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A. Status of the Spectacled Eider - U.S. Fish and Wildlife Service

A. Status of the Spectacled Eider - U.S. Fish and Wildlife Service

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APPENDIX I<br />

POPULATION VIABILITY ANALYSIS FOR SPECTACLED ElDERS<br />

1nttQdu~tiQn<br />

PVA Background<br />

Population Viability Analysis (PVA) is an analytical technique that is used to estimate a<br />

Minimum Viable Population (MVP) (Gilpin & Sou1~ 1986). UViableU is defined as a chosen<br />

probability <strong>of</strong> persisting for a given time (Shaffer 1981; Frankel & Soul~ 1981). For example,<br />

Shaffer (1987) proposed that Minimum Viable Population be defined as that population size<br />

that will have a 99% chance <strong>of</strong> surviving for 1,000 years. The future is unpredictable, so it is<br />

impossible to predict <strong>the</strong> exact extinction time <strong>of</strong> any population. An underst<strong>and</strong>ing <strong>of</strong> how<br />

population growth rates vary temporally allows <strong>the</strong> calculation <strong>of</strong> a distribution <strong>of</strong> possible<br />

extinction times. Numerous factors that influence <strong>the</strong> growth rate <strong>of</strong> populations, such as<br />

susceptibility to changing wea<strong>the</strong>r <strong>and</strong> food resources, genetics, <strong>and</strong> behavior, must be<br />

integrated into <strong>the</strong>se calculations. These risk factors fall into four categories (Shaffer 1987).<br />

The first risk factor is demographic stochasticity, which is caused by chance changes in birth<br />

<strong>and</strong> survival rates (Goodman 1987). A stochastic event implies an event that occurs by<br />

chance, such as a 50% chance <strong>of</strong> rain. Birth <strong>and</strong> survival events are chance events that, when<br />

taken over many individuals, have average probabilities <strong>of</strong> occurrence depending on age.<br />

When <strong>the</strong> number <strong>of</strong> individuals (sample size) becomes small, observed demographic rates<br />

vary simply because <strong>of</strong> sampling error. For example, with a population <strong>of</strong> 10 animals <strong>and</strong> a<br />

survival rate <strong>of</strong>0.95, in any given year it is not possible to observe a survival rate <strong>of</strong> 0.95.<br />

Instead, <strong>the</strong> observed rate would be 1.0, 0.9 or rarely =0.8.Thus, demographic stochasticity<br />

is a sampling phenomenon in which average demographic parameters remain constant.<br />

Demographic stochasticity is only important for populations <strong>of</strong> small sizes (

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