Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networks
Abstract River networks’ universal fractal structure not only defines their hydrology and connectivity, but has also profound biological consequences, especially regarding stability and persistence of organismal populations. While rivers’ scaling features are captured by Optimal Channel Networks, kn...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-05-01
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| Series: | Communications Earth & Environment |
| Online Access: | https://doi.org/10.1038/s43247-022-00454-1 |
| _version_ | 1797736389248286720 |
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| author | Luca Carraro Florian Altermatt |
| author_facet | Luca Carraro Florian Altermatt |
| author_sort | Luca Carraro |
| collection | DOAJ |
| description | Abstract River networks’ universal fractal structure not only defines their hydrology and connectivity, but has also profound biological consequences, especially regarding stability and persistence of organismal populations. While rivers’ scaling features are captured by Optimal Channel Networks, knowledge on adequate network topologies has hitherto been only partially transferred across geo- and biosciences. Consequently, ecologists have often studied riverine populations via random networks not respecting real rivers’ scaling character. Here we show that branching probability of random networks is a scale-dependent quantity in that it varies with the length scale or spatial resolution of observations. Therefore, our findings suggest that this property is not a robust driver of ecological dynamics. Moreover, we show that random networks lead to biased estimates of population stability and persistence, while only Optimal Channel Networks yield estimates comparable to real rivers. We hence advocate Optimal Channel Networks as model landscapes for realistic and generalizable projections of ecohydrological dynamics in riverine networks. |
| first_indexed | 2024-03-12T13:13:02Z |
| format | Article |
| id | doaj.art-1baf48b488ce4854acccf4166a7c555a |
| institution | Directory Open Access Journal |
| issn | 2662-4435 |
| language | English |
| last_indexed | 2024-03-12T13:13:02Z |
| publishDate | 2022-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Earth & Environment |
| spelling | doaj.art-1baf48b488ce4854acccf4166a7c555a2023-08-27T11:29:32ZengNature PortfolioCommunications Earth & Environment2662-44352022-05-013111010.1038/s43247-022-00454-1Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networksLuca Carraro0Florian Altermatt1Department of Aquatic Ecology, Swiss Federal Institute of Aquatic Science and TechnologyDepartment of Aquatic Ecology, Swiss Federal Institute of Aquatic Science and TechnologyAbstract River networks’ universal fractal structure not only defines their hydrology and connectivity, but has also profound biological consequences, especially regarding stability and persistence of organismal populations. While rivers’ scaling features are captured by Optimal Channel Networks, knowledge on adequate network topologies has hitherto been only partially transferred across geo- and biosciences. Consequently, ecologists have often studied riverine populations via random networks not respecting real rivers’ scaling character. Here we show that branching probability of random networks is a scale-dependent quantity in that it varies with the length scale or spatial resolution of observations. Therefore, our findings suggest that this property is not a robust driver of ecological dynamics. Moreover, we show that random networks lead to biased estimates of population stability and persistence, while only Optimal Channel Networks yield estimates comparable to real rivers. We hence advocate Optimal Channel Networks as model landscapes for realistic and generalizable projections of ecohydrological dynamics in riverine networks.https://doi.org/10.1038/s43247-022-00454-1 |
| spellingShingle | Luca Carraro Florian Altermatt Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networks Communications Earth & Environment |
| title | Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networks |
| title_full | Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networks |
| title_fullStr | Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networks |
| title_full_unstemmed | Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networks |
| title_short | Optimal Channel Networks accurately model ecologically-relevant geomorphological features of branching river networks |
| title_sort | optimal channel networks accurately model ecologically relevant geomorphological features of branching river networks |
| url | https://doi.org/10.1038/s43247-022-00454-1 |
| work_keys_str_mv | AT lucacarraro optimalchannelnetworksaccuratelymodelecologicallyrelevantgeomorphologicalfeaturesofbranchingrivernetworks AT florianaltermatt optimalchannelnetworksaccuratelymodelecologicallyrelevantgeomorphologicalfeaturesofbranchingrivernetworks |