# Calculates trophic level from percentage based quantitative diet data (volumetric, weight, etc.) for species, populations, and individuals. 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). ```r 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? ## Returns A list length of the columns in taxonomy, each containing trophic level estimation at the respective taxonomic level. ## Examples ```r ###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")) ``` ## Author(s) Samuel Borstein

DietTroph function