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Linking models across scales to assess the viability and restoration potential of a threatened population of steelhead (Oncorhynchus mykiss) in the Middle Fork John Day River, Oregon, USA

Author

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  • McHugh, Peter A.
  • Saunders, W. Carl
  • Bouwes, Nicolaas
  • Wall, C. Eric
  • Bangen, Sara
  • Wheaton, Joseph M.
  • Nahorniak, Matthew
  • Ruzycki, James R.
  • Tattam, Ian A.
  • Jordan, Chris E.

Abstract

Species conservation is often informed by the use of models evaluating the effect of different management strategies on the status of at-risk populations. For Pacific salmon and steelhead (Oncorhynchus sp.), which have complex life cycles spanning diverse environments and jurisdictions, life-cycle models (LCMs) have proven particularly useful for this task. Yet, most salmonid LCM applications to date have not been able to tie projections of population performance to specific tributary habitat management actions, which is integral to many recovery plans. Here we describe a modelling framework that links reach-scale stream habitat models with a basin-scale LCM, bridged by statistical extrapolation models, to evaluate recovery opportunities for an imperiled population of steelhead (O. mykiss) in the Middle Fork John Day River, USA. We parameterized a LCM by leveraging results from (1) a large-scale environmental monitoring program that supports ecohydraulic modelling and characterizes habitat quality (with a salmonid emphasis) within individual stream reaches (ca. 100–600m segments), and (2) detailed demographic studies that provide estimates of survival, age structure, fecundity, etc. relevant to the model population. We then applied the model to quantify population performance under current/base (status quo) conditions and under two classes of restoration that aim to increase survival for juvenile steelhead: riparian revegetation, which reduces (otherwise limiting) stream temperatures during the warm summer months; and woody structure addition, which increases in-stream hydraulic complexity and thus juvenile rearing capacity. Status quo simulations produced abundance dynamics consistent with recent population monitoring data and the population’s current threatened status. Our evaluation of these basic restoration scenarios revealed that while both strategies have the potential to improve the conservation status of steelhead, the benefits of woody structure addition were relatively minor compared to those resulting from stream temperature reductions. Together, our findings suggest that in thermally stressed systems the benefits of wood addition will be optimized if (1) structures are added at a considerably higher rate than is often done, focusing on reaches that are not thermally limited initially, and (2) these efforts are paired with extensive riparian planting (i.e., in reaches that have the highest potential for effective shading), which will address thermal limitations (if relevant) and offer a natural source for future wood recruitment. In addition to shedding light on effective strategies for recovering steelhead, our study illustrates the power of coordinated monitoring programs that can parameterize the relationships needed to integrate modelling possibilities across scales.

Suggested Citation

  • McHugh, Peter A. & Saunders, W. Carl & Bouwes, Nicolaas & Wall, C. Eric & Bangen, Sara & Wheaton, Joseph M. & Nahorniak, Matthew & Ruzycki, James R. & Tattam, Ian A. & Jordan, Chris E., 2017. "Linking models across scales to assess the viability and restoration potential of a threatened population of steelhead (Oncorhynchus mykiss) in the Middle Fork John Day River, Oregon, USA," Ecological Modelling, Elsevier, vol. 355(C), pages 24-38.
  • Handle: RePEc:eee:ecomod:v:355:y:2017:i:c:p:24-38
    DOI: 10.1016/j.ecolmodel.2017.03.022
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    References listed on IDEAS

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    1. Hafs, Andrew W. & Harrison, Lee R. & Utz, Ryan M. & Dunne, Thomas, 2014. "Quantifying the role of woody debris in providing bioenergetically favorable habitat for juvenile salmon," Ecological Modelling, Elsevier, vol. 285(C), pages 30-38.
    2. Matthew Nahorniak & David P Larsen & Carol Volk & Chris E Jordan, 2015. "Using Inverse Probability Bootstrap Sampling to Eliminate Sample Induced Bias in Model Based Analysis of Unequal Probability Samples," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-19, June.
    3. Stevens, Don L. & Olsen, Anthony R., 2004. "Spatially Balanced Sampling of Natural Resources," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 262-278, January.
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