Chlorophyll a relationships with nutrients and temperature, and predictions for lakes across perialpine and Balkan mountain regions
Chlorophyll a relationships with nutrients and temperature, and predictions for lakes across perialpine and Balkan mountain regions
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叶绿素与营养物和温度的关系，以及对高山周围和巴尔干山区湖泊的预测
DOI：
10.1080/20442041.2019.1689768
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发表时间：
2020
期刊：
影响因子：
3.1
通讯作者：
Markovic
中科院分区：
文献类型：
--
作者：
Kärcher;Filstrup;Brauns;Tasevska;Patceva;Hellwig;Markovic
模型推导出的叶绿素（Chl-a）与营养盐和温度之间的关系对于理解用于湖泊分类的水质指标之间的复杂相互作用具有根本性意义，但不同方法的准确性比较却很少。在这里，我们（1）通过线性和非线性统计方法比较叶绿素模型的性能;（2）评估营养物质，深度和温度作为湖泊表面水温（LSWT）或海拔高度对叶绿素a的单一和综合影响;（3）研究最佳水质模型的可靠性，在13个湖泊从阿尔卑斯山和中央巴尔干半岛的山区。叶绿素a模拟使用原位水质数据从157个欧洲湖泊，海拔数据和LSWT原位数据补充遥感测量。非线性方法表现得更好，这意味着叶绿素a和解释变量之间的复杂关系。提升回归树，作为最好的表现的方法，容纳预测变量之间的相互作用。叶绿素a营养盐的关系，其特征在于S形曲线，与总磷具有最大的解释力，我们的研究区域。与LSWT相比，利用高度，经常使用的温度代理，导致不同的影响方向，但相似的预测性能。这些结果支持利用海拔高度的模式，叶绿素-aprodictions。相比，叶绿素aobservations，叶绿素apredictions的最佳表现的方法，山区湖泊（贫营养-富营养）导致营养状态分类的微小差异。我们的研究结果表明，这两个模型与LSWT和海拔是适合山区湖泊的水质预测，并强调将变量之间的相互作用时，面临湖泊管理的挑战的重要性。
Model-derived relationships between chlorophylla(Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-amodel performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-awas modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-aand the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a–nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-apredictions. Compared to Chl-aobservations, Chl-apredictions of the best performing approach for mountain lakes (oligotrophic–eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
影响因子：
5.7
作者：
S. Poikane;R. Portielje;M. Berg;G. Phillips;S. Brucet;L. Carvalho;U. Mischke;I. Ott;H. Soszka;J. Wichelen
通讯作者：
J. Wichelen
影响因子：
11.6
作者：
Markovic, Danijela;Carrizo, Savrina F.;David, Jonathan N. W.
通讯作者：
David, Jonathan N. W.