Rapid evaluation of pasture quality for a critically endangered mammal, the northern hairy-nosed wombat (Lasiorhinus krefftii)

Abstract

Near-infrared spectroscopy (NIRS) was used to predict the nutritive value of forage species available to the critically endangered northern hairy-nosed wombat (Lasiorhinus krefftii). Nutritive attributes of the forage successfully estimated included total nitrogen concentration, fibre (including neutral detergent fibre, acid detergent fibre and acid lignin), organic matter, water soluble carbohydrates and in vitro dry matter digestibility. The reported results demonstrate the seasonal variability of the forage resource available to L. krefftii in its tropical savanna habitat. Multivariate modelling of the spectra enabled the nutritive value of forage samples to be estimated with coefficients of determination (r²) of 0.770–0.995 and standard errors of the cross-validation of 0.070–2.850 using a modified partial least-squares analysis technique. The standard error of the laboratory was 0.02–1.42. This study demonstrates that broad-based NIRS predictive equations can be used to predict the nutritive value of a number of plant types available to a herbivore over time. By using NIRS the analyst can rapidly analyse large numbers of samples with limited reduction of precision, thereby enabling large-scale ecological applications that may have previously been impeded by time and costs.