IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v220y2009i15p1787-1796.html
   My bibliography  Save this article

Combining a generic process-based productivity model and a statistical classification method to predict the presence and absence of tree species in the Pacific Northwest, U.S.A

Author

Listed:
  • Coops, Nicholas C.
  • Waring, Richard H.
  • Schroeder, Todd A.

Abstract

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.

Suggested Citation

  • Coops, Nicholas C. & Waring, Richard H. & Schroeder, Todd A., 2009. "Combining a generic process-based productivity model and a statistical classification method to predict the presence and absence of tree species in the Pacific Northwest, U.S.A," Ecological Modelling, Elsevier, vol. 220(15), pages 1787-1796.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:15:p:1787-1796
    DOI: 10.1016/j.ecolmodel.2009.04.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380009002907
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2009.04.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wulder, Michael A. & White, Joanne C. & Coops, Nicholas C. & Nelson, Trisalyn & Boots, Barry, 2007. "Using local spatial autocorrelation to compare outputs from a forest growth model," Ecological Modelling, Elsevier, vol. 209(2), pages 264-276.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mathys, A.S. & Coops, N.C. & Simard, S.W. & Waring, R.H. & Aitken, S.N., 2018. "Diverging distribution of seedlings and mature trees reflects recent climate change in British Columbia," Ecological Modelling, Elsevier, vol. 384(C), pages 145-153.
    2. Gupta, Rajit & Sharma, Laxmi Kant, 2019. "The process-based forest growth model 3-PG for use in forest management: A review," Ecological Modelling, Elsevier, vol. 397(C), pages 55-73.
    3. Coops, Nicholas C. & Waring, Richard H., 2011. "Estimating the vulnerability of fifteen tree species under changing climate in Northwest North America," Ecological Modelling, Elsevier, vol. 222(13), pages 2119-2129.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:220:y:2009:i:15:p:1787-1796. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.