Reproductive Potential of Salmon Spawning Substrates Inferred from Grain Size and Fish Length

Abstract:

The river restoration industry spends millions of dollars every year on improving salmon spawning in riverbeds where sediment is too big for fish to move and thus use during redd building. However, few studies have addressed the question of how big is too big in salmon spawning substrates. Hence managers have had little quantitative basis for gauging the amount of spawning habitat in coarse-bedded rivers. Moreover, the scientific framework has remained weak for restoration projects that seek to improve spawning conditions. To overcome these limitations, we developed a physically based, field-calibrated model for the fraction of the bed that is fine-grained enough to support spawning by fish of a given size. Model inputs are fish length and easy-to-measure indices of bed-surface grain size. Model outputs include the number of redds and eggs the substrate can accommodate when flow depth, temperature, and other environmental factors are not limiting. The mechanistic framework of the model captures the biophysical limits on sediment movement and the space limitations on redd building and egg deposition in riverbeds. We explored the parameter space of the model and found a previously unrecognized tradeoff in salmon size: bigger fish can move larger sediment and thus use more riverbed area for spawning; they also tend to have higher fecundity, and so can deposit more eggs per redd; however, because redd area increases with fish length, the number of eggs a substrate can accommodate is highest for moderate-sized fish. One implication of this tradeoff is that differences in grain size may help regulate river-to-river differences in salmon size. Thus, our model suggests that population diversity and, by extension, species resilience are linked to lithologic, geomorphic, and climatic factors that determine grain size in rivers. We cast the model into easy-to-use look-up tables, charts, and computer applications, including a JavaScript app that works on tablets and mobile phones. 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.