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Estimating species response to environmental change is a key challenge for ecologists and a core mission of the USGS. Effective forecasting of species response requires models that are detailed enough to capture critical processes and at the same time general enough to allow broad application. This tradeoff is difficult to reconcile with most existing methods. We propose to extend and combine existing models that operate at different scales and with different levels of data complexity into a modeling framework that will allow robust estimation of population response to environmental change across a species’ range. This integrated modeling is now possible with the increasing development and application of population...
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The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark-recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the...
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