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18 January 2011 Structural complexity, movement bias, and metapopulation extinction risk in dendritic ecological networks
Evan H. Campbell Grant
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Abstract

Spatial complexity in metacommunities can be separated into 3 main components: size (i.e., number of habitat patches), spatial arrangement of habitat patches (network topology), and diversity of habitat patch types. Much attention has been paid to lattice-type networks, such as patch-based metapopulations, but interest in understanding ecological networks of alternative geometries is building. Dendritic ecological networks (DENs) include some increasingly threatened ecological systems, such as caves and streams. The restrictive architecture of dendritic ecological networks might have overriding implications for species persistence. I used a modeling approach to investigate how number and spatial arrangement of habitat patches influence metapopulation extinction risk in 2 DENs of different size and topology. Metapopulation persistence was higher in larger networks, but this relationship was mediated by network topology and the dispersal pathways used to navigate the network. Larger networks, especially those with greater topological complexity, generally had lower extinction risk than smaller and less-complex networks, but dispersal bias and magnitude affected the shape of this relationship. Applying these general results to real systems will require empirical data on the movement behavior of organisms and will improve our understanding of the implications of network complexity on population and community patterns and processes.

Evan H. Campbell Grant "Structural complexity, movement bias, and metapopulation extinction risk in dendritic ecological networks," Journal of the North American Benthological Society 30(1), 252-258, (18 January 2011). https://doi.org/10.1899/09-120.1
Received: 31 August 2009; Accepted: 1 November 2010; Published: 18 January 2011
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KEYWORDS
dendritic ecological network
dendritic metapopulation
dispersal bias
metapopulation persistence
network complexity
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