DOI: 10.5061/dryad.533534r
title: Data from: When are extinctions simply bad luck? rarefaction as a framework for disentangling selective and stochastic extinctions

description: 1. A key challenge in conservation biology is that not all species are
 equally likely to go extinct when faced with a disturbance. Traditionally,
 differences in species extinction risk are considered a form of extinction
 selectivity, a nanrondom process by which species’ extinction risks are
 associated with their traits. While selectivity clearly contributes to
 varation in extinction among taxa, it is also clear that rare species are
 more likely to go extinct than are common species. While obvious, this law
 of extinction suggests that random chance, operating on species abundance,
 plays an important role in the extinction process. Unless ecologists and
 conservation biologists can disentangle random and nonrandom extinction
 processes, then the prediction and prevention of future extinctions will
 continue to be an elusive challenge. 2. We suggest that a modified version
 of a common null model procedure, rarefaction, can be used to disentangle
 the influence of stochastic species loss from selective nonrandom
 processes. To this end we applied a rarefaction based null model to three
 published data sets to characterize the influence of species rarity in
 driving biodiversity loss following three disturbance events: i)
 disease-associated bat declines; ii) disease-associated amphibian
 declines; and iii) habitat loss and invasive species-associated gastropod
 declines. For each case study, we used rarefaction to generate null
 expectations of stochastic biodiversity loss and species-specific
 extinction probabilities. 3. In each of our case studies we find evidence
 for random and nonrandom (selective) extinctions. Our findings highlight
 the importance of explicitly considering that some species extinctions are
 the result of stochastic processes, i.e., bad luck. 4. Policy Implications
 If there is a first law of extinction, it is that rare species are most
 likely than common species to go extinct. We suggest that taking this law
 into account in analyses of extinction risk is critical to the
 identification of selective extinctions. Our results suggest that
 rarefaction can be used to identify nonrandom decline, extirpation, and
 extinction events and provide an important baseline comparison point for
 future extinction analyses.12-Jul-2019
description: Chiba & Roy (2011)
 DataThis is the data
 described in Chiba & Roy (2011), which documents the declines of
 endemic gastropods in the Ogasawara archipelago.Chiba&Roy2011_Data.xlsFrancl et al. (2012) DataThis is the data described in Table 1 of Francl et al. (2012), which documents the decline of bat species in West Virginia due to white nose syndrome.FranclEtAl2012_Table1.xlsxRarefaction Example DataThis is an example data set based on arthropod communities to be used in conjunction with the script RarefactionNullModel.R.Rarefaction_ExampleData.xlsxRarefaction-based null model scriptThis script outlines a step by step procedure for using rarefaction analyses as a null model for stochastic species loss. It is designed to be used in conjunction with the data described in Rarefaction_ExampleData.xlsx and uses the packages vegan, plyr, and readxl.RarefactionNullModel.R