Bayesian stable isotope mixing models effectively characterize the diet of an arctic raptor,Journal of Animal Ecology

当前位置： X-MOL 学术 › J. Anim. Ecol. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Bayesian stable isotope mixing models effectively characterize the diet of an arctic raptor
Journal of Animal Ecology ( IF 3.5 ) Pub Date : 2020-10-19 , DOI: 10.1111/1365-2656.13361
Devin L. Johnson ₁ , Michael T. Henderson ₂ , David L. Anderson ₂ , Travis L. Booms ₃ , Cory T. Williams ₄

Affiliation

Bayesian stable isotope mixing models (BSIMMs) for δ13 C and δ15 N can be a useful tool to reconstruct diets, characterize trophic relationships, and assess spatiotemporal variation in food webs. However, use of this approach typically requires a priori knowledge on the level of enrichment occurring between the diet and tissue of the consumer being sampled (i.e., a trophic discrimination factor or TDF). TDFs derived from captive feeding studies are highly variable, and it is challenging to select the appropriate TDF for diet estimation in wild populations. We introduce a novel method for estimating TDFs in a wild population: a proportionally balanced equation that uses high-precision diet estimates from nest cameras installed on a subset of nests in lieu of a controlled feeding study (TDFCAM ). We tested the ability of BSIMMs to characterize diet in a free-living population of gyrfalcon (Falco rusticolus) nestlings by comparing model output to high-precision nest camera diet estimates. We analyzed the performance of models formulated with a TDFCAM against other relevant TDFs and assessed model sensitivity to an informative prior. We applied the most parsimonious model inputs to a larger sample to analyze broad-scale temporal dietary trends. BSIMMs fitted with a TDFCAM and uninformative prior had the best agreement with nest camera data, outperforming TDFs derived from captive feeding studies. BSIMMs produced with a TDFCAM produced reliable diet estimates at the nest level and accurately identified significant temporal shifts in gyrfalcon diet within and between years. Our method of TDF estimation produced more accurate estimates of TDFs in a wild population than traditional approaches, consequently improving BSIMM diet estimates. We demonstrate how BSIMMs can complement a high-precision diet study by expanding its spatiotemporal scope of inference and recommend this integrative methodology as a powerful tool for future trophic studies.

中文翻译：

贝叶斯稳定同位素混合模型有效表征北极猛禽的饮食

δ13 C 和 δ15 N 的贝叶斯稳定同位素混合模型 (BSIMM) 可以成为重建饮食、表征营养关系和评估食物网时空变化的有用工具。然而，使用这种方法通常需要先验知识，了解饮食和被采样的消费者组织之间发生的丰富程度（即，营养鉴别因子或 TDF）。来自圈养喂养研究的 TDF 变化很大，选择合适的 TDF 来估计野生种群的饮食具有挑战性。我们引入了一种估计野生种群 TDF 的新方法：一种比例平衡方程，该方程使用安装在一组巢穴上的巢穴摄像机的高精度饮食估计值，而不是受控喂养研究 (TDFCAM)。我们通过将模型输出与高精度巢穴相机饮食估计值进行比较，测试了 BSIMM 表征自由生活的 gyrfalcon (Falco rusticolus) 雏鸟的饮食特征的能力。我们针对其他相关 TDF 分析了使用 TDFCAM 制定的模型的性能，并评估了模型对信息先验的敏感性。我们将最简约的模型输入应用于更大的样本，以分析广泛的时间饮食趋势。配备 TDFCAM 和无信息先验的 BSIMM 与巢穴相机数据的一致性最好，优于来自圈养喂养研究的 TDF。使用 TDFCAM 生成的 BSIMM 产生了可靠的巢级饮食估计，并准确识别了几年内和之间海隼饮食的显着时间变化。我们的 TDF 估计方法比传统方法对野生种群中的 TDF 产生了更准确的估计，从而改进了 BSIMM 饮食估计。我们展示了 BSIMM 如何通过扩展其推理的时空范围来补充高精度饮食研究，并推荐这种综合方法作为未来营养研究的有力工具。

更新日期：2020-10-19

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11