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Proxy problems: Why a calibration is essential for interpreting quantified changes in energy expenditure from biologging data
Functional Ecology ( IF 4.6 ) Pub Date : 2021-01-11 , DOI: 10.1111/1365-2435.13749
Lewis G. Halsey 1 , Caleb M. Bryce 2
Affiliation  

  1. We do not yet have the means to directly measure the energy expenditure of wild animals, particularly at a high temporal resolution. However, we can instead measure factors that correlate with energy expenditure, such as heart rate or accelerometry, that is, energy expenditure proxies.
  2. To estimate the magnitude of differences in energy expenditure between contexts (such as day and night, or travelling singly vs. in a group), our energy expenditure proxy must be calibrated. However, perhaps because of the logistical challenges of conducting such calibrations and the observation that most calibrations are linear, researchers sometimes interpret the degree of change in energy expenditure between contexts based on uncalibrated proxy data. When doing so, they implicitly assume that the ratio of the proxy values between contexts represents the ratio of energy expenditure values between those contexts.
  3. This approach, however, is usually spurious because unless the relationship between energy expenditure and proxy passes through the origin (i.e. y‐intercept = 0), the ratio of change in the proxy between contexts does not represent the ratio of change in energy expenditure.
  4. We model the error induced when data from an uncalibrated proxy are used to interpret changes in energy expenditure. We also estimate the errors made in published articles that employ this approach, by comparing the claimed change in energy expenditure between two contexts with the change in energy expenditure estimated by applying the best available calibrations now available. As predicted by the models we developed, the apparent size of the error in published articles is related to the relative size of the calibration y‐intercept.
  5. Species‐ and activity‐specific empirical calibrations are the best option for interpreting proxies of energy expenditure. However, for mammals and birds, enough data have been amassed such that energy expenditure can be predicted from measures of heart rate by knowing animal heart mass or even body mass; perhaps a somewhat analogous predictive tool will be available in the future for accelerometry.


中文翻译:

代理问题:为什么校准对于从生物记录数据解释能源消耗的量化变化至关重要?

  1. 我们还没有办法直接测量野生动物的能量消耗,特别是在高时间分辨率下。但是,我们可以改为测量与能量消耗相关的因素,例如心率或加速计,即能量消耗代理。
  2. 要估算环境之间的能源消耗差异的大小(例如白天和黑夜,或单独旅行或与一群人旅行),必须对我们的能源消耗代理进行校准。但是,也许由于进行此类校准的后勤挑战以及大多数校准是线性的观察结果,研究人员有时会根据未校准的代理数据来解释环境之间能源消耗的变化程度。这样做时,他们隐式地假设上下文之间的代理值之比表示这些上下文之间的能源消耗值之比。
  3. 但是,这种方法通常是虚假的,因为除非能源消耗和代理之间的关系通过原点(即y截距= 0),否则上下文之间的代理变化比率并不代表能源消耗的变化比率。
  4. 当来自非校准代理的数据用于解释能源支出的变化时,我们对引起的误差进行建模。我们还通过将两种环境下的能源消耗变化与通过应用目前可用的最佳校准方法估算的能源消耗变化进行比较,来估计采用这种方法的已发表文章中的错误。正如我们开发的模型所预测的那样,已发表文章中的表观误差大小与校准y截距的相对大小有关。
  5. 特定于物种和活动的经验校准是解释能源消耗代理的最佳选择。但是,对于哺乳动物和鸟类,已经积累了足够的数据,从而可以通过了解动物的心脏质量甚至体重来从心率测量值中预测能量消耗。也许将来会有一些类似的预测工具用于加速度计。
更新日期:2021-03-08
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