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jenningsdecomp.Rmd
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jenningsdecomp.Rmd
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---
title: "JenningsDecomp"
author: "Colleen Cosgrove"
date: "February 20, 2019"
output: html_document
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
```{r Add plot andecosys to dataset}
decomp=read.csv("C:/Users/Colleen/OneDrive/Documents/School/Research/Data/Decomp/decomprawdata.csv")
plotnames=read.csv("C:/Users/Colleen/OneDrive/Documents/School/Research/Data/Decomp/decompsampleplots.csv")
colnames(plotnames)
decomp=merge(decomp, plotnames)
decomp=decomp[decomp$Harvest=="H1"|decomp$Harvest=="H2"|decomp$Harvest=="H3"|decomp$Harvest=="H0",]
colnames(decomp)[1]="Sample"
dim(decomp)
#decomp=na.omit(decomp)
#read these columns correctly so things work later. Important for plotting and the glmm.
decomp$Harvest<-as.factor(as.character(decomp$Harvest))
decomp$PropInitial<-as.numeric(as.character(decomp$PropInitial))
rownames(decomp)=decomp[,1]
library(ggplot2)
library(lattice)
library(gridExtra)
library(nlme)
```
```{r AsFDM Plotting}
nrow(decomp)
ncol(decomp)
colnames(decomp)
#Remove Samples that have not been collected yet
decomp=decomp[!is.na(decomp$TotalLeafWeight),]
decomp=decomp[!is.na(decomp$propsoil),]
nrow(decomp)
#ANOVA. RV: dryweight, EV: Harvest and species
afdmharvest=aov(decomp$PropInitial~decomp$Harvest*decomp$Species)
#afdmharvest=aov(decomp$PropInitial~decomp$Harvest*decomp$Species*decomp$Ecotone)
summary(afdmharvest)
TukeyHSD(afdmharvest)
plot(decomp$PropInitial~decomp$Harvest*decomp$Species, ylim=c(0,1))
plot(decomp$PropInitial~decomp$Ecosystem)
#ANOVA. RV: dryweight, EV: harvest and ecosystem
afdmeco=aov(decomp$PropInitial~decomp$Harvest*decomp$Species)
summary(afdmeco)
TukeyHSD(afdmeco)
herewego=lme(PropInitial~Harvest*Species*Ecotone, random=~1|Plot,data=decomp)
#herewego=lmer(as.numeric(as.character(PropInitial))~Harvest+Species+Ecotone +(1|Plot),decomp)
summary(herewego)
```
```{r plots}
#subset data into species
maple=decomp[decomp$Species=="ACESAC",]
oak=decomp[decomp$Species=="QUERUB",]
hickory=decomp[decomp$Species=="CAROVA",]
mapleeco=maple[maple$Ecotone=="Ecotone",]
mapleeco=mapleeco[mapleeco$Ecosystem=="BU"|mapleeco$Ecosystem=="RU"|mapleeco$Ecosystem=="RB",]
oakeco=oak[oak$Ecotone=="Ecotone",]
oakeco=oakeco[oakeco$Ecosystem=="BU"|oakeco$Ecosystem=="RU"|oakeco$Ecosystem=="RB",]
hickoryeco=hickory[hickory$Ecotone=="Ecotone",]
hickoryeco=hickoryeco[hickoryeco$Ecosystem=="BU"|hickoryeco$Ecosystem=="RU"|hickoryeco$Ecosystem=="RB",]
#plot box and whiskers
par(mfrow=c(2,3))
par(tck=0.025)
par(pin=c(4,3),mar=c(4,4,2,1))
plot(hickory$Harvest,hickory$PropInitial, main="Shagbark Hickory", ylab="Prop Initial", xlab=NULL, ylim=c(0,1)) #has outlier above 1
plot(maple$Harvest,maple$PropInitial, main="Sugar Maple", ylab="Prop Initial", xlab=NULL, ylim=c(0,1))
plot(oak$Harvest,oak$PropInitial, main="Red Oak", ylab="Prop Initial", xlab=NULL, ylim=c(0,1))
plot(hickoryeco$Harvest,hickoryeco$PropInitial, main="Hickory Ecotones", ylab="Prop Initial", xlab="Harvest", ylim=c(0,1))
plot(mapleeco$Harvest,mapleeco$PropInitial, main="Maple Ecotones", ylab="Prop Initial", xlab="Harvest", ylim=c(0,1))
plot(oakeco$Harvest,oakeco$PropInitial, main="Oak Ecotones", ylab="Prop Initial", xlab="Harvest", ylim=c(0,1))
#breakout each ecosystem and species, I guess? There's gotta be a better way
ecotones=decomp
#ggplot attempt for line graphs
plot1=ggplot(data=hickory, aes(x=Harvest,y=PropInitial,group=Ecotone,color=Ecotone))+
stat_summary(geom="line",size=1.5, fun.y=mean) +
stat_summary(geom="errorbar",width=0.2)+
ggtitle("Shagbark Hickory")+
scale_x_discrete(expand=c(0,0),labels=c("H0"="Dec 2017","H1"="Jun 2018","H2"="Jan 2019","H3"="Jun 2019"))+
ylim(0,1)+
ylab("Proportion Mass Loss")+
theme_bw()+
theme(legend.position="none",
plot.margin = margin(10,10,10,10),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_text(size=12),
axis.text.y = element_text(size=12),
axis.line = element_line(color="black", size=0.5, linetype = "solid"))
plot2=ggplot(data=maple, aes(x=Harvest,y=PropInitial,group=Ecotone,color=Ecotone))+
stat_summary(geom="line",size=1.5, fun.y=mean) +
stat_summary(geom="errorbar",width=0.2)+
scale_x_discrete(expand=c(0,0),labels=c("H0"="Dec 2017","H1"="Jun 2018","H2"="Jan 2019","H3"="Jun 2019"))+
ggtitle("Sugar Maple")+
ylim(0,1)+
ylab("Proportion Mass Loss")+
theme_bw()+
theme(legend.position="none",
plot.margin = margin(10,10,10,10),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_text(size=12),
axis.text.y = element_text(size=12),
axis.line = element_line(color="black", size=0.5, linetype = "solid"))
plot3=ggplot(data=oak,aes(x=Harvest,y=PropInitial,group=Ecotone,color=Ecotone))+
stat_summary(geom="line",size=1.5, fun.y=mean)+
stat_summary(geom="errorbar",width=0.2)+
ggtitle("Red Oak")+
ylim(0,1)+
ylab("Proportion Mass Loss")+
scale_x_discrete(expand=c(0,0),labels=c("H0"="Dec 2017","H1"="Jun 2018","H2"="Jan 2019","H3"="Jun 2019"))+
theme_bw()+
theme(legend.position=c(0.75,0.8),
plot.margin = margin(10,10,10,10),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_text(size=12),
axis.text.y = element_text(size=12),
axis.line = element_line(color="black", size=0.5, linetype = "solid"))
plot4=ggplot(data=hickoryeco, aes(x=Harvest,y=PropInitial,group=Ecosystem,color=Ecosystem))+
stat_summary(geom="line",size=1.5, fun.y=mean) +
stat_summary(geom="errorbar",width=0.2)+
ggtitle("Hickory Ecotone")+
scale_x_discrete(expand=c(0,0),labels=c("H0"="Dec 2017","H1"="Jun 2018","H2"="Jan 2019","H3"="Jun 2019"))+
ylim(0,1)+
ylab("Proportion Mass Loss")+
theme_bw()+
theme(legend.position="none",
plot.margin = margin(10,10,10,10),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_text(size=12),
axis.text.y = element_text(size=12),
axis.line = element_line(color="black", size=0.5, linetype = "solid"))
plot5=ggplot(data=mapleeco, aes(x=Harvest,y=PropInitial,group=Ecosystem,color=Ecosystem))+
stat_summary(geom="line",size=1.5, fun.y=mean) +
stat_summary(geom="errorbar",width=0.2)+
ggtitle("Maple Ecotone")+
ylim(0,1)+
ylab("Proportion Mass Loss")+
scale_x_discrete(expand=c(0,0),labels=c("H0"="Dec 2017","H1"="Jun 2018","H2"="Jan 2019","H3"="Jun 2019"))+
theme_bw()+
theme(legend.position="none",
plot.margin = margin(10,10,10,10),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_text(size=12),
axis.text.y = element_text(size=12),
axis.line = element_line(color="black", size=0.5, linetype = "solid"))
plot6=ggplot(data=oakeco,aes(x=Harvest,y=PropInitial,group=Ecosystem,color=Ecosystem))+
stat_summary(geom="line",size=1.5, fun.y=mean)+
stat_summary(geom="errorbar",width=0.2)+
ggtitle("Oak Ecotone")+
ylim(0,1)+
ylab("Proportion Mass Loss")+
scale_x_discrete(expand=c(0,0),labels=c("H0"="Dec 2017","H1"="Jun 2018","H2"="Jan 2019","H3"="Jun 2019"))+
theme_bw()+
theme(legend.position=c(0.75,0.8),
plot.margin = margin(10,10,10,10),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_text(size=12),
axis.text.y = element_text(size=12),
axis.line = element_line(color="black", size=0.5, linetype = "solid"))
grid.arrange(plot1,plot2,plot3,plot4,plot5,plot6, nrow=2, ncol=3)
```