Critical Shields values ( τc*) suitable for specific applications are back‐calculated from representative bed load samples in mountain streams and a flow competence/critical flow approach. The general increase of τc50* (for the bed D50 size) as well as τc16* and τc84* (for the bed D16 and D84 sizes) with stream gradient Sx and also the stratification of τc50* by relative flow depth and relative roughness are confirmed. Critical Shields values τc16* are shown to exceed τc50* by about threefold, while those for τc84* are nearly half of τc50*. However, it remains unclear to what extent physical processes or numerical artifacts contribute to determining critical Shields values. Critical bankfull Shields values ( τcbf*) back‐computed from the average largest particles mobile at bankfull flow DBmax,bf approach τc16* at steep gradients and τc84* at low gradients and therefore increase very steeply with Sx. The relation τcbf*=f(Sx) is stratified by bed stability (D50/DBmax,bf) and predictable if bed stability can be field categorized. Noncritical Shields values ( τbf50*) computed from bankfull flow depth and the D50 size differ from τc50* and τcbf*. Only in bankfull mobile streams where D50/DBmax = 1 can τ*cbf, τc50*, and τbf50* be used interchangeably. In highly mobile streams, substituting τcbf* by τbf50* overpredicts the DBmax,bf size by up to fivefold and underpredicts DBmax,bf by the same amount in highly stable streams. A value of 0.03 is appropriate for τcbf* only on low stability beds with Sx ≅ 0.01, but overpredicts DBmax,bf by 30‐fold on highly stable beds with Sx ≅ 0.1. Differences in field and computational methods also affect critical Shields values.

Gravel bedload transport rates were measured at eight study sites in coarse-bedded Rocky Mountain streams using 4-6 bedload traps deployed across the stream width and a 76 by 76 mm opening Helley Smith sampler. Transport rates obtained from bedload traps increased steeply with flow which resulted in steep and well-defined transport rating curves with exponents of 8 to 16. Gravel transport rates measured by the HelleySmith sampler started with much higher transport rates during low flows and increased less steeply, thus fitted bedload rating curves were less steep with exponents of 2 to 4. Transport rates measured with both samplers approached similar results near or above bankfull flow, but at 50 % of bankfull, transport rates from the bedload traps were 2-4 orders of magnitude lower than those obtained from the Helley-Smith sampler. The maximum bedload particle sizes also differed between the two samplers. They were smaller in the bedload traps than the Helley-Smith sampler at low flows, while at higher flows bedload traps collected larger particles than the Helley-Smith sampler. Differences in sampler opening size and sampling time contribute to the measured differences, but the biggest effect is likely attributable to the bedload traps being mounted on ground plates thus avoiding direct contact between the sampler and the bed and preventing involuntary particle pick up.

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Although the term ``pebble count'' is in widespread use, there is no standardized methodology used for the field application of this procedure. Each pebble count analysis is the product of several methodological choices, any of which are capable of influencing the final result. Because there are virtually countless variations on pebble count protocols, the question of how their results differ when applied to the same study reach is becoming increasingly important. This study compared three pebble count protocols: the reach‐averaged Environmental Monitoring and Assessment Program (EMAP) protocol named after the EMAP developed by the Environmental Protection Agency, the habitat‐unit specific U.S. Forest Service’s PACFISH/INFISH Biological Opinion (PIBO) Effectiveness Monitoring Program protocol, and a data‐intensive method developed by the authors named Sampling Frame and Template (SFT). When applied to the same study reaches, particle‐size distributions varied among the three pebble count protocols because of differences in sample locations within a stream reach and along a transect, in particle selection, and particle‐size determination. The EMAP protocol yielded considerably finer, and the PIBO protocol considerably coarser distributions than the SFT protocol in the pool‐riffle study streams, suggesting that the data cannot be used interchangeably. Approximately half of the difference was due to sampling at different areas within the study reach (i.e., wetted width, riffles, and bankfull width) and at different locations within a transect. The other half was attributed to using different methods for particle selection from the bed, particle‐size determination, and the use of wide, nonstandard size classes. Most of the differences in sampling outcomes could be eliminated by using simple field tools, by collecting a larger sample size, and by systematically sampling the entire bankfull channel and all geomorphic units within the reach.