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    Author(s): Louis R. IversonAnantha M. Prasad
    Date: 2001
    Source: Ecosystems. 4: 186-199.
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (660.05 KB)


    Potential changes in tree species richness and forest community types were evaluated for the eastern United States according to five scenarios of future climate change resulting from a doubling of atmospheric carbon dioxide (CO2). DISTRIB, an empirical model that uses a regression tree analysis approach, was used to generate suitable habitat, or potential future distributions, of 80 common tree species for each scenario. The model assumes that the vegetation and climate are in equilibrium with no barriers to species migration. Combinations of the individual species model outcomes allowed estimates of species richness (from among the 80 species) and forest type (from simple rules) for each of 2100 counties in the eastern United States. Average species richness across all counties may increase slightly with climatic change. This increase tends to be larger as the average temperature of the climate change scenario increases. Dramatic changes in the distribution of potential forest types were modeled. All five scenarios project the extirpation of the spruce-fir forest types from New England. Outputs from only the two least severe scenarios retain aspen-birch, and they are largely reduced. Maple-beech-birch also shows a large reduction in area under all scenarios. By contrast, oak-hickory and oak-pine types were modeled to increase by 34% and 290%, respectively, averaged over the five scenarios. Although many assumptions are made, these modeled outcomes substantially agree with a limited number of predictions from researchers using paleoecological data or other models.

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    Iverson, Louis R.; Prasad, Anantha M. 2001. Potential Changes in Tree Species Richness and Forest Community Types following Climate Change. Ecosystems. 4: 186-199.


    climate change, species richness, forest, types, GIS, statistical model, eastern United States

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