Using imaging spectroscopy to estimate integrated measures of foliage nutritional quality

Kara N. Youngentob*, Luigi J. Renzullo, Alex A. Held, Xiuping Jia, David B. Lindenmayer, William J. Foley

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    29 Citations (Scopus)

    Abstract

    1.Integrated measures of foliage nutritional quality that consider the influence of fibre and tannins on the digestibility of nitrogen (N) may provide a more meaningful estimate of forage quality than total foliar N for many herbivorous species. The ability to estimate available nitrogen (AvailN) on a landscape scale could have important applications for herbivore conservation and management. However, AvailN has never been modelled with imaging spectroscopy. 2.We collected hyperspectral remote sensing data (HyMap) over Eucalyptus trees in south-eastern Australia. Using a combination of laboratory near infrared spectrophotometry, a recently developed in vitro assay for AvailN and two powerful spectral transformation methods, continuum removal and derivative analysis, we developed linear regression models to scale concentrations of total foliar N, AvailN and digestible dry matter (DDM) from leaf to canopy-level. 3.The model estimates achieved R 2-values between 0·55 and 0·64 for AvailN, 0·54-0·60 for N and 0·75-0·78 for DDM. Ninety-five per cent of the wavebands selected by the models corresponded to known absorption features. This and the large contribution of a small number of wavebands suggest that it may be possible to develop prediction algorithms based on a few wavelengths that could be extrapolated to other landscape types. 4.This is the first time that integrated measures of foliage nutritional quality have been estimated with imaging spectroscopy. In combination with appropriate crown-delineation techniques, our methodology will enable users to map variations in these foliar constituents across forest canopies.

    Original languageEnglish
    Pages (from-to)416-426
    Number of pages11
    JournalMethods in Ecology and Evolution
    Volume3
    Issue number2
    DOIs
    Publication statusPublished - Apr 2012

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