Large herbivore grazing distribution patterns are influenced by both abiotic factors (e.g., slope, water distance) and biotic factors (e.g., forage quantity and quality). Abiotic factors primarily determine large-scale distribution patterns and act as constraints for biotic mechanisms. The time spent by herbivores in a plant community is proportional to the available forage quantity and quality. Grazing patterns may result from decisions made at different spatial and temporal scales. Foraging velocity decreases and intake rate increases in areas with abundant palatable forage. Non-cognitive mechanisms at smaller scales (bites, feeding stations, small patches) can lead to observed grazing patterns. However, large herbivores also select areas (patches and feeding sites) based on forage quality. Optimal foraging models assume animals use "rules of thumb" to decide where to forage, while cognitive mechanisms involve spatial memory, allowing herbivores to return to nutrient-rich sites more frequently. Empirical studies show herbivores have accurate spatial memories and use them to improve foraging efficiency. Body size and perceptual abilities constrain foraging choices. A conceptual model integrates animal responses to abiotic and biotic factors, showing how cognitive foraging mechanisms work within abiotic constraints. Predictions of the model correspond to observed grazing patterns. Understanding these mechanisms is crucial for managing grazing patterns. Grazing distribution results from decisions and processes at various spatial and temporal scales. Key factors include foraging, grazing, ungulates, distribution, grazing patterns, spatial memory, landscape, and scale. Abiotic factors like slope and water distance are primary determinants of grazing distribution. Biotic factors such as forage quantity and quality also affect distribution. Management practices like water development, salt placement, and fertilizer application can improve grazing distribution. Foraging decisions at different scales influence grazing patterns. Cognitive mechanisms, such as spatial memory, allow herbivores to select foraging areas. Non-cognitive mechanisms, like foraging velocity and turning frequency, also affect grazing patterns. Intake rate and neck angle influence foraging behavior. Cognitive mechanisms, including learning and memory, affect diet selection and feeding site choices. Optimal foraging theory and rule-based models help predict grazing patterns. Spatial memory is crucial for selecting feeding sites and patches. Herbivores must perceive differences in plant parts and feeding stations to select forage. Body size and interactions between spatial and temporal scales affect foraging behavior. Scaling relationships between body size and foraging behavior provide insights into how herbivores respond to spatial heterogeneity. Abiotic factors like slope and water distance are primary determinants of grazing distribution. A conceptual model integrates cognitive foraging mechanisms with abiotic factors to predict grazing patterns. Understanding these mechanisms is essential for managing grazing distribution.Large herbivore grazing distribution patterns are influenced by both abiotic factors (e.g., slope, water distance) and biotic factors (e.g., forage quantity and quality). Abiotic factors primarily determine large-scale distribution patterns and act as constraints for biotic mechanisms. The time spent by herbivores in a plant community is proportional to the available forage quantity and quality. Grazing patterns may result from decisions made at different spatial and temporal scales. Foraging velocity decreases and intake rate increases in areas with abundant palatable forage. Non-cognitive mechanisms at smaller scales (bites, feeding stations, small patches) can lead to observed grazing patterns. However, large herbivores also select areas (patches and feeding sites) based on forage quality. Optimal foraging models assume animals use "rules of thumb" to decide where to forage, while cognitive mechanisms involve spatial memory, allowing herbivores to return to nutrient-rich sites more frequently. Empirical studies show herbivores have accurate spatial memories and use them to improve foraging efficiency. Body size and perceptual abilities constrain foraging choices. A conceptual model integrates animal responses to abiotic and biotic factors, showing how cognitive foraging mechanisms work within abiotic constraints. Predictions of the model correspond to observed grazing patterns. Understanding these mechanisms is crucial for managing grazing patterns. Grazing distribution results from decisions and processes at various spatial and temporal scales. Key factors include foraging, grazing, ungulates, distribution, grazing patterns, spatial memory, landscape, and scale. Abiotic factors like slope and water distance are primary determinants of grazing distribution. Biotic factors such as forage quantity and quality also affect distribution. Management practices like water development, salt placement, and fertilizer application can improve grazing distribution. Foraging decisions at different scales influence grazing patterns. Cognitive mechanisms, such as spatial memory, allow herbivores to select foraging areas. Non-cognitive mechanisms, like foraging velocity and turning frequency, also affect grazing patterns. Intake rate and neck angle influence foraging behavior. Cognitive mechanisms, including learning and memory, affect diet selection and feeding site choices. Optimal foraging theory and rule-based models help predict grazing patterns. Spatial memory is crucial for selecting feeding sites and patches. Herbivores must perceive differences in plant parts and feeding stations to select forage. Body size and interactions between spatial and temporal scales affect foraging behavior. Scaling relationships between body size and foraging behavior provide insights into how herbivores respond to spatial heterogeneity. Abiotic factors like slope and water distance are primary determinants of grazing distribution. A conceptual model integrates cognitive foraging mechanisms with abiotic factors to predict grazing patterns. Understanding these mechanisms is essential for managing grazing distribution.