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Modeling cyanobacteria biomass by surface sediment diatoms in lakes: problems and suggestions
Ecological Modelling ( IF 3.1 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.ecolmodel.2020.109056
Bo Liu , Shuo Chen , Hui Liu , Yueqiang Guan

Abstract Cyanobacteria dominance threats ecological integrity and diminishes ecological service of lakes throughout the world. Variety kinds of chemical and physical environmental factors have been used to model cyanobacteria condition in lakes except biological environmental factors. Essential resources competition plays a central role in shaping algae community in lakes. Cyanobacteria and diatoms are assumed to have conserved species’ functional traits and use resources and habitats in similar ways. Therefore, diatom metric, inferred-total phosphorus based on diatoms (DI-TP), could be a valuable predictor for cyanobacteria biomass in lakes. With data sets from the 2007 National Lakes Assessment (NLA) of the US Environmental Protection Agency, we compared the performance of DI-TP with TP and other predictors on predicting cyanobacteria biomass (CBB) by boost regression tree analysis in around 1,000 lakes. In light of effects of lake types and diverse cyanobacteria functional groups on model performance, we did a priori classification on lakes based on lakes types (deep/shallow, natural/man-made lakes) and cyanobacteria functional groups (bloom-forming, potential toxigenic, heterocyst-producing and potential N2-fixing cyanobacteria). Our results showed: (1) DI-TP was informative for modeling CBB in different lake types or various cyanobacteria functional groups, but its importance was not as significant as traditional TP; (2) Performance of DI-TP on modeling CBB was better in deep man-made lakes than in shallow natural lakes; (3) DI-TP performed better on modeling the biomass of potential N2-fixing cyanobacteria than other functional groups of cyanobacteria. The lower importance of DI-TP could be caused by different sampling locations of diatom and cyanobacteria from a same site. The uneven distribution of number of shallow lakes along TP gradient could contribute to a better performance of DI-TP on predicting CBB in deep lakes than in shallow lakes. In man-made lakes, a shorter water residence helped diatoms coexist with cyanobacteria and contributed to a better performance of DI-TP on predicting CBB. We conclude that DI-TP performed better on modeling CBB in deep man-made lakes and potential N2-fixing cyanobacteria biomass. Further studies are needed to thoroughly assess the valuableness of DI-TP on predicting CBB in lakes.

中文翻译:

湖泊表层沉积硅藻模拟蓝藻生物量:问题与建议

摘要 蓝藻优势威胁着生态完整性并削弱了世界各地湖泊的生态服务。除生物环境因素外,各种化学和物理环境因素已被用于模拟湖泊中的蓝藻条件。基本资源竞争在塑造湖泊藻类群落中起着核心作用。蓝藻和硅藻被认为具有受保护物种的功能特征,并以类似的方式使用资源和栖息地。因此,基于硅藻(DI-TP)的硅藻指标推断总磷可能是湖泊中蓝藻生物量的有价值的预测指标。根据美国环境保护署 2007 年国家湖泊评估 (NLA) 的数据集,我们通过增强回归树分析在大约 1,000 个湖泊中比较了 DI-TP 与 TP 和其他预测因子在预测蓝藻生物量 (CBB) 方面的性能。鉴于湖泊类型和不同蓝藻功能群对模型性能的影响,我们根据湖泊类型(深湖/浅湖、天然/人工湖)和蓝藻功能群(成花、潜在产毒)对湖泊进行了先验分类。 ,产生杂囊的和潜在的固氮蓝藻)。我们的研究结果表明:(1)DI-TP 为模拟不同湖泊类型或各种蓝藻功能组的 CBB 提供了信息,但其重要性不如传统 TP;(2) DI-TP 模拟 CBB 的性能在深部人工湖中优于浅部天然湖;(3) DI-TP 在模拟潜在固氮蓝藻的生物量方面表现优于蓝藻的其他官能团。DI-TP 的重要性较低可能是由于来自同一地点的硅藻和蓝藻的不同采样位置造成的。沿TP梯度的浅湖数量分布不均可能有助于DI-TP在预测深湖CBB方面优于浅湖。在人造湖泊中,较短的水停留时间有助于硅藻与蓝藻共存,并有助于 DI-TP 更好地预测 CBB。我们得出结论,DI-TP 在模拟深人造湖中的 CBB 和潜在的固氮蓝藻生物量方面表现更好。需要进一步的研究来彻底评估 DI-TP 在预测湖泊 CBB 方面的价值。
更新日期:2020-08-01
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