Click here for a high resolution photograph. |
Last year, the World Conservation Union reported an unprecedented decline in biodiversity, with nearly 16,000 species facing extinction. The biggest threat to most species is loss of habitat. And as habitat loss and degradation proceed nearly unabated, the need to accurately predict the population dynamics and extinction risk of potentially endangered species has never been greater. In a new study, John Drake tests models traditionally used to estimate the likelihood of extinction and shows that because they ignore a critical parameter in projecting risk, they underestimate extinction rates.
Standard models for predicting extinction assume that population growth and decline are governed by random, or stochastic, variables. But few scientists have actually tested the accuracy of these models with empirical data. To do this, Drake first manipulated the available food sources in 281 populations of water fleas, because it's generally assumed that fluctuating environments, a given in the natural world, increase a species's chance of extinction. Drake then used half of the experimental data generated from testing the effects of environmental variability on water flea survival to select his models and estimate a range of parameters that might affect extinction, and the other half to test the models' reliability. From the estimated parameters, Drake wrote a computer program to simulate all the possible population outcomes and predict extinction rates. However, one set of simulations included a parameter for density-dependent random interactions and another did not. The idea is that if organisms interact with each other in their environments--which of course they do--then these interactions will likely affect an individual's probability of dying or reproducing, which ultimately affects species survival. Drake calls this variable density-dependent demographic stochasticity. Only when density-dependence was included did the models match the observed extinction rates in the flea experiments. When density dependence was not included, extinction rates were greatly underestimated.
Drake's results underscore the importance of bolstering extinction models with empirical validation--and of accounting for population density--to accurately evaluate risk and enhance recovery programs for at-risk populations. As threats to endangered species continue to mount, biologists will need ever more robust methods to estimate extinction risk. Unfortunately, field biologists typically can't generate the large, high-quality datasets that led to the precise predictions reported here. Conservation efforts will depend on developing methods of generating reliable predictions with the limited data available from the field.
Citation: Drake JM (2005) Density-dependent demographic variation determines extinction rate of experimental populations. PLoS Biol 3(7): e222.
CONTACT:
John Drake
University of California, Santa Barbara
National Center for Ecological Analysis and Synthesis
735 State Street
Santa Barbara, CA USA 93101
+1-805-892-2529
+1-805-892-2510 (fax)
drake@nceas.ucsb.edu
PLEASE MENTION PLoS Biology (www.plosbiology.org) AS THE SOURCE FOR THESE ARTICLES. THANK YOU.
All works published in PLoS Biology are open access. Everything is immediately available without cost to anyone, anywhere--to read, download, redistribute, include in databases, and otherwise use--subject only to the condition that the original authorship is properly attributed. Copyright is retained by the authors. The Public Library of Science uses the Creative Commons Attribution License.
Journal
PLoS Biology