Grazing influences biomass production and protein content of alpine meadows.

Alpine grasslands are essential for carbon sequestration and food supply for domestic and wild herbivores inhabiting mountainous areas worldwide. These biomes, however, are alternatively threatened by the abandonment of agricultural and livestock practices leading to a fast-growing shrubification process while other mountain grasslands are suffering from the impacts of overgrazing. The functioning of alpine meadow ecosystems is primarily driven by climatic conditions, land-use legacies and grazing. However, although it is critically important, the role of large herbivores on the aboveground biomass and protein content of palatable plants is poorly understood for most alpine meadows. In this work, we explore the effects of grazing on grassland vegetation at two different spatial and temporal scales in the Eastern Pyrenees, Spain. Remote sensing was used to assess the effect of high and moderate grazing (HG and MG respectively) on grass biomass using the leaf area index (LAI) at the meso-scale (patches between 2.3 and 38.7 ha). We also explored the impact of null (NG), overgrazing (MO, mimicked overgrazing) and high (HG) grazing intensities at local scale setting eighteen 1 m2 exclusion boxes in six meadows (three boxes each) commonly used by domestic and wild ungulates. Historical satellite data showed that LAI values are greater in high than in low grazed areas (HG, mean = 0.66, LG, mean = 0.55). Along the same lines, high and moderate grazing pressures improved biomass production at the local-scale (HG, mean = 590.3 g/m2, MO, mean = 389.3 g/m2 and NG, mean = 110.8 g/m2). Crude protein content reached higher values under MO pressure than under HG pressure. Our results confirm that grazing intensity exerts significant changes on the above-ground biomass production and the protein content of plants consumed by domestic (cattle and horses) and wild ungulates (Southern Chamois, Rupicapra pyrenaica). We can conclude that ungulates sustain biomass and nutritive values of grass exerting a negligible effect on biomass and protein content of woody vegetation. Our results will inform management guidelines to support profitable grazing activities and promote conservation of the open landscapes in the alpine ecosystems under the current global change scenario.

Predicting herbivore faecal nitrogen using a multispecies near-infrared reflectance spectroscopy calibration.

Optimal management of free-ranging herbivores requires the accurate assessment of an animal's nutritional status. For this purpose 'near-infrared reflectance spectroscopy' (NIRS) is very useful, especially when nutritional assessment is done through faecal indicators such as faecal nitrogen (FN). In order to perform an NIRS calibration, the default protocol recommends starting by generating an initial equation based on at least 50-75 samples from the given species. Although this protocol optimises prediction accuracy, it limits the use of NIRS with rare or endangered species where sample sizes are often small. To overcome this limitation we tested a single NIRS equation (i.e., multispecies calibration) to predict FN in herbivores. Firstly, we used five herbivore species with highly contrasting digestive physiologies to build monospecies and multispecies calibrations, namely horse, sheep, Pyrenean chamois, red deer and European rabbit. Secondly, the equation accuracy was evaluated by two procedures using: (1) an external validation with samples from the same species, which were not used in the calibration process; and (2) samples from different ungulate species, specifically Alpine ibex, domestic goat, European mouflon, roe deer and cattle. The multispecies equation was highly accurate in terms of the coefficient of determination for calibration R2 = 0.98, standard error of validation SECV = 0.10, standard error of external validation SEP = 0.12, ratio of performance to deviation RPD = 5.3, and range error of prediction RER = 28.4. The accuracy of the multispecies equation to predict other herbivore species was also satisfactory (R2 > 0.86, SEP < 0.27, RPD > 2.6, and RER > 8.1). Lastly, the agreement between multi- and monospecies calibrations was also confirmed by the Bland-Altman method. In conclusion, our single multispecies equation can be used as a reliable, cost-effective, easy and powerful analytical method to assess FN in a wide range of herbivore species.

Fecal nitrogen concentration as a nutritional quality indicator for European rabbit ecological studies.

Measuring the quality of the nutritional resources available to wild herbivores is critical to understanding trophic regulation processes. However, the direct assessment of dietary nutritional characteristics is usually difficult, which hampers monitoring nutritional constraints in natural populations. The feeding ecology of ruminant herbivores has been often assessed by analyzing fecal nitrogen (FN) concentrations, although this method has been less evaluated in other taxa. This study analyzed the suitability of FN as an indicator of ingesta quality in the European rabbit (Oryctolagus cuniculus), which is a keystone lagomorph species in Mediterranean ecosystems and of great conservation interest. Firstly, domestic O. cuniculus were used to evaluate under experimental conditions the accuracy of total FN and the metabolic FN as diet quality indicators of forages with characteristics similar to those available under natural conditions. Secondly, the accuracy of Near-Infrared Spectroscopy (NIRS) to calculate FN was tested using partial least squares regression. Thirdly, a pilot field study was conducted to monitor FN dynamics from wild O. cuniculus in three different habitats during wet and drought periods. A strong association was found between diet type and total FN and metabolic FN (Pseudo-R(2) ≥ 0.89). It was also found that NIRS calibrations were accurate for depicting nitrogen concentrations (R(2) > 0.98 between NIRS and chemical results). Finally, the seasonal FN dynamics measured in the field were consistent with current knowledge on vegetation dynamics and forage limitations in the three habitats. The results support the use of NIRS methods and FN indices as a reliable and affordable approach to monitoring the nutritional quality of rabbit habitats. Potential applications include the assessment of the mechanistic relationships between resource limitations and population abundance, e.g., in relation to natural drought cycles and to habitat interventions aimed at reinforcing rabbit populations.