Elsevier

Ecological Modelling

Volume 355, 10 July 2017, Pages 24-38
Ecological Modelling

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

https://doi.org/10.1016/j.ecolmodel.2017.03.022Get rights and content

Highlights

  • Reach-scale ecohydraulic models were combined with a population model to evaluate the benefits of habitat scenarios for a threatened fish population.

  • Scenarios involved reducing water temperatures via riparian restoration and increasing complexity of habitat via wood addition.

  • The population-level benefits of cooler water temperatures exceeded those due to wood addition.

  • This work highlights the value of integrating across habitat and population modelling disciplines.

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. 100–600 m 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.

Introduction

Efforts to recover threatened and endangered species often rely on models to identify management strategies that will improve the status of at-risk populations (Good et al., 2007, Sweka and Wainwright, 2014). Fundamental to this work is the task of building models that are structurally or numerically consistent with the spatial and temporal scales of relevant biological processes and management actions (Green et al., 2005). For species like Pacific salmon and steelhead (Oncorhynchus spp.), this task is especially challenging given that they respond to factors operating at widely varying spatial and temporal scales. For example, the foraging success, growth, and survival of individuals can be influenced by conditions within small (10–100 m2) patches of stream habitat (e.g., Rosenfeld and Taylor, 2009), yet a river’s overall capacity to produce juvenile fish may be set by habitat limitation for another life stage that is governed by broader-scale geomorphic controls (e.g., spawning gravel availability, Buffington et al., 2004, Palm et al., 2007). Similarly, global climatic phenomena (e.g., El Niño Southern Oscillation) can affect the survival of salmon during marine life stages (e.g., Sharma et al., 2013) to an extent that makes it difficult to detect the effects of factors operating during freshwater stages (e.g., Schaller et al., 2013). Accordingly, there is a need for modelling approaches that can accurately depict complex life histories and simultaneously maximize the realism of species–environment relationships for life stages targeted by management and restoration.

The need for such tools is particularly acute in the Columbia River Basin, home to a large-scale, long-term, and costly stream restoration program that was developed to recover salmon and steelhead populations through spawning and rearing habitat improvements and barrier removal (Leonard et al., 2015). Although restoration comes in many forms, the general goal of most projects is to increase the quality or quantity of habitats that are believed to limit particular life stages and overall population abundance (Barnas et al., 2015). In our study region, ongoing restoration aims to improve in-stream habitat complexity and water quality (e.g., cooler summer temperatures), among other conditions, based on a combination of riparian restoration and woody structure placement projects (Rine et al., 2016). To support prioritization of specific restoration activities, regional panels have identified restoration projects that are expected to confer the greatest demographic benefits to populations (e.g., Booth et al., 2016). However, at least two key uncertainties must be addressed before this question can be reliably answered. Firstly, candidate restoration projects must be translated into an expected habitat change (e.g., reduced fine sediment levels or cooler summer temperatures, Bartz et al., 2006, Jorgensen et al., 2009) and associated fish response (e.g., an increase in freshwater survival, Honea et al., 2009). Secondly, because the benefits of specific restoration projects are often localized in nature, these reach-scale expectations must be upscaled to the basin/population level so that their overall value can be assessed (Wheaton et al., In Press). If such uncertainties can be addressed quantitatively, then the long-term population-level benefits of restoration alternatives can be assessed using a life-cycle modelling approach.

Despite a rich history of life-cycle model (LCM) applications to salmon recovery-related questions (see Good et al., 2007 for a recent review), previous attempts to link habitat restoration scenarios with future population performance have met with limited success. For example, studies have modelled population responses to hypothetical survival increases assumed to be achievable through habitat restoration, but without explicit consideration of current conditions or restoration feasibility (e.g., Kareiva et al., 2000). More recent assessments have integrated habitat–survival relationships and basin-specific habitat condition into modelling (e.g., Honea et al., 2009, McHugh et al., 2004, Scheuerell et al., 2006), assessed restoration potential based on relationships between watershed condition and in-stream habitat metrics (e.g., Bartz et al., 2006, Jorgensen et al., 2009, Sharma et al., 2005), or increased the spatial resolution of LCMs (Scheuerell et al., 2006). The realism of LCMs has thus improved greatly, yet these tools continue to inform restoration practice at a coarse level and in the absence of mechanistic insight on fish–habitat associations. Thus, approaches that integrate LCMs with reach-level habitat observations and restoration plans are needed.

Recent advances in fish-habitat monitoring and modelling within the Columbia River Basin have made it possible to integrate biological responses and habitat condition at scales relevant to individual restoration projects. Specifically, the Columbia Habitat Monitoring Program, initiated in 2011, has collected the data necessary to parameterize hydraulic, drift-foraging, and habitat suitability models at several hundred survey sites (i.e., ca. 100–600 m long stream reaches) across the region (Wheaton et al., In Press). Using the Middle Fork John Day River (MFJD) as a test case, here we demonstrate a modelling framework that (1) leverages these data to estimate reach-level juvenile rearing and adult spawning capacity as a function of physical habitat, (2) upscales these reach predictions using larger scale basin data (e.g. GIS, remote sensing) to provide an estimate of population or basin total carrying capacity for key life stages, and (3) uses these values, along with other demographic data for the target population, in a LCM context to quantify the current status of the basin’s threatened steelhead (O. mykiss) population. We apply this framework retrospectively for validation purposes, then prospectively to assess the potential benefits of two commonly pursued restoration approaches; one that aims to enhance rearing capacity and survival for juveniles by providing cooler summer temperatures (ODEQ, 2010) and another that aims to increase juvenile carrying capacity through increased structural/hydraulic complexity of select reaches (via large wood addition; Li et al., 2016). Our objectives are two-fold: (1) to describe the modelling approach, which is sufficiently flexible for other applications in which similar data exist (note, our description here is brief, but we provide complete details in a companion supplement); (2) to apply it to a specific case and interpret our findings relative to the population’s conservation status. Additionally, in pursuit of these objectives, we demonstrate a practical approach for upscaling reach-level mechanistic models to inform population-level assessments.

Section snippets

Study system and model population

The Middle Fork John Day River drains the highlands of north central Oregon and is a primary tributary to the John Day River (Fig. 1). Its basin is moderate in size (ca. 2100 km2; average base flow 7.2 m3 s−1 [gauging station at rkm 24]) and spans habitats ranging from near-alpine at its crest (ca. 2200 m) to sagebrush steppe near its confluence with the North Fork John Day River (ca. 650 m) (O'Brien et al., In Review). The climate of the MFJD basin is semi-arid, characterized by cool, wet winters

Baseline scenario validation and results

The base (SQ) LCM parameterization, informed by a combination of published and unpublished data synthesis, original analysis, and network extrapolation results (Fig. 3, Appendices A & B in Supplementary Material), produced abundance dynamics consistent with recent sampling observations for MFJD steelhead. Escapement from baseline simulations ranged from 489 to 5482 whereas sampling estimates ranged from 811 to 5859 (Fig. 5). Total life cycle productivity (spawner-to-spawner) values computed

Discussion

Our analysis offers three insights of relevance to the management of habitat for steelhead within the Middle Fork John Day River basin. Firstly, based on an independent analysis and using a different set of criteria (i.e., IUCN, 2016), our status quo simulation results corroborate recent assessments (e.g., Ford, 2011) concluding that the MFJD steelhead population continues to warrant conservation attention. For example, although simulated escapements often met recovery targets, quasi-extinction

Acknowledgements

This work was funded by the Bonneville Power Administration (BPA) as part of the Integrated Status and Effectiveness Monitoring Program (BPA project # 2013-017-00) and the Columbia Habitat Monitoring Program (BPA project # 2011-006-00) and is the culmination of efforts from many affiliated with these programs, as well as other entities working within the Middle Fork John Day River Basin, including: Chris Beasley, Jody White, and Kevin See (Quantitative Consultants, Inc.); David Byrnes and Joe

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