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On the Potential Extinction of High-Elevation Species
Volume 12, Number 38: 23 September 2009

In his 26 April 2007 testimony before the Select Committee of Energy Independence and Global Warming of the U.S. House of Representatives entitled "Dangerous Human-Made Interference with Climate," NASA's James Hansen stated that life in alpine regions is "in danger of being pushed off the planet" in response to continued anthropogenic-induced global warming. Why? Because that's what all the species distribution models or SDMs predicted at the time. Now, however, a set of new-and-improved models is raising some serious questions about this overly zealous contention.

The concept behind the new models is described by Randin et al. (2009) in the pages of Global Change Biology, where they write that "the mean temperature interpolated from local stations at a 20-meter resolution contains more variability than expressed by the mean temperature within a 50-km x 50-km grid cell in which variation in elevation is poorly represented." Or as they describe it in another part of their paper, "climatic differences along elevation gradients, as apparent at 25-m x 25-m resolution allow plant species to find suitable climatic conditions at higher elevation under climate change," whereas "models at a 10 x 10' resolution [10 minutes of latitude x ten minutes of longitude, which correspond to 16-km x 16-km cells in the Swiss Alps, where they carried out their analyses] reflect the mean climatic conditions within the cell, and thus provide imprecise values of the probability of occurrence of species along a thermal gradient."

In testing this "local high-elevation habitat persistence hypothesis," as they describe it, the group of Swiss, French and Danish researchers assessed "whether climate change-induced habitat losses predicted at the European scale (10 x 10' grid cells) are also predicted from local-scale data and modeling (25-m x 25-m grid cells)." In doing so, they found that for 78 mountain species modeled at both European and local scales, the "local-scale models predict persistence of suitable habitats in up to 100% of species that were predicted by a European-scale model to lose all their suitable habitats in the area."

In discussing their findings, Randin et al. suggest that the vastly different results they obtained when using fine and coarse grid scales might help to explain what they call the Quaternary Conundrum, i.e. "why fewer species than expected went extinct during glacial periods when models predict so many extinctions with similar amplitude of climate change (Botkin et al., 2007)." In addition, they note that "coarse-resolution predictions based on SDMs are commonly used in the preparation of reports by the Intergovernmental Panel on Climate Change," which are then used by "conservation planners, managers, and other decision makers to anticipate biodiversity losses in alpine and other systems across local, regional, and larger scales."

In light of this large-scale usage of coarse-grid analyses of species responses to climate change, it is important that both public and private policies are not based on the findings of such studies. All they do is provide a pseudo-scientific basis for folks such as NASA's James Hansen to feed their faulty predictions to decision makers at the highest levels of government -- both in our country (the United States) and elsewhere -- all in the guise of what they portray to be sound science, which they clearly are not.

Sherwood, Keith and Craig Idso

Botkin, D.B., Saxe, H., Araujo, M.B., Betts, R., Bradshaw, R.H.W., Cedhagen, T., Chesson, P., Dawson, T.P., Etterson, J.R., Faith, D.P., Ferrier, S., Guisan, A., Hansen, A.S., Hilbert, D.W., Loehle, C., Margules, C., New, M., Sobel, M.J. and Stockwell, D.R.B. 2007. Forecasting the effects of global warming on biodiversity. BioScience 57: 227-236.

Randin, C.F., Engler, R., Normand, S., Zappa, M., Zimmermann, N.E., Pearman, P.B., Vittoz, P., Thuiller, W. and Guisan, A. 2009. Climate change and plant distribution: local models predict high-elevation persistence. Global Change Biology 15: 1557-1569.