US Geological Survey, Columbia Environmental Research Center, Columbia, Missouri, USA.
Department of Ecology, Evolution, and Organismal Biology, Kennesaw State University, Kennesaw, Georgia, USA.
Integr Environ Assess Manag. 2024 Nov;20(6):1954-1968. doi: 10.1002/ieam.4992. Epub 2024 Sep 18.
Many sampling and analytical methods can estimate the abundance, distributions, and diversity of birds and other wildlife. However, challenges with sample size and analytical capacity can make these methods difficult to implement for resource-limited monitoring programs. To apprise efficient and attainable sampling designs for landbird monitoring programs with limited observational data, we used breeding season bird point survey data collected in 2016 at four forest restoration sites in Indiana, USA. We evaluated three subsets of observed species richness, total possibly breeding landbirds, Partners in Flight Regional Conservation Concern (PIF RCC) landbirds, and interior forest specialists (IFSs). Simulated surveys based on field data were used to conduct Bayesian Michaelis-Menten curve analyses estimating observed species as a function of sampling effort. On comparing simulated survey sets with multiple habitat types versus those with one habitat, we found that those with multiple habitat types had estimated 39%-83% greater observed PIF RCC species richness and required 41%-55% fewer visits per point to observe an equivalent proportion of PIF RCC species. Even with multiple habitats in a survey set, the number of visits per point required to detect 50% of observable species was 30% higher for PIF RCC species than for total breeding landbird species. Low detection rates of IFS species at two field sites made precise estimation of required effort to observe these species difficult. However, qualitatively, we found that only sites containing mature forest fragments had detections of several bird species designated as high-confidence IFS species. Our results suggest that deriving specialized species diversity metrics from point survey data can add value when interpreting those data. Additionally, designing studies to collect these metrics may require explicitly planning to visit multiple habitat types at a monitoring site and increasing the number of visits per survey point. Integr Environ Assess Manag 2024;20:1954-1968. © 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
许多采样和分析方法可用于估计鸟类和其他野生动物的数量、分布和多样性。然而，由于样本量和分析能力的挑战，这些方法对于资源有限的监测计划来说可能难以实施。为了为资源有限的鸟类监测计划提供高效且可行的采样设计方案，我们使用了美国印第安纳州四个森林恢复地点在繁殖季节收集的鸟类点调查数据。我们评估了三个观察到的物种丰富度子集，即可能繁殖的全部陆地鸟类、飞行伙伴组织（Partners in Flight）区域保护关注鸟类（PIF RCC）和内部森林专家（IFS）。基于实地数据的模拟调查用于进行贝叶斯米氏门限曲线分析，根据采样努力估计观察到的物种。在比较具有多种生境类型的模拟调查集与具有一种生境类型的模拟调查集时，我们发现具有多种生境类型的模拟调查集估计的 PIF RCC 物种丰富度高 39%-83%，每个点观察到的 PIF RCC 物种数量减少 41%-55%。即使在调查集中有多种生境，为了观察到 PIF RCC 物种的相同比例，每个点需要的访问次数也比总繁殖陆地鸟类物种多 30%。在两个实地地点，IFS 物种的低检测率使得难以准确估计观察这些物种所需的努力。然而，从定性上看，我们发现只有包含成熟森林片段的地点才能检测到几种被指定为高置信度 IFS 物种的鸟类。我们的结果表明，从点调查数据中得出专门的物种多样性指标可以在解释这些数据时增加价值。此外，设计收集这些指标的研究可能需要明确计划在监测地点访问多种生境类型，并增加每个调查点的访问次数。《综合环境评估与管理》2024 年；20：1954-1968。©2024 作者。综合环境评估与管理由 Wiley 期刊 LLC 代表环境毒理与化学学会（SETAC）出版。本文由美国政府雇员贡献，其工作在美国属于公有领域。
