Social network models predict movement and connectivity in ecological landscapes

Proceedings of the National Academy of Sciences of the United States of America
US Army Corps of Engineers; US Fish and Wildlife Service; US Geological Survey; National Science Foundation (NSF) Quantitative Spatial Ecology, Evolution, and Environment (QSE3) at the University of Florida
By: , and 

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Abstract

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Social network models predict movement and connectivity in ecological landscapes
Series title Proceedings of the National Academy of Sciences of the United States of America
DOI 10.1073/pnas.1107549108
Volume 108
Issue 48
Year Published 2011
Language English
Publisher National Academy of Sciences
Publisher location Washington, D.C.
Contributing office(s) Coop Res Unit Atlanta
Description 6 p.
First page 19282
Last page 19287
Online Only (Y/N) N
Additional Online Files (Y/N) N