Abstract
We developed a mechanistic life-cycle model derived from the elicitation of multiple factors influencing the success of individual life-stages of the imperiled delta smelt (Hypomesus transpacificus). We discuss the relevance of limiting factors in population ecology and problems with additive models in detecting them. We identify limiting factors and assess their significance using a non-linear optimization routine, combined with traditional metrics to assess the value of covariates and model performance. After reviewing previous conceptual models and multivariate analyses, we identified a set of factors that were consistent with conceptual models and useful in explaining the erratic fluctuations in a common abundance index: food at certain times in certain locations, predation by introduced species primarily in the spring, and entrainment. The analytical approach provides a transparent and intuitive framework in which to consider the contribution of covariates and consequences for population trends, and has the potential to assist with the evaluation of proposed recovery measures.