Plot mixtures against monocultures for one species

Shows what sharing a cell does to total aboveground carbon: the species alone against every two-cohort mixture it appears in. This is the question the single-species calibration cells cannot answer, since they never let two cohorts compete for light.

Usage

plot_growth_structures(
  summary,
  species,
  x_max = 100,
  max_panels = NULL,
  regen_flags = NULL
)

Arguments

summary

A tibble from growth_structure_summary().

species

Character. Modelled species code to plot.

x_max

Numeric or NULL. Clip the data to this simulation year.

max_panels

Integer or NULL. Keep only this many compositions, those with the most cells behind them. NULL (the default) keeps all, which is right when cells hold at most a couple of cohorts and a species appears in a handful of compositions. Where cells carry many age classes a species can appear in over a hundred, and a facet per composition renders as unreadable slivers with truncated strips. What was dropped is stated in the subtitle rather than left implied.

regen_flags

Named character vector, or NULL (the default). Names are species codes; values name a regeneration mechanism that CANNOT operate in the runs behind summary – typically serotiny or resprouting, both of which LANDIS-II arms only from a disturbance-caused cohort death, in a run carrying no disturbance extension. Panels whose composition holds a named species are marked, and the marker is explained in the caption. Needs the species_set column to match on; without it the flags are ignored with a warning, since composition is a display label and parsing it would mis-read Hw x2 as a species named Hw x2.

Value

A ggplot, or NULL when the species appears in no composition.

Details

The x axis is SIMULATION YEAR, not stand age. Unlike the verification runs, which plant a single age-1 cohort, these cells start at the cohort ages the initial-communities map actually carries, which can be several centuries. A panel therefore begins at whatever carbon those cohorts already hold, and a mid-run collapse is usually an old cohort reaching longevity rather than anything the parameters did.

See also

Other growth calibration helpers: extract_landscape_cohort_structures(), growth_add_objective(), growth_auto_window(), growth_best_candidates(), growth_bin_observations(), growth_calibration_design(), growth_calibration_partition(), growth_calibration_work_root(), growth_climatic_distance(), growth_climatic_weight(), growth_expand_over_pseudo_species(), growth_factorial_ratio_grid(), growth_fitting_windows(), growth_identifiability(), growth_inflation_factor(), growth_mortality_onset_frac(), growth_plot_palette(), growth_pseudo_species_name(), growth_reference_curves(), growth_reference_inflection(), growth_score_fit(), growth_scoring_for(), growth_smooth_observations(), growth_structure_cell_curves(), growth_structure_cohort_table(), growth_structure_design(), growth_structure_summary(), growth_window_for(), plot_growth_calibration(), plot_growth_candidate(), plot_growth_factorial_sensitivity(), read_growth_scoring(), read_landscape_cohort_structures(), scale_linetype_growth_reference(), write_growth_review_bundle()