
#> 2 377 SMB WB E 1990 244 DHO 7 2 80
#> 3 377 SMB WB E 1990 244 DHO 7 3 114
#> 4 377 SMB WB E 1990 244 DHO 7 4 144
#> 5 377 SMB WB E 1990 244 DHO 7 5 175
#> 6 377 SMB WB E 1990 244 DHO 7 6 212
#> 7 377 SMB WB E 1990 244 DHO 7 7 244
#> 8 378 SMB WB E 1990 205 DHO 6 1 52
#> 9 378 SMB WB E 1990 205 DHO 6 2 83
#> 10 378 SMB WB E 1990 205 DHO 6 3 117
#> 11 378 SMB WB E 1990 205 DHO 6 4 153
#> 12 378 SMB WB E 1990 205 DHO 6 5 177
#> 13 378 SMB WB E 1990 205 DHO 6 6 205
#> 14 379 SMB WB E 1990 117 DHO 2 1 61
#> 15 379 SMB WB E 1990 117 DHO 2 2 117
## Situation with no radial measurements for some fish
# Create an extra fish with length (tmp1) but no rad
tmp1a <- rbind(tmp1,
data.frame(id=999,
species="SMB",lake="WB",gear="E",
yearcap=1990,lencap=225))
wdat2 <- merge(tmp1a,tmp2,by="id",all.x=TRUE)
wdat2
#> id species lake gear yearcap lencap reading agecap radcap rad1 rad2
#> 1 377 SMB WB E 1990 244 DHO 7 7.32901 1.14855 2.40505
#> 2 378 SMB WB E 1990 205 DHO 6 5.68903 1.44620 2.30517
#> 3 379 SMB WB E 1990 117 DHO 2 3.05503 1.59628 3.05503
#> 4 999 SMB WB E 1990 225 <NA> NA NA NA NA
#> rad3 rad4 rad5 rad6 rad7 rad8 rad9
#> 1 3.43185 4.32332 5.25482 6.36840 7.32901 NA NA
#> 2 3.24254 4.23761 4.91082 5.68903 NA NA NA
#> 3 NA NA NA NA NA NA NA
#> 4 NA NA NA NA NA NA NA
# wide in and wide out
wwres2 <- backCalc(wdat2,lencap,BCM="DALE",inFormat="wide",digits=0)
#> ✔ Using the Dahl-Lea model.
wwres2
#> # A tibble: 4 × 15
#> id species lake gear yearcap lencap reading agecap len1 len2 len3
#> <dbl> <fct> <fct> <fct> <dbl> <dbl> <chr> <int> <dbl> <dbl> <dbl>
#> 1 377 SMB WB E 1990 244 DHO 7 38 80 114
#> 2 378 SMB WB E 1990 205 DHO 6 52 83 117
#> 3 379 SMB WB E 1990 117 DHO 2 61 117 NA
#> 4 999 SMB WB E 1990 225 NA NA NA NA NA
#> # ℹ 4 more variables: len4 <dbl>, len5 <dbl>, len6 <dbl>, len7 <dbl>