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    Author(s): Nicholas C. Coops; Richard H. Waring; Todd A. Schroeder
    Date: 2009
    Source: Ecological Modelling. 220: 1787-1796.
    Publication Series: Miscellaneous Publication
    PDF: View PDF  (843.66 KB)

    Description

    Although long-lived tree species experience considerable environmental variation over their life spans, their geographical distributions reflect sensitivity mainly to mean monthly climatic conditions.We introduce an approach that incorporates a physiologically based growth model to illustrate how a half-dozen tree species differ in their responses to monthly variation in four climatic-related variables: water availability, deviations from an optimum temperature, atmospheric humidity deficits, and the frequency of frost. Rather than use climatic data directly to correlate with a species' distribution,we assess the relative constraints of each of the four variables as they affect predicted monthly photosynthesis for Douglas-fir, the most widely distributed species in the region. We apply an automated regression-tree analysis to create a suite of rules, which differentially rank the relative importance of the four climatic modifiers for each species, and provide a basis for predicting a species' presence or absence on 3737 uniformly distributed U.S. Forest Services' Forest Inventory and Analysis (FIA) field survey plots. Results of this generalized rule-based approach were encouraging, with weighted accuracy, which combines the correct prediction of both presence and absence on FIA survey plots, averaging 87%. A wider sampling of climatic conditions throughout the full range of a species' distribution should improve the basis for creating rules and the possibility of predicting future shifts in the geographic distribution of species.

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    Citation

    Coops, Nicholas C.; Waring, Richard H.; Schroeder, Todd A. 2009. Combining a generic process-based productivity model classification method to predict the presence and absence species in the Pacific Northwest, U.S.A. Ecological Modelling. 220: 1787-1796.

    Keywords

    3-PG model, Regression-tree analysis, Climate change, US Forest Inventory and Analysis, Sitka spruce, Ponderosa pine, Western juniper, Lodgepole pine, Douglas-fir, Western hemlock

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