Length-frequency histogram with Gabelhouse lengths highlighted.

Constructs a length-frequency histogram with Gabelhouse lengths highlighted.

Usage

psdPlot(
  formula,
  data,
  species = "List",
  units = c("mm", "cm", "in"),
  startcat = 0,
  w = 1,
  justPSDQ = FALSE,
  main = "",
  xlab = "Length",
  ylab = "Number",
  xlim = NULL,
  ylim = c(0, max(h$counts) * 1.05),
  substock.col = "white",
  stock.col = "gray90",
  psd.col = "black",
  psd.lty = 2,
  psd.lwd = 1,
  show.abbrevs = TRUE,
  psd.add = TRUE,
  psd.pos = "topleft",
  psd.cex = 0.75,
  ...
)

Arguments

formula: A formula of the form ~length where “length” generically represents a variable in data that contains length measurements. Note that this formula can only contain one variable.
data: A data.frame that minimally contains the length measurements given in the variable in the formula.
species: A string that contains the species name for which Gabelhouse length categories exist. See psdVal for details.
units: A string that indicates the type of units used for the length measurements. Choices are mm for millimeters (DEFAULT), cm for centimeters, and in for inches.
startcat: A number that indicates the beginning of the first length-class.
w: A number that indicates the width of length classes to create.
justPSDQ: A logical that indicates whether just stock and quality (for PSD-Q calculations) categories should be used. If FALSE (default) then the five Gabelhouse categories will be used.
main: A string that serves as the main label for the histogram.
xlab: A string that serves as the label for the x-axis.
ylab: A string that serves as the label for the y-axis.
xlim: A numeric vector of length two that indicates the minimum and maximum values (i.e., fish lengths) for the x-axis.
ylim: A numeric vector of length two that indicates the minimum and maximum values for the y-axis.
substock.col: A string that indicates the color to use for the bars representing under-stock size fish.
stock.col: A string that indicates the color to use for the bars representing stock size fish.
psd.col: A string that indicates the color to use for the vertical lines at the Gabelhouse length category values.
psd.lty: A numeric that indicates the line type to use for the vertical lines at the Gabelhouse length category values.
psd.lwd: A numeric that indicates the line width to use for the vertical lines at the Gabelhouse length category values.
show.abbrevs: A logical that indicates if the abbreviations for the Gabelhouse length categories should be added to the top of the plot.
psd.add: A logical that indicates if the calculated PSD values should be added to the plot (default is TRUE).
psd.pos: A string that indicates the position for where the PSD values will be shown. See details in legend.
psd.cex: A numeric value that indicates the character expansion for the PSD values text.
...: Arguments to be passed to the low-level plotting functions.

Value

None. However, a graphic is produced.

Details

Constructs a length-frequency histogram with the stock-sized fish highlighted, the Gabelhouse lengths marked by vertical lines, and the (traditional) PSD-X values superimposed.

The length of fish plotted on the x-axis can be controlled with xlim, however, the minimum value in xlim must be less than the stock length for that species.

IFAR Chapter

6-Size Structure.

References

Ogle, D.H. 2016. Introductory Fisheries Analyses with R. Chapman & Hall/CRC, Boca Raton, FL.

Guy, C.S., R.M. Neumann, and D.W. Willis. 2006. New terminology for proportional stock density (PSD) and relative stock density (RSD): proportional size structure (PSS). Fisheries 31:86-87. [Was (is?) from http://pubstorage.sdstate.edu/wfs/415-F.pdf.]

Guy, C.S., R.M. Neumann, D.W. Willis, and R.O. Anderson. 2006. Proportional size distribution (PSD): A further refinement of population size structure index terminology. Fisheries 32:348. [Was (is?) from http://pubstorage.sdstate.edu/wfs/450-F.pdf.]

Willis, D.W., B.R. Murphy, and C.S. Guy. 1993. Stock density indices: development, use, and limitations. Reviews in Fisheries Science 1:203-222. [Was (is?) from http://web1.cnre.vt.edu/murphybr/web/Readings/Willis%20et%20al.pdf.]

Author

Derek H. Ogle, DerekOgle51@gmail.com

Examples

## Random length data
# suppose this is yellow perch to the nearest mm
df <- data.frame(spec=rep("Yellow Perch",170),
                 mm=c(rnorm(100,mean=125,sd=15),rnorm(50,mean=200,sd=25),
                      rnorm(20,mean=300,sd=40)))

## Example graphics
op <- par(mar=c(3,3,2,1),mgp=c(1.7,0.5,0))
# Using 10-mm increments
psdPlot(~mm,data=df,species="Yellow perch",w=10)

psdPlot(~mm,data=df,species="Yellow perch",w=10,substock.col="gray90",
        stock.col="gray30")

# ... but without the PSD values
psdPlot(~mm,data=df,species="Yellow perch",w=10,psd.add=FALSE)

par(op)