Abstract

The sedimentary record contains unique information about landscape response to environmental forcing at timescales that far exceed landscape observations over human timescales. However, stochastic processes can overprint and shred evidence of environmental signals, such as sediment flux signals, and so inhibit their transfer to strata. Our community currently lacks a quantitative framework to differentiate between environmental signals and autogenic signals in field-scale analysis of strata. Here we develop a framework and workflow to estimate autogenic thresholds for ancient sediment routing systems. Crucially these thresholds can be approximated using measurements that are readily attainable from field systems, circumventing the low temporal resolution offered by strata. This work demonstrates how short-term system dynamics can be accessed from ancient sediment routing systems to place morphodynamic limits on environmental signal propagation across ancient landscapes and into strata.

Highlights

  • The sedimentary record contains unique information about landscape response to environmental forcing at timescales that far exceed landscape observations over human timescales

  • Sedimentation rates generally decrease with increasing time window of measurement[21] as stochastic autogenic fluctuations in these rates saturate at a rate equal to the long-term aggradation or subsidence rate (r)[1,7,22]

  • We find that obliquity- and precession-scale sediment flux signals are likely to have exceeded the Kerinitis Delta System (KDS)-autogenic threshold function (ATF) (Fig. 3b), supporting the assertion that the KDS succession preserves signatures of these environmental forcing[19]

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Summary

Introduction

The sedimentary record contains unique information about landscape response to environmental forcing at timescales that far exceed landscape observations over human timescales. A general framework that is frequently applied to ancient field-scale sediment routing systems (SRSs) is landscape or fluvial diffusion[1,10], and the estimation of associated basin response timescales, Teq[11].

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