sapfluxnetr

 1# load packages
 2library(sapfluxnetr)
 3library(ggplot2)
 4
 5# ARG_MAZ example site data
 6data('ARG_MAZ', package = 'sapfluxnetr')
 7data('sfn_metadata_ex', package = 'sapfluxnetr')
 8
 9# plot site sapflow measurements versus vpd
10sfn_plot(ARG_MAZ, formula_env = ~ vpd)

1
2# daily sapflow and environmental metrics
3arg_maz_metrics <- daily_metrics(
4  ARG_MAZ, tidy = TRUE, metadata = sfn_metadata_ex
5)
6#> [1] "Crunching data for ARG_MAZ. In large datasets this could take a while"
7#> [1] "General data for ARG_MAZ"

1
2# plot daily aggregations
3ggplot(arg_maz_metrics, aes(x = vpd_q_95, y = sapflow_q_95, colour = pl_code)) +
4  geom_point()

1# ARG_TRE and AUS_CAN_ST2_MIX example sites
2data('ARG_TRE', package = 'sapfluxnetr')
3data('AUS_CAN_ST2_MIX', package = 'sapfluxnetr')
4multi_sfn <- sfn_data_multi(ARG_TRE, ARG_MAZ, AUS_CAN_ST2_MIX)
5
6# plotting the individual sites. It creates a list of plots
7plots_list <- sfn_plot(multi_sfn, formula_env = ~ vpd)
8plots_list[['AUS_CAN_ST2_MIX']]
9#> Warning: Removed 526066 rows containing missing values or values outside the scale range (`geom_point()`).

 1
 2# daily sapflow standard metrics
 3multi_metrics <- daily_metrics(
 4  multi_sfn, tidy = TRUE, metadata = sfn_metadata_ex
 5)
 6#> [1] "Crunching data for ARG_TRE. In large datasets this could take a while"
 7#> [1] "General data for ARG_TRE"
 8#> [1] "Crunching data for ARG_MAZ. In large datasets this could take a while"
 9#> [1] "General data for ARG_MAZ"
10#> [1] "Crunching data for AUS_CAN_ST2_MIX. In large datasets this could take a while"
11#> [1] "General data for AUS_CAN_ST2_MIX"

1
2# plot daily aggregations
3ggplot(multi_metrics, aes(x = vpd_q_95, y = sapflow_q_95, colour = si_code)) +
4  geom_point(alpha = 0.2)
5#> Warning: Removed 10966 rows containing missing values or values outside the scale range (`geom_point()`).

1install.packages('sapfluxnetr')