1. Monitoring the abundance of mobile and wide‐ranging cetacean populations for conservation management is challenging, especially when the management is focused on static protected areas. Where abundance estimates are derived from mark–recapture data, such as photo‐identification of naturally marked individuals, unpredictable movements of animals in and out of the survey area can reduce ‘capture’ probabilities and affect the precision and accuracy of resulting estimates.
2. A Bayesian hierarchical log–linear model was applied to photo‐identification data collected in summer 2014 to derive a multi‐site abundance estimate for a population of bottlenose dolphins, Tursiops truncatus, ranging widely throughout the coastal waters of western Ireland. In addition, the effects of varying levels of sampling effort on the minimum detectable decrease in population size were examined.
3. The abundance (median) of dolphins was estimated as 189 (coefficient of variation (standard deviation/mean), 0.11; 95% highest‐posterior density interval, 162–232). Over 50% of the well‐marked dolphins encountered throughout the study were sighted in more than one distinct coastal area, thus displaying high mobility. In addition, it was found that it would require biennial surveys to detect a 25% decline in abundance within the six‐year reporting period of the EU’s Habitats Directive.
4. Given that the Special Area of Conservation designated for these dolphins consists of two separate areas covering a substantial portion of the west coast of Ireland, the multisite approach is appropriate for monitoring this population. It produces a more precise estimate and is well suited for sparse recapture data collected opportunistically at multiple sites, when the lack of resources prevents large‐scale surveys or when concentrating surveys on smaller localized areas fails to capture the broad range and unpredictable occurrence of the animals. The Bayesian multi‐site approach could be applied to the management of other wide‐ranging marine or terrestrial taxa.

中文翻译：

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监测流动人口的挑战：将贝叶斯多站点标记捕获再捕捞丰度估算应用于监测高度流动的沿海海豚

1. 监测流动的和广泛的鲸类种群的数量以进行保护管理是一项挑战，特别是当管理重点放在静态保护区时。如果从标记回收数据（例如对自然标记的个体的照片识别）得出的丰度估计值，则动物进出调查区域的不可预测的移动会降低“捕获”的可能性，并影响所得估计值的准确性和准确性。
2. 将贝叶斯分层对数线性模型应用于2014年夏季收集的照片识别数据，以得出宽吻海豚Tursiops truncatus种群的多站点丰度估计，其分布范围遍及整个西爱尔兰的沿海水域。此外，还研究了不同程度的抽样工作对可检测的最小人口规模减少的影响。
3. 海豚的丰度（中位数）估计为189（变异系数（标准差/平均值），为0.11；最高后密度区间为95％，162-232）。在整个研究过程中，超过50％的标记清晰的海豚在一个以上独特的沿海地区被发现，因此具有很高的机动性。此外，还发现，需要进行两年一次的调查，以在欧盟人居指令的六年报告期内发现丰度下降25％。
4. 鉴于为这些海豚指定的特别保护区由两个独立的区域组成，覆盖了爱尔兰西海岸的大部分地区，因此采用多站点方法可监测该种群。当资源不足导致无法进行大规模调查时，或者当集中在较小的局部区域进行调查无法捕获动物的广泛范围和不可预测的发生时，它会产生更精确的估计值，非常适合在多个地点进行机会性收集的稀疏捕获数据。贝叶斯多站点方法可应用于其他范围广泛的海洋或陆地生物分类的管理。