As important marine mesopredators and sensitive indicators of Antarctic ecosystem change, penguins have been a major focus of long-term biological research in the Antarctic. However, the vast majority of such studies have been constrained by logistics and relate mostly to the temporal dynamics of individual breeding populations from which regional trends have been inferred, often without regard for the complex spatial heterogeneity of population processes and the underlying environmental conditions. Integrating diverse census data from 70 breeding sites across 31 years in a robust, hierarchical analysis, we find that trends from intensely studied populations may poorly reflect regional dynamics and confuse interpretation of environmental drivers. Results from integrated analyses confirm that Pygoscelis adeliae (Adélie Penguins) are decreasing at almost all locations on the Antarctic Peninsula. Results also resolve previously contradictory studies and unambiguously establish that P. antarctica (Chinstrap Penguins), thought to benefit from decreasing sea ice, are instead declining regionally. In contrast, another open-water species, P. papua (Gentoo Penguin), is increasing in abundance and expanding southward. These disparate population trends accord with recent mechanistic hypotheses of biological change in the Southern Ocean and highlight limitations of the influential but oversimplified "sea ice" hypothesis. Aggregating population data at the regional scale also allows us to quantify rates of regional population change in a way not previously possible.
Abstract. 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 Nmixture 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 data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark-recapture) and extensive (e.g., counts) data sources.
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