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. Model-based 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.

中文翻译：

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生成穴居海鸟种群的无偏估计

最大限度地提高调查效率有助于减少将有限的保护资源用于识别人口变化和通过管理应对这些变化之间的权衡。巢穴海鸟的调查尤其具有挑战性，因为无法直接计算巢穴。我们评估了分层随机调查设计，以同时为在澳大利亚麦格理岛筑巢的四种海燕物种生成无偏的种群估计，其中所有物种的调查线索，洞穴入口都是相似的。我们还比较了使用基于设计和基于模型的分析来最小化估计中的不确定性。我们记录了 2845 个南极朊病毒洞穴、306 个白头海燕洞穴和两个蓝海燕洞穴，同时沿 154 公里的样带进行了距离采样。对于蓝海燕和灰海燕，我们完成了另外 71 公里的夜间搜索，并在后续地面搜索期间搜索了 249 公里的轨道。从我们的分层随机调查中，我们未能对两种稀有和本地化的物种蓝海燕和灰海燕产生公正的种群估计。只有对于最广泛和最丰富的物种南极朊病毒，该估计才具有合理的能力来检测快速的种群变化。分层随机调查数据的基于模型的分析在人口估计的不确定性方面并没有改进传统的基于设计的分析，但它们确实提供了当前人口的有用空间表示。使用有针对性的调查数据的模型没有反映两种稀有和本地化物种的当前种群规模和分布。我们发现，当物种生态、分布和丰度发生变化时，需要采用多种方法进行调查。使用有针对性的调查可能最好地估计分布在大岛上的低丰度物种，而可以使用基于信息模型的分析从随机调查中准确和精确地估计广泛和丰富的物种。