Ceptometer Points - Original Set and Validation Set

CGREC Original Study Sample

from summer 2017 and summer 2018

LAIDat <- read.csv("C:/Users/micayla.lakey/Desktop/R/data/ceptdata.csv")
LAIDat$kg.ha<-with(LAIDat, TOTAL*4.325)

lai.gg <- ggplot(data=LAIDat, aes(x=LAI, y=kg.ha))+
  geom_point(color="red") +
  theme_bw(20)+
  labs(x="Leaf Area Index (LAI)",
       y="Actual Biomass(kg/ha)")

lai.gg +
  geom_smooth(method = "lm",se=FALSE)+
  annotate("text", x=1, y=1750, label="paste(\"t=12.9, \", \"p<0.001, \", R^2,\"=0.71\")",
           parse=TRUE, size=4)+
  ggtitle("Sorted Ceptometer Samples")

Validation Points Samples

without high biomass points - less than 1000 kg/ha biomass

Val <- read.csv("C:/Users/micayla.lakey/Desktop/R/data/validpts.csv")
Val$kg.ha<-with(Val, biomass*4.325)

val.gg <- ggplot(data=Val, aes(x=LAI, y=kg.ha))+
  geom_point(color="orange") +
  theme_bw(20)+
  labs(x="Leaf Area Index (LAI)",
       y="Actual Biomass (kg/ha)")

val.gg +
  geom_smooth(method = "lm",se=FALSE, color="green")+
  annotate("text", x=0.5, y=700, label = "paste(R ^ 2, \" = 0.67\")",
           parse=TRUE, size=4)+
  ggtitle("Validation samples WITHOUT high biomass")+
    theme(plot.title = element_text(size = 20))

Validation Points Samples

with high biomass points - up to almost 3000 kg/ha

Valplus <- read.csv("C:/Users/micayla.lakey/Desktop/R/data/validptshigh.csv")
Valplus$kg.ha<-with(Valplus, biomass*4.325)

valplus.gg <- ggplot(data=Valplus, aes(x=LAI, y=kg.ha))+
  geom_point(color="orange") +
  theme_bw(20)+
  labs(x="Leaf Area Index (LAI)",
       y="Actual Biomass (kg/ha)")

valplus.gg +
  geom_smooth(method = "lm",se=FALSE, color="green")+
  annotate("text", x=0.5, y=2000, label = "paste(R ^ 2, \" = 0.39\")",
           parse=TRUE, size=4)+
  ggtitle("Validation samples WITH high biomass")+
    theme(plot.title = element_text(size = 20))