| Type: | Package |
| Title: | Data Processing for Aquatic Ecology |
| Version: | 1.0.1 |
| Maintainer: | Zhao-Jun Yong <nuannuan0425@gmail.com> |
| Description: | Facilitate the analysis of data related to aquatic ecology, specifically the establishment of carbon budget. Currently, the package allows the below analysis. (i) the calculation of greenhouse gas flux based on data obtained from trace gas analyzer using the method described in Lin et al. (2024). (ii) the calculation of Dissolved Oxygen (DO) metabolism based on data obtained from dissolved oxygen data logger using the method described in Staehr et al. (2010). Yong et al. (2024) <doi:10.5194/bg-21-5247-2024>. Staehr et al. (2010) <doi:10.4319/lom.2010.8.0628>. |
| Imports: | tibble, lubridate, stats, dplyr, openxlsx, readxl, ggplot2, readr, tidyr, stringr |
| License: | GPL (≥ 3) |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| Depends: | R (≥ 2.10) |
| VignetteBuilder: | knitr |
| LazyData: | true |
| NeedsCompilation: | no |
| Packaged: | 2024-12-24 00:57:30 UTC; yangshaojun |
| Author: | Zhao-Jun Yong [cre, aut] |
| Repository: | CRAN |
| Date/Publication: | 2025-01-09 04:10:02 UTC |
calculate_do
Description
Calculate the Net Ecosystem Production, Gross Primary Production and Ecosystem respiration based on the change in dissolved oxygen concentration.
Usage
calculate_do(df)
Arguments
df |
Merged dataframe produced by process_hobo(), process_weather() and process_info() functions. |
Value
A dataframe.
Examples
data(hobo)
calculate_do(hobo)
calculate_ghg_flux
Description
Calculate the greenhouse gas (GHG) flux based on input parameters from a data frame.
Usage
calculate_ghg_flux(
data,
slope = "slope",
area = "area",
volume = "volume",
temp = "temp"
)
Arguments
data |
A data frame containing relevant data with columns for slope, area, volume, and temperature. |
slope |
Name of the column in 'data' that contains the slope values of the GHG concentration change (in ppm/s). |
area |
Name of the column in 'data' that contains the values of the area of the chamber (in square meter). |
volume |
Name of the column in 'data' that contains values of the volume of the chamber (in litre). |
temp |
Name of the column in 'data' that contains values of the temperature of the gas (in Celsius). |
Value
A list containing the calculated flux and its unit.
Examples
data <- data.frame(
slope = c(1.2, 1.5, 1.1),
area = c(100, 150, 120),
volume = c(10, 15, 12),
temp = c(25, 30, 22)
)
results <- calculate_ghg_flux(data)
print(results)
calculate_regression
Description
Calculate the slope of greenhouse gas (GHG) concentration change over time using simple linear regression.
Usage
calculate_regression(
data,
ghg,
reference_time,
duration_minutes = 7,
num_rows = 300
)
Arguments
data |
Data from the LI-COR Trace Gas Analyzer that has been processed and time-converted. |
ghg |
Column name of the file containing data on GHG concentration (e.g., "CH4", "N2O"). |
reference_time |
The date and time at which the measurement started. |
duration_minutes |
The duration of the measurement, default to 7. |
num_rows |
The number of rows used to perform the regression, default to 300. |
Value
A tibble containing the time range (POSIXct format) of the slope and R2 (both numeric) from the simple linear regression.
Examples
data(n2o)
calculate_regression(n2o, "N2O", as.POSIXct("2023-05-04 09:16:15", tz = "UTC"))
combine_hobo
Description
Tidy multiple data retrieved from HOBO U26 Dissolved Oxygen Data Logger.
Usage
combine_hobo(file_path, file_prefix = "no.")
Arguments
file_path |
Directory of the folder containing the files. |
file_prefix |
The prefix before the code for the data logger, defaults to "no." |
Value
A dataframe.
Examples
hobo_data_path <- system.file("extdata", package = "aelab")
df <- combine_hobo(hobo_data_path, file_prefix = "ex_ho")
combine_weather
Description
Tidy multiple daily weather data downloaded from weather station in Taiwan.
Usage
combine_weather(file_path, start_date, end_date, zone)
Arguments
file_path |
Directory of folder containing the files (including the character in the file name that precedes the date). |
start_date |
Date of the daily weather data in yyyy-mm-dd format. |
end_date |
Date of the daily weather data in yyyy-mm-dd format. |
zone |
Code for the region of the weather station. |
Value
A dataframe.
Examples
weather_data_path <- system.file("extdata", package = "aelab")
modified_data_path <- paste0(weather_data_path, "/ex_")
df <- combine_weather(modified_data_path,
start_date = "2024-01-01",
end_date = "2024-01-02", "site_A")
convert_ghg_unit
Description
Convert the greenhouse gas (GHG) flux to micromoles per square meter per hour.
Usage
convert_ghg_unit(ghg_value, ghg, mass = "µmol", area = "m2", time = "h")
Arguments
ghg_value |
The value of the flux. |
ghg |
The molecular formula of greenhouse gases (co2: carbon dioxide; ch4: methane; n2o: nitrous oxide). |
mass |
The mass component of the input GHG flux, default to micromoles. |
area |
The area component of the input GHG flux, default to square meter. |
time |
The time component of the input GHG flux, default to hour. |
Value
A numeric value.
Examples
convert_ghg_unit(1, ghg = "co2")
convert_time
Description
Convert the time of the LI-COR Trace Gas Analyzer to match the time in real life.
Usage
convert_time(data, day = 0, hr = 0, min = 0, sec = 0)
Arguments
data |
Data from the LI-COR Trace Gas Analyzer that had been processed by tidy_licor(). |
day |
Day(s) to add or subtract. |
hr |
Hour(s) to add or subtract. |
min |
Minute(s) to add or subtract. |
sec |
Second(s) to add or subtract. |
Value
The input data with a new column in POSIXct format converted based on the input value.
Examples
data(n2o)
converted_n2o <- convert_time(n2o, min = -10, sec = 5)
Processed data from Onset HOBO Dissolved Oxygen Data Logger. A dataset containing 336 dissolved oxygen concentrations changed over time.
Description
Processed data from Onset HOBO Dissolved Oxygen Data Logger. A dataset containing 336 dissolved oxygen concentrations changed over time.
Format
A data.frame with 336 rows and 13 variables:
date_time: Date and time in POSIXct format.
pressure_hpa: Atmospheric pressure (hpa).
wind_ms: Wind speed (m/s).
do: Dissolved oxygen concentrations (mg/L)
temp: Water temperature (Celsius)
depth: Water depth (m).
salinity: Salinity (ppt).
start_date_time: Start date and time of the deployment.
end_date_time: End date and time of the deployment.
sunrise: Sunrise time during that day.
sunset: Sunset time during that day.
no_hobo: Name for the data logger .
site: Name for the site.
Source
own data.
Processed data from N2O LI-COR Trace Gas Analyzer. A dataset containing 567 N2O concentrations changed over time.
Description
Processed data from N2O LI-COR Trace Gas Analyzer. A dataset containing 567 N2O concentrations changed over time.
Format
A data.frame with 567 rows and 4 variables:
DATE: Date in character format.
TIME: Time in character format.
N2O: Concentrations of nitrous oxide (N2O), in ppb.
date_time: Date and time in POSIXct format.
Source
own data.
plot_hobo
Description
Plot the dissolved oxygen concentration over time series grouped by different data loggers to observe the variations.
Usage
plot_hobo(df)
Arguments
df |
Dataframe produced by process_hobo() function. |
Value
A plot generated by ggplot2.
Examples
data(hobo)
plot_hobo(hobo)
process_hobo
Description
Tidy the data retrieved from HOBO U26 Dissolved Oxygen Data Logger.
Usage
process_hobo(file_path, no_hobo)
Arguments
file_path |
Directory of file. |
no_hobo |
The code for the data logger. |
Value
A dataframe.
Examples
hobo_data_path <- system.file("extdata", "ex_hobo.csv", package = "aelab")
df <- process_hobo(hobo_data_path, "code_for_logger")
process_info
Description
Import and process the necessary information, including the sunrise and sunset times of the day, the date and time range of the deployment, and the code for the data logger.
Usage
process_info(file_path)
Arguments
file_path |
Directory of file. |
Value
A dataframe.
Examples
info_data_path <- system.file("extdata", "info.xlsx", package = "aelab")
df <- process_info(info_data_path)
convert_time
Description
Tidy the daily weather data downloaded from weather station in Taiwan.
Usage
process_weather(file_path, date, zone)
Arguments
file_path |
Directory of file. |
date |
Date of the daily weather data in yyyy-mm-dd format. |
zone |
Code for the region of the weather station. |
Value
A dataframe.
Examples
weather_data_path <- system.file("extdata", "ex_weather.csv", package = "aelab")
df <- process_weather(weather_data_path, "2024-01-01", "site_A")
tidy_ghg_analyzer
Description
Tidy the data downloaded from GHG Analyzer.
Usage
tidy_ghg_analyzer(file_path, gas, analyzer = "licor")
Arguments
file_path |
Directory of file. |
gas |
Choose between CO2/CH4 or N2O LI-COR Trace Gas Analyzer, which is "ch4" and "n2o", respectively. |
analyzer |
The brand of the analyzer which the data was downloaded from. |
Value
Return the loaded XLSX file after tidying for further analysis.
Examples
ghg_data_path <- system.file("extdata", "ch4.xlsx", package = "aelab")
tidy_ghg_analyzer(ghg_data_path, "ch4")