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Modelling the consequence of glacier retreat on mixotrophic nanoflagellate bacterivory: a Bayesian approach
Oikos ( IF 3.4 ) Pub Date : 2020-05-18 , DOI: 10.1111/oik.07170
Luca Schenone 1 , Esteban G. Balseiro 1 , Marcela Bastidas Navarro 1 , Beatriz E. Modenutti 1
Affiliation  

Mixotrophic nanoflagellate bacterivory is affected by light; however, in glacially influenced lakes, glacial clay may also interfere with prey uptake. Mechanistic models based on prior quantitative hypotheses and tested with field data are useful for predicting these predator–prey interactions under a changing climate. We modelled the effect of glacial particles on the bacterivory of mixotrophic nanoflagellates, the dominant phytoplankton in mountain lakes in the North Patagonian Andes. Our model equation is based on the classical Michaelis–Menten formulation and Platt's photosynthesis–irradiance curve to account for the interference by glacial particles and the effect of light intensity, respectively. Bayesian inference was applied to estimate model parameters using data from field bacterivory experiments. Light experiments (LE) were performed in lakes with different levels of light penetration without clay particles, while clay experiments (CE) were performed with an experimental gradient of glacial clay concentration at constant light intensity. The LE showed a non‐monotonic effect of light intensity and the CE revealed an exponential negative effect of clay concentration. The obtained model was tested with two independent experiments carried out in a turbid proglacial lake. Our proposed mechanistic model successfully predicted the combined effect of light availability and particle interference on the mixotrophic nanoflagellate–bacteria relationship. The model demonstrated that the effect of light is dampened as clay concentration increases.

中文翻译:

模拟冰川退缩对混合营养的纳米鞭毛细菌的影响:贝叶斯方法

杂养纳米鞭毛细菌受到光的影响;但是,在受冰川影响的湖泊中,冰川黏土也可能会干扰猎物的摄取。基于先前的定量假设并用现场数据进行测试的机理模型对于预测气候变化下的这些捕食者与被捕食者之间的相互作用非常有用。我们对北巴塔哥尼亚安第斯山脉山区湖泊中混合营养型纳米鞭毛(主要的浮游植物)的细菌作用进行了模拟。我们的模型方程式基于经典的Michaelis-Menten公式和Platt的光合作用-辐照度曲线,分别解释了冰川颗粒的干扰和光强度的影响。贝叶斯推断被用于使用野外细菌实验数据估算模型参数。在没有粘土颗粒的情况下,在具有不同水平的光透过率的湖泊中进行光实验(LE),而在恒定光强度下以冰川粘土浓度的实验梯度进行粘土实验(CE)。LE显示出光强度的非单调效应,而CE显示出粘土浓度的指数级负效应。在浑浊的湖中进行了两次独立的实验,测试了获得的模型。我们提出的机械模型成功地预测了光利用率和粒子干扰对混合营养型纳米鞭毛-细菌关系的综合影响。该模型表明,随着粘土浓度的增加,光的影响会减弱。而粘土实验(CE)是在恒定光强度下以冰川粘土浓度的实验梯度进行的。LE显示出光强度的非单调效应,而CE显示出粘土浓度的指数级负效应。在浑浊的湖中进行了两次独立的实验,测试了获得的模型。我们提出的机械模型成功地预测了光利用率和粒子干扰对混合营养型纳米鞭毛-细菌关系的综合影响。该模型表明,随着粘土浓度的增加,光的影响会减弱。而粘土实验(CE)是在恒定光强度下以冰川粘土浓度的实验梯度进行的。LE显示出光强度的非单调效应,而CE显示出粘土浓度的指数级负效应。在浑浊的湖中进行了两次独立的实验,测试了获得的模型。我们提出的机械模型成功地预测了光利用率和粒子干扰对混合营养型纳米鞭毛-细菌关系的综合影响。该模型表明,随着粘土浓度的增加,光的影响会减弱。LE显示出光强度的非单调效应,而CE显示出粘土浓度的指数级负效应。通过在浑浊的长廊湖中进行的两个独立实验测试了获得的模型。我们提出的机械模型成功地预测了光利用率和粒子干扰对混合营养型纳米鞭毛-细菌关系的综合影响。该模型表明,随着粘土浓度的增加,光的影响会减弱。LE显示出光强度的非单调效应,而CE显示出粘土浓度的指数级负效应。在浑浊的湖中进行了两次独立的实验,测试了获得的模型。我们提出的机械模型成功地预测了光利用率和粒子干扰对混合营养型纳米鞭毛-细菌关系的综合影响。该模型表明,随着粘土浓度的增加,光的影响会减弱。
更新日期:2020-05-18
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