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    Author(s): Bettina Ohse; Falk Huettmann; Stefanie M. Ickert-Bond; Glenn P. Juday
    Date: 2009
    Source: Polar Biology. 32: 1717-1729
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Northwest Research Station
    PDF: View PDF  (2.28 MB)


    Most wilderness areas still lack accurate distribution information on tree species. We met this need with a predictive GIS modeling approach, using freely available digital data and computer programs to efficiently obtain high-quality species distribution maps. Here we present a digital map with the predicted distribution of white spruce (Picea glauca) in Alaska (4 km resolution, accuracy over 90%). Our presented concept represents a role-model for predicting tree species distribution for remote areas world-wide. Although this model intends to be accurate in making predictions rather than to give detailed biological mechanistic explanations, it can also be used as a baseline for further research and testable hypothesis on the importance of the environmental variables used to build a generalizable model. Further, we emphasize that work like presented here is a pre-condition for assessing human impacts and impacts of climate change on species distribution in a quantitative and transparent fashion, allowing for improved sustainable decision-making world-wide.

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    Ohse, Bettina; Huettmann, Falk; Ickert-Bond, Stefanie M.; Juday, Glenn P. 2009. Modeling the distribution of white spruce (Picea glauca) for Alaska with high accuracy: an open access role-model for predicting tree species in last remaining wilderness areas. Polar Biology. 32: 1717-1729.


    species distribution models (SDM), Alaska, tree species, predictive modeling, open access (OA), white spruce Picea glauca

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