FroeseWs: Computes the standard weight equation using the methods...
In droglenc/FSAWs: Construct and Validate Standard Weight (Ws) Equations for Fish

FroeseWs

R Documentation

Computes the standard weight equation using the methods described in Froese (2006).

Description

Computes the standard weight equation using the geometric mean of a and the mean of b from weight-length regression equations as described in Froese (2006).

Usage

FroeseWs(log.a, b)

## S3 method for class 'FroeseWs'
coef(object, ...)

## S3 method for class 'FroeseWs'
plot(
  x,
  min,
  max,
  what = c("both", "raw", "log"),
  col.pop = "rainbow",
  lwd.pop = 1,
  lty.pop = 1,
  order.pop = TRUE,
  col.Ws = "black",
  lwd.Ws = 3,
  lty.Ws = 1,
  ...
)

Arguments

`log.a`	A numeric vector that contains the log_{10}(a) values for the population of length-weight regression equations.
`b`	A numeric vector that contains the b values for the population of length-weight regression equations
`...`	Additional arguments for methods.
`x, object`	An object saved from the `FrowseWs()` call (i.e., of class `Froese`).
`min`	A number that indicates the midpoint value of the smallest X-mm length to model.
`max`	A number that indicates the midpoint value of the largest X-mm length category.
`what`	A string that indicates the type of plot to produce. See details.
`col.pop`	A string that indicates the type of color or palette to use for the population of length-weight regression lines. See details.
`lwd.pop`	A numeric that indicates the width of the line to use for the population of length-weight regression lines.
`lty.pop`	A numeric that indicates the type of line to use for the population of length-weight regression lines.
`order.pop`	A logical that indicates whether the populations should be plotted from the smallest to largest weight in the initial length category. See details.
`col.Ws`	A string that indicates the type of color to use for the standard length-weight regression line.
`lwd.Ws`	A numeric that indicates the width of the line to use for the standard length-weight regression line.
`lty.Ws`	A numeric that indicates the type of line to use for the standard length-weight regression line.

Details

The main function computes the mean of the log_{10}(a) and b values for the standard weight equation as detailed in Froese (2006). Note that log_{10}(a) and b must be from the regression of log_{10}(W) on log_{10}(L) where W is measured in grams and L is the total length measured in mm.

The what argument in the plot method can be set to "both", "log", or "raw". The "raw" plot shows lines on the length-weight scale for each population with the resultant standard weight equation superimposed in red. The "log" plot constructs a similar plot but on the log_{10}(weight)-log_{10}(length) scale. The "both" option produces both plots side-by-side. If the col.pop argument is one of "rainbow", "heat", "topo", "terrain", "cm", "default", or "grey" and order.pop=TRUE then the populations plotted should form a general color gradient from smallest to largest weight in the initial length category. This will make it easier to identify populations that “cross over” other populations.

coef returns the geometric mean of a and the mean of b to serve as the standard weight equation as described in Froese (2006).

Value

A list is returned with the following items:

log.a is a numeric vector of the observed log_{10}(a) values sent in the log.a argument.
b is a numeric vector of the observed b values sent in the b argument.
gm.a is a numeric that contains the geometric mean of the a parameter. This is simply the back-transformed mean log_{10}(a) value – i.e., 10^{log_{10}(a)}.
mn.b is the arithmetic mean of the b parameter. mn.log.a is the arithmetic mean of log_{10}(a).

References

Froese, R. 2006. Cube law, condition factor and weight-length relationships: history, meta-analysis and recommendations. Journal of Applied Ichthyology 22:241-253.