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Table 1 Predictions for expected patterns in time allocation, state occupancy probabilities and activity scheduling if muskoxen were to follow either of the three proposed strategies according to optimal foraging theory, for the summer and winter season, respectively

From: An application of upscaled optimal foraging theory using hidden Markov modelling: year-round behavioural variation in a large arctic herbivore

Summer season (snow-free) Winter season (snow-covered)
Energy intake maximisation strategy: muskoxen aim to maximise energy intake (i.e. time spent foraging and forage quality), only limited by digestive physiological constraints (i.e. time required for rumination)
S1INTAKE: time allocation only influenced by forage quality/quantity (e.g. landcover, NDVI) since forage quality/quantity determines time required for rumen fill and rumination W1INTAKE: time allocation only influenced by forage quality/quantity/accessibility (e.g. landcover, snow depth) since forage quality/quantity/accessibility determines time required for rumen fill and rumination
S2INTAKE: probability of foraging remains constant independent of changes in environmental conditions (e.g. temperature, wind) W2INTAKE: probability of foraging/resting remains constant independent of changes in environmental conditions (e.g. temperature, snow depth)
S3 INTAKE: no specific daily scheduling of activities W3INTAKE: no specific daily scheduling of activities
S4INTAKE: no interannual differences in time allocation W4INTAKE: no interannual differences in time allocation
Time minimisation strategy: muskoxen only forage the minimum required time to satisfy basic energetic needs, while reducing e.g. risk of predation
S1TIME: time allocation/state switching mainly influenced by forage quality/quantity (e.g. landcover, NDVI), time of day and light conditions W1TIME: time allocation/state switching mainly influenced by forage quality/quantity/accessibility (e.g. landcover, snow depth), time of day and light conditions
S2TIME: proportion of time spent foraging decreases with increasing forage quality/quantity as same foraging effort yields higher energetic gains W2TIME: proportion of time spent foraging increases with decreasing forage quality/quantity/accessibility to compensate for reduced energetic gains of foraging effort
S3TIME: specific daily scheduling of activities indicates avoidance of periods with e.g. higher risk of predation W3TIME: specific daily scheduling of activities indicates avoidance of periods with e.g. higher risk of predation
Net energy maximisation strategy: muskoxen aim to maximise energy intake but switch to resting (i.e. energy conservation) as soon as constraints/costs of foraging outweigh gains of foraging effort
S1NET: time allocation/state switching mainly influenced by forage quality/quantity and environmental conditions representing constraints W1NET: time allocation/state switching mainly influenced by forage quality/quantity/accessibility and environmental conditions representing constraints
S2NET: probability of foraging decreases with environmental conditions causing thermal stress or insect harassment (e.g. high temperature, low wind speed) W2NET: probability of resting increases with conditions causing heat loss (e.g. low temperature, high wind speed) or increasing energetic costs of movement and forage access (e.g. deep snow)
S3NET: specific daily scheduling of activities indicates avoidance of daily periods during which constraints peak (e.g. highest temperatures) W3NET: less pronounced specific daily scheduling of activities because peaks in constraints (e.g. temperature/snow depth) do not necessarily follow regular daily patterns
S4NET: interannual differences in time allocation depending on interannual differences in the strength of environmental constraints W4NET: interannual differences in time allocation depending on interannual differences in the strength of environmental constraints