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Effects of branching spatial structure and life history on the asymptotic growth rate of a population
Authors
A Goto
A Hastings
+63 more
AP Russell
B Pusey
BA McKeown
BE Rieman
C Nilsson
CM Hunter
D Fairless
D Reznick
DC Speirs
DD Williams
DJ Watts
DT Bilton
DW Schneider
E Pachepsky
EHC Grant
Emma E. Goldberg
F Lutscher
GT Skalski
H Caswell
Heather J. Lynch
I Hanski
I Koizumi
J Labonne
JB Dunham
JM Elliott
JM Levine
KE Anderson
M Fortuna
M Roy
M Smith
MA Barbeau
MA Mallin
MD Holland
MF Hill
MF Hill
Michael G. Neubert
MM McClure
N Schtickzelle
NJ Gotelli
P Humphries
P Kareiva
P Maitland
PH Wilson
R Froese
R Johnson
R Muneepeerakul
R Muneepeerakul
R Muneepeerakul
RD MacCulloch
RF Reynolds
RL Burgner
RS Schick
S Charles
S Charles
S Vuilleumier
TW Pluto
W Graf
WF Fagan
WF Fagan
WH Lowe
WH Lowe
William F. Fagan
Y Vindenes
Publication date
8 September 2010
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
Abstract
Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Theoretical Ecology 3 (2010): 137-152, doi:10.1007/s12080-009-0058-0.The dendritic structure of a river network creates directional dispersal and a hierarchical arrangement of habitats. These two features have important consequences for the ecological dynamics of species living within the network.We apply matrix population models to a stage-structured population in a network of habitat patches connected in a dendritic arrangement. By considering a range of life histories and dispersal patterns, both constant in time and seasonal, we illustrate how spatial structure, directional dispersal, survival, and reproduction interact to determine population growth rate and distribution. We investigate the sensitivity of the asymptotic growth rate to the demographic parameters of the model, the system size, and the connections between the patches. Although some general patterns emerge, we find that a species’ mode of reproduction and dispersal are quite important in its response to changes in its life history parameters or in the spatial structure. The framework we use here can be customized to incorporate a wide range of demographic and dispersal scenarios.Funding for this work came from the James S. McDonnell Foundation (EEG, HJL, WFF). MGN was supported by grants from the National Science Foundation (CMG-0530830, OCE-0326734, ATM-0428122)
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