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Plot environmental contours showing depth-time patterns

Source: R/plot_enviro.R
pr_plot_NRSEnvContour.Rd

Create contour plots showing how environmental variables change with both time (x-axis) and depth (y-axis). This visualisation is particularly effective for identifying vertical structure, stratification, and the deep chlorophyll maximum.

Usage

pr_plot_NRSEnvContour(dat, na.fill = TRUE)

Arguments

dat

A dataframe from pr_get_NRSEnvContour() containing environmental data formatted for contour plotting

na.fill

How to handle missing data (gaps) in the contour:

  • TRUE - Fill gaps using linear interpolation (default, creates smoother contours)

  • FALSE - Leave gaps as-is (shows only measured data)

  • A function - Use custom interpolation (e.g., mean, median)

Value

A ggplot2 object with contour plots faceted by station and parameter

Details

Contour plots are excellent for visualising:

Vertical Structure

  • Deep chlorophyll maximum (DCM) depth and intensity

  • Nutricline depth and strength

  • Stratification patterns (steep vs. gradual gradients)

  • Surface vs. subsurface maxima

Temporal Patterns

  • Seasonal shoaling/deepening of features

  • Upwelling events (nutrient-rich water at surface)

  • Mixing events (homogenisation of the water column)

  • Long-term changes in vertical structure

Gap Filling

When na.fill = TRUE, the function uses metR::geom_contour_fill() with linear interpolation to create smooth contours. This is appropriate for environmental data with regular sampling patterns and small gaps. For irregular sampling or large gaps, consider setting na.fill = FALSE to show only measured data.

The function automatically creates one facet per station and parameter combination. Contours are filled with a colour scale, and contour lines are overlaid in grey.

See also

pr_get_NRSEnvContour() for preparing the input data, pr_plot_Enviro() for alternative line plot visualisation, pr_get_NRSChemistry(), pr_get_NRSPigments(), pr_get_NRSPico() for data sources

Examples

dat <- pr_get_NRSEnvContour("Chemistry") %>% dplyr::filter(Parameters == "Nitrate_umolL",
StationCode %in% c('YON', 'MAI', 'PHB', 'NSI'))
plot <- pr_plot_NRSEnvContour(dat, na.fill = TRUE)