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1 I BASIS FOR QUANTIFIABLE POPULATION OBJECTIVES Recent advancements in the application of population viability analysis, demographic population models, and population genetics theory to endangered species recovery have improved methods to accurately estimate quantifiable recovery objectives (Soule 1987, Waples 1990 and 1991, Mace and Soule 1991, Nunney and Campbell 1993, Ralls et al. 1996, Allendorf et al. 1997). In general, these methods incorporate the concept of maintaining a minimum genetic effective population size while maintaining a sufficient number of individuals in the population to account for demographic and environmental stochasticity (Rails et al. 1996). The effective number of breeders includes only those individuals contributing genes to the next generation. The number of individuals required to buffer the population from stochastic events is dependent on the demographic profile of the population (e.g. birth and death rates, fecundity, generation time, etc.). Mathematical population models (e.g. Lotka-Volterra), have been the basis upon which these complicated biological parameters have been described for small populations. As a result, the criteria to determine demographic viability has included an element of risk. As a general rule, scientists have suggested that a 95% (1 in 20) chance of persistence for a specified period of time (e.g. 100 yrs) as a biologically acceptable level of risk within most demographic models (Soule 1987). Maintenance of Genetic Variability The goal of management objectives from a genetic perspective is to maintain genetic variability within populations such that they can respond to changing environmental pressures while reducing the chance loss of genetic variability through drift. Maintenance of a sufficient effective population size is critical to meeting these objectives. Natural populations are exposed to both temporal and spatial variation in the environment. Genetic diversity is necessary for adaptive evolutionary change of the population to these variable selection pressures and the ability to respond is proportional the genetic variance (Falconer 1989). This ability to respond may be particularly important for endangered species exposed to selection pressures that are much greater than they have experienced in their evolutionary history due to, for example, introduction of non-native species and habitat destruction (Lynch 1996). Populations with an effective population size of N, are expected to lose a fraction 1/(2 N of their genetic variation each generation through drift (Falconer 1989). For example, if Ne = 50 then the population will lose I% of its genetic variation each generation or 10% after ten generations. This is a substantial loss in terms of fitness where it has been shown that in historically outbreeding populations a 10% loss of genetic variability can translate to a 10% loss in fitness (Falconer 1989, Ralls and Ballou 1983). Franklin (1980) suggested that when N, = 50 the population would experience short-term inbreeding depression whereas an N, of 500, as a lower limit, provides long-term maintenance of genetic diversity. This estimate of 500 was derived by Franklin (1980) and Soule (1980) by assuming a balance between mutation and random genetic drift. However, this number (N. = 500) is (somewhat arbitrarily) based upon the maintenance of 90% of the genetic variability for 200 years (Franklin 1980, Soule 1980, Soule et al. 1986, Lande 4