Example I

Here we consider the sighting rate of one of our targets, Plagiobothrys tenellus, as an example. We will use this sighting rate to test the null hypothesis that extinction has not occurred.

First, we assume 1958, the date of the first botanical collection on Galiano Island, as the earliest date that observations of this species might have been made, and 2019—the date that our study began—as the time frame bracketing our analysis.

How many times has this species been observed historically on Galiano Island?

records <- read.csv("Analysis_Inputs/Galiano_Island_vascular_plant_records_2024-10-09.csv")

# Filter for Plagiobothrys tenellus records
Ptenellus <- records %>% filter(scientificName == 'Plagiobothrys tenellus')

# Omit list records, retaining only vouchered specimens
Ptenellus <- Ptenellus %>% filter(basisOfRecord != 'MaterialCitation')
n_Ptenellus <- nrow(Ptenellus)

cat("Plagiobothrys tenellus has been observed", 
    n_Ptenellus, "times historically.")

## Plagiobothrys tenellus has been observed 3 times historically.

When was the most recent sighting?

records <- read.csv("Analysis_Inputs/Galiano_Island_vascular_plant_records_2024-10-09.csv")

# Identify the most recent sighting
recent_sighting <- max(Ptenellus$eventDate)

cat("Plagiobothrys tenellus was last observed in", 
    recent_sighting, ".")

## Plagiobothrys tenellus was last observed in 1998-04-10 .

\(t_n = 1998\)

The interactive calculator below ascribes these to values to Solow's extinction equation. The resulting Bayes factor, \(B(t)\), favours the null hypothesis that extinction has not occurred. We also report our prior probability of presence, \(PP(t)\), and \(EP(t) = 1 - PP(t)\), our prior probability of extinction—which feed into subsequent analyses.