Raw moments are used as a way to estimate species abundance distribution. The almost linear pattern of the log transformation of raw moments across scales allow us to extrapolate species abundance distribution for larger areas. However, results may produce errors. Some of these errors are due to computational complexity, fittings of patterns, binning methods, and so on. We provide some methods to reduce some of the errors. The main result is introducing new techniques for evaluating a more accurate species abundance distributions across scales through moments across scales.

翻译：原始瞬间被用作估计物种丰度分布的一种方法。 原始瞬间对不同规模的原始瞬间进行日志转换的几乎线性模式, 使我们可以推断较大区域的物种丰度分布。 但是, 结果可能会产生错误。 有些错误是由于计算的复杂性、 模式的搭配、 宾机方法等原因造成的。 我们为减少某些错误提供了一些方法。 主要结果就是引入新技术, 来评估不同规模的物种丰度在不同尺度之间更为准确的分布。