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The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

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  • Brock M Huntsman
  • Jeffrey A Falke
  • James W Savereide
  • Katrina E Bennett

Abstract

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.

Suggested Citation

  • Brock M Huntsman & Jeffrey A Falke & James W Savereide & Katrina E Bennett, 2017. "The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-21, May.
  • Handle: RePEc:plo:pone00:0177467
    DOI: 10.1371/journal.pone.0177467
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    References listed on IDEAS

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    1. J. Andrew Royle, 2004. "N-Mixture Models for Estimating Population Size from Spatially Replicated Counts," Biometrics, The International Biometric Society, vol. 60(1), pages 108-115, March.
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