Plot environmental data with depth profiles

Source: R/plot_enviro.R

Create a two-panel figure showing environmental variables (nutrients, pigments, picophytoplankton) as both time series and climatology plots, with separate lines for different sampling depths. This is useful for visualising vertical structure and temporal patterns in water column properties.

pr_plot_Enviro(df, Trend = "None", trans = "identity")

Arguments

df

A dataframe from pr_get_NRSChemistry(), pr_get_NRSPigments(), or pr_get_NRSPico() containing environmental data with depth information

Trend

Type of trend line to add:

  • "None" - No trend line

  • "Smoother" - LOESS smooth (default, good for non-linear patterns)

  • "Linear" - Linear regression line

trans

Transformation for the y-axis scale:

  • "identity" - No transformation (default)

  • "log10" - Log base 10 transformation (useful for pigments, nutrients)

  • "sqrt" - Square root transformation

  • Any other transformation accepted by ggplot2::scale_y_continuous()

Value

A patchwork object containing two ggplot2 panels side-by-side

Details

This function creates a two-panel figure:

Panel 1: Time Series (left, wider)

Shows the full time series with different colours/line types for each depth. Useful for identifying:

  • Long-term trends at different depths

  • Episodic events (e.g., upwelling, mixing)

  • Vertical stratification patterns

  • Deep chlorophyll maximum dynamics

Panel 2: Monthly Climatology (right, narrower)

Shows the mean seasonal cycle at each depth. Useful for identifying:

  • Typical seasonal patterns (e.g., spring bloom, summer stratification)

  • Depth of maximum values by season

  • Seasonal vertical migration of features

The function automatically rounds depth values and creates appropriate legends. Use pr_remove_outliers() before plotting if extreme values are present.

See also

pr_get_NRSChemistry() for nutrient data, pr_get_NRSPigments() for pigment data, pr_get_NRSPico() for picophytoplankton data, pr_plot_NRSEnvContour() for contour plot visualisation

Examples

# Plot total chlorophyll a with depth
df <- pr_get_NRSPigments(Format = "binned") %>%
  pr_remove_outliers(2) %>%
  dplyr::filter(Parameters == "TotalChla",
                StationCode %in% c("NSI", "MAI"))
pr_plot_Enviro(df, Trend = "Smoother", trans = "log10")
#> Warning: no non-missing arguments to max; returning -Inf


# Plot nitrate concentrations
df <- pr_get_NRSChemistry() %>%
  dplyr::filter(Parameters == "Nitrate_umolL",
                StationCode == "PHB")
pr_plot_Enviro(df, Trend = "Linear", trans = "identity")
#> Warning: Removed 42 rows containing non-finite outside the scale range
#> (`stat_smooth()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_line()`).


# Plot Prochlorococcus abundance
df <- pr_get_NRSPico() %>%
  dplyr::filter(Parameters == "Prochlorococcus_cellsmL",
                StationCode == "NSI")
pr_plot_Enviro(df, Trend = "Smoother", trans = "log10")
#> Warning: Removed 1 row containing non-finite outside the scale range (`stat_smooth()`).


df <- pr_get_NRSChemistry() %>% dplyr::filter(Parameters == "SecchiDepth_m",
StationCode %in% c('PHB', 'NSI'))
pr_plot_Enviro(df)