rate_change_interval {codyn}

Differences in community composition over successive time lag intervals

Description

Calculates the differences in species composition within a community over increasing time intervals. Differences in species composition are characterized by Euclidean distances, which are calculated on pair-wise communities across the entire time series. For example, a data set with 6 time intervals will have distance values for five one-year time lags (year 1 vs year 2, year 2 vs year 3 ...), 4 two-year time lags (year 1 vs year 3, year 2 vs year 4 ...) and so forth. Returns the full set of community distance values and associated time lag intervals.

Usage

rate_change_interval(
  df,
  time.var,
  species.var,
  abundance.var,
  replicate.var = NA
)

Arguments

df

A data frame containing time, species and abundance columns and an optional column 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

Value

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

• interval: A numeric column containing the interval length between time periods.

• distance: A numeric column containing the Euclidean distances.

• replicate.var: A column that shares the same name and type as the replicate.var column in the input data frame.

The input data frame needs to contain columns for time, species and abundance; time.var, species.var and abundance.var are used to indicate which columns contain those variables. If multiple replicates are included in the data frame, that column should be specified with replicate.var. Each replicate should reflect a single experimental unit - there must be a single abundance value per species within each time point and replicate.

References

Collins, S. L., Micheli, F. and Hartt, L. 2000. A method to determine rates and patterns of variability in ecological communities. - Oikos 91: 285-293.

Examples

data(knz_001d)
rate_change_interval(knz_001d[knz_001d$subplot=="A_1",], 
                     time.var = "year", 
                     species.var = "species",
                     abundance.var = "abundance") # for one subplot
                     
                     
rate_change_interval(knz_001d, 
                     time.var = "year", 
                     species.var = "species",
                     abundance.var = "abundance",
                      replicate.var = "subplot") # across all subplots