tRophicPosition, an r package for the Bayesian estimation of trophic position from consumer stable isotope ratios
tRophicPosition, an r package for the Bayesian estimation of trophic position from consumer stable isotope ratios
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DOI：
10.1111/2041-210x.13009
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发表时间：
2018-06
影响因子：
6.6
通讯作者：
Claudio Quezada-Romegialli;A. Jackson;B. Hayden;K. Kahilainen;C. Lopes;C. Harrod
中科院分区：
文献类型：
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作者：
Claudio Quezada-Romegialli;A. Jackson;B. Hayden;K. Kahilainen;C. Lopes;C. Harrod
稳定同位素分析提供了一个强大的工具来确定能源的燃料消费者，了解营养相互作用和推断消费者营养位置（TP），一个重要的概念，描述消费者在食物网中的生态作用。然而，目前使用稳定同位素估计总磷的方法是有限的，不能完全发挥同位素方法的潜力。例如，研究人员通常使用点估计来计算关键参数，包括营养区分因子和同位素基线，并且在计算TP时没有明确地包括与这些参数相关的方差。我们提出了“tRophicPosition”，这是一个包含贝叶斯模型的软件包，用于使用稳定同位素计算种群水平上的消费者总磷，有一个或两个基线。它结合了通过JAGS进行的马尔可夫链蒙特卡罗模拟和使用r进行的统计和图形分析。我们使用相关的统计分布对消费者和基线观察进行建模，允许它们被视为随机变量。一个基线的tp（随机参数）的计算遵循将每个营养水平的15N富集与基线的营养位置（例如主要生产者或主要消费者）联系起来的标准方程。在两条基线的情况下，一个包含δ13C的简单混合模型允许区分两种不同的氮源，从而包括δ15N替代源的异质性。“tRophicPosition”目前采用的方法包括加载、绘制和汇总来自多个站点和/或群落或局部组合的稳定同位素数据；从内部数据库加载或生成营养区分因子；定义和初始化TP的贝叶斯模型；抽样后验参数；分析、比较和绘制TP和其他参数的后验估计；并计算参数（非贝叶斯）TP估计。此外，还可以下载完整的文档，包括示例、多个插图和代码。
Stable isotope analysis provides a powerful tool to identify the energy sources which fuel consumers, to understand trophic interactions and to infer consumer trophic position (TP), an important concept that describes the ecological role of consumers in food webs. However, current methods for estimating TP using stable isotopes are limited and do not fulfil the complete potential of the isotopic approach. For instance, researchers typically use point estimates for key parameters including trophic discrimination factors and isotopic baselines, and do not explicitly include variance associated with these parameters when calculating TP. We present “tRophicPosition,” an r package incorporating a Bayesian model for the calculation of consumer TP at the population level using stable isotopes, with one or two baselines. It combines Markov Chain Monte Carlo simulations through JAGS and statistical and graphical analyses using R. We model consumer and baseline observations using relevant statistical distributions, allowing them to be treated as random variables. The calculation of TP—a random parameter—for one baseline follows standard equations linking 15N enrichment per trophic level and the trophic position of the baseline (e.g. a primary producer or primary consumer). In the case of two baselines, a simple mixing model incorporating δ13C allows for the differentiation between two distinct sources of nitrogen, thus including heterogeneity derived from alternatives sources of δ15N. Methods currently implemented in “tRophicPosition” include loading, plotting and summarizing stable isotope data either from multiple sites and/or communities or a local assemblage; loading trophic discrimination factors from an internal database or generating them; defining and initializing a Bayesian model of TP; sampling posterior parameters; analysing, comparing and plotting posterior estimates of TP and other parameters; and calculating a parametric (non‐Bayesian) TP estimate. Additionally, full documentation including examples, multiple vignettes and code are available for download.