Niches, models, and climate change: Assessing the assumptions and uncertainties

Niches, models, and climate change: Assessing the assumptions and uncertainties

November 17, 2009 | John A. Wiens, Diana Stralberg, Dennis Jongsomjit, Christine A. Howell, and Mark A. Snyder
The article "Niches, models, and climate change: Assessing the assumptions and uncertainties" by John A. Wiens, Diana Stralberg, Dennis Jongsomjit, Christine A. Howell, and Mark A. Snyder explores the use of species distribution models (SDMs) to predict future species distributions in response to climate change. The authors highlight the assumptions and uncertainties inherent in SDMs, which can affect the reliability of projections. They illustrate these concepts using two climate models and two distributional algorithms to project future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070, with significant losses in "hotspots" of vulnerability. The study also examines how differences in distributional shifts among species will alter species co-occurrences, creating spatial variations in assemblages. The authors discuss ways to address assumptions and reduce uncertainties, emphasizing the importance of documenting sources and magnitudes of uncertainty and the need for conservationists and resource managers to act despite these uncertainties. They conclude that while SDMs provide valuable insights, they must be used with caution and in conjunction with other methods to inform conservation and management decisions.The article "Niches, models, and climate change: Assessing the assumptions and uncertainties" by John A. Wiens, Diana Stralberg, Dennis Jongsomjit, Christine A. Howell, and Mark A. Snyder explores the use of species distribution models (SDMs) to predict future species distributions in response to climate change. The authors highlight the assumptions and uncertainties inherent in SDMs, which can affect the reliability of projections. They illustrate these concepts using two climate models and two distributional algorithms to project future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070, with significant losses in "hotspots" of vulnerability. The study also examines how differences in distributional shifts among species will alter species co-occurrences, creating spatial variations in assemblages. The authors discuss ways to address assumptions and reduce uncertainties, emphasizing the importance of documenting sources and magnitudes of uncertainty and the need for conservationists and resource managers to act despite these uncertainties. They conclude that while SDMs provide valuable insights, they must be used with caution and in conjunction with other methods to inform conservation and management decisions.
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