Generating unbiased estimates of burrowing seabird populations

Abstract

Maximising survey efficiency can help reduce the tradeoff between spending limited conservation resources on identifying population changes and responding to those changes through management. Burrow-nesting seabirds are particularly challenging to survey because nests cannot be counted directly. We evaluated a stratified random survey design for generating unbiased population estimates simultaneously for four petrel species nesting on Macquarie Island, Australia, where the survey cue, burrow entrances, is similar for all species. We also compared the use of design-based and model-based analyses for minimising uncertainty in estimates. We recorded 2845 Antarctic prion burrows, 306 white-headed petrel burrows and two blue petrel burrows while distance-sampling along 154 km of transects. For blue petrels and grey petrels, we completed nocturnal searches along a further 71 km and searched 249 km of tracks during follow-up ground searches. We failed to generate unbiased population estimates for two rare and localised species, blue and grey petrels, from our stratified random survey. Only for the most widespread and abundant species, Antarctic prion, did the estimate have reasonable power to detect a rapid population change. Modelbased analyses of the stratified random survey data did not improve upon traditional design-based analyses in terms of uncertainty in population estimates, but they did provide useful spatial representation of current populations. Models that used the targeted survey data did not reflect current population sizes and distributions of the two rare and localised species. We found that when species ecologies, distributions and abundances vary, a multi-method approach to surveys is needed. Species with low abundance that occur patchily across large islands are likely to be best estimated using targeted surveys, whereas widespread and abundant species can be accurately and precisely estimated from randomised surveys using informative model-based analyses.

Adaptive sampling by citizen scientists improves species distribution model performance: A simulation study

“…Several other studies have also found that model‐based adaptive sampling designs can have important benefits for model performance (e.g. Camp et al., 2020; Flint et al., 2023; Shanahan et al., 2021, but see Bird et al., 2022). Interestingly, we found that the type of model‐based method had little effect on model performance: provided some form of model‐based sampling was used, the benefits to SDM performance were similar.…”

“…For example, Pacifici et al. (2016) found adaptive cluster sampling to be an improvement over random sampling only when detection probability was low (Bird et al., 2022; Camp et al., 2020). The contrast with our results, where adaptive sampling was generally beneficial, might be explained by the non‐random and spatially biased nature of the citizen science datasets on which our simulations were based.…”

Patterns of recovery in extant and extirpated seabirds after the world's largest multipredator eradication

“…With a population of <1000 mature individuals, gray petrels still meet the criteria for vulnerable in Australia (EPBC), irrespective of their increasing population trend. However, based on current rates of population growth and a population of 252 breeding pairs (∼500 mature individuals) in 2018, we project they will exceed this threshold by 2026, possibly sooner if breeding starts to occur in the high proportion of nonbreeding birds recorded during recent surveys (Bird et al, 2022;Bird, Fuller, et al, 2021). Vulnerability to invasive species impacts is not uniform, but it can be predicted from species' physiology and life histories, especially if quantitative data are lacking.…”

A review of records and research actions for the poorly known Vanuatu Petrel Pterodroma [cervicalis] occulta

“…Key consideration should be given to Red List thresholds. With a priori estimates suggesting the Vanuatu Petrel is not widespread on Vanua Lava, targeted search surveys informed by local knowledge, spot-lighting/auditory surveys, and habitat assessment are likely to be more effective than an unbiased survey design (Bird et al 2022). In the presence of dense ground cover, call surveys to map the colony and call playback to detect burrows are likely to be the most effective techniques (e.g.…”