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Advanced Analysis Panel (rank/occupancy/SAR/decay/rarefaction + optional PPC)

Source: R/panel.R
generate_advanced_panel.Rd

Build a multi‑panel summary of key ecological diagnostics from a simulation run: rank–abundance (SAD), occupancy–abundance, species–area (accumulation), distance–decay, and per‑quadrat rarefaction curves. If the point‑process packages spatstat.geom and spatstat.explore are available, an additional row of point–process diagnostics is appended, showing Ripley’s K (border correction), \(L(r)-r\), and the pair‑correlation function \(g(r)\).

Usage

generate_advanced_panel(res)

Arguments

res

A list produced by the main simulator containing at least:

P

Parameter list (used for labels/themes if needed).

species_dist

An sf POINT layer of individuals with a species column.

abund_matrix

Site \(\times\) species abundance data frame (first column site).

site_coords

Data frame with site, x, y for quadrat centroids.

domain

An sf polygon/multipolygon of the study area (used for PPC window).

Value

A patchwork object (a ggplot layout). You can print it or save it with ggplot2::ggsave().

Details

The optional point–process diagnostics are computed only when both spatstat.geom (for spatial windows and point patterns) and spatstat.explore (for summary functions such as Kest and pcf) are installed. The domain is converted to a window (owin) using spatstat.geom::as.owin() on the sf polygon; the individuals are converted to a ppp with that window. We then compute:

  • Kest(ppp, correction = "border") and plot the border‑corrected K.

  • \(L(r) = \sqrt{K(r)/\pi}\) and \(L(r)-r\) (\(>0\) suggests clustering).

  • pcf(ppp) as an estimate of the pair‑correlation \(g(r)\) (\(>1\) suggests clustering; \(<1\) inhibition).

If conversion to owin/ppp fails, the PPC row is omitted gracefully.

See also

calculate_rank_abundance, plot_rank_abundance, calculate_occupancy_abundance, plot_occupancy_abundance, calculate_species_area, plot_species_area, calculate_distance_decay, plot_distance_decay, calculate_rarefaction, plot_rarefaction

Examples

if (FALSE) { # \dontrun{
panel <- generate_advanced_panel(results_list)
ggplot2::ggsave("advanced_panel.png", panel, width = 12, height = 14, dpi = 300)
} # }