Optimal foraging and beyond: how starlings cope with changes in food availability

Am Nat. 1998 Oct;152(4):543-61. doi: 10.1086/286189.


Foraging adaptations include behavioral and physiological responses, but most optimal foraging models deal exclusively with behavioral decision variables, taking other dimensions as constraints. To overcome this limitation, we measured behavioral and physiological responses of European starlings Sturnus vulgaris to changes in food availability in a laboratory environment. The birds lived in a closed economy with a choice of two foraging modes (flying and walking) and were observed under two treatments (hard and easy) that differed in the work required to obtain food. Comparing the hard with the easy treatment, we found the following differences. In the hard treatment, daily amount of work was higher, but daily intake was lower. Even though work was greater, total daily expenditure was smaller, partly because overnight metabolism was lower. Body mass was lower, but daily oscillation in body mass did not differ. Feces' caloric density was lower, indicating greater food utilization. Energy expenditure rate expressed as multiples of basal metabolic rate (BMR) increased during the working period from 3.5 x BMR (easy) to 5.2 x BMR (hard), but over the 24-h period, it was close to 2.4 x BMR in both treatments. We also found that rate of expenditure during flight was very high in both treatments (52.3 W in easy and 45.5 W in hard), as expected for short (as opposed to cruising) flights. The relative preferences between walking and flying were incompatible with maximizing the ratio of energy gains per unit of expenditure (efficiency) but compatible with maximizing net gain per unit of time during the foraging cycle (net rate). Neither currency explained the results when nonforaging time was included. Time was not a direct constraint: the birds rested more than 90% of the time in both treatments. Understanding this complex picture requires reasoning with ecological, physiological, and cognitive arguments. We defend the role of optimality as an appropriate tool to guide this integrative perspective.