Geology topics
James T. Peterson
Publications and source records attributed to James T. Peterson.
Imperfect detection and misidentification affect inferences from data informing water operation decisions
Objective Managers can modify river flow regimes using fish monitoring data to minimize impacts from water management infrastructure. For example, operation of the gate-controlled Delta Cross Channel (DCC) in California can negatively affect the endangered Sacramento River winter-run Chinook Salmon Oncorhynchus tshawytscha . Although guidelines have been developed for DCC operations by using real-time juvenile fish sampling count data, there is uncertainty about how environmental conditions influence fish occupancy and the extent to which those relationships are affected by sampling and identification error. Methods We evaluated the effect of environmental conditions, imperfect detection, and misidentification error on salmon occupancy by analyzing data using hierarchical multistate occupancy models. A total of 14,147 trawl tows and beach seine hauls were conducted on 1058 sampling days between October and December from 1996 to 2019. During these surveys, 2803 juvenile winter-run Chinook Salmon were identified, and approximately 29% of the sampling days had at least one winter-run juvenile detected. Result The probability of misidentifying an individual juvenile winter-run Chinook Salmon in the field was estimated to be 0.056 based on fish identification examinations and genetic sampling. Occupancy varied considerably and was related to flow characteristics, water clarity, weather, time of year, and whether occupancy was detected during the previous sampling day. However, these relationships and their significance changed considerably when accounting for imperfect detection and the probability of misidentifying individual juvenile salmon. Detection was <0.3 under average sampling conditions during a single sample and was influenced by flow, water clarity, site, and volume sampled. Conclusion Our modeling results indicate that DCC gate closure decisions could occur on fewer days when imperfect detection and misidentification error are not accounted for. These findings demonstrate the need to account for identification and detection error while using monitoring data to assess factors influencing fish occupancy and inform future management decisions.
Intestinal lesions and parasites associated with senescence and prespawn mortality in Chinook Salmon (Oncorhynchus tshawytscha)
Prespawn mortality (PSM) presents a major problem for the recovery of spring Chinook Salmon ( Oncorhynchus tshawytscha ) populations. In the Willamette River, Oregon, PSM exceeds 90% in some years but factors explaining it are not well understood. We examined intestinal tissue samples using histological slides from over 783 spring Chinook Salmon collected between 2009 and 2021, which included tissues from PSM fish, artificially spawned captive broodstock (BS) and normal river run fish, comprised of trapped (Live) and naturally post-spawned river (RPS) fish collected from the river. We observed degeneration of the intestinal epithelium and loss of villous structure, with concurrent severe enteritis. A natural progression of decline in epithelial integrity (EI) through the summer and fall until spawning and subsequent death was also observed. Live fish exhibited high EI scores (mean = 68%), BS exhibited variable EI scores (35%) and RPS exhibited severe loss of EI (14%). PSM fish exhibited prominent loss of intestinal epithelium with EI scores (13%), very similar to RPS fish, despite having been collected earlier in the year. Hence, we argue that low EI scores are strongly linked with PSM. Ceratonova shasta and Enterocytozoon schreckii were common in all groups, but neither were linked to either PSM or a decline in EI.
Gut microbiome composition associates with corticosteroid treatment, morbidity, and senescence in Chinook salmon (Oncorhynchus tshawytscha)
Pacific salmon experience prolonged elevation in corticosteroid hormones during important life history events including migration, reproduction, and senescence. These periods of elevated corticosteroids correspond with changes to immunity and energy metabolism; therefore, fish may be particularly vulnerable to mortality at these times. Recent studies found that stress-induced cortisol release associated with microbial community shifts in salmonids, raising the question of how longer-term corticosteroid dynamics that accompany life history transitions affect salmonid microbiomes. In this work, we experimentally evaluated the relationships between gut microbiome composition, chronically elevated corticosteroids, and mortality in juvenile Chinook salmon ( Oncorhynchus tshawytscha) . We found that treatment with slow-release implants of the corticosteroids cortisol or dexamethasone resulted in persistent changes to the gut microbiome. Morbidity was also associated with microbiome composition, suggesting that the gut microbiome reflects individual differences in susceptibility to opportunistic pathogens. Additionally, we analyzed a small number of samples from adult fish at various stages of senescence. Results from these samples suggest that microbiome composition associated with gut integrity, and that the microbial communities of corticosteroid treated juveniles shift in composition toward those of senescent adults. Overall, findings from this work suggest that the gut microbiome associates with mortality risk during periods of chronic corticosteroid elevation.
Evaluating the institutional and ecological effects of invasive species prevention policy: A case study from the U.S. Fish and Wildlife Service
Wildlife and natural resource institutions play key roles in invasive species monitoring and management. Paradoxically, the extensive fieldwork undertaken by these institutions and their partners may result in the inadvertent movement and spread of invasive species within and between sensitive ecosystems. In this work, we consider the potential effects of internal guidelines and policies designed to prevent the spread of invasive species by the field activities of management institutions and their partners. Such policies could be high-leverage tools for invasive species prevention, however, as large, complex organizations seek to implement policies to limit the spread of invasive species, it may be challenging to accommodate the wide diversity of potential invasion pathways and mitigation efforts facilitated via the programs, activities, and ecosystems they manage. Prevention policies may also be met with resistance due to the costs of implementation unless concrete benefits can be demonstrated. Assessing and communicating the effects of prevention policies could motivate improved implementation and adherence by institutional units and partners and could help inform adaptive policy changes. However, assessing the effectiveness of invasive species prevention presents a unique set of challenges, including incomplete data on invasive species distribution and pathways, that make it difficult to measure the effects of prevention efforts. In this work, we present a conceptual framework for evaluating institutional policies for invasive species prevention. We describe a flexible, multifaceted approach that considers policy implementation and adherence as well as ecological outcomes. We discuss potential application of this framework using a policy recently implemented by the Pacific Region of the U.S. Fish and Wildlife Service to prevent the introduction and spread of invasive species by service personnel and partners during field activities as a case study.
A comprehensive multi-state conditional occupancy model for evaluating interactions of non-native and native species
A major challenge in ecology is disentangling interactions of non-native, potentially invasive species on native species. Conditional two-species occupancy models examine the effects of dominant species (e.g., non-native) on subordinate species (e.g., native) while considering the possibility that occupancy of one species may affect occupancy and/ or detection of the other. Although conditional two-species models are useful for evaluating the influence of one species on presence of another, it is possible that species interactions are density dependent. Therefore, we developed a novel two-species occupancy model that incorporates multiple abundance states (i.e., absent, present, abundant) of the native species. We showcase the utility of this model with a case study that incorporates random effects and covariates on both occupancy and detection to help disentangle species interactions given varying occupancy and detection in different abundance states. We use snorkel survey data from the Umpqua basin, Oregon, where it is hypothesized that smallmouth bass Micropterus dolomieu , a non-native piscivore, exclude Umpqua chub Oregonichthys kalawatseti , a small endemic minnow. From our two-species multi-state (2SMS) model, we concluded that average occupancy was low for both fishes, and that when non-native bass were present, overall native chub occupancy in the present (0.18 ± 0.05 SD) and abundant (0.19 ± 0.03) states was higher than when non-natives were absent (0.14 ± 0.02/ 0.08 ± 0.02), indicating the non-native was not excluding the native species. By incorporating a species interaction factor, we found a positive association (6.75 ± 5.54 SD) between native chub and non-native bass. The covariates strongly related to occupancy were elevation, algae, and land cover type (urban and shrub). Detection probability for both species (0.21–0.82) was most strongly related to the covariates day of year, water temperature, gravel substrate, and stream order/ magnitude. Incorporation of detection probability and covariates enabled interpretation of interactions between the two species that may have been missed without their inclusion in the modeling process. Our new 2SMS occupancy model can be used by scientists and managers with a broad range of survey and covariate data to disentangle species interactions problems to help them inform management decisions.
An evaluation of multistate occupancy models for estimating relative abundance and population trends
Detecting spatiotemporal changes in the abundances of organisms is key to effectively conserving species. While indices of abundance have long been used, there has been a shift toward model-based estimators that account for the detection process. Popular approaches including traditional occupancy models and N-mixture models entail tradeoffs. The traditional occupancy approach requires the researcher coarsen the characterization of abundance to the probability that a site is occupied or unoccupied. Conversely, N-mixture models make use of variation in counts, but perform poorly when individuals have low detectability or move into or out of sites between visits. Multistate occupancy models that differentiate relatively abundant from non-abundant states have the potential to fill this gap but have been underexplored. We conducted a simulation study to test whether multistate occupancy models could capture spatial abundance patterns and detect population declines in the face of low individual detection probability ( p ≤ 0.3) and unmodeled heterogeneity (e.g., that arising from individual movement). We considered 10,773 scenarios to examine the effects of differing amounts of heterogeneity as well as alternative study designs, population parameters, and modeling choices. We tracked bias in the proportion of sites estimated to be in the abundant state for single-season models, and power to detect a declining trend across multiple years. We also evaluated data diagnostic metrics to provide guidance to users. Multistate occupancy models were able to differentiate sites with higher abundances from sites with lower abundances when there were at least medium levels of spatial heterogeneity in true abundances. If different sites were randomly selected each year, power to detect even large population declines (65%) was poor (power < 0.8). However, if the same sites were surveyed each year, and a dynamic multistate occupancy was used, multistate occupancy models could detect (power ≥ 0.8) relatively small declines (5-40%) in 20% of scenarios, and frequently detect large declines of 45-60% (mean power = 0.92). Conservation decisions rely on detecting change reliably, rarely needing absolute abundance information. Multistate occupancy models can improve our ability to detect changing abundance while accommodating low individual detection probability and heterogeneity in count monitoring data.
Scope of the cortisol stress response in Chinook salmon during maturation
In semelparous Pacific salmon, increased cortisol levels accompany sexual maturation and may be related to the rapid senescence and death that occur after spawning. In fish with extremely high cortisol, pre-spawning mortality is more likely. This may be because elevated cortisol is accompanied by energy depletion and reduces the immune capacity of sexually maturing individuals, thus increasing their susceptibility to parasites and pathogens. Several studies have measured cortisol levels in Pacific salmon during the last few weeks prior to spawning, but there is a lack of information regarding longer-term changes in resting and stressed cortisol levels of migrating adult Pacific salmon. A better understanding of the scope of the cortisol response during sexual maturation could contribute to understanding the extremely high pre-spawning mortality experienced by some threatened populations of Pacific salmon. The objective of this study was to determine the scope of the cortisol stress response in spring Chinook salmon as well as the dynamics of resting cortisol during maturation. We conducted a laboratory experiment in which plasma cortisol in adult Chinook salmon was measured before and after application of a standardized stressor applied at monthly intervals during the last three months prior to spawning. We found that resting and stressed cortisol levels increased during the last three months prior to spawning. We also found that sexually maturing Chinook salmon are able to mount a cortisol response to acute stressors when resting levels are elevated during maturation. Additionally, the effects of stress and time on cortisol dynamics differed between males and females as well as between individuals, which has implications for population resilience to anthropogenic stressors in wild populations.
Progression of infection and detection of Pseudoloma neurophilia in zebrafish Danio rerio Hamilton by PCR and histology
Pseudoloma neurophilia is a critical threat to the zebrafish ( Danio rerio ) model, as it is the most common infectious agent found in research facilities. In this study, our objectives were two-fold: (1) compare the application of diagnostic tools for P. neurophilia and (2) track the progression of infection using PCR and histology. The first experiment showed that whole-body analysis by qPCR (WB-qPCR) can be a standardized process, providing a streamlined diagnostic protocol, without the need for extraction of specific tissues. Evaluating the course of infection in experimentally infected fish, we showed key dynamics in infection. Starting with a low dose exposure of 8000 spores/fish, the prevalence remained low until 92 days post-exposure (dpe), followed by a 30%–40% prevalence by histology or 40%–90% by PCR until the end of the experiment at 334 dpe. WB-qPCR positively detected infection in more fish than histology throughout the study, as WB-qPCR detected the parasite as early as 4 dpe, whereas it was undetected by histology until 92 dpe. We also added a second slide for histologic analyses, showing an increase in detection rate from 24% to 26% when we combined all data from our experiments, but this increase was not statistically significant.
Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon
The Willamette River, Oregon, is home to two salmonid species listed as threatened under the Endangered Species Act, Upper WIllamette River spring Chinook salmon ( Oncorhynchus tshawytscha ) and Upper Willamette River winter steelhead ( O. mykiss ). Streamflow in the Willamette River is regulated by upstream dams, 13 of which are operated by the U.S. Army Corps of Engineers (USACE) as part of the Willamette Valley Project. In 2008, these dams were determined to have a deleterious effect on Endangered Species Act-listed salmonids, resulting in USACE taking actions to mitigate those effects. Mitigation actions included setting seasonal streamflow targets at various locations along the river to improve survival and migration of juvenile salmonids. Although these targets were established with the best available information at the time, recent data and models have advanced understanding of Willamette River bathymetric, hydraulic, and thermal conditions, allowing for a more robust analysis of the effect of streamflow on downstream habitat. This study integrates those recent advances to build high-resolution models of usable habitat for juvenile Chinook salmon and steelhead to assess variation in spatial and seasonal patterns of habitat availability. Specifically, this study develops detailed maps of habitat availability for juvenile Chinook salmon and steelhead for two size classes (fry and pre-smolt). Habitat availability is modeled in a three-step process whereby (1) two-dimensional hydraulic models are paired with literature-supplied data on habitat preferences to create spatially explicit maps of rearing habitats for a wide range of streamflows; (2) reach-specific relations between streamflow and habitat area are developed and paired with streamgage records to create habitat time series for 2011, 2015, and 2016, which reflect “cool and wet,” “hot and dry,” and “warm but average precipitation” conditions, respectively; (3) temperature models are coupled with literature-based thermal thresholds to determine time periods and locations along the river corridor when rearing habitat has optimal, harmful, or lethal temperature conditions; (4) finally, habitat availability is summarized at several spatial scales to characterize longitudinal and seasonal patterns. Findings show that modeled area of rearing habitat for Chinook salmon and steelhead responds non-uniformly to streamflow, where habitat in some reaches of the Willamette River consistently increase with additional streamflow, while in other reaches, habitat area decreases when streamflows increase from low to moderate flows. Modeled differences in flow-habitat relations are primarily explained by local geomorphology in each reach and resulting hydraulic conditions that arise with different streamflows. These are most pronounced when comparing laterally active, multi-channel reaches upstream from Corvallis with downstream reaches that are laterally stable with single-channel planforms. The reaches upstream from Corvallis generally have more habitat available per unit stream distance than downstream reaches, but all reaches display greatest amounts of habitat at the highest streamflows. Finally, results show that warm water temperature in summer greatly decreases the utility of habitat available to the focal species, particularly downstream from Corvallis. Together, these findings serve to inform flow management by characterizing spatial and seasonal patterns of habitat availability for juvenile spring Chinook salmon and winter steelhead and provide a quantitative assessment of the effects of streamflow on rearing habitat.
Phenomenological and mechanistic modeling of recreational angling behavior using creel data
Improved understanding of angling behavior in recreational fisheries can help managers account for partial controllability in systems in which angling effort is not directly regulated. Relevant aspects of angling behavior include fishing participation, site choice, and catch-and-release actions and can be considered at scales of both aggregate fishing effort and individual-decision-making. Using creel survey data collected across eight fishery seasons, we predicted aggregate angling effort (e.g., daily number of boating trips engaged in fishing) and characterized influences of individual trip-based site choice for recreational fisheries acting on fall-run Chinook salmon and coho salmon near the mouth of the Columbia River, United States of America. We applied an overdispersed Poisson likelihood-based generalized linear model with an autoregressive structure to aggregate boating effort and a multinomial logit model to trip-based site choice decisions among separate ocean and estuary fishing zones. Predictive models explained 71% and 79% of out-of-sample and in-sample variability in aggregate effort, respectively, and included the covariates weekend status, Chinook salmon catch rate, tidal range, and pre-season expectations of fish abundance. In addition to reinforcing the importance of Chinook salmon catch rate and tidal range, site choice model selection revealed influences of weather, fishery restrictions, expected fishery season lengths, and the individual-specific characteristics of boat length and guide status on decision-making. Model results provide predictive models for short-term fishery planning, highlight heterogeneity in individual decision-making, and illustrate the value of standardized creel data for evaluating angling behavior.
Integrating monitoring and optimization modeling to inform flow decisions for Chinook salmon smolts
Monitoring is usually among the first actions taken to help inform recovery planning for declining species, but these data are rarely used formally to inform conservation decision making. For example, Central Valley Chinook salmon were once abundant, but anthropogenic activities have led to widespread habitat loss and degradation resulting in significant population declines. Monitoring data suggest survival through the southern Sacramento-San Joaquin River Delta, in particular, may be a limiting factor for juvenile Chinook salmon outmigrating from the San Joaquin River and its tributaries. However, survival and routing monitoring data have not been formally used to inform water management in a decision analytic framework. Here, we illustrate how estimates derived from disjunct monitoring data can be used to inform water management and as a basis for adaptively managing flows. We aggregated a meta-analysis of Chinook salmon smolt survival and routing estimates through the south Delta with other sources of data to develop a survival and routing simulation model to estimate optimal flows for the San Joaquin River during smolt outmigration from February–May. We found that large flow pulses at predictable times during the spring are projected to be optimal for increasing Chinook salmon smolt survival to the San Francisco Bay and that optimal scenarios differed somewhat with water year type. Sensitivity analysis revealed temperature and smolt outmigration timing are driving optimal pulse distribution and that water allocation changes little with parameter uncertainty. This case study highlights the utility of the decision-analytic framework for solving conservation problems.
Integrated tools for identifying optimal flow regimes and evaluating alternative minimum flows for recovering at-risk salmonids in a highly managed system
Water resource managers are faced with difficult decisions on how to satisfy human water needs while maintaining or restoring riverine ecosystems. Decision sciences have developed approaches and tools that can be used to break down difficult water management decisions into their component parts. An essential aspect of these approaches is the use of quantitative models to evaluate alternative management strategies. Here, we describe four integrated decision support models for evaluating the effect of flows on two life history stages of Chinook salmon ( Oncorhynchus tshawytscha ) and Steelhead ( O. mykiss ). We then use constrained nonlinear optimization to identify optimal flow regimes for the water year type with the least available water. These flow regimes were then used by managers to develop candidate minimum flow strategies that were evaluated using forward simulation and sensitivity analyses. We found that optimal flow regimes differed markedly from existing regulations and varied among species and life history stages. However, evaluation of tradeoffs among the four competing objectives indicated relatively minimal losses for most objectives when the optimal flows were based on equally weighting the objectives. Sensitivity analysis indicated that water temperature was the primary driver of estimated outcomes and suggested that managers consider alternative means of managing temperatures. Decision sciences have created multiple analytical tools and approaches that simplify complex problems, such as water resource management, and we believe that water resource management would benefit from their increased use.
Space-for-time is not necessarily a substitution when monitoring the distribution of pelagic fishes in the San Francisco Bay-Delta
Occupancy models are often used to analyze long-term monitoring data to better understand how and why species redistribute across dynamic landscapes while accounting for incomplete capture. However, this approach requires replicate detection/non-detection data at a sample unit and many long-term monitoring programs lack temporal replicate surveys. In such cases, it has been suggested that surveying subunits within a larger sample unit may be an efficient substitution (i.e., space-for-time substitution). Still, the efficacy of fitting occupancy models using a space-for-time substitution has not been fully explored and is likely context dependent. Herein, we fit occupancy models to Delta Smelt ( Hypomesus transpacificus ) and Longfin Smelt ( Spirinchus thaleichthys ) catch data collected by two different monitoring programs that use the same sampling gear in the San Francisco Bay-Delta, USA. We demonstrate how our inferences concerning the distribution of these species changes when using a space-for-time substitution. Specifically, we found the probability that a sample unit was occupied was much greater when using a space-for-time substitution, presumably due to the change in the spatial scale of our inferences. Furthermore, we observed that as the spatial scale of our inferences increased, our ability to detect environmental effects on system dynamics was obscured, which we suspect is related to the tradeoffs associated with spatial grain and extent. Overall, our findings highlight the importance of considering how the unique characteristics of monitoring programs influences inferences, which has broad implications for how to appropriately leverage existing long-term monitoring data to understand the distribution of species.
Laboratory infection rates and associated mortality of juvenile Chinook Salmon (Oncorhynchus tshawytscha) from parasitic copepod (Salmincola californiensis)
Pacific salmon ( Oncorhynchus spp.) rearing in lakes and reservoirs above dams have been known to become heavily infected with an ectoparasitic copepod ( Salmincola californiensis ). Little is known about the factors that affect the parasite infection prevalence and intensity. However, previous research suggests that the parasite may negatively affect the fitness and survival of the host fish. The effect of water temperature, confinement and the density of the free-swimming infectious stage of S. californiensis , the copepodid, on infection prevalence and intensity was evaluated by experimentally exposing juvenile Chinook Salmon ( O. tshawytscha ). Infection rates observed in wild populations were achieved under warm water (15–16°C) and high copepodid density (150–300/L) treatment conditions. Infection prevalence and intensity were also significantly higher in larger fish. During the infection experiment, 4.5% of infected fish died within 54 days with mortality significantly related to copepod infection intensity. The potential for autoinfection was compared to cross-infection by cohabitation of infected fish with naïve fish. Previously infected fish had significantly greater infection intensity compared with naïve fish, indicating that infected fish can be reinfected and that they may be more susceptible than naïve fish.
Rapid phenotypic stock identification of Chinook Salmon in recreational fishery management
Rapid phenotypic stock identification in mixed-stock fisheries can provide a useful alternative to more time-intensive methods (e.g., coded wire tags, genetics) in assessing harvest and informing management decisions. We leveraged local ecological knowledge, existing stock identification methods, and understanding of life history differences to develop rapid stock identification tools for fall-run Chinook Salmon Oncorhynchus tshawytscha encountered in the Buoy 10 recreational fishery at the mouth of the Columbia River. Specifically, we sought to differentiate between the fishery’s two dominant genetic lineages: lower river tules and upriver brights. We sampled recreationally landed Chinook Salmon in 2017, 2018, and 2019, assigned sampled individuals to functional reporting groups using a single-nucleotide-polymorphism-based genetic baseline, and collected measurements on phenotypic traits. Using traits including pigmentation patterns (e.g., spotting), fin morphology, characteristics indicative of sexual maturity, and muscle lipid content, random forest classification models provided consistently high classification success across and within genetic groups (i.e., up to 90%). Classification success remained consistent over time within fishery seasons and between years but showed meaningful bias between sexes. Based on observed classification success, we developed and evaluated a categorical visual identification guide capable of facilitating more rapid trait observations and on-site stock identification. The resulting classification key, built using classification trees and visual guide observations from 2019, achieved slightly lower classification success across and within genetic groups and had variable success among samplers. Compared with the existing use of coded wire tags in harvest assessment, phenotypic stock identification methods can provide more rapid and more numerous assignments, albeit with a greater degree of individual assignment error. Applied as a complement to standard methods like coded wire tags, the use of rapid phenotypic stock identification methods offers the potential for increased overall precision and timeliness in harvest assessments.
Application of genetic stock identification and parentage-based tagging in a mixed-stock recreational chinook salmon fishery
Genetic methods can guide and improve the management of recreational mixed-stock fisheries by informing stock-specific estimates of harvest. We applied genetic stock identification and parentage-based tagging to a recreational Chinook Salmon Oncorhynchus tshawytscha fishery in the Columbia River to illustrate the value of genetic analysis in management. We sampled landed catch in 2017 and 2018, assigned the fish to genetic reporting groups, explored temporal trends in harvest composition within and between seasons, and assessed the accuracy and precision of genetic methods against estimates from conventional tagging methodology. The genetic stock identification and parentage-based tagging produced concordant stock assignments, and the harvest composition estimates were validated with independent data. High assignment rates, relative to expended sampling effort, and precise harvest composition estimates with adequate sample sizes demonstrate that both genetic methods can be complementary, effective tools in advancing harvest assessment and recreational fisheries management. The success of genetic stock identification and parentage-based tagging supports the expanded application of genetics to similar fisheries, potentially alongside existing or emerging assessment methods, and guides future improvements in data collection and analysis.
Decision analysis for greater insights into the development and evaluation of Chinook salmon restoration strategies in California’s Central Valley
Considerable amounts of resources have been invested in ecological restoration projects across the globe to restore ecosystem integrity. Restoration strategies are often diverse and have been met with mixed success. In this paper, we describe the Chinook salmon (Oncorhynchus tshawytscha) decision-support models developed by the Central Valley Project Improvement Act Science Integration Team as part of a larger structured decision making effort aimed at maximizing natural adult production of Chinook salmon in California’s Central Valley, USA. We then describe the decision analytic tools the stakeholder group used to solve the models and explore model results, including stochastic dynamic programming, forward simulation, proportional scoring, relative loss, expected value of perfect information, response profile analyses, and indifference curves. Using these tools, the stakeholder group was able to develop and evaluate restoration strategies for multiple Chinook salmon runs simultaneously, a first for the restoration program. We found that actions targeted at one run were detrimental to others, which was unexpected. Furthermore, information uncovered during this process was used to direct efforts towards targeted research/monitoring to reduce critical uncertainties in salmon demographic rates and make better restoration decisions moving forward. The decision sciences have established a wide range of analytical tools and approaches to simplify complex problems into key components, and we believe the concepts described in this paper are of great interest and can be applied by many restoration practitioners that undoubtedly face similar difficulties when implementing restoration strategies for complex systems.