Conservation Biology Division, National Marine Fisheries Service, 2725 Montlake Boulevard East, Seattle, WA 98112, USA.
Trends Ecol Evol. 2004 Feb;19(2):101-8. doi: 10.1016/j.tree.2003.10.013.
Recently, researchers in several areas of ecology and evolution have begun to change the way in which they analyze data and make biological inferences. Rather than the traditional null hypothesis testing approach, they have adopted an approach called model selection, in which several competing hypotheses are simultaneously confronted with data. Model selection can be used to identify a single best model, thus lending support to one particular hypothesis, or it can be used to make inferences based on weighted support from a complete set of competing models. Model selection is widely accepted and well developed in certain fields, most notably in molecular systematics and mark-recapture analysis. However, it is now gaining support in several other areas, from molecular evolution to landscape ecology. Here, we outline the steps of model selection and highlight several ways that it is now being implemented. By adopting this approach, researchers in ecology and evolution will find a valuable alternative to traditional null hypothesis testing, especially when more than one hypothesis is plausible.
最近，生态学和进化领域的研究人员开始改变他们分析数据和进行生物学推论的方式。他们不再采用传统的零假设检验方法，而是采用了一种称为模型选择的方法，其中同时面对几个相互竞争的假设。模型选择可用于确定单个最佳模型，从而支持一个特定的假设，或者可以用于根据完整的一组竞争模型的加权支持进行推断。模型选择在某些领域得到广泛认可和良好发展，尤其是在分子系统学和标记重捕分析中。然而，它现在在从分子进化到景观生态学等其他几个领域也得到了支持。在这里，我们概述了模型选择的步骤，并强调了现在实施模型选择的几种方法。通过采用这种方法，生态学和进化领域的研究人员将找到一种有价值的替代传统零假设检验的方法，特别是当有多个假设合理时。
