Abstract Factors controlling the three-decade long rise in cyanobacteria biomass in a eutrophic shallow lake
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Factors controlling the three-decade long rise in cyanobacteria biomass in a eutrophic shallow lake

机译:控制富营养化浅水湖泊中蓝细菌生物量连续三年增长的因素

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AbstractWe aimed at quantifying the importance of limnological variables in the decadal rise of cyanobacteria biomass in shallow hemiboreal lakes. We constructed estimates of cyanobacteria (blue-green algae) biomass in a large, eutrophic lake (Estonia, Northeastern Europe) from a database comprising 28 limnological variables and spanning more than 50years of monitoring. Using a dual-model approach consisting in a boosted regression trees (BRT) followed by a generalized least squares (GLS) model, our results revealed that six variables were most influential for assessing the variance of cyanobacteria biomass. Cyanobacteria response to nitrate concentration and rotifer abundance was negative, whereas it was positive to pH, temperature, cladoceran and copepod biomass. Response to total phosphorus (TP) and total phosphorus to total nitrogen ratio was very weak, which suggests that actual in-lake TP concentration is still above limiting values. The most efficient GLS model, which explained nearly two thirds (r2=0.65) of the variance of cyanobacteria biomass included nitrate concentration, water temperature and pH. The very high number of observations (maximumn=525) supports the robustness of the models. Our results suggest that the decadal rise of blue-green algae in shallow lakes lies in the interaction between cultural eutrophication and global warming which bring in-lake physical and chemical conditions closer to cyanobacteria optima.Graphical abstractDisplay OmittedHighlightsWe assessed the influence of 28 variables on cyanobacteria.Cyanobacteria biomass did not respond to phosphorus concentration.Nitrates, temperature and pH had a major influence.Zooplankton could be positively or negatively correlated.Lake condition may deteriorate with global warming.
机译: 摘要 我们的目标是量化浅层半透明湖泊中蓝变生物量在蓝细菌生物量年代际上升中的重要性。我们从一个包含28个湖泊学变量并跨越50多年监测的数据库中,构建了一个大型富营养化湖泊(爱沙尼亚,东北欧)中蓝细菌(蓝藻)生物量的估算值。使用包含增强回归树(BRT)和广义最小二乘(GLS)模型的双模型方法,我们的结果表明,六个变量对评估蓝细菌生物量的变化最有影响。蓝细菌对硝酸盐浓度和轮虫的丰度响应为阴性,而对pH,温度,枝角类和co足类生物量则为阳性。对总磷(TP)和总磷与总氮之比的响应非常弱,这表明实际湖中TP浓度仍高于极限值。最有效的GLS模型,可以解释蓝细菌生物量方差的近三分之二( r 2 = 0.65)包括硝酸盐浓度,水温和pH值。大量观察(最大 n = 525)支持模型的鲁棒性。我们的研究结果表明,浅水湖泊中蓝藻的年代际增长在于文化富营养化和全球变暖之间的相互作用,这使湖内的物理和化学条件更接近于蓝细菌的最佳状态。 图形摘要 省略显示 突出显示 •• < / ce:label> 我们评估了28个变量对蓝细菌的影响。 蓝藻生物量对磷浓度没有反应。 硝酸盐,温度和pH产生重大影响。 Zooplankton可以正相关或负相关。 湖泊状况可能会随着全球变暖而恶化。

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