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

biodiversity dispersal ecological modeling landscape metacommunity optimal channel network river networks spanning trees

Journal

Ecology and evolution
ISSN: 2045-7758
Titre abrégé: Ecol Evol
Pays: England
ID NLM: 101566408

Informations de publication

Date de publication:
Jul 2020
Historique:
received: 27 02 2020
revised: 21 05 2020
accepted: 26 05 2020
entrez: 8 8 2020
pubmed: 8 8 2020
medline: 8 8 2020
Statut: epublish

Résumé

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

Identifiants

pubmed: 32760547
doi: 10.1002/ece3.6479
pii: ECE36479
pmc: PMC7391543
doi:

Types de publication

Journal Article

Langues

eng

Pagination

7537-7550

Informations de copyright

© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

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Auteurs

Luca Carraro (L)

Department of Aquatic Ecology Swiss Federal Institute of Aquatic Science and Technology (Eawag) Dübendorf Switzerland.
Department of Evolutionary Biology and Environmental Studies University of Zurich Zürich Switzerland.

Enrico Bertuzzo (E)

Department of Environmental Sciences, Informatics and Statistics University of Venice Ca' Foscari Venice Italy.

Emanuel A Fronhofer (EA)

ISEM CNRS EPHE Université de Montpellier Montpellier France.

Reinhard Furrer (R)

Department of Mathematics and Department of Computational Science University of Zurich Zürich Switzerland.

Isabelle Gounand (I)

Department of Aquatic Ecology Swiss Federal Institute of Aquatic Science and Technology (Eawag) Dübendorf Switzerland.
Department of Evolutionary Biology and Environmental Studies University of Zurich Zürich Switzerland.
CNRS UPEC CNRS IRD INRA, Institut d'écologie et des sciences de l'environnement, IEES Sorbonne Université Paris France.

Andrea Rinaldo (A)

Laboratory of Ecohydrology Swiss Federal Institute of Technology in Lausanne (EPFL) Lausanne Switzerland.
Department of Civil, Environmental and Architectural Engineering University of Padua Padova Italy.

Florian Altermatt (F)

Department of Aquatic Ecology Swiss Federal Institute of Aquatic Science and Technology (Eawag) Dübendorf Switzerland.
Department of Evolutionary Biology and Environmental Studies University of Zurich Zürich Switzerland.

Classifications MeSH