Atomic rarefaction / extrapolation plot (internal) — RarefactionPlotAtomic • plotthis

Core implementation for drawing a single rarefaction (or extrapolation) curve from biodiversity data. This is the workhorse behind the exported RarefactionPlot — it takes a single fortifed data frame (produced by fortify() on an iNEXT object) and returns a ggplot object.

The function renders three types of curves:

Sample-size-based (type = 1) — species diversity as a function of sample size (number of individuals or sampling units), with rarefaction (interpolation) and extrapolation segments.
Sample completeness (type = 2) — sample coverage as a function of sample size.
Coverage-based (type = 3) — species diversity as a function of sample coverage.

Observed data points are marked with geom_point() (shape per group), the rarefaction / extrapolation lines are drawn with geom_line() using a solid/dashed linetype to distinguish the two phases, and confidence intervals are rendered as semi-transparent ribbons when se = TRUE and the fortifed data contains y.lwr / y.upr columns.

Usage

RarefactionPlotAtomic(
  data,
  type = 1,
  se = TRUE,
  group_by = "group",
  group_name = NULL,
  pt_size = 3,
  line_width = 1,
  theme = "theme_this",
  theme_args = list(),
  palette = "Spectral",
  palcolor = NULL,
  palreverse = FALSE,
  alpha = 0.2,
  facet_by = NULL,
  facet_scales = "fixed",
  facet_ncol = NULL,
  facet_nrow = NULL,
  facet_byrow = TRUE,
  aspect.ratio = 1,
  legend.position = "right",
  legend.direction = "vertical",
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  ...
)

Arguments

data: A data frame produced by fortify() on an iNEXT object. Expected to contain columns x (sample size or coverage), y (diversity or coverage estimate), Method ("Observed", "Rarefaction", "Extrapolation"), y.lwr / y.upr (confidence bounds, optional), datatype ("abundance" or "incidence"), group (assemblage name, renamed from Assemblage), and q (diversity order, renamed from Order.q).
type: An integer specifying the curve type: 1 for sample-size-based rarefaction/extrapolation, 2 for sample completeness, or 3 for coverage-based rarefaction/extrapolation. A vector of types can be passed and the data will be fortifed for all of them; faceting or splitting then separates the panels. Default: 1.
se: A logical value indicating whether to display confidence intervals as semi-transparent ribbons around the estimated curve. When NULL (the default), it resolves to TRUE if the fortifed data contains y.lwr and y.upr columns, and FALSE otherwise.
group_by: A character vector specifying how to group the data for colouring the lines. Must be one or both of "q" (diversity order) and "group" (assemblage/site). Multiple values are concatenated with group_by_sep. When NULL, a dummy ".group" column is created and the legend is hidden. Default: "group".
group_name: A character string used as the title for the colour (and shape) legend. When NULL (the default), the value of group_by is used.
pt_size: A numeric value specifying the size of the observed-data points. Default: 3.
line_width: A numeric value specifying the width of the rarefaction / extrapolation lines. Default: 1.
theme: A character string or a theme class (i.e. ggplot2::theme_classic) specifying the theme to use. Default is "theme_this".
theme_args: A list of arguments to pass to the theme function.
palette: A character string specifying the colour palette to use. A named list or vector can be used to specify palettes for different split_by levels in the exported RarefactionPlot. Default: "Spectral".
palcolor: A character string specifying the color to use in the palette. A named list can be used to specify the colors for different split_by values. If some values are missing, the values from the palette will be used (palcolor will be NULL for those values).
palreverse: A logical value indicating whether to reverse the palette. Default is FALSE.
alpha: A numeric value between 0 and 1 specifying the transparency of the confidence-interval ribbon fill. Default: 0.2.
facet_by: A character string specifying the column name of the data frame to facet the plot. Otherwise, the data will be split by split_by and generate multiple plots and combine them into one using patchwork::wrap_plots
facet_scales: Whether to scale the axes of facets. Default is "fixed" Other options are "free", "free_x", "free_y". See ggplot2::facet_wrap
facet_ncol: A numeric value specifying the number of columns in the facet. When facet_by is a single column and facet_wrap is used.
facet_nrow: A numeric value specifying the number of rows in the facet. When facet_by is a single column and facet_wrap is used.
facet_byrow: A logical value indicating whether to fill the plots by row. Default is TRUE.
aspect.ratio: A numeric value specifying the aspect ratio of the plot.
legend.position: A character string specifying the position of the legend. if waiver(), for single groups, the legend will be "none", otherwise "right".
legend.direction: A character string specifying the direction of the legend.
title: A character string specifying the title of the plot. A function can be used to generate the title based on the default title. This is useful when split_by is used and the title needs to be dynamic.
subtitle: A character string specifying the subtitle of the plot.
xlab: A character string specifying the x-axis label.
ylab: A character string specifying the y-axis label.
...: Additional arguments (currently unused in the atomic function; accepted for forward compatibility with the exported wrapper).

Value

A ggplot object with height and width attributes (in inches) attached.

Architecture

ggplot dispatch — selects gglogger::ggplot or ggplot2::ggplot based on getOption("plotthis.gglogger.enabled").
Axis labels — set according to the combination of type and the data's datatype attribute ("abundance" vs. "incidence"):
- type = 2: x = "Number of individuals" or "Number of sampling units", y = "Sample coverage".
- type = 3 || 4: x = "Sample coverage", y = "Species diversity".
- type = 1 (abundance): x = "Number of individuals", y = "Species diversity".
- type = 1 (incidence): x = "Number of sampling units", y = "Species diversity".
Group name fallback — if group_name is NULL, it is set to the value of group_by (i.e. "q" or "group").
Base ggplot — initialises ggplot(data, aes(x, y, color = group_by)).
Observed data points — geom_point() on rows where Method == "Observed", with shape mapped to the group variable.
Colour scale — scale_color_manual() using palette_this(). The legend is suppressed when group_by is the dummy ".group".
Shape scale — scale_shape_discrete() with the same legend-suppression logic.
Rarefaction / extrapolation lines — geom_line() with linetype mapped to the lty column ("Rarefaction" vs. "Extrapolation").
Linetype scale — scale_linetype_manual() with solid and dashed values, legend key width set to 1 cm.
Theme and labels — do_call(theme, theme_args), panel.grid.major (grey80 dashed), aspect ratio, legend position / direction, and title / subtitle.
Confidence ribbon — when se = TRUE, a geom_ribbon(aes(ymin = y.lwr, ymax = y.upr, fill = group_by)) is added with the same per-group palette at transparency alpha.
Dimension calculation — calculate_plot_dimensions() computes height / width attributes from base_height = 4.5, aspect.ratio, and legend metrics.
Faceting — facet_plot() wraps the plot with facet_wrap / facet_grid if facet_by is provided.