Pierson Kawika
Atkinson Graduate School of Management Willamette University Salem OR USA.
Ecol Evol. 2020 May 26;10(20):10965-10973. doi: 10.1002/ece3.6353. eCollection 2020 Oct.
Causally consistent evenness measures can only be changed when the populations they refer to change. This novel property is deeply important for making causal inferences, and yet every prominent evenness measure is not causally consistent. This paper proposes a family of causally consistent evenness measures, and while any evenness measure can be made to be causally consistent, the family I introduce has the added benefit of a straightforward interpretation as a percentage evenness. I go on to illustrate the performance of these measures, and demonstrate the importance of causal consistency not only for causal inference but also for correctly reflecting the evenness of ecological communities. I also present several alternative transformations of my preferred measures, which work to address potential critiques in advance, communicate evenness to nontechnical audiences, and connect my work to more familiar ecological indicators.
因果一致的均匀度度量只有在其所指的总体发生变化时才能改变。这一新颖特性对于进行因果推断极为重要，然而每一种著名的均匀度度量都不是因果一致的。本文提出了一族因果一致的均匀度度量，虽然任何均匀度度量都可以被制成因果一致的，但我引入的这一族度量还有一个额外的好处，即可以直接解释为百分比均匀度。我接着说明了这些度量的性能，并证明了因果一致性不仅对于因果推断很重要，而且对于正确反映生态群落的均匀度也很重要。我还给出了我所偏好的度量的几种替代变换，这些变换有助于预先应对潜在的批评，向非专业受众传达均匀度，并将我的工作与更熟悉的生态指标联系起来。
