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    Author(s): Aaron R. Weiskittel; Nicholas L. Crookston; Philip J. Radtke
    Date: 2011
    Source: Canadian Journal of Forest Research. 41: 1710-1721.
    Publication Series: Scientific Journal (JRNL)
    Station: Rocky Mountain Research Station
    PDF: Download Publication  (517.36 KB)


    Assessing forest productivity is important for developing effective management regimes and predicting future growth. Despite some important limitations, the most common means for quantifying forest stand-level potential productivity is site index (SI). Another measure of productivity is gross primary production (GPP). In this paper, SI is compared with GPP estimates obtained from 3-PG and NASA's MODIS satellite. Models were constructed that predict SI and both measures of GPP from climate variables. Results indicated that a nonparametric model with two climate-related predictor variables explained over 68% and 76% of the variation in SI and GPP, respectively. The relationship between GPP and SI was limited (R2 of 36%-56%), while the relationship between GPP and climate (R2 of 76%-91%) was stronger than the one between SI and climate (R2 of 68%-78%). The developed SI model was used to predict SI under varying expected climate change scenarios. The predominant trend was an increase of 0-5 m in SI, with some sites experiencing reductions of up to 10 m. The developed model can predict SI across a broad geographic scale and into the future, which statistical growth models can use to represent the expected effects of climate change more effectively.

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    Weiskittel, Aaron R.; Crookston, Nicholas L.; Radtke, Philip J. 2011. Linking climate, gross primary productivity, and site index across forests of the western United States. Canadian Journal of Forest Research. 41: 1710-1721.


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    future growth, forests, site index (SI), gross primary production (GPP)

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