codyn (version 2.0.5)

curve_change: Curve Change

Description

Calculates the area difference between two rank abundance curves between two time periods. If replicate is specified, it must be measured in both time points, otherwise it will be dropped for that time period comparison.

Usage

curve_change(
  df,
  time.var,
  species.var,
  abundance.var,
  replicate.var = NULL,
  reference.time = NULL
)

Arguments

df

A data frame containing time, species, and abundance columns and an optional columns of replicates.

time.var

The name of the time column.

species.var

The name of the species column.

abundance.var

The name of the abundance column.

replicate.var

The name of the optional replicate column. If specified, replicate must be unique within the dataset and cannot be nested within treatments or blocks.

reference.time

The name of the optional time point that all other time points should be compared to (e.g. the first year of data). If not specified, each comparison is between consecutive time points (the first and second year, second and third year, etc.)

Value

The curve_change function returns a data frame with the following attributes:

• time.var: A column with the specified time.var and a second column, with '2' appended to the name. Time is subtracted from time2.

• curve_change: A numeric column of the change in curves between time points.

• replicate.var: A column that has same name and type as the replicate.var column, if specified.

References

Avolio et al. Submitted

Examples

# NOT RUN {
data(pplots)
# Without replicates
df <- subset(pplots, plot == 25)
curve_change(df = df,
           species.var = "species",
           abundance.var = "relative_cover",
           time.var = "year")

# With replicates
df <- subset(pplots, year < 2004 & plot %in% c(6, 25, 32))
curve_change(df = df,
           species.var = "species",
           abundance.var = "relative_cover",
           replicate.var = "plot",
           time.var = "year")
           
# With reference year
df <- subset(pplots, year < 2005 & plot %in% c(6, 25, 32))
curve_change(df = df,
           species.var = "species",
           abundance.var = "relative_cover",
           replicate.var = "plot",
           time.var = "year",
           reference.time = 2002)
# }