rescale_species: Rescale species values for indicator

In BiologicalRecordsCentre/BRCindicators: Creating multispecies biodiversity indicators

Rescale species values for indicator

Description

This function takes in a dataframe of multi-species data and rescales them so that the value in the starting year is the same. This function accounts for species that have no data at the beginning of the period or those that have no data at teh end of the period.

Usage

rescale_species(Data, index = 100, max = 10000, min = 1)

Arguments

Data	A matrix, the first column, named year, gives the year. Subsequent named columns give the species. Values in the table are the yearly values to be rescaled.
index	The index value for the first year, defaults to 100.
max	The upper limit allowed for scaled values. Values greater than this will be set equal to max.
min	The upper limit allowed for scaled values. Values greater than this will be set equal to min.

Value

A matrix. In each row we have the year, the species and the scaled value. There is also an additional column, 'geomean' giving the geometric mean for each year.

Examples

# We will create fake data which will mimic a summarised output from a sparta package occupancy detection model. Please see the vignette for more details.

# Create a matrix with random data using set.seed for reproducibility
set.seed(123)
data <- matrix(rnorm(50 * 27), nrow = 50, ncol = 27)

# Assign column names
col_names <- c("year", letters[1:26])
dimnames(data) <- list(NULL, col_names)

# Create the 'trends_summary' object
trends_summary <- data

# Re-scale the data so that the value for all species in the first year is the same (all defaults used).
# This function accounts for species that have no data at the beginning of the dataset by entering them at the geometric mean for that year, this stops them dramatically changing the indicator value in the year they join the dataset.
# It also accounts for species that leave the dataset before the end by holding them at their last value.
# Finally it limits the species values that can be given, preventing extremely high or low values biasing the indicator.
rescale_species(Data = trends_summary)

# Now, I have 'messed up' the data a bit by including two species with data missing at the beginning and one species with data missing at the end. We also have one species with some very high values.
trends_summary[1:3, 'a'] <- NA
trends_summary[1:5, 'b'] <- NA
trends_summary[2:4, 'c'] <- 1000
trends_summary[45:50, 'd'] <- NA

# Let's run this data again through our scaling function (all defaults used)
rescale_species(Data = trends_summary)

BiologicalRecordsCentre/BRCindicators documentation built on June 12, 2024, 4:10 a.m.