Hydrology and Land Surface Studies
Effects of anisotropy on pattern formation in wetland ecosystems
Article first published online: 23 FEB 2011
Copyright 2011 by the American Geophysical Union.
Geophysical Research Letters
Volume 38, Issue 4, February 2011
How to Cite
2011), Effects of anisotropy on pattern formation in wetland ecosystems, Geophys. Res. Lett., 38, L04402, doi:10.1029/2010GL046091., , , and (
- Issue published online: 23 FEB 2011
- Article first published online: 23 FEB 2011
- Manuscript Accepted: 3 JAN 2011
- Manuscript Revised: 22 DEC 2010
- Manuscript Received: 5 NOV 2010
- vegetation pattern;
- scale dependent feedback;
 Wetland ecosystems are often characterized by distinct vegetation patterns. Various mechanisms have been proposed to explain the formation of these patterns; including spatially variable peat accumulation and water ponding. Recently, short-range facilitation and long-range competition for resources (a.k.a scale dependent feedback) has been proposed as a possible mechanism for pattern formation in wetland ecosystems. We modify an existing, spatially explicit, advection-reaction-diffusion model to include for a regional hydraulic gradient and effective anisotropy in hydraulic conductivity. This effective anisotropic hydraulic conductivity implicitly represents the effect of ponding: a reduction in the long-range inhibition of vegetation growth in the direction perpendicular to the prevailing hydraulic gradient. We demonstrate that by accounting for effective anisotropy in a simple modeling framework that encompasses only a scale dependent feedback between biomass and nutrient flow, we can reproduce the various vegetation patterns observed in wetland ecosystems: maze, and vegetation bands both perpendicular and parallel to prevailing flow directions. We examine the behavior of this model over a range of plant transpiration rates and regional hydraulic gradients. Results show that by accounting for the effective x-y anisotropy that results from biomass-water interaction (i.e., ponding) we can better understand the mechanisms that drive ecosystem patterning.