Neubauer Philipp, Jensen Olaf P
Dragonfly Science , Wellington , New Zealand.
Department of Marine and Coastal Science, Rutgers University, Institute of Marine & Coastal Sciences , New Brunswick, NJ , USA.
PeerJ. 2015 Apr 23;3:e920. doi: 10.7717/peerj.920. eCollection 2015.
Quantitative analysis of stable isotopes (SI) and, more recently, fatty acid profiles (FAP) are useful and complementary tools for estimating the relative contribution of different prey items in the diet of a predator. The combination of these two approaches, however, has thus far been limited and qualitative. We propose a mixing model for FAP that follows the Bayesian machinery employed in state-of-the-art mixing models for SI. This framework provides both point estimates and probability distributions for individual and population level diet proportions. Where fat content and conversion coefficients are available, they can be used to improve diet estimates. This model can be explicitly integrated with analogous models for SI to increase resolution and clarify predator-prey relationships. We apply our model to simulated data and an experimental dataset that allows us to illustrate modeling strategies and demonstrate model performance. Our methods are provided as an open source software package for the statistical computing environment R.
稳定同位素（SI）的定量分析以及最近的脂肪酸谱（FAP）分析，是用于估计不同猎物在捕食者饮食中相对贡献的有用且互补的工具。然而，迄今为止，这两种方法的结合一直是有限的且定性的。我们提出了一种用于FAP的混合模型，该模型遵循用于SI的最新混合模型中的贝叶斯机制。这个框架为个体和种群水平的饮食比例提供了点估计和概率分布。在脂肪含量和转换系数可用的情况下，可以用它们来改进饮食估计。该模型可以与SI的类似模型明确整合，以提高分辨率并阐明捕食者 - 猎物关系。我们将我们的模型应用于模拟数据和一个实验数据集，这使我们能够说明建模策略并展示模型性能。我们的方法作为一个用于统计计算环境R的开源软件包提供。
