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Point Pattern Analysis of Channel Organization from the Cretaceous John Henry Member of the Straight Cliffs Formation, Kaiparowits Plateau, Southern Utah


The John Henry Member (JHM) of the Straight Cliffs Formation exposed along the Kaiparowits Plateau provides a record of ∼6 my of coastal plain to marginal marine deposition. Understanding the mechanisms influencing stratigraphic trends throughout the basin requires elucidating the controls responsible for spatial changes in alluvial architecture. In particular, base-level driven change in accommodation is commonly hypothesized to be a major downstream control on fluvial systems. In this study, we test this hypothesis using the record of fluvial deposition preserved in the JHM that is coeval with known shoreline shifts in shoreface equivalents. One way to correlate the fluvial succession with the mapped shoreline is to characterize the spatial organization of channel-belts within the fluvial JHM. To this end, point pattern analysis techniques are applied on a dataset of 136 channel-belts collected from a 220 m thick and 2000 m wide outcrop in east Bull Canyon. These techniques describe the channel-belts spatial organization as clustered, uniform, or random. The resulting variation in spatial organization, combined with data on channel-belt architecture, is then correlated with relative sea-level fluctuations from the shoreline stratigraphy. Three point patterns analysis techniques are used: quadrat method, nearest neighbor method, and K-function. Results from all techniques yield consistent classification of channel-belts spatial organization in all depositional units. A moving window spatial analysis is also performed on the same dataset to correlate the spatial organization of channel belts with the mapped shoreline. The analysis reveals three major trends in channel belt spatial organization starting with an increase in clustering throughout the lower stratigraphic interval, a progressive decline in clustering and increase in regularity in the middle interval, and a final trend of increasing randomness. These clustering trends are also linked to trends in net-to-gross estimates in the fluvial sections. Three roughly time-equivalent trends are also observed in the onlap curve: progradation, retrogration, and aggradation, in this order. A correlation study suggests long-term trends of increasing clustering are linked to trends of decreasing accommodation space. However, higher frequency clustering cycles are likely the result of autogenic processes such as the progradation of a distributive fluvial system and compensational avulsion patterns.