Scale matters–A multi-resolution study of the determinants of patterned ground activity in subarctic Finland

Abstract

Numerical studies of earth surface processes in relation to their environment are one of the central topics in physical geography. However, collinearity between explanatory variables and spatial autocorrelation can hinder the detection of key environmental correlates underlying response–explanatory variables' relationships identified by traditional regression methods. Moreover, conclusions about the potential importance of environmental variables have generally made on analysis conducted only at one spatial scale (resolution). In this study, a variation partitioning method provided a framework to obtain new insights into the relative roles of different factors determining patterned ground activity at multiple spatial resolutions. The variation in the distribution of the sorted and non sorted patterned ground was decomposed into independent and joint effects of relief, soil and spatial variables (geographical location) based on a multi resolution system of 1 ha, 25 ha and 100 ha cells covering in total 100 km 2 of a subarctic landscape in northern Finland. The independent effects of relief and soil variables captured the largest fraction of the variation in the non-sorted patterned ground distribution, while relief had a major contribution for sorted patterned ground activity. The independent effect of spatial autocorrelation on sorted patterned ground was higher than that on non-sorted patterned ground. However, a considerable amount of variation in the distribution of both patterned ground types was accounted for by the joint effects of explanatory variables and may thus be causally related to two or all three groups of variables. Our analyses produced often contradicting results at different resolutions. Consequently, this has substantial implications for the study of geomorphological systems, since the choice of resolution can have a major effect on the inferences of analyses. Our results draw attention to the roles of resolution and spatial autocorrelation in the study of geomorphological systems.