codyn (version 2.0.0)

multivariate_difference: Using dissimilarity-based metrics to calculate differences in composition and dispersion between pairs of treatments at a single time point

Description

Calculates the difference in composition and dispersion between treatments based off a Bray-Curtis dissimilarity matrix at a single point in time. Composition difference is the euclidean distance between the centroids of different treatments. Since centroid distance is based on plotted distance between centroids, it is context dependent and depends on how many centroids are being plotted. The centroid distance between treatments depends on how many treatments are being compared. Dispersion difference is the difference of average dispersion of each replicate to its centroid between two treatments.

Usage

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

Arguments

df

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

time.var

The name of the optional time column

species.var

The name of the species column

abundance.var

The name of the abundance column

replicate.var

The name of the replicate column. Replicate must be unique within the dataset and cannot be nested within treatments or blocks.

treatment.var

the name of the treatment column

reference.treatment

The name of the optional treatment that all other treatments will be compared to (e.g. only controls will be compared to all other treatments). If not specified all pairwise treatment comparisons will be made.

Value

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

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

• treatment.var2: A column that has the same type as the treatment.var column, and is named treatment.var with a 2 appended to it.

• composition_diff: A numeric column that is the euclidean distance between the centroids of two treatments at a single point in time.

• abs_dispersion_diff: A numeric column that is the absolute value of the difference in the average dispersion of the replicates around the centroid for the two treatments.

• trt_greater_disp: A column that has same type as the treatment.var column, and specifies which of the two treatments has greater dispersion.

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

References

Avolio et al. Submitted to MEE, Avolio et al. 2015, Marti Anderson et al. 2006

Examples

# NOT RUN {
 
data(pplots)
# Without time
df <- subset(pplots, year == 2002)
multivariate_difference(df, 
                        replicate.var = "plot", 
                        treatment.var = "treatment", 
                        species.var = "species", 
                        abundance.var = "relative_cover")
# There are 6 replicates for each of three treatments, thus 18 total
# observations.

# Without time and with reference treatment
df <- subset(pplots, year == 2002)
multivariate_difference(df, 
                        replicate.var = "plot", 
                        treatment.var = "treatment", 
                        species.var = "species", 
                        abundance.var = "relative_cover",
                        reference.treatment = "N1P0")
# There are 6 replicates for each of three treatments, thus 18 total
# observations.

# With time
multivariate_difference(pplots, 
                        time.var = "year", 
                        replicate.var = "plot", 
                        species.var = "species", 
                        abundance.var = "relative_cover", 
                        treatment.var = "treatment")
# In each year there are 6 replicates for each of three treatments, for a
# total of 18 observations.
# }