## read in the file and attach variable names
benthic <- read.table("Benthicfluxes.txt", header=TRUE) # read in file + header = TRUE to inform that first line contains variable names
benthic
attach(benthic) # attach variable names, so R recognizes them

#load package for re-arranging datasets
library(plyr) 
library(tidyr)
library(car)
#load packages for plotting
library(ggplot2)

## calculate the average counts for each biotic component (zoo, phyto and macro) per location
mean.zooplankton=tapply(zooplankton, location, mean) # special function tapply() to calculate mean values
mean.phytoplankton=tapply(phytoplankton, location, mean)
mean.macrobenthos=tapply(macrobenthos, location, mean)

## explore the data using graphs (! more advanced plots can be used with ggplot function)
# relationships between biotic components (regression, all continuous)
plot(zooplankton~phytoplankton)
abline(lm(zooplankton~phytoplankton, data=benthic), col="red") # add regression line

plot(macrobenthos~zooplankton)
abline(lm(macrobenthos~zooplankton, data=benthic), col="red")

plot(macrobenthos~phytoplankton)
abline(lm(macrobenthos~phytoplankton, data=benthic), col="red")

# densities per location (discrete independent variable, so boxplots)
plot(zooplankton ~ location)
plot(phytoplankton ~ location)
plot(macrobenthos ~ location)

# macrofauna densities per location and the influence of predators
library(lattice)
bwplot(macrobenthos ~ predators | location) # plot for two different variables

detach(benthic)