Pollard E, Lakhani K H, Rothery P
Ecology. 1987 Dec;68(6):2046-2055. doi: 10.2307/1939895.
We report a distribution-free approach to the detection of density-dependence in the variation of population abundance, measured by a series of annual censuses. The method uses the correlation coefficient between the observed population changes and population size and proposes a randomization procedure to define a rejection region for the hypothesis of density-independence. It is shown that the use of the proposed statistic under the randomization approach is equivalent to the likelihood ratio test for a particular family of time series models. The randomization test is compared with two other recently proposed tests. Using computer-generated density-independent and density-dependent data, it is shown that, unlike the other tests, the randomization test is effective whether or not there is a marked trend in the observed data. Arguments are presented showing how one of the other two tests can be further improved. Caution is urged in the use and interpretation of any test for detecting density-dependence in census data because (a) the tests depend on assumptions about population processes, (b) errors of measurement may lead to spurious detection of density-dependence.
我们报告了一种无分布方法，用于检测通过一系列年度普查测量的种群丰度变化中的密度依赖性。该方法使用观察到的种群变化与种群大小之间的相关系数，并提出了一种随机化程序来定义密度独立性假设的拒绝区域。结果表明，在随机化方法下使用所提出的统计量等同于对特定时间序列模型族的似然比检验。将随机化检验与其他最近提出的两种检验进行了比较。使用计算机生成的密度独立和密度依赖数据表明，与其他检验不同，无论观察数据中是否存在明显趋势，随机化检验都是有效的。还提出了论据，说明如何进一步改进其他两种检验中的一种。在使用和解释任何用于检测普查数据中密度依赖性的检验时，都应谨慎，因为（a）这些检验依赖于关于种群过程的假设，（b）测量误差可能导致对密度依赖性的虚假检测。
