Literature DB >> 17257104

Living in the branches: population dynamics and ecological processes in dendritic networks.

Evan H Campbell Grant1, Winsor H Lowe, William F Fagan.   

Abstract

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

Mesh:

Year:  2007        PMID: 17257104     DOI: 10.1111/j.1461-0248.2006.01007.x

Source DB:  PubMed          Journal:  Ecol Lett        ISSN: 1461-023X            Impact factor:   9.492


  51 in total

1.  Population persistence under advection-diffusion in river networks.

Authors:  Jorge M Ramirez
Journal:  J Math Biol       Date:  2011-11-03       Impact factor: 2.259

2.  Dendritic connectivity controls biodiversity patterns in experimental metacommunities.

Authors:  Francesco Carrara; Florian Altermatt; Ignacio Rodriguez-Iturbe; Andrea Rinaldo
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-28       Impact factor: 11.205

3.  Use of multiple dispersal pathways facilitates amphibian persistence in stream networks.

Authors:  Evan H Campbell Grant; James D Nichols; Winsor H Lowe; William F Fagan
Journal:  Proc Natl Acad Sci U S A       Date:  2010-03-29       Impact factor: 11.205

4.  Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks.

Authors:  Yasmine Samia; Frithjof Lutscher; Alan Hastings
Journal:  J R Soc Interface       Date:  2015-09-06       Impact factor: 4.118

5.  Predicting spatial similarity of freshwater fish biodiversity.

Authors:  Sandro Azaele; Rachata Muneepeerakul; Amos Maritan; Andrea Rinaldo; Ignacio Rodriguez-Iturbe
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-09       Impact factor: 11.205

6.  Population persistence in river networks.

Authors:  Jonathan Sarhad; Robert Carlson; Kurt E Anderson
Journal:  J Math Biol       Date:  2013-07-12       Impact factor: 2.259

7.  River-stream connectivity affects fish bioassessment performance.

Authors:  Nathaniel P Hitt; Paul L Angermeier
Journal:  Environ Manage       Date:  2008-04-09       Impact factor: 3.266

8.  Spatial effects on species persistence and implications for biodiversity.

Authors:  Enrico Bertuzzo; Samir Suweis; Lorenzo Mari; Amos Maritan; Ignacio Rodríguez-Iturbe; Andrea Rinaldo
Journal:  Proc Natl Acad Sci U S A       Date:  2011-02-28       Impact factor: 11.205

9.  Unravelling river system impairments in stream networks with an integrated risk approach.

Authors:  Kris Van Looy; Jérémy Piffady; Thierry Tormos; Bertrand Villeneuve; Laurent Valette; André Chandesris; Yves Souchon
Journal:  Environ Manage       Date:  2015-04-02       Impact factor: 3.266

10.  The role of river drainages in shaping the genetic structure of capybara populations.

Authors:  María Soledad Byrne; Rubén Darío Quintana; María Luisa Bolkovic; Marcelo H Cassini; Juan Ignacio Túnez
Journal:  Genetica       Date:  2015-09-18       Impact factor: 1.082

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