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    Author(s): Brian Roy LockhartEmile S. Gardiner; Theran P. Stautz; Theodore D. Leininger; Paul B. Hamel; Kristina F. Connor; Nathan M. SchiffA. Dan WilsonMargaret S. Devall
    Date: 2007
    Source: Res. Note SE-14. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 8 p.
    Publication Series: Research Note (RN)
    Station: Southern Research Station
    PDF: View PDF  (0.99 MB)

    Description

    Pondberry (Lindera melissifolia [Walt.] Blume) is a federally listed endangered shrub found as isolated populations in seasonally flooded forests across the Southeastern United States. Because this shrub is rare, it has received little research attention, and basic knowledge of its ecology and physiology is lacking. To facilitate future ecological and physiological studies on pondberry, we developed and tested a model to predict area of individual leaf blades from simple dimensions that are obtained nondestructively. A linear function, using the product of blade length and width as the independent variable, was found to be the most suitable predictor of pondberry leaf blade area based on correlation coefficients (r2 = 0.99561, plots of actual versus predicted values, and predicted versus residual values. We demonstrate that simple dimensions that are obtained nondestructively, such as blade length and width, can be used to reliably predict leaf blade area of pondberry, but model coefficients should be calibrated for local colonies to improve estimates. Development of this model allows for leaf blade area determination at the plant level without the need to destructively harvest foliage.

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    Citation

    Lockhart, Brian Roy; Gardiner, Emile S.; Stautz, Theran P.; Leininger, Theodore D.; Hamel, Paul B.; Connor, Kristina F.; Schiff, Nathan M.; Wilson, A. Dan.; Devall, Margaret S. 2007. Nondestructive estimation of leaf area for pondberry. Res. Note SE-14. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 8 p.

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