View source: R/joinSoilLabData.R
joinSoilLabData | R Documentation |
This function verifies whether O and A horizons were named corrected based on For duplicate horizons on a plot, chemistry variables are corrected using weighted averages, with sample depth as the weight. Must run importData first. Note that Earthworms are summarized in joinStandData(). Only works for complete visits and plots that haven't been abandoned. Note that data starts at 2007 because 2006 methods were pretty different.
joinSoilLabData(
park = "all",
from = 2007,
to = as.numeric(format(Sys.Date(), "%Y")),
QAQC = FALSE,
panels = 1:4,
locType = c("VS", "all"),
layer = c("all", "O", "A")
)
park |
Combine data from all parks or one or more parks at a time. Valid inputs:
|
from |
Year to start analysis, ranging from 2007 to current year. |
to |
Year to stop analysis, ranging from 2007 to current year |
QAQC |
Allows you to remove or include QAQC events.
|
panels |
Allows you to select individual panels from 1 to 4. Default is all 4 panels (1:4). If more than one panel is selected, specify by c(1, 3), for example. |
locType |
Allows you to only include plots that are part of the GRTS sample design or include all plots, such as deer exclosures.
|
layer |
Allows you to filter on soil horizons
|
returns a dataframe containing each plot and visit with soil chemistry data for each horizon on a plot Plots that weren't sampled during a given cycle are not returned. Horizon depths are averaged across samples. Note that horizons that were combined after lab QC may be > 10 cm deep.
## Not run:
importData() #imports using default odbc
# join only O horizon data for most recent cycle in ACAD. Note soil chemistry data are typically a year behind plot data.
soil_ACAD_O <- joinSoilLabData(park = 'ACAD', from = 2015, to = 2018, layers = 'O')
# join all park data from all layers and all years
soil_df_all <- joinSoilLabData(from = 2007, to = 2018, layers = 'all')
## End(Not run)
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