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是测量变化还是运动变化?跨代生物记录技术中的采样尺度与运动模型可识别性。

Changing measurements or changing movements? Sampling scale and movement model identifiability across generations of biologging technology.

作者信息

Johnson Leah R, Boersch-Supan Philipp H, Phillips Richard A, Ryan Sadie J

机构信息

Department of Statistics Virginia Tech Blacksburg VA USA.

Department of Integrative Biology University of South Florida Tampa FL USA.

出版信息

Ecol Evol. 2017 Oct 3;7(22):9257-9266. doi: 10.1002/ece3.3461. eCollection 2017 Nov.

Abstract

Animal movement patterns contribute to our understanding of variation in breeding success and survival of individuals, and the implications for population dynamics. Over time, sensor technology for measuring movement patterns has improved. Although older technologies may be rendered obsolete, the existing data are still valuable, especially if new and old data can be compared to test whether a behavior has changed over time. We used simulated data to assess the ability to quantify and correctly identify patterns of seabird flight lengths under observational regimes used in successive generations of wet/dry logging technology. Care must be taken when comparing data collected at differing timescales, even when using inference procedures that incorporate the observational process, as model selection and parameter estimation may be biased. In practice, comparisons may only be valid when degrading all data to match the lowest resolution in a set. Changes in tracking technology, such as the wet/dry loggers explored here, that lead to aggregation of measurements at different temporal scales make comparisons challenging. We therefore urge ecologists to use synthetic data to assess whether accurate parameter estimation is possible for models comparing disparate data sets before planning experiments and conducting analyses such as responses to environmental changes or the assessment of management actions.

摘要

动物的运动模式有助于我们理解个体繁殖成功率和生存率的差异及其对种群动态的影响。随着时间的推移,用于测量运动模式的传感器技术不断改进。尽管旧技术可能会过时,但现有数据仍然很有价值,特别是如果新旧数据能够进行比较,以检验某种行为是否随时间发生了变化。我们使用模拟数据来评估在连续几代干湿记录技术所采用的观测条件下,量化和正确识别海鸟飞行长度模式的能力。在比较不同时间尺度上收集的数据时必须谨慎,即使使用纳入观测过程的推断程序,因为模型选择和参数估计可能会有偏差。实际上,只有在将所有数据降分辨率以匹配数据集中最低分辨率时,比较才可能有效。追踪技术的变化,比如这里探讨的干湿记录器,会导致不同时间尺度上的测量数据聚合,从而使比较变得具有挑战性。因此,我们敦促生态学家在规划实验和进行诸如对环境变化的响应或管理行动评估等分析之前,使用合成数据来评估对于比较不同数据集的模型是否有可能进行准确的参数估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ca/5696428/2543d7abc2e2/ECE3-7-9257-g001.jpg

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