QFASA (version 1.2.1)

p.sim.QFASA: Simultaneous estimation of diet composition and calibration coefficients

Description

Computes the diet estimate for each predator in pred.sig as well as an overall estimate of the calibration coefficient vector.

Usage

p.sim.QFASA(pred.sig, prey.mat, FC = rep(1, nrow(prey.mat)))

Value

A list with components:

diet.est

A matrix of the diet estimates for each predator where each row corresponds to a predator and the columns to prey species. The estimates are expressed as proportions summing to one.

cc.est

Estimated vector of calibration coefficients

Arguments

pred.sig

matrix containing the FA signatures of the predator

prey.mat

matrix containing a representative FA signature from each prey group (usually the mean). The first column must index the prey group.

FC

vector of fat content of length equal to the number of prey groups (or species)

Details

Starting values for the diet estimates are equal proportions and a vector of ones is used for the calibration coefficients.

References

Bromaghin, Jeffrey F., Budge, Suzanne M., Thiemann, Gregory and Rode, Karyn D. (2017) Simultaneous estimation of the diet composition and calibration coefficients with fatty acid signature data. Ecology and Evolution, 7(16), 6103-6113

Examples

##  This example takes some time to run.
## Please uncomment code below to run.

## Fatty Acids
#data(FAset)
#fa.set = as.vector(unlist(FAset))

## Predators
#data(predatorFAs)
#tombstone.info = predatorFAs[,1:4]
#predator.matrix = predatorFAs[,5:(ncol(predatorFAs))]
#npredators = nrow(predator.matrix)

## Need predator and prey to have same length

#predator.ext <- predator.matrix[fa.set]
#predator.ext <- predator.ext/rowSums(predator.ext)

## Prey
#data(preyFAs)
#prey.sub=(preyFAs[,4:(ncol(preyFAs))])[fa.set]
#prey.sub=prey.sub/apply(prey.sub,1,sum)
#group=as.vector(preyFAs$Species)
#prey.matrix=cbind(group,prey.sub)
#prey.matrix=MEANmeth(prey.matrix)

## Fat Content
#FC = preyFAs[,c(2,3)]
#FC = as.vector(tapply(FC$lipid,FC$Species,mean,na.rm=TRUE))

#Q.sim <-p.sim.QFASA(predator.ext,prey.matrix,FC)
## Average Diet Estimate
#round(colMeans(Q.sim[[1]]),3)
## Calibration Coefficients
#Q.sim[[2]]