Conceptual diagram of a sediment routing system (SRS) and the major impediments to stratigraphic storage of environmental signals. SRSs transport sediment from erosional sources to depositional sinks and are sensitive to environmental forcings (climate, tectonics, and sea level). Propagation of signals of these forcings across the Earth surface and into the stratigraphic record is influenced by three primary impediments shown in schematic form in subpanels. Each impediment can affect any section of a SRS, but for simplicity we highlight just one impediment per transport system segment. (a) The propagation of environmental signals is buffered via the interaction of channels with landscapes. For example, step changes in tectonic uplift experienced in catchments produce muted sediment flux signals with time lags at catchment outlets. These sediment flux signals become more muted with additional transport through fluvial SRSs. The amount of buffering can be predicted by comparing the duration or period of an environmental forcing with a system's equilibrium timescale (Teq). (b) The stochastic relocation of SRSs, for example, through depositional lobe avulsions in deepwater systems, can convert a continuous input sediment supply signal into a discrete and discontinuous record with time preserved in sedimentary beds separated by gaps or hiatuses of nondeposition. The duration of these hiatuses is limited by the system's compensation timescale (Tc). (c) Cut‐and‐fill processes in net depositional settings can shred environmental signals prior to stratigraphic storage by smearing input signals though space and time. When environmental forcings, for example, changing sea level, have magnitudes and periods less than autogenic timescales, they are prone to shredding. As such, stratigraphic scales, for example, deposition rates, parasequences or scours associated with the forcing, might be indistinguishable from autogenic stratigraphic scales.

Conceptual diagram of a sediment routing system (SRS) and the major impediments to stratigraphic storage of environmental signals. SRSs transport sediment from erosional sources to depositional sinks and are sensitive to environmental forcings (climate, tectonics, and sea level). Propagation of signals of these forcings across the Earth surface and into the stratigraphic record is influenced by three primary impediments shown in schematic form in subpanels. Each impediment can affect any section of a SRS, but for simplicity we highlight just one impediment per transport system segment. (a) The propagation of environmental signals is buffered via the interaction of channels with landscapes. For example, step changes in tectonic uplift experienced in catchments produce muted sediment flux signals with time lags at catchment outlets. These sediment flux signals become more muted with additional transport through fluvial SRSs. The amount of buffering can be predicted by comparing the duration or period of an environmental forcing with a system's equilibrium timescale (Teq). (b) The stochastic relocation of SRSs, for example, through depositional lobe avulsions in deepwater systems, can convert a continuous input sediment supply signal into a discrete and discontinuous record with time preserved in sedimentary beds separated by gaps or hiatuses of nondeposition. The duration of these hiatuses is limited by the system's compensation timescale (Tc). (c) Cut‐and‐fill processes in net depositional settings can shred environmental signals prior to stratigraphic storage by smearing input signals though space and time. When environmental forcings, for example, changing sea level, have magnitudes and periods less than autogenic timescales, they are prone to shredding. As such, stratigraphic scales, for example, deposition rates, parasequences or scours associated with the forcing, might be indistinguishable from autogenic stratigraphic scales.

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Plain Language Summary Reconstructing the history of Earth prior to the age of scientific instrumentation relies heavily on interpretations of layers of sedimentary rocks, collectively called the stratigraphic record. The composition, architecture, chemistry, and fossils contained in these rocks provide signals of past climate, tectonics, and biolo...

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... External environmental perturbations (e.g., base level, water and sediment supply) can change the pace and magnitude of river processes and cause architectural changes in fluvial stratigraphy. Reading preserved fluvial strata for past changes is, however, complicated by noise generated by autogenic dynamics (Ganti et al., 2014;Hajek & Straub, 2017;Jerolmack & Paola, 2010;Romans et al., 2016), which can buffer, distort or even obliterate the record of past environmental changes (Foreman & Straub, 2017;Straub et al., 2020). Previous work quantified the scales of environmental changes that can be influenced by noise in sediment transport systems (Foreman & Straub, 2017;Ganti et al., 2014;Jerolmack & Paola, 2010). ...
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Plain Language Summary Bedforms are wavy features found regularly on the beds of rivers. Bedform deposits are the building blocks of the rock record on Earth and Mars. Bedforms and their deposits respond to floods; however, it is unclear if all floods are similarly represented in bedforms and their deposits. To address this, we identified the timescales over which bed elevation and sediment discharge are variable in a steady‐state experiment of bedform evolution using high‐resolution data. We investigated the time series of bed elevation to document the existence of bedform groups, which represent a collection of bedforms that have deep scours at their upstream and downstream end. We find that the turnover timescales (time required to move an entire land feature) of bedforms and bedform groups are the key controls on noise in bedform evolution. Results suggest that the signal of floods with duration less than bedform turnover timescale will not be found in bedform data and their deposits. However, floods with duration greater than the bedform‐group turnover timescale are likely to be expressed in bedform data and their deposits. These results provide a new theory for how floods are represented in river deposits.
... The internal dynamics within sediment-transport systems (STSs) are characterized by local episodes of sediment storage and release that occur naturally, known as autogenic processes, which are ubiquitous across all landscapes and generate stochastic fluctuations in sediment transport in the absence of external (allogenic) forcing Jerolmack, 2011;Jerolmack & Paola, 2010;Kim & Jerolmack, 2008;Paola, 2016;Pelletier et al., 2015;Romans et al., 2016;Straub et al., 2020). Stochastic sediment transport resulting from autogenic processes generates noise within a STS, and the resultant stratigraphy, and limits the predictability of STS dynamics (Ganti et al., 2014;Jerolmack, 2011;Jerolmack & Paola, 2010;Paola, 2016;Romans et al., 2016;Van De Wiel et al., 2011). ...
... However, a time series of stratigraphic information is inherently incomplete owing to the presence of hiatuses over a variety of spatiotemporal scales from laminae to basin-scale unconformities, which reduce the preservation of autogenic processes within vertical sections (Ager, 1973;Davies et al., 2019;Foreman & Straub, 2017;Jerolmack & Sadler, 2007;Kemp, 2012;Sadler, 1981;Schumer & Jerolmack, 2009;Sommerfield, 2006). Within all geomorphic environments, variations exist in the duration of depositional, stasis (non-deposition) and erosional events driven by autogenic reorganization, which generates hiatal surfaces with a range of frequencies and durations Kim & Jerolmack, 2008;Sadler, 1981;Sommerfield, 2006;Straub & Foreman, 2018;Straub et al., 2020;Strauss & Sadler, 1989;Tipper, 2015;. As a result, part of the original autogenic signal is removed and imposed sediment flux signals can be distorted (e.g., Burgess et al., 2019;Foreman & Straub, 2017;, making it challenging to accurately reconstruct sediment-transport processes and detect environmental signals from landscapes and strata (Kemp, 2012(Kemp, , 2016Kemp & Sexton, 2014;Miall, 2015;Paola et al., 2018;Straub et al., 2020;Tofelde et al., 2021). ...
... Within all geomorphic environments, variations exist in the duration of depositional, stasis (non-deposition) and erosional events driven by autogenic reorganization, which generates hiatal surfaces with a range of frequencies and durations Kim & Jerolmack, 2008;Sadler, 1981;Sommerfield, 2006;Straub & Foreman, 2018;Straub et al., 2020;Strauss & Sadler, 1989;Tipper, 2015;. As a result, part of the original autogenic signal is removed and imposed sediment flux signals can be distorted (e.g., Burgess et al., 2019;Foreman & Straub, 2017;, making it challenging to accurately reconstruct sediment-transport processes and detect environmental signals from landscapes and strata (Kemp, 2012(Kemp, , 2016Kemp & Sexton, 2014;Miall, 2015;Paola et al., 2018;Straub et al., 2020;Tofelde et al., 2021). Furthermore, limits on our ability to date strata mean sediment age is often assigned by linear interpolation between dated horizons (Abels et al., 2010;Ramos-Vázquez et al., 2017), providing additional challenges to the incompleteness problem by distorting the apparent representation of time in strata relative to true time (Barefoot et al., 2023;. ...
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Spectral analysis is a central tool regularly used by the scientific community to identify the presence of periodic processes within a time series of information, as spectral peaks at an imposed periodicity can be differentiated from internal (autogenic) variance. In scientific disciplines, such as seismology, the time series of information is of high temporal resolution. Hence, although temporal gaps are present, they do not impact the overall noise structure, meaning that the full spectrum of autogenic variance can be reconstructed. However, power spectra generated from stratigraphic information are affected by temporal incompleteness due to varying episodes of erosion and geomorphic stasis, which generate gaps over a range of scales. This removes information related to the natural and autogenic variability present within sediment‐transport systems, which makes it challenging to accurately reconstruct the structure and strength of paleo‐surface processes, which defines the detectability of past environmental signals. We explore how incompleteness impacts the temporal structure of autogenic noise within power spectra, and how this influences the detectability of spectral spikes related to environmental signals. We utilize a sediment flux time series from a physical rice pile and progressively degrade these data to mimic varying degrees of stratigraphic incompleteness. We find that incompleteness strongly influences the timescales and spectral structure of autogenic noise evident, and can render signals over all periodicities undetectable within a highly incomplete time series. This offers the ability to confidently justify the interpretation of subtle environmental signals from field measurements and understand the records that may best preserve paleoenvironmental variability.
... One of the challenges for geologists trying to improve the interpretation of the stratigraphic records is how to embrace hypothesis testing and the quantification of uncertainty in our interpretations of stratum (Straub et al., 2020) because of these factors, such as the sediment supply from the eroding source region, the grain size distribution of that sediment supply, and the area available or accommodation for sediment accumulation in the downstream regions, can make the interpretation of a climatic or tectonic signal complex, particularly as these processes are nonlinear (Armitage et al., 2011). Variations of stratal patterns are repositories for climate and lake level fluctuation signals, as they are sensitive to tectonic activity and dramatic climate change (Molnar, 2001;Zhang et al., 2001;Lu et al., 2022;Vallati et al., 2023). ...
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The formation of vertical sedimentary succession of delta in the arid and semi-arid basin-margin progradation dramatically depends on the variation of sediment flux and accommodation, but the discontiguous record of signals tends to exist enormous variable, which renders the bulk record of microfacies difficult to quantify from the vertical sedimentary succession. We analyzed the 18 vertical sedimentary successions collected from 18 field trenches of lake delta by cusp-catastrophe model, allowing detailed mapping of microfacies. The present detailed study indicates the suitability of cusp-catastrophe theory for explaining vertical sedimentary succession in the BWH (Bawanghe) delta. Three equilibrium states of processes responsible for the deposition of BWH delta's evolution were established: sandy-dominated upper leaves primarily exhibit delta plain; sandy/muddy-dominated lower leaves present delta plain and pro-delta; and sandy-dominated middle leaves which commonly developed delta front. The result of analysis shows that the reliability of cusp-catastrophe model to identity mutation of vertical sedimentary succession exceeds 50 %, and to identity microfacies transitions with a precipitation periodicity exceeds 70 %. These cognitions support the previous view that changing precipitation results in an abrupt change in margin progradation. Simultaneously, the study gives new insights into the microfacies quantification of lake delta and reveals the influence of crest value changes of precipitation on vertical sedimentary succession can be understood from the dependence of microfacies distribution on the change of sediment flux and accommodation.
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... The importance of internal dynamics as a driver of stratigraphic changes in the absence of dynamic external forcing has recently received considerable attention (for example, compensational stacking, Mutti & Sonnino, 1981;Mohrig et al., 2000; fluvial terraces generated by auto-incision, Muto & Steel, 2004; auto-reorganization of fluvial systems in hanging-wall basins, Kim & Paola, 2007). The findings in this work expand the current understanding of internal feedbacks in sedimentrouting systems and their resultant stratigraphic record, which in turn can provide important insight for discerning stratigraphic products of autogenic processes from the stratigraphic signals of climatic, tectonic and sea-level changes (Hajek et al., 2010;Burgess et al., 2019;Toby et al., 2019;Straub et al., 2020). ...
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... Strata are often analysed to identify what, if any, signal they contain that records climate change, sea-level variations, or tectonic events (e.g. Blum et al., 2018;Somme et al., 2019;Straub et al., 2019;Tofelde et al., 2021;Sharman et al., 2023). Such analysis is an important element in reconstructing Earth history, but preservation and subsequent identification of external signals in strata is complicated. ...
... However, the relative values of periodicity, so the difference between shorter-period dominant allogenic signals and longer-period dominant autogenic signals, may well be significant, reflecting the rates at which depositional topography develops, influences subsequent flow deposition and avulsion, and creates organised stacking patterns, as documented in other modelling and outcrop studies (e.g. Hawie et al., 2015;Li et al., 2020;Hajek & Straub, 2019). In these models that autogenic stacking is typically expressed at longer periods of 50-100 flows, so 50-100ky. ...
... As ever, it is important to consider the limitations of any numerical model being used to make interpretations and draw conclusions. For example, Straub et al. (2019) state that "many numerical formulations do not generate the rich structure of strata that is required to explore limits of environmental signal recovery because they do not account for the stochastic variability of processes that contribute to the construction of strata". The implication seems to be that only stochastic processes can generate the necessary variability to create realistic strata, but the strata produced by simple, deterministic Lobyte3D models suggest otherwise. ...
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... This may reflect spatio-temporal consistency of grainsize fractions generated in the source areas and/or buffering and mixing of sediment supply in source-area catchments (e.g. Castelltort and Van Den Driessche, 2003;Jerolmack and Paola, 2010;Straub et al., 2020). The small gravel grain-size fractions (Fig. 11B) and net-depositional fluxes (Fig. 16) imply that gravel may have been retained in source-area catchments. ...
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We reconstruct upsystem-to-downsystem grain-size variations in the sediment routing systems of the data-rich Middle Jurassic Brent Group of the northern North Sea, using published stratigraphic, thickness, palaeogeographic, provenance and age constraints combined with representative core and wireline-log data. Facies associations provide a textural proxy for gravel, sand and mud grain-size fractions, and their distributions define spatio-temporal variations in grain size within four previously documented genetic sequences (J22, J24, J26, J32). Sediment was sourced from the west (Shetland Platform), east (Norwegian Landmass) and south (Mid-North Sea High). The corresponding sediment routing systems were geographically distinct in the oldest (J22) and youngest (J32) genetic sequences, but combined to feed a large wave-dominated delta (‘Brent Delta’) in genetic sequences J24 and J26.Few of the Brent Group sediment routing systems exhibit the downsystem-fining grain-size trend predicted by sediment mass balance theory. Deviations from this reference trend reflect: (1) sparse sampling of channelised fluvial and fluvio-tidal sandbodies in upsystem locations; (2) preferential trapping of sand in underfilled antecedent and syn-depositional, half-graben depocentres in genetic sequences J22 and J32; and (3) nearshore retention of sand by shoaling waves in wave-dominated shoreface and barrier-strandplain systems. This third type of deviation reveals that spatial facies partitioning due to shallow-marine process regime distorts the simple downsystem-fining reference trend, and supports the interpretation that large volumes of predominantly muddy sediment were bypassed beyond the ‘Brent Delta’ into neighbouring basins. In summary, our analysis demonstrates a practical tool to interpret sediment supply and sediment dispersal in the stratigraphic record.
... Sediment transport systems (STSs) are sensitive to external environmental perturbations; these can be natural (e.g., related to climatic or tectonic processes) or anthropogenic in origin (1)(2)(3)(4)(5). STSs respond and adjust to these perturbations in a number of ways and over a range of temporal and physical scales (2,6). ...
... STSs respond and adjust to these perturbations in a number of ways and over a range of temporal and physical scales (2,6). A fundamental response of a STS to these perturbations is a variation in the generation of sediment supplied to the STS and transmitted down system as an environmental signal (4,7). These environmental sediment flux signals can generate geomorphic and stratigraphic signatures that allow for the reconstruction of past environmental perturbations (4,(7)(8)(9)(10)(11) and provide insight into the response of landscapes to future environmental change (12,13). ...
... A fundamental response of a STS to these perturbations is a variation in the generation of sediment supplied to the STS and transmitted down system as an environmental signal (4,7). These environmental sediment flux signals can generate geomorphic and stratigraphic signatures that allow for the reconstruction of past environmental perturbations (4,(7)(8)(9)(10)(11) and provide insight into the response of landscapes to future environmental change (12,13). ...
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Autogenic processes contribute noise to sediment transport systems that can degrade or mask externally derived environmental signals and hinder our ability to reconstruct past environmental signals from landscapes and strata. To explore this further, we measure efflux from a physical rice pile to ascertain the temporal structure of autogenic noise, and how this influences the degradation and detection of environmental signals. Our results reveal a tripartite temporal spectral structure segmented at two key autogenic time scales. The shorter autogen-ic time scale set limits on environmental signal degradation, while the longer autogenic time scale sets limits on environmental signal detection. This work establishes a framework that can be used to explore how autogenic processes interact with external environmental signals in field-scale systems to influence their detectability. We anticipate that the temporal structure and associated time scales identified will arise from autogenic processes in numerous sediment transport systems.
... Morphodynamic filtering of downstream sediment transport signals can occur to different degrees, including (a) dampening when the signal amplitude is scaled down but the amplitude-frequency dependence remains; (b) delaying which may or may not accompany dampening but where there is a shift in phase; and (c) shredding where the amplitude-frequency dependence is partially or completely destroyed (Straub et al., 2020). Understanding the extent to which there is filtering and the distance over which it occurs is important for several disciplines. ...
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Plain Language Summary Alpine glaciers have been retreating at increasing rates since the early 20th century due to the current climate warming. As a consequence, new, powerful and rapidly changing rivers have developed in the newly emerged terrain in front of shrinking glaciers (i.e., proglacial forefields). These environments are known to be among the most rapidly changing landscapes on Earth. In this study we present the first combined high frequency quantitative data on sediment export from an Alpine glacier for two melt seasons with very different climatic conditions. Results show that the low potential transport distances of particles traveling on the river bed together with the continuously changing shape of these streams, rapidly modify the glacier‐dictated export signal (i.e., subglacial sediment evacuation rates in time). For sediment transported in suspension in the river, that loss of information is less evident. These findings are important for the understanding of how much, when, and which kind of sediment are delivered to the populated places downstream in the valleys, in order to mitigate natural hazards, but also for sediment management in hydropower plants and ecological succession in the context of rapid glacier retreat. The results are also key to improving estimation of glacial erosion rates.