Comparing the reliability of relative bird abundance indices from standardized surveys and community science data at finer resolutions.
Comparing the reliability of relative bird abundance indices from standardized surveys and community science data at finer resolutions.
复制标题
DOI：
10.1371/journal.pone.0257226
复制
发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Che-Castaldo J
中科院分区：
文献类型：
--
作者：
Feng ME;Che-Castaldo J
生物多样性丧失是一场全球生态危机，既是环境变化的驱动力，也是对环境变化的回应。了解物种衰退与人类-自然系统其他组成部分之间的联系，涉及物理、生命和社会科学。从分析的角度来看，这需要整合来自不同科学领域的数据，这些数据通常具有不同的尺度和分辨率。eBird等社区科学项目可能有助于填补时空空白，提高标准化生物调查的分辨率。eBird和更全面的北美繁殖鸟类调查（BBS）之间的比较发现，这些数据集可以在国家和区域尺度上为鸟类种群产生一致的多年丰度趋势。在这里，我们调查这些数据集的可靠性，估计模式在更精细的分辨率，年际变化的丰富城镇边界内。以马萨诸塞州的14个重点物种为例，我们使用eBird和BBS数据集计算了四个年度相对丰度指数，每个数据集包括两种不同的建模方法。我们比较了这些指数之间的对应关系，在多年的趋势，年度估计，估计在国家和城镇一级的年际变化。我们发现eBird和BBS多年趋势之间的对应关系，但这在所有物种中并不一致，并且在更精细的年际时间分辨率下减少。我们进一步表明，标准化的建模方法可以增加索引的可靠性，即使在粗糙的时间分辨率的数据集之间。我们的研究结果表明，多个数据集和建模方法，应考虑在更精细的时间分辨率估计物种种群动态时，但标准化的建模方法可能会提高丰度数据集之间的估计对应。此外，这些指数在更精细的空间尺度上的可靠性可能取决于生境组成，这可能会影响调查的准确性。
Biodiversity loss is a global ecological crisis that is both a driver of and response to environmental change. Understanding the connections between species declines and other components of human-natural systems extends across the physical, life, and social sciences. From an analysis perspective, this requires integration of data from different scientific domains, which often have heterogeneous scales and resolutions. Community science projects such as eBird may help to fill spatiotemporal gaps and enhance the resolution of standardized biological surveys. Comparisons between eBird and the more comprehensive North American Breeding Bird Survey (BBS) have found these datasets can produce consistent multi-year abundance trends for bird populations at national and regional scales. Here we investigate the reliability of these datasets for estimating patterns at finer resolutions, inter-annual changes in abundance within town boundaries. Using a case study of 14 focal species within Massachusetts, we calculated four indices of annual relative abundance using eBird and BBS datasets, including two different modeling approaches within each dataset. We compared the correspondence between these indices in terms of multi-year trends, annual estimates, and inter-annual changes in estimates at the state and town-level. We found correspondence between eBird and BBS multi-year trends, but this was not consistent across all species and diminished at finer, inter-annual temporal resolutions. We further show that standardizing modeling approaches can increase index reliability even between datasets at coarser temporal resolutions. Our results indicate that multiple datasets and modeling methods should be considered when estimating species population dynamics at finer temporal resolutions, but standardizing modeling approaches may improve estimate correspondence between abundance datasets. In addition, reliability of these indices at finer spatial scales may depend on habitat composition, which can impact survey accuracy.
登录
查看更多内容
影响因子：
27.6
作者：
Liu, Lu;Hejazi, Mohamad;Forman, Barton A.
通讯作者：
Forman, Barton A.
影响因子：
56.9
作者：
Butchart, Stuart H. M.;Walpole, Matt;Watson, Reg
通讯作者：
Watson, Reg
影响因子：
10.1
作者：
Farley, Scott S.;Dawson, Andria;Williams, John W.
通讯作者：
Williams, John W.
影响因子：
5.9
作者：
Furnas, Brett J.
通讯作者：
Furnas, Brett J.
影响因子：
4
作者：
Heim, Wieland;Heim, Ramona J.;Kamp, Johannes
通讯作者：
Kamp, Johannes