Improving the accuracy of population size estimates for burrow‐nesting seabirds

Abstract

Seabird numbers can change rapidly as a result of environmental processes, both natural and anthropogenic. Informed management and conservation of seabirds requires accurate and precise monitoring of population size. However, for burrow‐nesting species this is rarely achieved due to spatial and temporal heterogeneity in burrow occupancy. Here, we describe a novel method for deriving more accurate population size estimates that employs mark‐recapture methods to correct for unknown variation in nest occupancy throughout a breeding season. We apply it to estimate breeding numbers of a colonial, burrowing seabird, the Little Penguin Eudyptula minor, on the Summerland Peninsula, Phillip Island, Australia. Estimates of active burrow numbers during the September 2008 to February 2009 breeding season were adjusted to numbers of breeding birds based on burrow occupation and modelled population demographics at six, fortnightly monitored reference sites. The population was estimated to be 26 100 (95% CI: 21 100–31 100) and 28 400 (23 800–33 000) breeding Penguins in two temporally separated surveys within one breeding season. We demonstrate using simulation that the method is robust to variation in burrow occupancy throughout the breeding season, providing consistent and more accurate estimates of population size. The advantage of using the corrected method is that confidence intervals will include the true population size. Confidence limits widened as burrow occupancy declined, reflecting the increased uncertainty as larger adjustments for low burrow occupancy were required. In contrast, the uncorrected method that uses burrow occupancy alone as a measure of breeding numbers was inconsistent and significantly underestimated population size across much of the breeding season. Although requiring considerably more survey effort, the corrected approach provides a more accurate means for monitoring population changes in colonially breeding animals while collecting demographic data that can help diagnose the drivers of population change.