PDF(Pubmed)
Abstract：
Discerning assimilated diets of wild animals using stable isotopes is well established where potential dietary items in food webs are isotopically distinct. With the advent of mixing models, and Bayesian extensions of such models (Bayesian Stable Isotope Mixing Models, BSIMMs), statistical techniques available for these efforts have been rapidly increasing. The accuracy with which BSIMMs quantify diet, however, depends on several factors including uncertainty in tissue discrimination factors (TDFs; Δ) and identification of appropriate error structures. Whereas performance of BSIMMs has mostly been evaluated with simulations, here we test the efficacy of BSIMMs by raising domestic broiler chicks (Gallus gallus domesticus) on four isotopically distinct diets under controlled environmental conditions, ideal for evaluating factors that affect TDFs and testing how BSIMMs allocate individual birds to diets that vary in isotopic similarity. For both liver and feather tissues, δ13C and δ 15N values differed among dietary groups. Δ13C of liver, but not feather, was negatively related to the rate at which individuals gained body mass. For Δ15N, we identified effects of dietary group, sex, and tissue type, as well as an interaction between sex and tissue type, with females having higher liver Δ15N relative to males. For both tissues, BSIMMs allocated most chicks to correct dietary groups, especially for models using combined TDFs rather than diet-specific TDFs, and those applying a multiplicative error structure. These findings provide new information on how biological processes affect TDFs and confirm that adequately accounting for variability in consumer isotopes is necessary to optimize performance of BSIMMs. Moreover, results demonstrate experimentally that these models reliably characterize consumed diets when appropriately parameterized.
摘要：
使用稳定同位素识别野生动物的同化饮食已经建立，其中食物网中的潜在饮食项目在同位素上是不同的。随着混合模型的出现，以及此类模型的贝叶斯扩展(贝叶斯稳定同位素混合模型，BSIMMs),可用于这些努力的统计技术正在迅速增加。BSIMMs量化饮食的准确性，然而,取决于几个因素，包括组织辨别因子（TDF；Δ）的不确定性和适当的错误结构的识别。尽管BSIMM的性能大多是通过模拟来评估的，在这里，我们通过在受控环境条件下在四种同位素不同的饮食上饲养家养肉鸡（家鸡）来测试BSIMMs的功效，非常适合评估影响TDF的因素，并测试BSIMMs如何将单个鸟类分配给同位素相似性不同的饮食。对于肝脏和羽毛组织，饮食组之间的δ13C和δ15N值不同。肝脏的Δ13C，但不是羽毛，与个体增加体重的速度呈负相关。对于Δ15N，我们确定了饮食组的影响，性别,和组织类型，以及性别和组织类型之间的相互作用，女性的肝脏Δ15N高于男性。对于这两种组织，BSIMMs分配了大多数小鸡来纠正饮食组，特别是对于使用组合TDF而不是饮食特异性TDF的模型，以及那些应用乘法错误结构的人。ThesefindingsprovidesnewinformationonhowbiologicalprocessesaffectTDFandconfirmthatadequatelyaccountingforvariabilityinconsumer同位素isnecessarytooptimizationperformanceofBSIMMs.实验结果表明，当适当地参数化时，这些模型可靠地表征了消耗的饮食。
