exec/RootBiomass_wholeprofile_org.R

In bmcnellis/SDEF.analysis: Data Analysis for 2016 San Dimas Experimental Forest Project

library(ggplot2)
library(gridExtra)
library(cowplot)
setwd("D:/R_Workspace/SDEF/SDEF.analysis/data")
load('SDEF_roots_post_aggregation_by_month.rda')
biodensity <- SDEF_roots_post_aggregation_by_month
######## Root biomass figures
biodensity$mean_biodensity_dm <- biodensity$mean_biodensity*1000
biodensity$sd_biodensity_dm <- biodensity$sd_biodensity*1000
biodensity[is.na(biodensity)] <- 0
biodensity$se_biodensity_dm <- ((biodensity$sd_biodensity_dm)/sqrt(biodensity$n_biodensity))
biodensity$se_length <- ((biodensity$sd_length)/sqrt(biodensity$n_length))
biodensity$se_diameter <- ((biodensity$sd_diameter)/sqrt(biodensity$n_diameter))
biodensity$minse <- abs((biodensity$mean_biodensity_dm -biodensity$se_biodensity_dm))
biodensity$maxse <- (biodensity$mean_biodensity_dm +biodensity$se_biodensity_dm)

#subset by month for graphing
Dec <- subset(biodensity, biodensity$month == "Dec")
Jan <- subset(biodensity, biodensity$month == "Jan")
Feb <- subset(biodensity, biodensity$month == "Feb")
Mar <- subset(biodensity, biodensity$month == "Mar")
May <- subset(biodensity, biodensity$month == "May")

##############

addec <- subset(Dec, Dec$site == 'adenostoma')
gdec <- subset(Dec, Dec$site == 'grass')
adjan <- subset(Jan, Jan$site == 'adenostoma')
gjan <- subset(Jan, Jan$site == 'grass')
adfeb <- subset(Feb, Feb$site == 'adenostoma')
gfeb <- subset(Feb, Feb$site == 'grass')
admar <- subset(Mar, Mar$site == 'adenostoma')
gmar <- subset(Mar, Mar$site == 'grass')
admay <- subset(May, May$site == 'adenostoma')
gmay <- subset(May, May$site == 'grass')


Totals <- data.frame(veg_type = as.character(), Month = as.character(),
                     biomass = as.numeric(), minse = as.numeric(),
                     maxse = as.numeric(), length= as.numeric(),
                     diameter = as.numeric(), se_length = as.numeric(),
                     se_diameter = as.numeric(), stringsAsFactors = FALSE)
Totals[1,1] <- "Adenostoma"
Totals[1,2] <- rep("12-01-2015", times = 1)
Totals[1,3] <- sum(addec$mean_biodensity_dm)
Totals[1,4] <- sum(addec$minse)
Totals[1,5] <- sum(addec$maxse)
Totals[1,6] <- sum(addec$mean_length)
Totals[1,7] <- sum(addec$mean_diameter)
Totals[1,8] <- sum(addec$se_length)
Totals[1,9] <- sum(addec$se_diameter)

Totals[2,1] <- "Grass"
Totals[2,2] <- rep("12-01-2015", times = 1)
Totals[2,3] <- sum(gdec$mean_biodensity_dm)
Totals[2,4] <- sum(gdec$minse)
Totals[2,5] <- sum(gdec$maxse)
Totals[2,6] <- sum(gdec$mean_length)
Totals[2,7] <- sum(gdec$mean_diameter)
Totals[2,8] <- sum(gdec$se_length)
Totals[2,9] <- sum(gdec$se_diameter)

Totals[3,1] <- "Adenostoma"
Totals[3,2] <- rep("01-01-2016", times = 1)
Totals[3,3] <- sum(adjan$mean_biodensity_dm)
Totals[3,4] <- sum(adjan$minse)
Totals[3,5] <- sum(adjan$maxse)
Totals[3,6] <- sum(adjan$mean_length)
Totals[3,7] <- sum(adjan$mean_diameter)
Totals[3,8] <- sum(adjan$se_length)
Totals[3,9] <- sum(adjan$se_diameter)

Totals[4,1] <- "Grass"
Totals[4,2] <- rep("01-01-2016", times = 1)
Totals[4,3] <- sum(gjan$mean_biodensity_dm)
Totals[4,4] <- sum(gjan$minse)
Totals[4,5] <- sum(gjan$maxse)
Totals[4,6] <- sum(gjan$mean_length)
Totals[4,7] <- sum(gjan$mean_diameter)
Totals[4,8] <- sum(gjan$se_length)
Totals[4,9] <- sum(gjan$se_diameter)


Totals[5,1] <- "Adenostoma"
Totals[5,2] <- rep("02-01-2016", times = 1)
Totals[5,3] <- sum(adfeb$mean_biodensity_dm)
Totals[5,4] <- sum(adfeb$minse)
Totals[5,5] <- sum(adfeb$maxse)
Totals[5,6] <- sum(adfeb$mean_length)
Totals[5,7] <- sum(adfeb$mean_diameter)
Totals[5,8] <- sum(adfeb$se_length)
Totals[5,9] <- sum(adfeb$se_diameter)


Totals[6,1] <- "Grass"
Totals[6,2] <- rep("02-01-2016", times = 1)
Totals[6,3] <- sum(gfeb$mean_biodensity_dm)
Totals[6,4] <- sum(gfeb$minse)
Totals[6,5] <- sum(gfeb$maxse)
Totals[6,6] <- sum(gfeb$mean_length)
Totals[6,7] <- sum(gfeb$mean_diameter)
Totals[6,8] <- sum(gfeb$se_length)
Totals[6,9] <- sum(gfeb$se_diameter)

Totals[7,1] <- "Adenostoma"
Totals[7,2] <- rep("03-01-2016", times = 1)
Totals[7,3] <- sum(admar$mean_biodensity_dm)
Totals[7,4] <- sum(admar$minse)
Totals[7,5] <- sum(admar$maxse)
Totals[7,6] <- sum(admar$mean_length)
Totals[7,7] <- sum(admar$mean_diameter)
Totals[7,8] <- sum(admar$se_length)
Totals[7,9] <- sum(admar$se_diameter)

Totals[8,1] <- "Grass"
Totals[8,2] <- rep("03-01-2016", times = 1)
Totals[8,3] <- sum(gmar$mean_biodensity_dm)
Totals[8,4] <- sum(gmar$minse)
Totals[8,5] <- sum(gmar$maxse)
Totals[8,6] <- sum(gmar$mean_length)
Totals[8,7] <- sum(gmar$mean_diameter)
Totals[8,8] <- sum(gmar$se_length)
Totals[8,9] <- sum(gmar$se_diameter)

Totals[9,1] <- "Adenostoma"
Totals[9,2] <- rep("05-01-2016", times = 1)
Totals[9,3] <- sum(admay$mean_biodensity_dm)
Totals[9,4] <- sum(admay$minse)
Totals[9,5] <- sum(admay$maxse)
Totals[9,6] <- sum(admay$mean_length)
Totals[9,7] <- sum(admay$mean_diameter)
Totals[9,8] <- sum(admay$se_length)
Totals[9,9] <- sum(admay$se_diameter)

Totals[10,1] <- "Grass"
Totals[10,2] <- rep("05-01-2016", times = 1)
Totals[10,3] <- sum(gmay$mean_biodensity_dm)
Totals[10,4] <- sum(gmay$minse)
Totals[10,5] <- sum(gmay$maxse)
Totals[10,6] <- sum(gmay$mean_length)
Totals[10,7] <- sum(gmay$mean_diameter)
Totals[10,8] <- sum(gmay$se_length)
Totals[10,9] <- sum(gmay$se_diameter)

Totals$Date <- strptime(Totals$Month, format = "%m-%d-%Y")
Totals$Date <- as.Date(Totals$Month, format = "%m-%d-%Y")

#save(Totals, file = "RootBiomass_totals.Rdata")
#graph



tot <- ggplot(Totals, (aes(x = Month, y = biomass))) +
                geom_line(aes(colour = veg_type, group = veg_type), size = 1) +
                geom_pointrange(aes(colour = veg_type, group = veg_type,  ymin = Totals$minse, ymax = Totals$maxse), size = 0.5, position = position_dodge(0.1))+
                scale_colour_manual(values= c("Black", "Gray")) +
                ylab(expression(paste("Root biomass per soil volume (g   ", dm^-3, ")"))) +
                theme_bw(base_family = "sans", base_size = 13) +
                scale_x_discrete(labels = c("Dec", "Jan", "Feb", "Mar", "May"))
tot