A global population assessment of the Chinstrap penguin (Pygoscelis antarctica).

Using satellite imagery, drone imagery, and ground counts, we have assembled the first comprehensive global population assessment of Chinstrap penguins (Pygoscelis antarctica) at 3.42 (95th-percentile CI: [2.98, 4.00]) million breeding pairs across 375 extant colonies. Twenty-three previously known Chinstrap penguin colonies are found to be absent or extirpated. We identify five new colonies, and 21 additional colonies previously unreported and likely missed by previous surveys. Limited or imprecise historical data prohibit our assessment of population change at 35% of all Chinstrap penguin colonies. Of colonies for which a comparison can be made to historical counts in the 1980s, 45% have probably or certainly declined and 18% have probably or certainly increased. Several large colonies in the South Sandwich Islands, where conditions apparently remain favorable for Chinstrap penguins, cannot be assessed against a historical benchmark. Our population assessment provides a detailed baseline for quantifying future changes in Chinstrap penguin abundance, sheds new light on the environmental drivers of Chinstrap penguin population dynamics in Antarctica, and contributes to ongoing monitoring and conservation efforts at a time of climate change and concerns over declining krill abundance in the Southern Ocean.

Parameter estimation using randomized phases in an integrated assessment model for Antarctic krill.

An integrated model assessing the status and productivity of Antarctic krill (Euphausia superba, hereafter krill) was configured to estimate different subsets of 118 potentially estimable parameters in alternative configurations. We fixed the parameters that were not estimated in any given configuration at pre-specified values. The model was fitted to over forty years of fisheries and survey data for krill in Subarea 48.1, a statistical reporting area around the Antarctic Peninsula used by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR). The number of estimated parameters was gradually increased across model configurations. Configurations that estimated more parameters fitted the data better, but the order in which the parameters were estimated became more important in finding the best fit. Twenty-two configurations estimating from 48 to 107 parameters were able to obtain an invertible Hessian matrix that was subsequently used to estimate parameter uncertainty. Parameter uncertainties calculated using asymptotic approximation around the maximum likelihood estimates were often larger than uncertainties based on Markov chain Monte Carlo sampling for the same parameters. Diagnostics applied to MCMC samples in the best model of each configuration that obtained an invertible Hessian indicated that the most highly parameterized configurations did not reach stationary distributions. A 96-parameter configuration was the best fitting model of those that passed the MCMC diagnostics. The ΔAIC and ΔBIC scores indicated essentially no support relative to the best model for the alternative models that also passed MCMC diagnostics. Simulated data using the configurations as operating models showed that while all configurations passed "self-tests" for spawning biomass and recruitment, there was a small negative bias due to model penalties in the fishing mortality estimates for years with the highest fishing mortalities. "Cross-tests" of configurations that estimated different parameters often differed from the operating model values.