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Time series plot of functional group composition

Source: R/plot_timeseries.R
pr_plot_tsfg.Rd

Create stacked area or bar plots showing the relative or absolute abundance of different functional groups over time. This visualisation is particularly useful for examining changes in community composition.

Usage

pr_plot_tsfg(df, Scale = "Actual", Trend = "Raw")

Arguments

df

A dataframe from pr_get_FuncGroups() containing functional group data

Scale

Scaling of the y-axis:

  • "Actual" - Plot actual abundance values (stacked)

  • "Proportion" - Plot as proportions summing to 1 (or 100%)

Trend

The temporal scale for plotting:

  • "Raw" - Plot all data points over time (default)

  • "Month" - Monthly climatology averaged across years

  • "Year" - Annual means for each year

Value

A ggplot2 object showing functional group composition over time

Details

This function creates stacked area plots (for Raw trends) or stacked bar plots (for Month/Year trends) showing how functional group composition changes over time.

Functional Groups Plotted

Phytoplankton (5 groups):

  • Centric diatoms (radially symmetrical, bloom-forming)

  • Pennate diatoms (bilaterally symmetrical)

  • Dinoflagellates (flagellated protists)

  • Cyanobacteria (photosynthetic bacteria)

  • Other (remaining groups)

Zooplankton (7 groups):

  • Copepods (dominant marine zooplankton)

  • Appendicularians (larvaceans, gelatinous filter feeders)

  • Molluscs (pteropods - sea butterflies and angels)

  • Cladocerans (water fleas, e.g., Penilia, Evadne)

  • Chaetognaths (arrow worms, predatory)

  • Thaliaceans (salps, doliolids, pyrosomes)

  • Other (remaining groups)

Interpretation

Actual Scale: Shows true abundance patterns. Useful for seeing:

  • Total community biomass/abundance changes

  • Bloom events

  • Which groups dominate numerically

Proportion Scale: Shows relative composition. Useful for seeing:

  • Community shifts (e.g., diatoms to dinoflagellates)

  • Seasonal succession patterns

  • Long-term regime shifts

  • Changes that might be masked by overall abundance changes

Colours are assigned consistently across plots for each functional group.

See also

pr_get_FuncGroups() for preparing the input data, pr_plot_PieFG() for pie chart visualisation of functional groups

Examples

# Plot actual abundances over time
df <- pr_get_FuncGroups("NRS", "Phytoplankton") %>%
  dplyr::filter(StationCode %in% c('MAI', 'PHB'))
pr_plot_tsfg(df, Scale = "Actual", Trend = "Raw")
#> Warning: Removed 5 rows containing non-finite outside the scale range (`stat_align()`).


# Plot as proportions to see community shifts
pr_plot_tsfg(df, Scale = "Proportion", Trend = "Raw")
#> Warning: Removed 5 rows containing non-finite outside the scale range (`stat_align()`).


# Monthly climatology showing seasonal patterns
pr_plot_tsfg(df, Scale = "Proportion", Trend = "Month")


# Zooplankton functional groups
df_zoo <- pr_get_FuncGroups("CPR", "Zooplankton", near_dist_km = 250) %>%
  dplyr::filter(BioRegion == "South-east")
pr_plot_tsfg(df_zoo, Scale = "Actual", Trend = "Raw")
#> Warning: Removed 70 rows containing non-finite outside the scale range (`stat_align()`).