ambiR (version 0.1.1)

DKI2: Calculates DKI (v2)

Description

DKI2() calculate a salinity-normalised version of the Danish quality index (DKI) (Carstensen et al., 2014)

The DKI index is based on AMBI and can only be calculated after first calculating AMBI, the AZTI Marine Biotic Index, and H', the Shannon diversity index. Both indices are included in output from the function AMBI().

This function uses linear relationships between salinity and limits for AMBI and Hdash to normalise the index. This is done to account for expected lower species diversity in regions with lower salinity.

Since the index is normalised to salinity, the function also requires measured or estimated salinity psal as an argument.

#' @references Carstensen, J., Krause-Jensen, D., Josefson, A. (2014). "Development and testing of tools for intercalibration of phytoplankton, macrovegetation and benthic fauna in Danish coastal areas." Aarhus University, DCE – Danish Centre for Environment and Energy, 85 pp. Scientific Report from DCE – Danish Centre for Environment and Energy No. 93. https://dce2.au.dk/pub/SR93.pdf

Usage

DKI2(AMBI, H, N, psal)

Value

DKI index value

Arguments

AMBI

AMBI, the AZTI Marine Biotic Index, calculated using AMBI()

H

H', the Shannon diversity index, calculated using Hdash()

N

number of individuals - generated by both AMBI() and Hdash()

psal

salinity

Details

The AMBI() and Hdash() functions take a dataframe of observations as an argument. The DKI functions, DKI2() and DKI(), do not take a dataframe as an argument. Instead they take values of the input parameters, either single values or as vectors.

To calculate DKI for a dataframe of AMBI values, it could be called from e.g. within a dplyr::mutate() function call. See the examples below.

See Also

• DKI() calculate DKI using the original method

• AMBI_sal() minimum AMBI for normalisation = f(salinity)

• H_sal() maximum H' for normalisation = f(salinity)

Examples

# Simple example

DKI2(AMBI = 1.61, H = 2.36, N = 25, psal = 21.4)


# ------ Example workflow for calculating DKI (v2) from species counts ----

# calculate AMBI index
dfAMBI <- AMBI(test_data, by = c("station"), var_rep = "replicate")[["AMBI"]]

# show AMBI results
dfAMBI

# add salinity values - these are realistic but invented values
dfAMBI <- dplyr::mutate(dfAMBI, psal=ifelse(station == 1, 21.3, 26.5))

# calculate DKI from AMBI results
dfAMBI <- dplyr::mutate(dfAMBI, DKI=DKI2(AMBI, H, N, psal))