Interpreting the physical dynamics of ancient environments requires an understanding of how current‐generated sedimentary structures, such as ripples and dunes, are created. Traditional interpretations of these structures are based on experimental flume studies of unconsolidated quartz sand, in which stepwise increases in flow velocity yield a suite of sedimentary structures analogous to those found in the rock record. Yet cyanobacteria, which were excluded from these studies, are pervasive in wet sandy environments and secrete sufficient extracellular polysaccharides to inhibit grain movement and markedly change the conditions under which sedimentary structures form. Here, the results of flume experiments using cyanobacteria‐inoculated quartz sand are reported which demonstrate that microbes strongly influence the behaviour of unconsolidated sand. In medium sand, thin (ca 0·1 to 0·5 mm thick) microbial communities growing at the sediment–water interface can nearly double the flow velocity required to produce the traditional sequence of ripple→dune→plane‐bed lamination bedforms. In some cases, these thin film‐like microbial communities can inhibit the growth of ripples or dunes entirely, and instead bed shear stresses result in flip‐over and rip‐up structures. Thicker (ca≥1 mm thick) microbial mats mediate terracing of erosional edges; they also, foster transport of multi‐grain aggregates and yield a bedform progression consisting of flip‐overs→roll‐ups→rip‐ups of bound sand.

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Summary Tracer studies are a commonly used tool to develop and test Einstein‐type stochastic bedload transport models. The movements of these tracers are controlled by many factors including grain characteristics, hydrologic forcing, and channel morphology. Although the influence of these sediment storage zones related to morphological features (e.g., bars, pools, riffles) have long been observed to “trap” bedload particles in transport, this influence has not been adequately quantified. In this paper we explore the influence of channel morphology on particle travel distances through the development of a Bayesian survival process model. This model simulates particle path length distributions using a location‐specific “trapping probability” parameter (pi), which is estimated using the starting and ending locations of bedload tracers. We test this model using a field tracer study from Halfmoon Creek, Colorado. We find that (1) the model is able to adequately recreate the observed multi‐modal path length distributions, (2) particles tend to accumulate in trapping zones, especially during large floods, and (3) particles entrained near a trapping zone will travel a shorter distance than one that is further away. Particle starting positions can affect path lengths by as much as a factor of two, which we confirm by modelling “starting‐location‐specific” path length probability distributions. This study highlights the importance of considering both tracer locations and channel topography in examinations of field tracer studies. © 2020 John Wiley & Sons, Ltd.

How do gravel bed pool‐riffle streams adjust to changing upstream water and bedload sediment supplies, and what analysis techniques can help to effectively identify how change occurs? Here, we use a mixture of field and experimental data to examine these problems and apply a suite of traditional and novel analysis approaches to highlight dynamics which might otherwise go undetected. Eleven years of monitoring channel morphology in a small forested watershed indicate that pool‐riffles persist through large changes in upstream water and bedload supply and that bed architecture relief is correlated to flow magnitude. A flume experiment consisting of eight runs was conducted to examine the field case in more detail. The experimental design splits the eight runs into four runs of relatively high water and sediment supply and four of relatively low water supply, with no upstream sediment supply. Experimental results corroborate the field‐based measurements of pool‐riffle persistence, which is due to a coupling between downstream width variations, and spatial patterns of flow velocity and bedload transport. More specifically, measurements made during the flume experiments along a prominent pool‐riffle pair indicate that temporal and spatial changes to topography, flow hydraulics, and bed surface sediment texture are more rich and nuanced than existing generalizations offer. For example, clustering analysis completed using self‐organizing maps indicates that sediment sorting between pools and riffles is not simply a binary type response of finer versus coarser described by some characteristic grain size.

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