A traditional and a less-invasive robust design: choices in optimizing effort allocation for seabird population studies

Abstract

For many animal populations, one or more life stages are not accessible to sampling, and therefore an unobservable state is created. For colonially-breeding populations, this unobservable state could represent the subset of adult breeders that have foregone breeding in a given year. This situation applies to many seabird populations, notably albatrosses, where skipped breeders are either absent from the colony, or are present but difficult to capture or correctly assign to breeding state. Kendall et al. have proposed design strategies for investigations of seabird demography where such temporary emigration occurs, suggesting the use of the robust design to permit the estimation of time-dependent parameters and to increase the precision of estimates from multi-state models. A traditional robust design, where animals are subject to capture multiple times in a sampling season, is feasible in many cases. However, due to concerns that multiple captures per season could cause undue disturbance to animals, Kendall et al. developed a less-invasive robust design (LIRD), where initial captures are followed by an assessment of the ratio of marked-to-unmarked birds in the population or sampled plot. This approach has recently been applied in the Northwestern Hawaiian Islands to populations of Laysan (Phoebastria immutabilis) and black-footed (P. nigripes) albatrosses. In this paper, we outline the LIRD and its application to seabird population studies. We then describe an approach to determining optimal allocation of sampling effort in which we consider a non-robust design option (nRD), and variations of both the traditional robust design (RD), and the LIRD. Variations we considered included the number of secondary sampling occasions for the RD and the amount of total effort allocated to the marked-to-unmarked ratio assessment for the LIRD. We used simulations, informed by early data from the Hawaiian study, to address optimal study design for our example cases. We found that the LIRD performed as well or nearly as well as certain variations of the RD in terms of root mean square error, especially when relatively little of the total effort was allocated to the assessment of the marked-to-unmarked ratio versus to initial captures. For the RD, we found no clear benefit of using 2, 4, or 6 secondary sampling occasions per year, though this result will depend on the relative effort costs of captures versus recaptures and on the length of the study. We also found that field-readable bands, which may be affixed to birds in addition to standard metal bands, will be beneficial in longer-term studies of albatrosses in the Northwestern Hawaiian Islands. Field-readable bands reduce the effort cost of recapturing individuals, and in the long-term this cost reduction can offset the additional effort expended in affixing the bands. Finally, our approach to determining optimal study design can be generally applied by researchers, with little seed data, to design their studies at the outset.