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Generation and application of river network analogues for use in ecology and evolution

Authors :
Emanuel A. Fronhofer
Florian Altermatt
Luca Carraro
Andrea Rinaldo
Isabelle Gounand
Enrico Bertuzzo
Reinhard Furrer
Department of Aquatic Ecology
Swiss Federal Insitute of Aquatic Science and Technology [Dübendorf] (EAWAG)
University of Ca’ Foscari [Venice, Italy]
Institut des Sciences de l'Evolution de Montpellier (UMR ISEM)
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS)
Universität Zürich [Zürich] = University of Zurich (UZH)
Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris )
Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Ecole Polytechnique Fédérale de Lausanne (EPFL)
Austrian Science Fund (FWF)31003A_173074PP00P3_179089
University of Zurich
Carraro, Luca
Altermatt, Florian
Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE)
Source :
Ecology and Evolution, Vol 10, Iss 14, Pp 7537-7550 (2020), Ecology and Evolution, Ecology and Evolution, Wiley Open Access, 2020, 10, pp.7537-7550. ⟨10.1002/ece3.6479⟩, Ecology and Evolution, 2020, 10, pp.7537-7550. ⟨10.1002/ece3.6479⟩
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

Several key processes in freshwater ecology are governed by the connectivity inherent to dendritic river networks. These have extensively been analyzed from a geomorphological and hydrological viewpoint, yet structures classically used in ecological modeling have been poorly representative of the structure of real river basins, often failing to capture well‐known scaling features of natural rivers. Pioneering work identified optimal channel networks (OCNs) as spanning trees reproducing all scaling features characteristic of natural stream networks worldwide. While OCNs have been used to create landscapes for studies on metapopulations, biodiversity, and epidemiology, their generation has not been generally accessible.Given the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we provide the R‐package OCNet. Owing to the stochastic process generating OCNs, multiple network replicas spanning the same surface can be built; this allows performing computational experiments whose results are irrespective of the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three‐dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the package provides functions that aggregate OCNs into an arbitrary number of nodes, calculate several descriptors of river networks, and draw relevant network features.We describe the main functionalities of the package and its integration with other R‐packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species.In conclusion, OCNet provides a powerful tool to generate realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems and enhances our knowledge on spatial processes in freshwater ecology in general.<br />Recently, research on spatial dynamics in ecology and evolution has bloomed. However, spatial structures used in theoretical and empirical ecological studies are often not representative of realistic landscapes. This is particularly true for river networks, which are of paramount interest to ecologists owing to their wide (but currently severely declining) biodiversity. Indeed, most of ecological work has been neglecting the scaling character of real river networks, despite well‐established knowledge in the fields of geomorphology and hydrology. Here, we present a method to create optimal channel networks (OCNs, i.e., river network analogues reproducing all topographic and scaling features of natural rivers), and the respective R‐package allowing their generation and analysis. We review the theoretical background underlying the OCN concept, present the main package functionalities, discuss possible applications in the realm of ecology and evolution, and detail how the package can be integrated with other popular R‐packages in spatial ecology.

Details

Language :
English
ISSN :
20457758
Database :
OpenAIRE
Journal :
Ecology and Evolution, Vol 10, Iss 14, Pp 7537-7550 (2020), Ecology and Evolution, Ecology and Evolution, Wiley Open Access, 2020, 10, pp.7537-7550. ⟨10.1002/ece3.6479⟩, Ecology and Evolution, 2020, 10, pp.7537-7550. ⟨10.1002/ece3.6479⟩
Accession number :
edsair.doi.dedup.....13c48df0f80110a6012838b033d2cb0c
Full Text :
https://doi.org/10.1101/2020.02.17.948851