Community Dynamics Toolbox

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##Community stability

#data format: long

#summing cover values by treatment then by species

require(plyr)

cs.sum <- ddply(data_raw.long, .(treatment, species). summarise,

					sum=sum(cover))

#calculating the mean sum and sd for each treatment

cs.sum.mean <- ddply(cs.sum, .(treatment), summarise,

						sumMean=mean(sum))

cs.sum.sd <- ddply(cs.sum, .(treatment), summarise,

						sumSd=sd(sum))

cs.m.sd <- join(cs.sum.mean, cs.sum.sd, type="full")

#calculating final comm. stability value per treatment

cs_final <- ddply(cs.m.sd, .(treatment), summarise,

					cs=mean/sd)

#ANOVA on cs values

require(car)

lm.cs.sum <- lm(sum ~ treatment, data=cs.sum)

Anova(lm.cs.sum, type=3)

summary(lm.cs.sum)

#KW ANOVA

fit.cs.kw <- kruskal.test(sum ~ treatment, data=sc.sum)