Nearest neighbor methods applied to dune field organization: The Coral Pink Sand Dunes, Kane County, Utah, USA

Abstract

Dune fields have recently come to be recognized as self-organizing systems that can be seen progressing from states of disorganization or randomness to uniformity. Dune systems can be highly sensitive to changes in factors, such as climate and sediment transport, that determine system state. Changes in climate and sediment state can take time to work their way through a dune system; this, in turn, leads to spatial heterogeneity in dune field organization. Using the Coral Pink Sand Dunes in southern Utah as a model, this study tests nearest neighbor analysis adapted as a method to objectively identify and characterize differences in two dimensional dune patterns within a dune field and to identify changes in dune patterns over time. Reducing transverse and barchanoid dunes from linear to three-point features in planar space emphasizes the clustering that occurs when dune lengths and wavelengths are more disorganized or random. This clustering may be in response to a system perturbation, such as an influx of sediment, and is reflected in lower nearest neighbor index ( R) values. As the system adjusts to the perturbation and moves towards steady state, dune length and spacing increase through migration and coalescing of smaller dunes; the resulting higher R values reflect this move towards greater uniformity in dune pattern. With the organizational states of dune systems recording feedback to changes in extrinsic climate and sediment factors, nearest neighbor analysis provides a proxy measure of system stability.