time to loss of skill vs population size
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1 changed files with 4 additions and 29 deletions
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@ -403,7 +403,7 @@ extinction_summary <- data.frame(
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)
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```
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```{r skill-extinction-boxplot, fig.width=3.5, fig.height=7.5, fig.cap=paste("Time to extinction among runs with observed extinction, from", extinction_repeats, "runs per population size. ")}
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```{r skill-extinction-boxplot, fig.width=5, fig.height=7.5, fig.cap=paste("Time to extinction among runs with observed extinction, from", extinction_repeats, "runs per population size. ")}
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old_par <- par(mar = c(6, 4.5, 1, 1))
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if (any(lengths(extinction_times) > 0)) {
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@ -414,21 +414,13 @@ if (any(lengths(extinction_times) > 0)) {
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border = line_cols,
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outpch = 16,
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outcex = 0.7,
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ylim = range(0, unlist(extinction_times)),
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ylim = c(10,5000),
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range=0,
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xlab = "",
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xlab = "Population size",
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ylab = "Generations until extinction",
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lig="y",
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log="y",
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las = 1
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)
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mtext(
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paste0(lengths(extinction_times), "/", extinction_repeats, " extinctions"),
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side = 1,
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at = seq_along(population_sizes),
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line = 2.3,
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cex = 0.9
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)
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mtext("Population size", side = 1, line = 4.3)
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} else {
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plot.new()
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text(0.5, 0.5, "No extinctions were observed within the generation limit.")
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@ -437,20 +429,3 @@ if (any(lengths(extinction_times) > 0)) {
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par(old_par)
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```
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```{r skill-extinction-summary}
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knitr::kable(
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extinction_summary,
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digits = 1,
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caption = paste(
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"Outcomes across", extinction_repeats,
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"runs per population size. Median extinction times are in generations",
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"and include only observed extinctions."
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)
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)
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```
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The spread of extinction times shows why one run is insufficient to characterise
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the loss of highly skilled people. Larger populations can retain these skills
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for longer, but outcomes still vary because copying is random. These boxplots
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describe the timing of loss **conditional on extinction being observed**; the
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table also shows how often extinction occurred among all the runs.
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