Assessing population viability while accounting for demographic and environmental uncertainty

Abstract

Predicting the future trend and viability of populations is an essential task in ecology. Because many populations respond to changing environments, uncertainty surrounding environmental responses must be incorporated into population assessments. However, understanding the effects of environmental variation on population dynamics requires information on several important demographic parameters that are often difficult to estimate. Integrated population models facilitate the integration of time series data on population size and all existing demographic information from a species, allowing the estimation of demographic parameters for which limited or no empirical data exist. Although these models are ideal for assessments of population viability, they have so far not included environmental uncertainty. We incorporated environmental variation in an integrated population model to account for both demographic and environmental uncertainty in an assessment of population viability. In addition, we used this model to estimate true juvenile survival, an important demographic parameter for population dynamics that is difficult to estimate empirically. We applied this model to assess the past and future population trend of a rare island endemic songbird, the Montserrat Oriole Icterus oberi , which is threatened by volcanic activity. Montserrat Orioles experienced lower survival in years with volcanic ashfall, causing periodic population declines that were compensated by higher seasonal fecundity in years with high pre‐breeding season rainfall. Due to the inclusion of both demographic and environmental uncertainty in the model, the estimated population growth rate in the immediate future was highly imprecise (95% credible interval 0.844–1.105), and the probability of extinction after three generations (in the year 2028) was low (2.1%). This projection demonstrates that accounting for both demographic and environmental sources of uncertainty provides a more realistic assessment of the viability of populations under unknown future environmental conditions.

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