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Using Age Structure to Detect Impacts on Threatened Populations: a Case Study with Steller Sea Lions
Authors:E E HOLMES  A E YORK
Institution:National Marine Mammal Laboratory, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA 98115, U.S.A.
Abstract:Abstract:   A delayed response to change is often a characteristic of long-lived species and presents a major challenge to monitoring their status. However, rapid shifts in age structure can occur even while population size remains relatively static. We used time-varying matrix models to study age-structure information as a tool for improving detection of survivorship and fecundity change and status. We applied the methods to Steller sea lions (  Eumetopias jubatus ), a long-lived endangered marine mammal found throughout the North Pacific Rim. Population and newborn counts were supplemented with information on the fraction of the population that was juvenile, obtained by measuring animals in aerial photographs taken during range-wide censuses. By fitting the model to 1976–1998 data, we obtained maximum-likelihood estimates and 95% confidence intervals for juvenile survivorship, adult survivorship, and adult fecundity in the mid-1980s, late 1980s, and 1990s. We used a series of nested models to test whether the data were best fit by a model with one, two, or three temporal changes in demographic rates, and we fit the models to different lengths of data to test the number of years of data needed to detect a demographic change. The declines in the early 1980s were associated with severely low juvenile survivorship, whereas declines in the 1990s were associated with disproportionately low fecundity. We repeated these analyses, fitting only to the count data without the juvenile-fraction information, to determine whether the age-structure information changed the conclusions and/or changed the certainty and speed with which demographic-rate changes could be detected. The juvenile-fraction data substantially improved the degree to which estimates from the model were consistent with field data and significantly improved the speed and certainty with which changes in demographic rates were detected.
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