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Proc Natl Acad Sci U S A. 2009 Nov 17;106 Suppl 2:19729-36. doi: 10.1073/pnas.0901639106. Epub 2009 Oct 12.

Niches, models, and climate change: assessing the assumptions and uncertainties.

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  • 1PRBO Conservation Science, 3820 Cypress Drive #11, Petaluma, CA 94954, USA. jwiens@prbo.org

Abstract

As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some "hotspots" of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option.

PMID:
19822750
[PubMed - indexed for MEDLINE]
PMCID:
PMC2780938
Free PMC Article
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