CCAMLR

This paper very briefly summarises some aspects Adelie penguin count data from east Antarctica to demonstrate the extent and nature of variability in data from this large region, and to provide some background to some aspects of the R program SEABIRD outlined in McKinlay and Southwell (submitted working paper).

In addition to a review of published studies on Adelie penguin abundance at breeding sites in Antarctica, Southwell (2004) proposed a general abundance estimator appropriate for a species of that kind. The present study attempts to implement this estimator in the form of a parametric bootstrap model, utilising as input data published counts of Adelie penguins and estimates of their uncertainty at breeding sites in Antarctica. To achieve this task, a menu-driven suite of routines titled SEABIRD (Seasonal Estimation of Abundance by Bootstrapping Inexact Research Data) has been developed in the R language for statistical computing (R Development Core Team 2008). Software is reliant on data being presented in a specified format congruent with CCAMLR databases designed to store historical survey data relating to penguin abundance. Usual sampling methodology considerations reported in work of this kind are accommodated, such as availability and perception bias, as well as many of the vagaries associated with combining diverse data collected in a variety of ways over many decades. Of particular concern was to ensure that different types of counts (eg. nests, chicks or adults), perhaps made at different time points in a breeding season, might usefully be combined in order to obtain regional-scale estimates of abundance. This was achieved by using independent estimates of availability throughout a breeding season collected at a few, frequently sampled sites, in order to standardise historical estimates to a common reference point of breeding chronology. Equally important was the idea that estimates of uncertainty associated with historical counts be faithfully incorporated and preserved, and methods have been developed to allow these to be combined or interpreted in several different ways. In order to help understand how these and other elements of the procedure contribute toward estimates of uncertainty when combining data, as far as practical different components of the estimation process can be switched on or off to assess their effect. Confidence intervals for final estimates at different scales of spatial aggregation are determined by examining the bootstrap distribution of population estimates at selected percentile intervals. While tailored for Adelie penguins, the method and implementation is sufficiently general to potentially be adapted for other Antarctic species showing seasonal variation in availability to sampling methodology. At the time of writing, SEABIRD is well developed but still very much an evolving work. It is anticipated that use of the software and discussion of the estimation issues involved will identify possibilities for improvement.

Published accounts of population surveys and population estimates for flying seabirds across Area 48 are reviewed. Spatial coverage of count data and population estimates varies greatly between species across their breeding ranges in Area 48. Most population estimates reviewed date from the 1970s and 1980s. Survey methodologies are often poorly described. Potential biases and uncertainties around existing estimates are rarely discussed.

Counts of Adélie penguin populations are most conveniently and most often undertaken at breeding sites during the breeding season. The objective of this paper is to identify and describe the aspects of Adélie penguin population structure, dynamics and demography that are relevant to the interpretation of counts made at breeding sites and the estimation of overall population abundance derived from such counts. To appreciate what counts conducted at different times within a breeding season represent, it is important to understand the population dynamics of the different components of the population throughout the breeding season. The conceptual model described here is specifically based on data obtained from the Adélie penguin population at Béchervaise Island, East Antarctica. While the various life stages described here are also likely to represent other Adélie penguin populations, details in the proportion of each category either at the breeding site or at sea may potentially differ.

The size of two of the inaccessible (non-breeding) components of the Adélie penguin population associated with the Béchervaise Island breeding population is estimated over the past decade using a series of mark-recapture analyses and some simple population modelling techniques.

Broad-scale surveys of penguin breeding abundance generally rely on on-off counts of adults, nests or chicks across several or many breeding sites, and the timing of these counts is often outside the control of researchers. Time series counts of Adelie penguin breeding population attributes (adults, nest and chicks) within the breeding period show considerable variability across space and time (between years). Given this variability, there will be substantial uncertainty in correcting one-off counts with date-specific correction factors to estimate the population attempting to breed at the beginning of the breeding season.

This paper presents spatial modelling based abundance and density estimates of pack-ice seals, crabeater, Weddell and leopard seals, based on aerial survey line transect data collected in January 1999 under the Antarctic Pack-Ice Seal (APIS) programme. Estimates are reported for the Antarctic Peninsula and the western Weddell Sea region (90º to 30º W and 60º to 80º S).

More white-chinned petrels (Procellaria aequinoctialis) are accidentally killed in fisheries than probably any other seabird in the world, but the population impact of this mortality is poorly understood, partly because there have been no estimates of the species’ abundance in recent decades. The largest breeding aggregation, comprising the majority of the worldwide total, is believed to be on the sub-Antarctic island of South Georgia. We estimated the size of this population by calculating the area of suitable habitat and the density of occupied burrows within it. Just less than one million pairs of white-chinned petrels laid on South Georgia in the survey seasons (2005/06 and 06/07). This is 50% of the previous estimate, but still represents around two-thirds of the global population. If the population is declining due to fishery bycatch off S America, as is likely, the scale of annual mortality in this population alone is at least in the high tens of thousands, and plausibly hundreds of thousands.

This paper describes methods and results from a recent aerial survey of the macaroni penguin population at South Georgia.