Boundary effects in network measures of spatially embedded networks
1 Potsdam Institute for Climate Impact Research - P.O. Box 60 12 03, D-14412 Potsdam, Germany, EU
2 Humboldt-Universität zu Berlin - Unter den Linden 6, D-10099 Berlin, Germany, EU
Received: 2 July 2012
Accepted: 24 September 2012
In studies of spatially confined networks, network measures can lead to false conclusions since most measures are boundary affected. This is especially the case if boundaries are artificial and not inherent in the underlying system of interest (e.g., borders of countries). An analytical estimation of boundary effects is not trivial due to the complexity of measures. The straightforward approach we propose here is to use surrogate networks that provide estimates of boundary effects in graph statistics. This is achieved by using spatially embedded random networks as surrogates that have approximately the same link probability as a function of spatial link lengths. The potential of our approach is demonstrated for an analysis of spatial patterns in characteristics of regional climate networks. As an example networks derived from daily rainfall data and restricted to the region of Germany are considered.
PACS: 89.75.Hc – Networks and genealogical trees / 89.75.Fb – Structures and organization in complex systems / 92.60.Ry – Climatology, climate change and variability
© EPLA, 2012