The diffusion approximation overestimates the extinction risk for count-based PVA

Kendall, Bruce E. (2009) The diffusion approximation overestimates the extinction risk for count-based PVA. Conservation Letters, 2 5: 216-225. doi:10.1111/j.1755-263X.2009.00069.x


Author Kendall, Bruce E.
Title The diffusion approximation overestimates the extinction risk for count-based PVA
Journal name Conservation Letters   Check publisher's open access policy
ISSN 1755-263X
Publication date 2009-10
Sub-type Article (original research)
DOI 10.1111/j.1755-263X.2009.00069.x
Open Access Status DOI
Volume 2
Issue 5
Start page 216
End page 225
Total pages 10
Place of publication Oxford, U.K.
Publisher Wiley-Blackwell Publishing
Language eng
Formatted abstract
Simple population models are increasingly being used to predict extinction risk using historical abundance estimates. A very simple model, the stochastic exponential growth (SEG) model, is surprisingly robust. Extinction risk is commonly computed for this model using a mathematical approximation (the “diffusion approximation”) that assumes continuous breeding throughout the year, an assumption that is violated by many species. Here I show that, for an organism with seasonal breeding, the diffusion approximation systematically overestimates the extinction risk. I demonstrate the conditions generating large bias (high environmental variance, intermediate extinction risk), and reanalyze 100 populations of conservation concern. Analyzing several policy applications, I find that the bias may be most important when classifying the risk status of species. The SEG model is still sound, but associated risk estimates should be calculated by performing stochastic simulations (as with all other population viability models) rather than by evaluating the diffusion approximation.
Keyword Density-independent population dynamics
Diffusion approximation
Extinction
IUCN red list
Mathematical models
Population decline
Population viability analysis
Stochastic exponential growth model
Population viability analysis
South-africa
Observation error
Nature-reserve
National-park
Model
Conservation
Probability
Meaningful
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Ecology Centre Publications
 
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Created: Sun, 11 Jul 2010, 00:07:46 EST