Many ecological studies rely heavily on chemical analysis of plant and animal tissues. Often, there is limited time and money to perform all the required analyses and this can result in less than ideal sampling schemes and poor levels of replication. Near infrared reflectance spectroscopy (NIRS) can relieve these constraints because it can provide quick, non-destructive and quantitative analyses of an enormous range of organic constituents of plant and animal tissues. Near infrared spectra depend on the number and type of C[Formula: see text]H, N[Formula: see text]H and O[Formula: see text]H bonds in the material being analyzed. The spectral features are then combined with reliable compositional or functional analyses of the material in a predictive statistical model. This model is then used to predict the composition of new or unknown samples. NIRS can be used to analyze some specific elements (indirectly - e.g., N as protein) or well-defined compounds (e.g., starch) or more complex, poorly defined attributes of substances (e.g., fiber, animal food intake) have also been successfully modeled with NIRS technology. The accuracy and precision of the reference values for the calibration data set in part determines the quality of the predictions made by NIRS. However, NIRS analyses are often more precise than standard laboratory assays. The use of NIRS is not restricted to the simple determination of quantities of known compounds, but can also be used to discriminate between complex mixtures and to identify important compounds affecting attributes of interest. Near infrared reflectance spectroscopy is widely accepted for compositional and functional analyses in agriculture and manufacturing but its utility has not yet been recognized by the majority of ecologists conducting similar analyses. This paper aims to stimulate interest in NIRS and to illustrate some of the enormous variety of uses to which it can be put. We emphasize that care must be taken in the calibration stage to prevent propagation of poor analytical work through NIRS, but, used properly, NIRS offers ecologists enormous analytical power.

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We investigated the utility of near-infrared reflectance spectroscopy (NIRS) as a means of rapidly assaying chemical constituents of Eucalyptus leaves and of directly predicting the intake of foliage from individual trees by greater gliders (Petauroides volans) and common ringtail possums (Pseudocheirus peregrinus). The concentrations of total nitrogen, neutral detergent fiber, condensed tannins and total phenolics could be predicted accurately by partial least squares regression models relating the near-infrared reflectance spectra of foliage samples to analyses performed using standard laboratory procedures. Coefficients of determination (r ) for all four constituents ranged between 0.88 and 0.98, and standard errors of prediction between 0.80 mg gdry matter (DM) for total nitrogen and 5.14 quebracho equivalents gDM for condensed tannins. Near-infrared spectral-based models of food intake had r values of 0.90 and 0.95 with a standard error of prediction of 3.4 and 8.3 g DM kg day for greater gliders and common ringtail possums respectively. We used the predictive model of food intake for greater gliders to examine the relationship between leaf palatability and documented food preferences of animals in the wild. Ranked differences in leaf palatability across four Eucalyptus species were consistent with documented food preferences of greater gliders in the wild. We conclude that NIRS provides a powerful tool to predict foraging behaviour of herbivores where forage choices are determined by compositional attributes of food.

1. Many field studies have shown that small herbivorous mammals include fungus (usually hypogeous sporocarps of ectomycorrhizal fungi) in their diets. However, the dietary importance of fungus relative to other foods is generally unclear because of limitations on the power of conventional techniques of diet analysis. Stable isotope analysis in conjunction with faecal analysis was used in an attempt to overcome these limitations. 2. Two foregut‐fermenting marsupials (the Northern Bettong Bettongia tropica and Rufous Bettong Aepyprymnus rufescens) and a hindgut fermenter (the Northern Brown Bandicoot Isoodon macrourus) were studied. The Northern Bettong and Northern Brown Bandicoot are of similar body size (around 1 kg); the Rufous Bettong is significantly larger at 3 kg. Faecal analysis showed that the two bettongs ate a variety of grasses, lilies and fungi; the bandicoot ate these foods and also invertebrates. 3. Ratios of 15N/14N and 13C/12C differed in major food types collected in the field (fungus, grass, lily and invertebrates). Grass was clearly separated from the other food types by its low 13C/12C ratio, while fungus was separated from the other types by its high 15N/14N ratio. Invertebrates and lilies differed slightly in 13C/12C ratios. 4. Isotope ratios in body tissue (sampled in hair) of the three mammals were also discrete, showing that the species differed in the predominant sources of their C and N. Estimates of the proportion of C assimilated in body tissue that was derived from grass were 80% for the Rufous Bettong, 40% for the Northern Bettong and 45% for the Northern Brown Bandicoot. Analysis of 15N/14N ratios suggested that the Northern Bettong derived almost all its N from fungus, the Northern Brown Bandicoot derived practically no N from fungus, and the Rufous Bettong was intermediate. 5. The results confirm that for the Northern Bettong, fungus is a predominant source of N and C assimilated into body tissue. Differences between the use of fungi by the Northern Bettong and the Northern Brown Bandicoot strengthen conclusions from other studies that foregut fermentation confers on small mammals a greater ability to utilize fungus than does hindgut fermentation. It is hypothesized that the limited use of fungus by the Rufous Bettong is due to the patchy distribution of hypogeous sporocarps, which would result in a high energy cost of foraging for this larger‐bodied species with a higher absolute food requirement.