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Estimating species richness using coverage-based rarefaction
This function uses the iNEXT package to approximate species richness for a given level of sample 'coverage' based on methods in:
Chao, Anne, and Lou Jost. "Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size." Ecology 93.12 (2012): 2533-2547.
The function requires a data.frame or matrix with species as rows and communities as columns.
The function returns a data.frame with the observed richness, observed coverage (Chat), observed sample size (N), estimated richness (based on sample coverage), and optionally, richness based on the Chao1 estimator, and/or finally rarefied richness (individual-based subsampling).
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Compute ultrametric trait matrix for functional traits
Computing ultrametric distance matrices from species' functional traits
fdist takes a functional trait matrix, and returns an ultrametric distance matrix using the method that best preserves the original (non-ultrametric) distances.
References:
Mouchet, M., Guilhaumon, F., Villéger, S., Mason, N. W., Tomasini, J. A., & Mouillot, D. (2008). Towards a consensus for calculating dendrogram‐based functional diversity indices. Oikos, 117(5), 794-800.
Mérigot, B., Durbec, J. P., & Gaertner, J. C. (2010). On goodness-of-fit measure for dendrogram-based analyses. Ecology, 91(6), 1850-1859.
simulateComm: simulate communities with predefined properties
Simulate community-by-species matrix of "functioning" (e.g., biomass) where the total community richness has a predefined correlation with total community biomass (i.e., the row sums).
# Generate community data
ncomms <- 100
nspecies <- 20
A revised function from the iNEXT package (https://github.com/JohnsonHsieh/iNEXT) that
calculates coverage-based rarefaction from abundance data. Instead of computing all orders
of q it allows the user to specify a single order, and additionally omits bootstrapping
of standard errors. The resulting function is much, much faster.
Calculation of chlorophyll concentration based on spectrophotometric equations
The function chlA uses the trichromatic equations to convert absorbance values (wavelengths, in nm) to estimates of chlorophyll concentration using the equations from:
Jeffrey, S. W., and G. F. Humphrey. 1975. New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochem Physiol Pflanz BPP:191–194.
The function takes a data.frame with the following values in the column names (corresponding to wavelengths in the equations in Jeffrey & Humphrey): "480", "510", "630", "647", "664", and "750." Additional arguments include extraction container volume (vol) and, optionally, area of extration (area, representing surface area for epiphytic algae).
The function returns the same data.frame with columns appending for chlorophyll-a, -b, and -c, and phaeopigment concentrations.
The Price Equation for Partitioning Diversity Effects on Ecosystem Function
This function takes a data.frame corresponding to the site-by-species "functioning" matrix (where cells contain the values of the ecosystem function), and returns the five additive components of the Price equation.
EXAMPLE
# Example 1: all species contribute equally to functioning and all occur at the baseline site
# Here, RICH_L should be negative and equal the total number of unshared species at each site
# COMP and CDE terms should be zero
Edgar Equations for Estimating Invertebrate Biomass from Size Structured Abundances
Generates estimates of ash-free dry weight from size-fractionated abundances of epifaunal invertebrates.
From:
Edgar, Graham J. "The use of the size structure of benthic macrofaunal communities to estimate faunal biomass
and secondary production." Journal of Experimental Marine Biology and Ecology 137.3 (1990): 195-214.