Learn R Programming

FSA (version 0.8.8)

WSlit: All known standard weight equations.

Description

Parameters for all known standard weight equations.

Arguments

Format

A data frame with observations on the following 13 variables:
species
Species name.
units
Units of measurements. Metric uses lengths in mm and weight in grams. English uses lengths in inches and weight in pounds.
type
Type of equation (linear or quadratic).
ref
Reference quartile (75, 50, or 25).
measure
The type of length measurement used -- total length (TL) or fork length (FL).
method
The type of method used to derive the equation (RLP,EmP, or Other).
min.len
Minimum total length (mm or in, depending on units) for which the equation should be applied.
max.len
Maximum total length (mm or in, depending on units) for which the equation should be applied.
int
The intercept for the model.
slope
The slope for the linear models or the linear coefficient for the quadratic equation.
quad
The quadratic coefficient in the quadratic equations.
source
Source of the equation. These match the sources given in Neumann et al. 2012.
comment
Comments about use of equation.

Source

Most of these equations can be found in Neumann, R.M., C.S. Guy, and D.W. Willis. 2012. Length, Weight, and Associated Indices. Chapter 14 in Zale, A.V., D.L. Parrish, and T.M. Sutton, editors. Fisheries Techniques. American Fisheries Society, Bethesda, MD. Some species were not in Neumann et al (2012) and are noted as such in the comments variable.

Topic(s)

  • Relative weight
  • Standard weight
  • Condition

IFAR Chapter

8-Condition.

Details

The minimum TL for the English units were derived by rounding the converted minimum TL for the metric units to what seemed like common units (inches, half inches, or quarter inches).

References

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

See Also

See wsVal and wrAdd for related functionality.

Examples

Run this code
data(WSlit)
str(WSlit)
head(WSlit)

Run the code above in your browser using DataLab