Download the poster from AGU ’19 HERE
Import data
Long thought to be a carbon sink, the Páramo region of the Andes may be a significant carbon source (Carrillo et al. 2019 AFM). We evaluated the spatiotemporal dynamics of CO2 concentration and flux in a high-elevation stream. We measured 15-min dissolved CO2, O2, and discharge, across a wetland-stream transition, characteristic of tropical, alpine environments. Here, we calculate evasion using Vaisala dissolved \(CO_{2}\) Sensors and compare estimates to directly measured flux from an eoSense eosFD flux chamber. We also evaluate how evasion relates to other variables such as precipitation and temperature. Our field campaign included in-stream \(CO_{2}\) injections to determine the impact of \(CO_{2}\) concentration on evasion. Here we ignore these injections and filter them out while we import the rest of our measurements.
Create new time variables for ease of plotting
These new variables will help us plot each seperate day on a timescale of midnight -> midnight
df$day <- as.factor(substr(as.character(df$DateTime),1,10))
times <- substr(as.character(df$DateTime),12,16)
df$time <- strftime(df$DateTime, format="%H:%M")
df$time <- as.POSIXct(df$time, format="%H:%M")
todayStart <- as.POSIXct(paste0(Sys.Date(),"00:00:00"))
todayEnd <- as.POSIXct(paste0(Sys.Date(),"23:59:59"))
CO2 Change
Change in CO2
So now that we know what the change in \(CO_{2}\) between stations, it’s time to account for stream metabolism. Stream metabolism includes Ecosystem Respiration (ER) and Gross Primary Production / phtosynthesis (GPP). Both of these processes include a 1:1 exchange of \(CO_{2}\) and DO molecules. Photosynthesis: Use \(CO_{2}\) and create O2 (1:1 ratio).
Respiration: Use O2, create \(CO_{2}\) (1:1 ratio).
Respiration can occur in the abscence of sunlight while photosynthesis cannot. At night, stream processes are respiration driven. During the day both respiration and photosynthesis occur. We can look at the changes in DO over the similar stretches of stream and time period. We did not have a DO sensor at station 3 but we did have one at station 2.
Dissolved Oxygen
Change in Dissolved Oxygen
Mass Conversion
Convert CO2 from concentration to mass
Now that we know the change in \(CO_{2}\) in terms of concentration [ppm], we can convert it to mass. Specifically, we will take this opportunity to convert to micromoles [umol], which we will eventually use to express evasion.
# Distances are 17,30,80
filt13$uMols_13 <- ((filt13$V1-filt13$V3)/ 37.6) *.0018*(1000000/44.01)*filt13$stn1_Q/1000
filt34$uMols_34 <- ((filt34$V3-filt34$V4)/ 64) *.0018*(1000000/44.01)*filt34$stn3_Q/1000
Plotting data
Histograms of change in CO2
CO2 Change over time
This plot shows how