STATE-DEPENDENT LIFE-HISTORY EVOLUTION IN SOAY SHEEP - DYNAMIC MODELING OF REPRODUCTIVE SCHEDULING

Adaptive decisions concerning the scheduling of reproduction in an ani mal's lifetime, including age at maturity and clutch or litter size, s hould depend on an animal's body condition or state. In this state-dep endent case, we are concerned with the optimization of sequences of ac tions and so dynamic optimization techniques are appropriate. Here we show how stochastic dynamic programming can be used to study the repro ductive strategies and population dynamics of natural populations, ass uming optimal decisions. As examples we describe models based upon fie ld data from an island population of Soay sheep on St. Kilda. This pop ulation shows persistent instability, with cycles culminating in high mortality every three or four years. We explore different assumptions about the extent to which Soay ewes use information about the populati on cycle in making adaptive decisions. We compare the observed distrib utions of strategies and population dynamics with model predictions; t he results indicate that Soay ewes make optimal reproductive decisions given that they have no information about the population cycle. This study represents the first use of a dynamic optimization life history model of realistic complexity in the study of a field population. The techniques we use are potentially applicable to many other populations , and we discuss their extension to other species and other life histo ry questions.