DietTroph {dietr}

Calculates trophic level from percentage based quantitative diet data (volumetric, weight, etc.) for species, populations, and individuals.

Description

Calculates trophic level from percentage based diet data following the routine described in TrophLab. While FishBase data obtained from rfishbase can be used, users can also upload their own data for use in with function (see vignette for a tutorial).

Usage

DietTroph(
  DietItems,
  PreyValues,
  Taxonomy,
  PreyClass = c("FoodI", "FoodII", "FoodIII", "Stage"),
  SumCheck = TRUE
)

Arguments

DietItems

A data frame with rows as individual entries and each row consisting of a prey classification and a corresponding diet percentages. The column names for prey classification of the diets should match those of PreyValues. The first column should contain the identifier of the individual and be named "Individual", The last column should contain the percent of the prey in the diet and be labelled "Percent".

PreyValues

a data frame with rows as prey item names and columns containing the trophic level of the prey item and the standard error of that trophic item. The column names of PreyValues except for TL and SE should match those in DietItems.

Taxonomy

a data frame starting with the least inclusive level progressing to more inclusive moving towards the right.

PreyClass

Column names of the PreyValues used for matching between DietItems and PreyValues, exclusive of TL and SE. Default is those of FishBase.

SumCheck

Logical. Should the sum of diet items be checked, and, if not equal to 100, recalculated?

Value

A list length of the columns in taxonomy, each containing trophic level estimation at the respective taxonomic level.

Author(s)

Samuel Borstein

Examples

###EXAMPLE USING RAW DATA FROM Magalhaes et al., 2015###
data(Herichthys)#load data
#Subset out individuals with diet data
HMdat<-Herichthys[Herichthys$total==100,]
#Make a data frame of the individuals, lake by year, and lake.
HMtax<-cbind.data.frame(HMdat$individual,paste(HMdat$lake,HMdat$year),HMdat$lake)
#Name the data frame
colnames(HMtax)<-c("Individual","Lake x Year","Lake (all years)")
#To calculate trophic level for the entire species, add a vecotr to the data frame of
#the species name
HMtax$species<-"Herichthys minckleyi"
HMdat<-HMdat[,c("individual","X.Gastrop","X.Insect","X.Fish","X.Zoopl"
,"X.plants","X.algae", "X.detritus")]
#Repeat the individual name the number of unique prey types (6)
Inds<-rep(x = HMdat$individual, times=6)[order(rep(x = HMdat$individual, times=6))]
#Repeat the number of food typed the length of the number of individuals
FoodTypes<-rep(x = colnames(HMdat[2:7]),times=length(unique(HMtax$Individual)))
#Make a data frame, the length of the individuals with three columns
HM.mat<-as.data.frame(matrix(nrow = length(Inds),ncol = 3))
#Name these columns
colnames(HM.mat)<-c("Individual","FoodItem","Percent")
#Populate the dataframes first column with the individual and the second column with the prey type
HM.mat$Individual<-Inds
HM.mat$FoodItem<-FoodTypes
#Run this for loop to find the diet data based on the individual and then match the 
#diet percentage based on the name of the prey type
for(i in 1:nrow(HMdat)){
rows2match<-which(HM.mat$Individual==HMdat$individual[i])
HM.mat$Percent[rows2match]<-as.vector(as.numeric(HMdat[i,2:7]))
}
#Remove prey that do not contribute to diets
HM.mat<-HM.mat[!HM.mat$Percent==0,]
#Create a empty data frame for prey values
PreyMat<-as.data.frame(matrix(ncol = 3,nrow = 6))
#Name the columns something useful
colnames(PreyMat)<-c("FoodItem","TL","SE")
#Add in the prey name to the PreyMat
PreyMat[,1]<-unique(FoodTypes)
#Add in the trophic levels of the prey
PreyMat[,2]<-c(2.37,2.2,3.5,2.1,2,2)
#Add in the SE of the prey
PreyMat[,3]<-c(.58,.4,.8,.3,0,0)
HM.TL<-DietTroph(DietItems = HM.mat,PreyValues = PreyMat, PreyClass = "FoodItem",
Taxonomy = HMtax, SumCheck = TRUE)
###EXAMPLE USING DATA FROM FISHBASE###
#Get some food item data from rfishbase
library(rfishbase)
#convert FishBase data into data for trophic calculation using dietr
converted.diet <- ConvertFishbaseDiet(ExcludeStage=NULL)
#Subset three studies out, as this contains all  studies from FishBase
my.diets <- converted.diet$DietItems[1:26,]
my.taxonomy <- converted.diet$Taxonomy[1:3,]
#Load Prey Values
data(FishBasePreyVals)
#Calculate Trophic Levels
my.TL <- DietTroph(DietItems = my.diets,PreyValues = FishBasePreyVals, Taxonomy = 
my.taxonomy, PreyClass=c("FoodI","FoodII","FoodIII","Stage"))