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Evidence for Resource Homogenization in 50 Trophic Ecosystem Networks

By Stuart R. Borrett and Andria K. Salas


Connectivity patterns of ecological elements are often the core concern of ecologists working at multiple levels of organization (e.g., populations, ecosystems, and landscapes) because these patterns often reflect the forces shaping the system's development as well as constraining their operation. One reason these patterns of direct connections are critical is that they establish the pathways through which elements influence each other indirectly. Here, we tested a hypothesized consequence of connectivity in ecosystems: the homogenization of resource distributions in flow networks. Specifically, we tested the generality of the systems ecology hypothesis of resource homogenization in 50 empirically derived trophic ecosystem models representing 35 distinct ecosystems. We applied Ecological Network Analysis to calculate resource homogenization for these models. We further evaluated the robustness of our results in two ways. First, we verified the close correspondence between the input- and output-oriented homogenization values to ensure that our results were not biased by our decision to focus on the output orientation. Second, we conducted a Monte Carlo based uncertainty analysis to determine the robustness of our results to +/-5% error introduced into the original flow matrices for each model. Our results show that resource homogenization occurs universally in the 50 ecosystem models tested. We confirm that our results are not biased by using the output-oriented homogenization values because there is a significant linear regression between the input and output oriented homogenization (r^2 = 0.38, p < 0.001). Finally, we found that our results are robust to +/-5% error in the flow matrices. In conclusion, we found strong support for the resource homogenization hypothesis in 50 empirically derived ecosystem models.Comment: 10 pages, 3 figures, 1 tabl

Topics: Quantitative Biology - Populations and Evolution
Year: 2011
DOI identifier: 10.1016/j.ecolmodel.2010.04.004
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