#c1-c3
#Note: Summersmrdataset is my 2017 preliminary data on soil microbial respiration (using T4 data)
library(ggplot2)
summer.2017<-read.csv("summersmrdata.csv",header=TRUE)
head(summer.2017)
## Sample Forest Age Stand Plot Treatment Horizon T4
## 1 1 Bartlett Young C1 1 P Oe 11.62
## 2 2 Bartlett Young C1 2 N Oe 9.08
## 3 3 Bartlett Young C1 3 Con Oe 10.08
## 4 4 Bartlett Young C1 4 NP Oe 5.09
## 5 5 Bartlett Young C2 1 NP Oe 6.69
## 6 6 Bartlett Young C2 2 Con Oe 12.45
summer.2017.plot<- ggplot(summer.2017,aes(x= Treatment,y=T4,colour=Stand))+geom_point()+theme_bw()
summer.2017.plot
#c4toc6
summer.2017b<-read.csv("c4toc6.csv",header=TRUE)
head(summer.2017b)
## Sample Forest Age Stand Plot Treatment Horizon T4
## 1 13 Bartlett Mid C4 1 NP Oe 9.51
## 2 14 Bartlett Mid C4 2 N Oe 11.11
## 3 15 Bartlett Mid C4 3 Con Oe 14.26
## 4 16 Bartlett Mid C4 4 P Oe 17.44
## 5 17 Bartlett Mid C5 1 Con Oe 10.04
## 6 18 Bartlett Mid C5 2 NP Oe 8.66
summer.2017.plotb<- ggplot(summer.2017b,aes(x= Treatment,y=T4,colour=Stand))+geom_point()+theme_bw()
summer.2017.plotb
#c7tohb
summer.2017c<-read.csv("c7tohb.csv",header=TRUE)
head(summer.2017c)
## ï..Sample Forest Age Stand Plot Treatment Horizon T4
## 1 25 Bartlett Mature C7 1 N Oe 9.74
## 2 26 Bartlett Mature C7 2 NP Oe 12.39
## 3 27 Bartlett Mature C7 3 P Oe 15.29
## 4 28 Bartlett Mature C7 4 Con Oe 9.20
## 5 29 Bartlett Mature C8 1 P Oe 9.14
## 6 30 Bartlett Mature C8 2 Con Oe 4.45
summer.2017.plotc<- ggplot(summer.2017c,aes(x= Treatment,y=T4,colour=Stand))+geom_point()+theme_bw()
summer.2017.plotc
#Predicted plots for hypotheses
#CUE plotting
getwd()
## [1] "C:/Users/Paul/Documents/Rwork"
setwd("C:/Users/Paul/Documents/Rwork")
library(ggplot2)
cue<-read.csv("predictions2.csv",header=TRUE)
head(cue)
## ï..Sample Forest Age Stand Plot Treatment Horizon CUE SMR..
## 1 1 Bartlett Young C1 1 P Oe 0.17 11.62
## 2 2 Bartlett Young C1 2 N Oe 0.24 9.08
## 3 3 Bartlett Young C1 3 Con Oe 0.10 10.08
## 4 4 Bartlett Young C1 4 NP Oe 0.31 5.09
## Soil.C.... MBC qCO2 SMR LML LML_LC
## 1 0.33 700 0.0011 0.75 60 70
## 2 0.48 750 0.0007 0.50 50 60
## 3 0.40 650 0.0015 1.00 70 80
## 4 0.55 800 0.0003 0.25 40 50
#CUE plot exploring horizon responses.
cue.plot1<- ggplot(cue,aes(x= Treatment,y=CUE,colour=MBC))+geom_point(alpha=0.6)+theme_bw()
cue.plot1
#SMR as a function of the MBC
smr.plot<- ggplot(cue,aes(x=MBC,y=SMR,colour=Treatment))+geom_point()+geom_smooth(method="lm")+theme_bw()
smr.plot
#CUE plot exploring CUE as a fuction of MBC
cue<-read.csv("predictions2.csv",header=TRUE)
head(cue)
## ï..Sample Forest Age Stand Plot Treatment Horizon CUE SMR..
## 1 1 Bartlett Young C1 1 P Oe 0.17 11.62
## 2 2 Bartlett Young C1 2 N Oe 0.24 9.08
## 3 3 Bartlett Young C1 3 Con Oe 0.10 10.08
## 4 4 Bartlett Young C1 4 NP Oe 0.31 5.09
## Soil.C.... MBC qCO2 SMR LML LML_LC
## 1 0.33 700 0.0011 0.75 60 70
## 2 0.48 750 0.0007 0.50 50 60
## 3 0.40 650 0.0015 1.00 70 80
## 4 0.55 800 0.0003 0.25 40 50
cue.plot2<- ggplot(cue,aes(x= MBC,y=CUE,colour=Treatment))+geom_point()+ geom_smooth(method="lm")+theme_bw()
cue.plot2
#qCO2 to treatment
cue<-read.csv("predictions2.csv",header=TRUE)
head(cue)
## ï..Sample Forest Age Stand Plot Treatment Horizon CUE SMR..
## 1 1 Bartlett Young C1 1 P Oe 0.17 11.62
## 2 2 Bartlett Young C1 2 N Oe 0.24 9.08
## 3 3 Bartlett Young C1 3 Con Oe 0.10 10.08
## 4 4 Bartlett Young C1 4 NP Oe 0.31 5.09
## Soil.C.... MBC qCO2 SMR LML LML_LC
## 1 0.33 700 0.0011 0.75 60 70
## 2 0.48 750 0.0007 0.50 50 60
## 3 0.40 650 0.0015 1.00 70 80
## 4 0.55 800 0.0003 0.25 40 50
cue.plot3<- ggplot(cue,aes(x=Treatment,y=qCO2))+geom_point()+ geom_smooth(method="lm")+theme_bw()
cue.plot3
#Litter loss
cue<-read.csv("predictions2.csv",header=TRUE)
head(cue)
## ï..Sample Forest Age Stand Plot Treatment Horizon CUE SMR..
## 1 1 Bartlett Young C1 1 P Oe 0.17 11.62
## 2 2 Bartlett Young C1 2 N Oe 0.24 9.08
## 3 3 Bartlett Young C1 3 Con Oe 0.10 10.08
## 4 4 Bartlett Young C1 4 NP Oe 0.31 5.09
## Soil.C.... MBC qCO2 SMR LML LML_LC
## 1 0.33 700 0.0011 0.75 60 70
## 2 0.48 750 0.0007 0.50 50 60
## 3 0.40 650 0.0015 1.00 70 80
## 4 0.55 800 0.0003 0.25 40 50
cue.plot4<- ggplot(cue,aes(x=Treatment,y=LML))+geom_point()+ geom_smooth(method="lm")+theme_bw()
cue.plot4
#Litter loss with labile carbon
cue<-read.csv("predictions2.csv",header=TRUE)
head(cue)
## ï..Sample Forest Age Stand Plot Treatment Horizon CUE SMR..
## 1 1 Bartlett Young C1 1 P Oe 0.17 11.62
## 2 2 Bartlett Young C1 2 N Oe 0.24 9.08
## 3 3 Bartlett Young C1 3 Con Oe 0.10 10.08
## 4 4 Bartlett Young C1 4 NP Oe 0.31 5.09
## Soil.C.... MBC qCO2 SMR LML LML_LC
## 1 0.33 700 0.0011 0.75 60 70
## 2 0.48 750 0.0007 0.50 50 60
## 3 0.40 650 0.0015 1.00 70 80
## 4 0.55 800 0.0003 0.25 40 50
cue.plot5<- ggplot(cue,aes(x=Treatment,y=LML_LC))+geom_point()+ geom_smooth(method="lm")+theme_bw()
cue.plot5
