knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.6.3
theme_set(theme_classic())
library(scales)
## Warning: package 'scales' was built under R version 3.6.3

Eddy Datasets

Import and Standardize

eddy1 <- read.csv('hf072-01-eddy-2002-04.csv')
r1 <- eddy1$fco2.valid*(378.769430000000)
#378.769430000000
r1pos <- replace(r1, which (r1 < 0), NA)
#r1 <- eddy1$r.estimate*(378769.43)
rn <- as.numeric(rownames(eddy1))

eddy2 <- read.csv('hf072-02-eddy-2005-2010.csv')
r2 <- eddy2$fco2.value*(378.769430000000)
r2pos <- replace(r2, which (r2 < 0), NA)
rn2 <- as.numeric(rownames(eddy2))

Standardization Equations

Given

  • 12.0107 g of Carbon = 1 mol

  • 31536000 s = 1 yr

  • 1.0e-6 μmol = 1 mol

\[\frac{x \textrm{ μmol}}{\textrm{m}^2s}×\frac{1 \textrm{ mol}}{1.0×10^{6} \textrm{μmol}}×\frac{31536000 s}{1 yr}×\frac{12.0107 \textrm{ g}}{1 \textrm{ mol}}\] \[\frac{x \textrm{ μmol}}{\textrm{m}^2s}(378.76)=\frac{x \textrm{ g}}{\textrm{m}^2yr} \textrm{ of Carbon}\]

Calculations

#Average for eddy1&2
av03 <- mean(r1pos[10147:27666],na.rm=TRUE)
av04 <- mean(r1pos[27666:45234],na.rm=TRUE)
av05 <- mean(r2pos[0:17520],na.rm=TRUE)
av06 <- mean(r2pos[17521: 35040],na.rm=TRUE)
av07<- mean(r2pos[35041: 52560],na.rm=TRUE)
av08<- mean(r2pos[52561: 70127],na.rm=TRUE)
av09<- mean(r2pos[70128: 87647],na.rm=TRUE)
av10<- mean(r2pos[87648: 105167],na.rm=TRUE)
av03
## [1] 533.5484
av04
## [1] 471.9997
av05
## [1] 651.0682
av06
## [1] 639.0083
av07
## [1] 544.4408
av08
## [1] 509.5319
av09
## [1] 448.4006
av10
## [1] 554.5751
av_all <- mean(c(av03, av04, av05, av06, av07, av08, av09, av10))
av_all
## [1] 544.0716
#sine_ed1 <- data.frame(as.list(eddy1$r.estimate[10147:45234]))
#b0 <- coef(sine_ed1)[1]
#alpha <- coef(sine_ed1)[2]
#beta <- coef(eddy1$r.estimate)[3]

#r <- sqrt(alpha^2 + beta^2)
#phi <- atan2(beta, alpha)

Plots

ggplot(data = eddy1, aes(x = rn, y = r1)) + 
  geom_point(alpha=0.5, color="#009E73") +
  ylim(0, 5000) +
  xlim(10147, NA) +
  labs(x = "Number of Measurements", y = expression(paste("Atmosphere Respiration ", frac(gC, m^2*yr)))) + 
  geom_vline(xintercept = 27667, linetype="dashed", alpha=0.5, color="red") +
  geom_smooth(method = "gam", alpha=0.5, color="black", size=0.5)
## `geom_smooth()` using formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 37788 rows containing non-finite values (stat_smooth).
## Warning: Removed 37788 rows containing missing values (geom_point).

ggplot(data = eddy2, aes(x = rn2, y = r2)) + 
  geom_point(alpha=0.5, color="#009E73") +
  ylim(0, 5000) +
  xlim(0, NA) +
  labs(x = "Number of Measurements", y = expression(paste("Atmosphere Respiration ", frac(gC, m^2*yr)))) + 
  geom_vline(xintercept = c(17520, 35040, 52560, 70127, 87647, 105167), linetype="dashed", alpha=0.5, color="red") +
  geom_smooth(method = "gam", alpha=0.5, color="black", size = 0.5)
## `geom_smooth()` using formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 62799 rows containing non-finite values (stat_smooth).
## Warning: Removed 62799 rows containing missing values (geom_point).

Comparison with Soil Respiration

Import Soil Data

soi03 <- c(768, 715, 713, 789, 554)
av_soi03 <- mean(soi03)
soi04 <- c(734, 682, 682, 752, 531)
av_soi04 <- mean(soi04)
soi05 <- c(783, 729, 726, 806, 563)
av_soi05 <- mean(soi05)
soi06 <- c(751, 699, 698, 770, 544)
av_soi06 <- mean(soi06)
soi07 <- c(704, 655, 655, 720, 511)
av_soi07 <- mean(soi07)
soi08 <- c(721, 670, 671, 736, 524)
av_soi08 <- mean(soi08)
soi09 <- c(740, 688, 688, 757, 536)
av_soi09 <- mean(soi09)

soil_av_mean <- mean(av_soi03, av_soi04, av_soi05, av_soi06, av_soi07, av_soi09)
soil_av_mean
## [1] 707.8
soil_av_frame <- c(av_soi03, av_soi04, av_soi05, av_soi06, av_soi07, av_soi09)

Difference

#Differences between yearly average of atmosphere and soil Carbon.
dif03 <- av03 - av_soi03
dif04 <- av04 - av_soi04
dif05 <- av05 - av_soi05
dif06 <- av06 - av_soi06
dif07 <- av07 - av_soi07
dif08 <- av08 - av_soi08
dif09 <- av09 - av_soi09
difav <- mean(dif03, dif04, dif05, dif06, dif07, dif07, dif09)
difav
## [1] -174.2516

Plotting the Difference

diff <- c(dif03, dif04, dif05, dif06, dif07, dif08, dif09)
year <- c(2003, 2004, 2005, 2006, 2007, 2008, 2009)
diffdata <- data.frame(year, diff)

ggplot(data = diffdata, aes(x = year, y = diff)) +
  geom_point(shape=1, color="#009E73") +
  labs(x = "Year", y = expression(paste("Average Plant Respiration ", frac(gC, m^2*yr)))) +
  geom_smooth(method = "lm", alpha = 0.2, color = "red")
## `geom_smooth()` using formula 'y ~ x'

Altitude Differences

Import Altitude Data

alt <- read.csv("hf197-02-lph-profile.csv")
alt1 <- mean(alt$l1.co2, na.rm="TRUE")
alt2 <- mean(alt$l2.co2, na.rm="TRUE")
alt3 <- mean(alt$l3.co2, na.rm="TRUE")
alt4 <- mean(alt$l4.co2, na.rm="TRUE")
alt5 <- mean(alt$l5.co2, na.rm="TRUE")
alt6 <- mean(alt$l6.co2, na.rm="TRUE")
alt7 <- mean(alt$l7.co2, na.rm="TRUE")
alt8 <- mean(alt$l8.co2, na.rm="TRUE")

##Plot Altitude Means

altmeans <- c(alt1, alt2, alt3, alt4, alt5, alt6, alt7, alt8)
height <- c(0.1, 0.3, 1, 2, 5, 10, 16, 21)
altdata <- data.frame(height, altmeans)
ggplot(data = altdata, aes(x = altmeans, y= height)) +
  geom_point() +
  scale_x_continuous(trans = 'log10') +
  scale_y_continuous(trans = 'log10') +
  annotation_logticks(sides="lb") + 
  labs(x = "Atmosphere Respiration (CO2 - no units provided)", y = "Height in Metres")

###Altnerative Plot

alternate <- c(1324, 1248, 826, 1197, 1085, 988, 1456)
year <- c(2003, 2004, 2005, 2006, 2007, 2008, 2009)
alternatedata <- data.frame(year, alternate)
ggplot(data = alternatedata, aes(x = year, y= alternate)) +
  geom_point() +
    ylim(500, 1500) +
  labs(x = "Year", y = expression(paste("Ecosystem Respiration ", frac(gC, m^2*yr)))) +
  geom_smooth(method="lm", se=FALSE)
## `geom_smooth()` using formula 'y ~ x'

soil_alternate <- c(741, 708, 756, 725, 680, 695, 714)
alternate_soil_data <- data.frame(year, soil_alternate)

mean_alternate <- mean(alternate)
difference_of_means <- mean_alternate - soil_av_mean
difference_of_means
## [1] 452.7714
alt_difference <- alternate - soil_alternate
alt_difference_Data <- data.frame(year, alt_difference)
ggplot(data=alt_difference_Data, aes(x=alt_difference_Data$year, y=alt_difference_Data$alt_difference)) +
  geom_point() +
  geom_smooth(method="lm", se=FALSE) +
  labs(y=expression(paste("Plant Respiration ", frac(gC, m^2*yr))), x="Year")
## Warning: Use of `alt_difference_Data$year` is discouraged. Use `year` instead.
## Warning: Use of `alt_difference_Data$alt_difference` is discouraged. Use
## `alt_difference` instead.
## Warning: Use of `alt_difference_Data$year` is discouraged. Use `year` instead.
## Warning: Use of `alt_difference_Data$alt_difference` is discouraged. Use
## `alt_difference` instead.
## `geom_smooth()` using formula 'y ~ x'