curve_change {codyn} | R Documentation |
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
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)