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改进贝叶斯同位素混合模型:对杰克逊等人(2009年)的回应。

Improving Bayesian isotope mixing models: a response to Jackson et al. (2009).

作者信息

Semmens Brice X, Moore Jonathan W, Ward Eric J

机构信息

Northwest Fisheries Science Center, National Marine Fisheries Service, Seattle, WA 98112, USA.

出版信息

Ecol Lett. 2009 Mar;12(3):E6-8. doi: 10.1111/j.1461-0248.2009.01283.x.

Abstract

We recently described a Bayesian framework for stable isotope mixing models and provided a software tool, MixSIR, for conducting such analyses (Ecol. Lett., 2008; 11:470). Jackson et al. (Ecol. Lett., 2009; 12:E1) criticized the performance of our software based on tests using simulated data. However, their simulation data were flawed, rendering claims of erroneous behaviour inaccurate. A re-evaluation of the MixSIR source code did, however, uncover two minor coding errors, which we have fixed. When data are correctly simulated according to eqns (1)-(4) in Jackson et al. (2009), MixSIR consistently and accurately estimated the proportional contribution of prey to a predator diet, and was surprisingly robust to additional unquantified error. Jackson et al. (2009) also suggested we use a Dirichlet prior on the source proportion parameters, which we agree with. Finally, Jackson et al. (2009) propose adding additional error parameters to our mixing model framework. We caution that such increases in model complexity should be evaluated based on data support.

摘要

我们最近描述了一种用于稳定同位素混合模型的贝叶斯框架,并提供了一个软件工具MixSIR来进行此类分析(《生态学快报》,2008年;11:470)。杰克逊等人(《生态学快报》,2009年;12:E1)基于使用模拟数据的测试批评了我们软件的性能。然而,他们的模拟数据存在缺陷,使得关于错误行为的说法不准确。不过,对MixSIR源代码的重新评估确实发现了两个小的编码错误,我们已经修复。当根据杰克逊等人(2009年)的方程(1) - (4)正确模拟数据时,MixSIR能够一致且准确地估计猎物对捕食者饮食的比例贡献,并且对额外的未量化误差具有惊人的鲁棒性。杰克逊等人(2009年)还建议我们在源比例参数上使用狄利克雷先验,我们对此表示认同。最后,杰克逊等人(2009年)提议在我们的混合模型框架中添加额外的误差参数。我们提醒,这种模型复杂性的增加应基于数据支持进行评估。

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