MAMBI: Compute the multivariate AMBI (M-AMBI) index score.

In SCCWRP/SQOUnified: Tools for calculating SQO scores based on three Lines of Evidence (Benthic, Tox, Chem)

Compute the multivariate AMBI (M-AMBI) index score.

Description

This is a function to calculate multivariate AMBI (M-AMBI) index scores following Pelletier et al. 2018 which is in turn built upon the work of Sigovini et al. 2013 and Muxica et al. 2007. This is an alternate version that allows for manipulation of the data within R before submitting it to the function in lieu of directly reading in an excel file to the function.

The function is designed for use in US estuarine waters and requires three arguments: BenthicData, EG_Ref_values, and EG_Scheme. More details are given below.

Two additional dataframes are also needed to run the script: Saline and Tidal freshwater good-bad standards for the M-AMBI that are in TidalFresh_Standards.RData and Saline_Standards.RData

For the function to run, the following packages NEED to be installed: tidyverse, reshape2, vegan, and readxl. Additionally the EQR.R function must also be installed and is included with this code.

Usage

MAMBI(benthic_data, EG_Ref_values = EG_Ref, EG_Scheme = "Hybrid")

Arguments

\strong{BenthicData}	a data frame with the following columns: StationID - an alpha-numeric identifier of the location; Replicate - a numeric identifying the replicate number of samples taken at the location; SampleDate - the date of sample collection; Latitude - latitude in decimal degrees; Longitude - longitude in decimal degrees. Make sure there is a negative sign for the Western coordinates; Taxon - name of the fauna, ideally in SCAMIT ed12 format, do not use sp. or spp., use sp only or just the Genus. If no animals were present in the sample use NoOrganismsPresent with 0 abundance; Abundance - the number of each Species observed in a sample; Salinity - the salinity observed at the location in PSU, ideally at time of sampling.
\strong{EG_Ref_values}	- A data frame with the suite of US Ecological Groups assigned initially in Gillett et al. 2015. This EG Ref values has multiple versions of the EG values and a Yes/No designation if the fauna are Oligochaetes or not. The default dataframe is one called EG_Ref which was originally read in from a csv called "Ref - EG Values 2018.csv." Replace with other data as you see fit, but make sure the data you use is in a similar format and uses the same column names. Additionally, new taxa can be added at the bottom of the list with the EG values the user feels appropriate, THOUGH THIS IS NOT RECOMMENDED
\strong{EG_Scheme}	A quoted string with the name of the EG Scheme to be used in the AMBI scoring. The default is Hybrid, though one could use US (all coasts), Standard (Values from Angel Borja and colleagues), US_East (US East Coast), US_Gulf (US Gulf of Mexico Coast), or US_West (US West Coast).

Value

The output of the function will be a dataframe with

StationID, Replicate, SampleDate,

Latitude, Longitude,

SalZone (The Salinity Zone assigned by M-AMBI),

AMBI_Score,

S (Species Richness),

H (Species Diversity),

Oligo_pct (Relative Abundance of Oligochaetes),

MAMBI_Score, Orig_MAMBI_Condition, New_MAMBI_Condition,

Use_MAMBI (Can M-AMBI be applied?), Use_AMBI (Can AMBI be applied?),

YesEG (percentage of Abundance with a EG value)

Author(s)

David Gillett [e-mail]

Examples

data(benthic_sampledata) # load sample dataset to environment
data(TidalFresh_Standards) # Load tidal fresh standards if you want to look at them
data(Saline_Standards) # Load Saline standards if you want to look at them
data(EG_Ref) # load the default EG_Ref values
MAMBI(benthic_sampledata, EG_Ref, "Hybrid")
MAMBI(benthic_sampledata, EG_Ref, "US Gulf")
MAMBI(benthic_sampledata) # uses default values for the last two args

SCCWRP/SQOUnified documentation built on Nov. 3, 2024, 12:54 a.m.