Substrate requirements of spawning Chinook salmon (<i>Oncorhynchus</i><i> tshawytscha</i>) are dependent on local channel hydraulics

Moir, H. J.; Pasternack, G. B.

doi:10.1002/rra.1292

Cited by 23 publications

(20 citation statements)

References 28 publications

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“…Because our study reaches are narrow (bankfull widths listed in Table ), and redds are rarely observed side by side in the channel (Sean Hayes, personal communication), we treat available spawning habitat as a one‐dimensional problem, ignoring the direct effects of channel width on the distribution of redds. In large channels, where redds are often aligned side by side, perpendicular to the flow (Geist et al, ; Moir and Pasternack, , ), channel width would be a necessary consideration.…”

Section: Methodsmentioning

confidence: 99%

Basin‐scale methods for predicting salmonid spawning habitat via grain size and riffle spacing, tested in a California coastal drainage

Pfeiffer

Finnegan

2016

Earth Surf Processes Landf

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Basin‐scale predictive geomorphic models for river characteristics, particularly grain size, can aid in salmonid habitat identification. However, these basin‐scale methods are largely untested with actual habitat usage data. Here, we develop and test an approach for predicting grain size distributions from high resolution LiDAR (Light Detection and Ranging)‐derived topographic data for a 77 km2 watershed along the central California Coast. This approach improves on previous efforts in that it predicts the full grain size distribution and incorporates an empirically calibrated shear stress partitioning factor. The predicted grain size distributions are used to calculate the fraction of the bed area movable by spawning fish. We then compare the ‘movable fraction’ with 7 years of observed spawning data. We find that predicted movable fraction explains the paucity of spawning in the upper reaches of the study drainage, but does not explain variation along the mainstem. In search of another morphologic characteristic that may help explain the variation within the mainstem, we measure riffle density, a proxy for physical habitat complexity. We find that field surveys of riffle density explain 64% of the variation in spawning in these mainstem reaches, suggesting that within reaches of appropriate sized gravel, spawning density is related to riffle density. Because riffle density varies systematically with channel width, predicting riffle spacing is straightforward with LiDAR data. Taken together, these findings demonstrate the efficacy of basin‐scale spawning habitat predictions made using high‐resolution digital elevation models. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Methodsmentioning

confidence: 99%

Basin‐scale methods for predicting salmonid spawning habitat via grain size and riffle spacing, tested in a California coastal drainage

Pfeiffer

Finnegan

2016

Earth Surf Processes Landf

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“…Numerous habitat modeling studies have been undertaken over time in North America and Europe, first mainly for salmonids (e.g., Northcote 1984;Shirvell 1989;Wollebaek et al 2008;Moir and Pasternack 2010) but later for non-salmonids also (e.g., Melcher and Schmutz 2010). Predominantly these studies applied univariate habitat use and preference curves.…”

Section: Multidimensional Statistical Analyses For Biological Modelingmentioning

confidence: 99%

Aquatic Habitat Modeling in Running Waters

Melcher

Hauer

Zeiringer

2018

Riverine Ecosystem Management

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“…Coverage by movable particles and the spawning capacity of substrates predicted from Equations (4) and (7) are both potentially useful in river management, because they constrain the maximum amount of redd building a substrate can accommodate when fish are spawning en masse, in conditions that are not limited by other factors such as flow velocity and depth (Moir and Pasternack, 2010), and hyporheic flow through redds (Tonina and Buffington, 2009). This is demonstrated in Figure 4 for spawning by three Pacific salmon species across the 31 sites of Riebe et al (2014).…”

Section: Like the Expression In Equationmentioning

confidence: 99%

Tools for gauging the capacity of salmon spawning substrates

Overstreet

Riebe

Wooster

et al. 2015

Earth Surf Processes Landf

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We present a set of river management tools based on a recently developed method for estimating the amount of salmon spawning habitat in coarse-bedded rivers. The method, which was developed from a mechanistic model of redd building by female salmon, combines empirical relationships between fish length, redd area, and the sizes of particles moved by fish during spawning. Model inputs are the grain-size indices D 50 and D 84 and an estimate of female fish length, which is used to predict the size of the redd that they will build and the size of the largest particle that they can move on the bed. Outputs include predictions of the fraction of the bed that the fish can use for redd building and the number of redds that they can build within the useable area. We cast the model into easy-to-use look-up tables, charts, an Excel worksheet, a JavaScript web applet, and a MATLAB user interface. We explain how these tools can be used in a new, mechanistic approach to assessing spawning substrates and optimizing gravel augmentation projects in coarse-bedded rivers.

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Substrate requirements of spawning Chinook salmon (Oncorhynchus tshawytscha) are dependent on local channel hydraulics

Cited by 23 publications

References 28 publications

Basin‐scale methods for predicting salmonid spawning habitat via grain size and riffle spacing, tested in a California coastal drainage

Basin‐scale methods for predicting salmonid spawning habitat via grain size and riffle spacing, tested in a California coastal drainage

Aquatic Habitat Modeling in Running Waters

Tools for gauging the capacity of salmon spawning substrates

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