Estimation of avian biodiversity is a cornerstone measure of ecosystem condition. Surveys conducted using autonomous recorders are often more efficient at estimating diversity than traditional point-count surveys. However, there is limited research into the optimal temporal resolution for sampling—the trade-off between the number of samples and sample duration when sampling a survey window with a fixed survey effort—despite autonomous recorders allowing easy repeat sampling compared to traditional survey methods. We assess whether the additional temporal coverage from high temporal resolution (HTR) sampling, consisting of 240 15-s samples spread randomly across a survey window detects higher alpha and gamma diversity than low temporal resolution (LTR) sampling of four 15-min samples at the same locations. We do so using an acoustic dataset collected from 29 locations in a region of very high avian biodiversity—the eastern Brazilian Amazon. We find HTR sampling outperforms LTR sampling in every metric considered, with HTR sampling predicted to detect approximately 50% higher alpha diversity, and 10% higher gamma diversity. This effect is primarily driven by increased coverage of variation in detectability across the morning, with the earliest period containing a distinct community that is often under sampled using LTR sampling. LTR sampling produced almost four times as many false absences for species presence. Additionally, LTR sampling incorrectly found 70 species (34%) at only a single forest type when they were in fact present in multiple forest types, while the use of HTR sampling reduced this to just two species (0.9%). When considering multiple independent detections of species, HTR sampling detected three times more uncommon species than LTR sampling. We conclude that high temporal resolution sampling of passive-acoustic monitoring-based surveys should be considered the primary method for estimating the species richness of bird communities in tropical forests.

中文翻译：

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使用被动声学监测和高时间分辨率采样优化热带森林鸟类调查

估计鸟类生物多样性是衡量生态系统状况的基石。使用自动记录仪进行的调查在估计多样性方面通常比传统的点数调查更有效。然而，对采样的最佳时间分辨率的研究有限——在使用固定的调查工作对调查窗口进行采样时样本数量和样本持续时间之间的权衡——尽管与传统调查方法相比，自主记录器允许轻松重复采样。我们评估了来自高时间分辨率 (HTR) 采样的额外时间覆盖，由 240 个随机分布在调查窗口中的 15 秒样本组成，是否检测到比四个 15 分钟样本的低时间分辨率 (LTR) 采样更高的 alpha 和 gamma 多样性相同的位置。我们使用从鸟类生物多样性非常高的地区（巴西亚马逊东部）的 29 个地点收集的声学数据集来做到这一点。我们发现 HTR 采样在所考虑的每个指标中都优于 LTR 采样，预计 HTR 采样可以检测到大约高 50% 的 alpha 多样性和高 10% 的 gamma 多样性。这种影响主要是由于上午可检测性变化的覆盖范围增加，最早的时期包含一个独特的群落，该群落通常使用 LTR 采样进行采样不足。LTR 采样产生了几乎四倍于物种存在的虚假缺席。此外，LTR 采样错误地发现了仅一种森林类型中的 70 种（34%），而实际上它们存在于多种森林类型中，而使用 HTR 采样将其减少到只有两种（0.9%）。在考虑对物种进行多次独立检测时，HTR 采样检测到的罕见物种是 LTR 采样的三倍。我们得出结论，基于被动声学监测的调查的高时间分辨率采样应被视为估计热带森林鸟类群落物种丰富度的主要方法。