Decisions about whether to designate a species for conservation and protection depend on the ability to summarize their population trajectories and their risk of extinction. Such decisions may rely on quantitative population viability analyses based on a time series of abundance index values that are derived from a monitoring program. In the case of the Longfin Smelt (Spirinchus thaleichthys), a decision to protect a distinct population segment of the species under the U.S. Endangered Species Act was informed by several indices of population abundance. In this paper, we combined individual population viability analyses into a single metric for extinction risk using a meta-analysis framework. Individual monitoring surveys for this species generally agreed that the trajectory of abundance was downward and combining data from all of the surveys produced a better summary of the population growth rate. We also used the population growth rates in a simulation to estimate the probability that the abundance of Longfin Smelt dropped too low to recover. We found that this probability of quasi-extinction was substantial, exceeding 20% over two decades. This study demonstrates a practical way that having multiple sources of information creates better information about the trajectory of a population. Individually, the surveys contribute information about specific life stages or ages to our understanding of the population. Combined into one metric and an associated graphical summary, this analysis succinctly communicates risk and creates a benchmark for evaluating future management decisions.
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