Data from: Estimating national population sizes: methodological challenges and applications illustrated in the common nightingale, a declining songbird in the UK

1. Estimation of national population size can be important for setting conservation priorities but its methodology has received little critical attention. Sites for highly aggregated species are often prioritised if they contain 1% of national or biogeographical populations but the utility of this approach for other species is unclear. 2. To make recommendations for study design, we present methods used to estimate the UK population size of the common nightingale Luscinia megarhynchos. We assess the sensitivity of the population estimate to the analytical method used and identify sites of national importance for this territorial songbird. 3. Survey effort was directed by prior knowledge of the species’ distribution and the survey design maximised detectability by focussing on the period of greatest song output. We used three different statistical methods to account for detectability, estimating that 55–65% of the national population was detected during surveys. 4. Birds in areas not known to contain the species accounted for 13–23% of the population estimate. Methods to account for these individuals contributed the greatest uncertainty to the results, due to the difficulty of surveying a very large sample of random sites and consequent need to stratify the sample. 5. The 12 derived estimates ranged between 5094 and 5938 territorial males, with the confidence limits ranging from 4764 to 6534. Site delimitation, using clustering based on nearest-neighbour distances, identified one site clearly of national importance and several others potentially nationally important, depending on the population threshold and clustering distance used. 6. Synthesis and applications. National population estimation is difficult and requires that species-specific variability in detectability and individuals present outside surveyed areas are accurately accounted for through survey design and statistical analysis. Accounting for these sources of error will not always be possible and will hamper efforts to assess true population size and consequently to determine whether sites, however defined, exceed critical thresholds of importance. Resources may be better invested in other activities, for example in generating population trends based on relative indices. The latter are generally easier to produce, potentially more robust and arguably more suitable for many conservation applications.

1. 种群数量的国家级估测可为保护优先级制定提供关键依据，但其相关方法学却鲜少受到批判性审视。对于高度聚集的物种，若某栖息地包含其1%的国家级或生物地理种群，通常会被列为优先保护地，但该方法对其他物种的适用性尚不明确。
2. 为给研究设计提供建议，本文详述了估测英国普通夜莺（Luscinia megarhynchos）种群国家级规模的方法。我们评估了种群估测结果对所采用分析方法的敏感性，并识别出该领域鸣禽的国家级重要栖息地。
3. 本研究依托该物种分布的先验知识规划调查工作，并将调查时段聚焦于鸣唱产出量最高的时期，以最大化检测率。我们采用三种不同的统计方法校正检测偏差，经估算，调查期间共检测到该国55%~65%的种群个体。
4. 未被记录分布的区域内的个体占种群估测值的13%~23%。由于难以对大量随机样地开展调查，进而需要对样本进行分层，因此针对这类个体的校正方法是导致研究结果不确定性最高的来源。
5. 本次研究得到的12项衍生估测值范围为5094~5938只领域雄鸟，对应的置信限区间为4764~6534。基于最近邻距离的聚类分析用于栖息地划界时，可识别出1处明确具有国家级重要性的栖息地，以及若干潜在具备国家级重要性的栖息地，这一结果取决于所采用的种群阈值与聚类距离。
6. 综合与应用：国家级种群数量估测颇具挑战性，需通过调查设计与统计分析，精准校正物种特异性的检测率差异以及调查区域外个体带来的偏差。但并非总能实现这类误差源的校正，这将阻碍对真实种群规模的评估，进而难以判定任意定义的栖息地是否超过重要性临界阈值。因此，科研资源或许更适宜投入其他工作，例如基于相对指数构建种群变化趋势。这类相对指数通常更易生成，潜在稳健性更强，且可论证为更适用于多数保护应用场景。