Spatial variability of the Po River food web and its comparison with the Danube River food web

被引:0
|
作者
Patonai, Katalin [1 ,2 ]
Jordan, Ferenc [3 ]
Castaldelli, Giuseppe [1 ]
Congiu, Leonardo [4 ]
Gavioli, Anna [1 ]
机构
[1] Univ Ferrara, Dept Environm & Prevent Sci, Ferrara, Italy
[2] Eotvos Lorand Univ, Dept Plant Systemat Ecol & Theoret Biol, Budapest, Hungary
[3] Univ Parma, Dept Chem Life Sci & Environm Sustainabil, Parma, Italy
[4] Univ Padua, Dept Biol, Padua, Italy
来源
PLOS ONE | 2023年 / 18卷 / 07期
关键词
DYNAMICS;
D O I
10.1371/journal.pone.0288652
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Freshwater ecosystems are experiencing unprecedented pressure globally. To address environmental challenges, systematic and comparative studies on ecosystems are needed, though mostly lacking, especially for rivers. Here, we describe the food web of the Po River (as integrated from the white literature and monitoring data), describe the three river sections using network analysis, and compare our results with the previously compiled Danube River food web. The Po River food web was taxonomically aggregated in five consecutive steps (T1-T5) and it was also analyzed using the regular equivalence (REGE) algorithm to identify structurally similar nodes in the most aggregated T5 model. In total, the two river food webs shared 30 nodes. Two network metrics (normalized degree centrality [nDC]) and normalized betweenness centrality [nBC]) were compared using Mann-Whitney tests in the two rivers. On average, the Po River nodes have larger nDC values than in the Danube, meaning that neighboring connections are better mapped. Regarding nBC, there were no significant differences between the two rivers. Finally, based on both centrality indices, Carassius auratus is the most important node in the Po River food web, whereas phytoplankton and detritus are most important in the Danube River. Using network analysis and comparative methods, it is possible to draw attention to important trophic groups and knowledge gaps, which can guide future research. These simple models for the Po River food web can pave the way for more advanced models, supporting quantitative and predictive-as well as more functional-descriptions of ecosystems.
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页数:19
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