1. Herbivores adopt foraging strategies to maximize efficiency in diverse, resource-constrained environments. However, the effectiveness of these strategies may be more constrained by their capacity for energy cost rather than their ability to acquire resources. The swift utilization of resources during acquisition is crucial for optimizing energy conversion efficiency in animals. Nonetheless, the energy expended in this process inherently limits food conversion efficiency (FCE), an aspect that remains insufficiently explored in current research. 2. In this study, we introduced a concept framework that integrates harvest rate (HR) and energy expenditures (EE) into evaluating herbivore FCE. Utilizing high-resolution tri-axial accelerometry within a grazing treatments platform, we analyzed the behaviors of herbivores (Ovis aries) to determine the energy costs and time allocation for both lamb and dry ewe groups. 3. Our analysis demonstrated an inverse correlation between HR and EE, exhibiting both positive and negative influences on FCE. Notably, the impact of EE was more pronounced in larger-sized grazers (dry ewes), while HR significantly influenced smaller-sized grazers (lambs). However, the interaction effects between these variables tended to neutralize the variations in FCE observed across both groups. 4. Our research highlights how the behavioral patterns of grazers, in terms of resource acquisition and relative energy costs, are pivotal in determining resource utilization efficiency. Additionally, it reveals the trade-offs in these behaviors, which transition from being beneficial to restrictive as the body grows. This finding substantiates the theory that the behavior of herbivores is a reliable predictor of their efficiency in resource utilization.

Strategically managing livestock grazing in arid regions optimizes land use and curtails the damage caused by overcultivation. Controlled grazing preserves soil quality and fosters sustainability despite resource limitations. Uneven resource distribution can lead to diverse grazing patterns and land degradation, particularly in undulating terrains. In this study of a complex desert landscape encompassing dunes and interdunes, we developed a herbivore foraging algorithm based on a Resource Selection Function model. Our findings reveal that cattle prefer areas with abundant vegetation and proximity to water sources while avoiding higher elevations. However, abundant resource availability mitigated these impacts and enhanced the role of water points, particularly during late grazing periods. In summary, resource-driven decisions influence livestock grazing patterns, indicating that effective management should prioritize resource-based strategies such as enhancing food resources near water points as vegetation declines. Further, thoughtful water source placement and the subdivision of pastures into areas with varied terrain are crucial considerations.

Increasing atmospheric nitrogen (N) deposition is a major threat to terrestrial vegetation biodiversity. The reactive N deposition includes reduced (NHx) and oxidized (NOy) forms, which play different roles in a variety of biological processes. Whether NHx and NOy affect the vegetation biodiversity differently or equivalently has been paid little attention despite decades of research on biodiversity changes in response to N deposition. Combining a meta-analysis and an N gradient experiment, we found that reduced N (i.e., NH4+) addition resulted in a significant species loss of forbs. By contrast, oxidized N (NO3-) addition showed a much weaker impact on species richness. The greater impact of reduced than oxidized N on the species loss could be due to the susceptibility of forbs to NH4+ toxicity and nitrification-induced acidification, which weakened their competition for light and other resources compared with grasses. These results provide direct evidence that reduced N exerts greater impacts on grassland plant species losses than oxidated N, emphasizing that the ratio of NHx to NOy, in addition to the total N deposition amount, should be considered as an important predictor of grassland biodiversity losses.