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John M. Plumb

Publications and source records attributed to John M. Plumb.

At least 19 recordsLinked to original sources
USGS2026

Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington

Restoration of salmon populations in the upper Lewis River Basin, Washington, depends on a trap-and-haul program owing to the Lewis River Hydroelectric Project (hereinafter referred to as “Project”) operated by PacifiCorp and Cowlitz Public Utilities District (hereinafter referred to as “Utilities”), which has been a barrier to salmon passage since the 1930s. Thus, sustaining the Oncorhynchus kisutch (Walbaum, 1792; coho salmon) population upstream from the Project currently depends on two fundamental factors: (1) the collection of upstream migrating adult coho salmon at Merwin Dam, the lowermost dam within the Project, and transporting them by truck to spawn above Swift Dam, the uppermost dam within the Project; and (2) the collection of out-migrating juvenile coho salmon at the downstream collection facility at Swift Dam for transport and release below the Project. The reintroduction program began once the downstream collection facility at Swift Dam was commissioned in late 2012, with the first year of transport data being collected in 2013. Over the past decade, the Utilities have been collecting data on juvenile outmigrants and adult fish returns at the dams. The need to construct a lifecycle model for Lewis River anadromous fish was identified by the Lewis River Aquatic Technical Subgroup, with the understanding that many years (more than 15 years) of data collection are needed to adequately measure the lifecycle production of salmon. The U.S. Geological Survey was contracted to develop and apply the model to past data at the Lewis River dams to help inform future data collection and provide a framework that can be updated annually to measure trap-and-haul program performance within a lifecycle context. Because coho salmon can live as long as 5 years, estimating demographic parameters for coho salmon populations over their lifecycle requires at least 10 or more years of data collection. Over the past decade, PacifiCorp has been collecting data on fish collection efficiency and the numbers of adult and juvenile salmon transported around the Lewis River dams, making this an ideal time to formulate a lifecycle model that can guide future data collection efforts and provide preliminary information to resource managers. The goal of the statistical lifecycle model is to estimate annual production and survival during two critical life-stage transitions: (1) the freshwater production from escapement of adults released upstream from Swift Dam, and the collection of downstream migrating juveniles at the downstream passage facility at Swift Dam; and (2) the smolt-to-adult survival from the time of collection at Swift Dam to their return as adults. We used the Beverton-Holt stock-recruitment model to estimate juvenile production from the number of spawners (Beverton and Holt, 1957). This approach allowed us to test for density dependence at current spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. Productivity was then expressed as a function of the number of juveniles collected and transported downstream from the Project. Because juvenile fish collection efficiency (FCE) directly affects the number of juveniles that survive to continue downstream migration, FCE is a primary determinant of fish production. Consequently, the modeling framework is well suited to evaluate the performance of trap-and-haul programs within a lifecycle context. The objectives of this study were to (1) gather and collate available data on adult and juvenile coho salmon at Merwin and Swift Dams; (2) quantify adult escapement, juvenile abundance, and the age at outmigration and adult return; (3) describe, formulate and fit the integrated population model to the data; and (4) summarize our findings, identify data gaps, and identify opportunities for future studies that could improve model estimation and inference. Our key findings were: (1) over and above the number of spawning females, FCE was the primary factor affecting productivity of coho salmon above Swift Dam; (2) smolt-to-adult return (SAR) rates were relatively high considering that harvest was included in the estimate, averaging about 4.5 percent and ranging as high as 12.9 percent; and (3) juvenile capacity upstream from Swift Dam was difficult to estimate due to the limited range in spawning females over the time series of data, suggesting the model may be improved by collecting data at higher spawner abundances. In addition, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE=1, was 64 juveniles per spawner. Because the two-stage lifecycle model partitions factors that affect fish production in rivers versus the ocean, the model estimates may help inform fishery managers about the overall role that fish collection at Swift Dam plays in the recovery and sustainability of Lewis River coho salmon. By providing the model with (1) more years of data, (2) higher numbers of spawning females, and (3) data on age at juvenile migration in relation to age at adult return, greater certainty in the estimates of capacity and SAR can be attained. Ultimately, information provided by the model may assist in the evaluation and continued improvement of the current trap-and-haul program to support anadromous fishes in the Lewis River Basin.

Washington↗
USGS2025

Calibration of the Stream Salmonid Simulator (S3) model to estimate annual survival, movement, and food consumption by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the restoration reach of the Trinity River, California, 2006–18

Executive Summary The Trinity River is managed in two sections: (1) from the upper 64-kilometer “restoration reach” downstream from Lewiston Dam to the confluence with the North Fork Trinity River, and (2) the 120-kilometer lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously applied to these reaches and the Klamath River. To estimate fish growth, past S3 calibration efforts in the Trinity and Klamath Rivers used maximum likelihood methods that considered only the abundance of juvenile Chinook salmon ( Oncorhynchus tshawytscha ) passing a fish trap to estimate survival and movement parameters, but not fish consumption. Previous calibrations did not estimate the average proportion of maximum consumption ( C y ) when estimating survival ( S y ) and movement ( M 0 y ) parameters across years ( y ) of data, but because no other information was available in the literature a fixed value of C y =0.66 was assumed. Therefore, the goal of this report is to present an alternative approach that calibrates the S3 model to multivariate data (that is, abundance and size), enabling the estimation of the average proportion of maximum consumption, in conjunction with survival and movement parameters for a particular migration year. We fit the S3 model to individual years of weekly trap abundance estimates and mean fish sizes (fork length) at the Pear Tree Gulch (hereafter referred to as Pear Tree) fish trap representing the restoration reach. We used the Earth Mover’s Distance (EMD) as the objective value to be minimized in parameter optimization. This approach estimated survival, movement, and consumption parameters for each migration year. Because we had information on the abundance of natural and hatchery produced juvenile salmon at the fish traps, we estimated survival and movement for natural and hatchery fish. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile Chinook Salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the restoration reach of the Trinity River was classified into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity time series were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival. We estimated movement, survival, and consumption parameters by calibrating the model to 12 years of weekly juvenile abundance estimates and fish sizes at the Pear Tree fish trap near the downstream end of the restoration reach. We estimated parameters for 12 years that included a wide range of female spawner abundances (1,414–11,494) and water year types (critically dry–extremely wet). We contrast the estimated parameters to the corresponding number of female spawners and the total annual volume of water discharged for the Trinity River (Trinity River Restoration Program; https://www.trrp.net/restoration/flows/summary/ ). The calibration consisted of replicating historical conditions as closely as possible (for example, discharge; temperature; spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location from each brood year of adults and subsequent migration year of their juvenile progeny. Because density-dependent movement was favored in past evaluations, we estimated S3 parameters based on density-independent survival and density-dependent movement. Likewise, each year’s estimated survival parameter for natural ( S N y ) and hatchery ( S H y ) fish may be interpreted as the mean daily survival probability from emergence or hatchery release to the Pear Tree fish trap. Under density dependence, the estimated movement parameter for natural ( M 0N y ) and hatchery ( M 0H y ) fish represents the intercept of the Beverton-Holt model; the probability of remaining in a habitat at near-zero abundance. We estimated C y by using EMD and incorporating abundance and fish size into model calibration. Average daily proportions of maximum consumption, , across the years were generally high (=0.640; standard deviation (SD) SD=0.176), suggesting that fish were feeding at about two-thirds of expected maximum consumption rates. This average proportion of maximum consumption,is very similar to what has been assumed (=0.66) in previous Trinity and Klamath River S3 calibration and simulation efforts. In 2017, we estimated the lowest C y , suggesting lower average consumption for juvenile salmon in high-discharge water years. When this high discharge year was excluded, there was no apparent trend in C y with annual water volume. Estimates of survival showed little trend over the range in spawner abundances, but a trend towards higher natural and hatchery fish survival with higher annual volumes of water was apparent. Over the 12 years, the average survival of hatchery fish was =0.888 (SD=0.079) and the average survival natural fish was=0.969 (SD=0.01). With respect to fish movement, we estimated higher M 0N y and M 0H y with higher annual volumes of water in the Trinity River. Higher M N0 y or M H0 y suggest greater probability of remaining in a habitat at low fish densities, with potential for density-dependent processes in movement to occur. The highest M 0N y = 0.676 was estimated during brood year 2012, and the overall average for natural fish was =0.276 (SD=0.188) and for hatchery fish was=0.467 (SD=0.235). Under the Beverton-Holt model, as M 0N y or M 0H y approach zero, there is less capacity for change in fish movement as fish density increases. The S3 model was initialized with only the spatiotemporal distribution of spawners, so it performed well at capturing the essential outmigration features that are ultimately governed by rates of growth, movement, and mortality. We used a new optimization method that could accommodate multivariate data on abundance and fish size collected at the Pear Tree fish trap, enabling the calibration of S3 to estimate five parameters for 12 separate years of data. Incorporating weekly fish size data for each year in our parameter optimization process made the estimation of C y possible and represents a step forward in the fitting of the S3 model to fish trap data for the purposes of parameter calibration and the estimation of growth parameters with respect to annual conditions. We identified lack of fit and adding important effects into the S3 model may improve the S3 estimation and simulation of water scenarios. The Trinity River Restoration Program (TRRP) Science Advisory Board recommended that the TRRP focus on developing core elements of a decision support system (DSS; Buffington and others, 2014). Toward that end, the habitat and S3 models described in this report are both core elements of the DSS. The structure of S3 makes it a particularly useful fish production model for the DSS because population dynamics are sensitive to (1) water temperature, (2) daily discharge management, and (3) habitat quality and quantity. Each of these variables are key management parameters under consideration in the TRRP. As such, the S3 model may provide valuable insights into the potentially variable effects of different management decisions on the Trinity River.

California↗
USGS2024

Back from the brink: Estimating daily and annual abundance of natural-origin salmon smolts from 30-years of mixed-origin capture-recapture data

Evaluating the status and trends of natural-origin anadromous fish populations over time requires robust estimates of out-migrating juvenile abundance. Information on abundance is typically acquired by capturing actively migrating fish as they pass stationary monitoring platforms. Challenges to estimation include protracted migration timing, temporally varying capture probabilities and the contemporaneous presence of unmarked hatchery-origin fish. The confounding effects of unmarked hatchery fish are especially pernicious in systems hosting multiple hatchery programs with variable mark-rates among releases. Here, we address this problem for a regionally and culturally important population of Chinook salmon ( Oncorhynchus tshawytscha ) supported by a hatchery-supplementation program implemented in response to the listing of this population under the U.S. Endangered Species Act. We developed a model to estimate daily and annual abundance of naturally produced age-0 fall Chinook salmon passing Lower Granite Dam (Snake River, USA) for each of the last 30 years. We accounted for variable hatchery marking rates by integrating two related data sources: 1) release-recapture data of fish with individually identifiable tags and 2) counts of marked and unmarked sample of fish captured each day. We fit joint parameters for daily fish arrival and capture probabilities to these data to estimate the daily abundance of hatchery- and natural-origin fish. Our results show that from 1992 to 2021, the annual abundance of juvenile natural-origin Snake River fall Chinook salmon increased by two orders of magnitude. These results are the first comprehensive evaluation of multi-decadal trends in abundance and run-timing for this population. Our approach can be adapted to other runs and locations within the Columbia River basin or similar systems where out-migrating fish are monitored at fixed locations.

Idaho, Oregon, Washington↗
USGS2024

Hydrologic, water operations, reservoir temperature, river temperature, sediment transport, habitat, and fish population modeling for the Trinity River Water Management Plan

Humboldt County is developing a Water Management Plan that will describe a range of proposed annual releases from Trinity Reservoir consistent with the 1959 water delivery contract between Humboldt County and the U.S. Bureau of Reclamation (Reclamation). The 1959 contract states that Reclamation shall release not less than an annual quantity of 50,000 acre-feet into the Trinity River for the beneficial use of Humboldt County and other downstream users (Contract Water). The Water Management Plan will outline how Contract Water should be released for the benefit of fisheries in the Trinity River and lower Klamath River, with the primary goal of expanding a harvestable surplus of Tribal, recreational, and commercial fisheries. A set of annual Contract Water release scenarios were developed during five workshops conducted in 2022 and 2023 with interested parties including Humboldt County, state and federal resource agencies, tribal representatives, Reclamation, and the U.S. Department of the Interior Solicitor’s office. A suite of modeling and technical tools was used to analyze annual conditions with and without Contract Water releases. This Modeling Report describes the modeling tools used to assess Contract Water release scenarios, including CalSim II, HEC-5Q, RBM10, sediment transport models, Chinook Salmon habitat models, and the Stream Salmonid Simulator. Results from all models are summarized to provide a comparative overview of modeled release scenarios to modeled baseline conditions. Mean annual Contract Water release scenarios ranged from 50,000 acre-feet to 170,000 acre-feet, and varied in timing, magnitude, and duration, though all releases were made between October and April. As shown in Table ES-1, a key finding of this modeling report is Contract Water releases that had the greatest modeled increase in Chinook Salmon abundance relative to baseline conditions included those that released 50,000 acre-feet in the fall period from October through December as pulse flows or baseflows, and those that released 170,000 acre-feet from October through April as a combination of pulse flows and baseflows. Modeled beneficial effects on populations were primarily due to either (1) increases in habitat area during the spawning life stage in October through December, which decreased redd superimposition (e.g., the process of a later arriving spawner building a redd on top of an existing redd) and improved egg survival, or (2) increases in flow during the fry emergence and juvenile rearing life stage in March through April, which increased the fry and parr carrying capacity (e.g., the upper limit for the number of fry or parr that a habitat unit can support) of individual habitat units. Another key finding of this report is all Contract Water scenarios that released at least 50,000 acre-feet annually from Trinity Reservoir had similar effects on Trinity Reservoir storage, Central Valley Project (CVP) storage, CVP contract water deliveries, and Sacramento River water temperatures. Whether these scenarios were released annually as a fall baseflow, fall pulse flow, spring pulse flow, or spring baseflow, they all resulted in similar storage patterns in Trinity Reservoir – an annual reduction in storage relative to the baseline that was relatively small in wetter years and larger in drier years. As a result of lower Trinity Storage levels, Trinity River Division (TRD) exports to the CVP were reduced. Because the timing of exports is similar each year, reaching a peak in July through September, the reduction to exports occurred at the same time each year, independent of Contract Water release timing, resulting in similar storage, CVP delivery, and water temperature effects in the Sacramento River basin portion of the CVP. The water temperature effects on the Sacramento River were limited to the months of July and August, relatively minor, and were primarily attributed to changes in storage, release magnitude, and release temperature from Lake Shasta, and not due explicitly to inflows from the TRD.

California↗
USGS2023

Application of the Stream Salmonid Simulator (S3) model to assess fall Chinook salmon (Oncorhynchus tshawytscha) production in the American River, California

Executive Summary Anadromous fish returning to the lower American River are restricted to 36 kilometers of free-flowing river between Nimbus Dam and American River’s confluence with the Sacramento River, California. Salmon in the American River provide an important freshwater recreational fishery. However, annual salmon production in the American River in recent years has been low relative to the mid-1990s (Surface Water Resources, Inc., 2001). To investigate the low production of fall-run Chinook salmon ( Oncorhynchus tshawytscha ), the Bureau of Reclamation requested that the U.S. Geological Survey apply the Stream Salmonid Simulator (S3) model to the population of fall-run Chinook salmon on the American River. The American River was chosen among seven candidate Sacramento Basin rivers for S3 application. The American River was selected because of its management and public interest, recently low anadromous fish production, and rich time series of key demographic data needed for S3 application. Data that were not available, however, were empirical estimates on juvenile salmon habitat suitability in the American River. Therefore, a large component of applying S3 to the American River was devoted to the estimation of juvenile salmon habitat suitability and capacity. This entailed snorkeling the lower American River for 3 weeks in March 2021 during the early out-migration period for juvenile Chinook salmon. These efforts were fruitful and showed that the typically small fish (<55 millimeters) in the American River preferred much shallower depths than predicted by habitat suitability criteria derived from the literature for this population. Having empirical estimates on juvenile salmon in the American River provided a solid foundation from which to simulate the population using the S3 model. The S3 model is a spatially explicit population model that runs on a daily time step to simulate redd superimposition, egg maturation, fry emergence and the subsequent growth, survival, and emigration of juvenile Chinook salmon from the river. The key features of this model relevant to this report include (1) a temperature-dependent bioenergetics model driving daily growth rates; (2) density-dependent dynamics that are influenced by the effect of flow on suitable habitat area; and (3) within-year habitat, river flow, and water temperature effects specific to spawning, egg incubation, and fry, parr, and smolt life stages. We used estimates of spawning escapement and geo-referenced redd locations to quantify the spatial and temporal distribution of female spawners for brood years 2014–19. These estimates of female spawners initiate the simulation of each year’s juvenile salmon emergence and emigration over a spatial domain extending from Nimbus Dam to the river’s confluence with the Sacramento River. Using weekly estimates of juvenile salmon abundance and size (fork length) that passed the Watt Avenue fish trap (river kilometer 14.7), we calibrated the S3 model by estimating three key demographic parameters for each year, y : (1) S y , the average daily survival probability, (2) M 0y , the intercept for density-dependence in movement, representing the average daily probability of remaining in a habitat at zero abundance, and (3) C y , the average daily proportion of maximum consumption. These parameters were obtained by minimizing the Mallow’s distance (Lupu and others, 2017) between distributions of weekly abundances and sizes of fish at the traps and weekly simulated abundances and sizes (by S3). Investigation of model fit showed excellent agreement between simulated annual abundances and the abundance of fish passing the fish trap. However, when we compared weekly abundances at the fish trap, S3 under-predicted peaks and over-predicted troughs in the time series of weekly abundances at the fish trap. Thus, some unknown within-year effects have yet to be identified and incorporated in the S3 model. Identifying these important effects and incorporating them in the S3 model would help explain the lack of fit between estimated and simulated weekly abundances. We estimated parameters for 6 years that included a wide range of female spawner abundances (3,057–10,753) and water year types (Critical–Wet). We contrast our estimated parameters to the corresponding number of female spawners and the water year type for the Sacramento Valley. By happenstance, years having higher annual spawner abundances concurred with Critical to Dry water year types. Estimates of survival trended lower with higher spawner abundances and Critical to Dry conditions. In contrast, the extremely wet water year of 2017 had the lowest M 0y , suggesting less density-dependence in fish movement, and the lowest C y , suggesting lower average consumption in this year. When this high-flow year was excluded, a trend towards higher probabilities of fish remaining in a habitat at low abundance and lower proportions of maximum consumption was apparent from Critical to Wet conditions, but only 5 years of data were included. Except for 2017, daily proportions of maximum consumption were relatively high ( C y > 0.83), suggesting that fish were feeding at reasonably high proportions relative to the expected maximum consumption as defined by the “Wisconsin” bioenergetics model (Stewart and Ibarra, 1991). Survival estimates from fry emergence to outmigration at the Sacramento River confluence were generally low when integrated over time. The highest daily survival probability was S y = 0.93 in 2019, or 50 percent total mortality after 10 days. In contrast, our lowest daily survival probability was S y = 0.74 in 2015, or 95 percent total mortality after 10 days. Consequently, even our highest estimated daily survival probability might be considered low. This is especially true given that S y was estimated over a relatively short distance (<14.7 kilometers) from emergence to the Watt Avenue fish trap. Several factors, including our assumed and relatively high daily egg survival rate of 0.9975, could influence juvenile survival estimates. For example, an egg survival rate of 0.9975 results in 3-percent total mortality after 10 days. Egg mortality estimates used in S3 calibration were approximated from egg survivorship studies in the Yakima River, Washington (Johnson and others, 2012), and remains one of the greater uncertainties in S3 when estimating survival across life stages. By including bona fide estimates of egg survival in S3 simulations, the validity of the S3’s current daily egg survival rate could be assessed specifically for the American River. Tagging studies also could provide S3 with direct estimates of juvenile survival and movement; survival during egg incubation then could be estimated indirectly via model fitting.

California↗
USGS2023

Calibration of the Trinity River Stream Salmonid Simulator (S3) with extension to the Klamath River, California, 2006–17

The Trinity River is managed in two sections: (1) the upper 64-kilometer (km) “restoration reach” downstream from Lewiston Dam and (2) the 120-km lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously constructed and calibrated for the restoration reach. In this report, we extended and parameterized S3 for the 120-km section of the lower Trinity River to the confluence with the Klamath River and then to the Pacific Ocean in northern California. S3 is a deterministic life-stage structured-population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive (1) survival and growth within each habitat unit and (2) movement of fish among habitat units. The physical template of the Trinity River was formed by classifying the river into 910 meso-habitat units that were designated into runs, riffles, or pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival. We estimated key movement and survival parameters by calibrating the model to 12 years (2007–18) of weekly juvenile abundance estimates from two rotary screw traps: (1) the Pear Tree trap near the downstream end of the restoration reach and (2) the Willow Creek trap site is about 40.2 km upriver from the Trinity River’s confluence with the Klamath River. The calibration consisted of replicating historical conditions as closely as possible (for example: flow, temperature, spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated four alternative model structures that included either no density-dependence, density-independent movement and survival, density-dependent survival, or density-dependent movement. Akaike information criterion model selection was used to evaluate the strength of evidence for alternative model structures to simulate the observed abundance estimates. Model selection supported the conclusion that the fully density-dependent model and density-dependent survival model was better supported by the data than the no density-dependence or density-dependent movement model. Because density-dependent movement was favored in past evaluations, we focus on the results from the fully density-dependent model. Parameter estimates from this model indicated that fry were less likely than parr to move downstream and that fry moved slower. Fry had a lower daily survival probability than parr. In contrast, hatchery fish had the highest probability of movement and the lowest daily survival probability. Fitting the model to both traps individually enabled us to independently compare the fit and performance of S3 at simulating fish abundance, timing, and growth of juvenile salmon in the upper restoration reach and lower Trinity River. We obtained a better fit to the data at the Willow Creek trap site than we obtained at the Pear Tree trap site, regardless of whether we fit the model to the abundances at the Pear Tree trap or Willow Creek trap. This better fit was surprising given that the S3 input data for the upper restoration reach required fewer assumptions than fitting to the Willow Creek trap site that is farther down river. Fitting S3 to weekly abundances at the Willow Creek trap site required making assumptions about (1) extrapolating capacity-flow relationships to unmeasured habitat units; (2) spatially allocating spawners within the lower Trinity River; and (3) approximating the abundance, timing, and size of juveniles entering from tributaries. The model provided better fit to the data at the Willow Creek trap site. In the weekly abundance estimates, in relation to the S3 simulated abundances, several migration years’ (2011, 2015–17) weekly abundance estimates appeared truncated and were near or at peak annual abundances in January, suggesting that a large fraction of juveniles was migrating as early as December at the Pear Tree trap site. Some early life dynamics may not be currently incorporated into S3. For example, the estimation of abundance at the Pear Tree trap may be biased because of size selectivity. Knowing about selectivity at the Pear Tree trap could greatly improve S3’s ability to predict weekly and peak abundances each year.

California↗
USGS2023

Assessment of habitat use by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, 2020–21

We conducted a field study during 2020–21 to describe habitat use patterns of juvenile Chinook salmon ( Oncorhynchus tshawytscha ) in the mainstem Willamette, McKenzie, and Santiam Rivers and to evaluate how habitat suitability criteria affected the predictive accuracy of a hydraulic habitat model. Two approaches were used to collect habitat use data: a stratified sampling design was used to ensure that a representative sample of available habitats was included in our sampling; and a targeted sampling design was used to collect additional data in habitat cells where juvenile Chinook salmon were observed. Habitat attributes and fish presence data were collected in habitat cells that were approximately 2 square meters during April, June, and July. A total of 632 cells were sampled during the study and included habitat located in the main channel (373 cells), side channels (228 cells), and in alcoves (31 cells). Juvenile Chinook salmon were observed in 42 percent of the cells located in the main channel, 38 percent of the cells located in side channels, and 7 percent of the cells located in alcoves. We used logistic regression to develop resource selection functions for April, June, and July, which produced probability-based predictions of habitat use for juvenile Chinook salmon based on water velocity and water depth. The resource selection functions revealed a habitat shift by juvenile Chinook salmon to locations with higher water velocities and greater water depths from April to July as juvenile Chinook salmon size increased. The resource selection functions that we developed are an important addition to habitat modeling in the Willamette River basin because they were developed from in-basin data, capture seasonal differences in habitat use, and facilitate probability-based estimates of habitat use for juvenile Chinook salmon. These advancements will improve habitat modeling efforts for juvenile Chinook salmon during spring and summer months within the Willamette River.

Oregon↗
USGS2023

Simulating post-dam removal effects of hatchery operations and disease on juvenile Chinook salmon (Oncorhynchus tshawytscha) production in the Lower Klamath River, California

Executive Summary The Federal Energy Regulatory Commission has been considering the approval to breach four dams on lower Klamath River in southern Oregon and northern California. Approval of this application would allow for Strikeouts indicate text deletion hereafter. decommissioning and dam removal, beginning as early as 2023. This action would affect Klamath River salmon ( Oncorhynchus ssp.) populations, a critical food source for federally endangered Southern Resident Killer Whales ( Orcinus orca ). In the long run, reintroduction of salmon populations to the upper Klamath River Basin may increase salmon abundance available to Southern Resident Killer Whales, but in the near term, it is uncertain how changes in hatchery management and disease-caused mortality by the myxosporean parasite Ceratonova shasta will influence abundance of salmon populations entering the ocean. To assess this uncertainty, we used the Stream Salmonid Simulator (S3) to simulate population dynamics of juvenile Chinook salmon ( Oncorhynchus tshawytscha ) for nine different population sources that rear and migrate through the Klamath River. S3 is a spatially explicit population model that runs on a daily time-step and simulates daily growth, survival, and movement of juvenile Chinook salmon from the time of spawning through ocean entry. The key features of this model relevant to this report include (1) a C. shasta disease submodel; (2) a temperature-dependent bioenergetics model that calculates daily growth rates; (3) size-dependent movement; (4) density-dependent dynamics that are influenced by the effect of flow on suitable habitat area; and (5) habitat, river flow, and water temperature specific to each scenario. We constructed and ran four scenarios: two scenarios for dams in place (Dams In) and dams removed (Dams Out), and given these dam-removal conditions, a low- and high-spore scenario for C. shasta . Each scenario was run for nine water years representing a range of conditions from dry to wet. Previously published daily river flows and water temperatures for Dams In and Dams Out provided physical inputs for each scenario. Daily spore concentrations were simulated using a three-part mechanistic model that used river discharge, water temperature, and the prevalence of infection (POI) of hatchery-origin Chinook salmon juveniles with C. shasta in the previous year 3 . We constructed two spore scenarios for each Dams In and Dams Out scenario, a “Low Spore” scenario and a “High Spore” scenario resulting in four scenarios for comparison. Spore scenarios were established by setting the prior-year POI of hatchery fish to 0.15 and 0.75 in the estimation of spore concentrations. Hatchery releases under Dams Out differed from those under the current Dams In scenario. Hatchery releases under the Dams Out scenario were modified to emulate changes in hatchery production that would occur under Dams Out conditions. This included moving hatchery production and releases from Iron Gate Dam to a proposed hatchery at Fall Creek, which would be located about 11 kilometers (km) upstream of Iron Gate Dam. It is anticipated that the Fall Creek hatchery would produce fewer fish at smaller and larger sizes at different release timings. For salmon inputs, we used observed historical abundance of main-stem spawners from brood year 2009 and juvenile salmon entering from tributaries in water year 2010, which represented an average return year for the 2005–18 period. Main-stem spawning was allowed to shift upstream from Iron Gate Dam under the Dams Out scenario. We also included hatchery-origin fish as natural spawners that would have otherwise returned to Iron Gate Hatchery in the first 3 years following dam removal. The S3 model simulated considerably higher total abundance for Dams Out relative to the respective Dams In scenarios, and higher abundance for the Low Spore scenario relative to the High Spore scenario. The difference in abundance between the four combinations of the dam-removal and spore scenarios varied among population groups. For main-stem natural production, juvenile abundance at ocean entry was 2–3 times higher for Dams Out scenarios than for Dams In scenarios, and juvenile abundance for High Spore scenarios was lower than that for the Dams Out Low Spores scenario. For hatchery releases, abundance at ocean entry was similar between Dams In and Dams Out scenarios for most water years, despite lower release sizes from Fall Creek Hatchery under Dams Out. For tributary populations, abundance for the High Spore scenarios was consistently lower than for the Low Spore scenarios, but differences between dam-removal scenarios varied among water years, with Dams Out scenarios having similar or higher abundance than Dams In scenarios, and dry water years having the largest difference between Dams In and Dams Out scenarios. We determined that different factors affected the response of each population group. For main-stem natural production, survival from fry emergence to ocean entry was higher under Dams Out scenarios compared to Dams In scenarios because juveniles emerged later and tended to arrive at the ocean sooner and at larger sizes, causing the population to have less time-dependent in-river mortality. Owing to their late release timing, hatchery populations had high disease-caused mortality in Dams In and Dams Out High Spore scenarios. Furthermore, a high proportion of infected fish (those that would be expected to die at some future point) survived to the ocean. Iron Gate Hatchery fish had lower survival rates than releases from Fall Creek Hatchery because the last mid-June release group from the 2010 Iron Gate Hatchery release incurred nearly total mortality in most water years owing to water temperatures exceeding 24 degrees Celsius. Our analysis shows how the S3 model was able to track different populations and provide insights on how the differential response of each population combined to influence the simulated number of juvenile Chinook salmon arriving at the Pacific Ocean where they become available as a food source for Southern Resident Killer Whales.

California↗
USGS2021

Predator and prey events at the entrance of a surface‐oriented fish collector at North Fork Dam, Oregon

Quantifiable estimates of predator–prey interactions and relationships in aquatic habitats are difficult to obtain and rare, especially when individuals cannot be readily observed. To overcome this observational impediment, imaging sonar was used to assess the cooccurrence of predator‐size fish and juvenile salmonids, Oncorhynchus spp., at the entrance to a floating surface collector (FSC) in the forebay of North Fork Dam on the Clackamas River, Oregon (USA). Imaging sonar can be used to transform active sound waves into visual data, making it possible to obtain continuous underwater observations on the presence and interspecific interactions between predator‐size fish and prey (juvenile salmonids). Hourly counts of smolt‐size fish tracks, diel phase, water clarity and river discharge were used as covariates within a zero‐inflated Poisson model to determine how these factors may influence the number of predators in front of the FSC. Both the number of smolt‐size fish tracks and diel phase had the strongest effects on the number of predator‐size fish tracks, with more predator‐size fish tracks observed during the daytime, and as the number of smolt‐size fish tracks increased. Additionally, the presence of predator‐size fish may affect the abundance and direction of travel of juvenile salmonids, as fewer smolt‐size fish were observed when predators were present, and a greater proportion of smolt‐size fish were observed travelling away from the FSC when predator‐size fish were present. This study provides estimates of predator and prey fish abundance in the vicinity of surface collection systems at moderate‐sized hydropower projects and could help resource managers better understand mechanisms that can influence the survival and passage behaviour of juvenile salmonids using surface collection structures at dams.

Oregon↗
USGS2021

Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River Fall Chinook salmon ESU

The portion of the Snake River fall Chinook salmon Oncorhynchus tshawytscha evolutionary significant unit (ESU) that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 1992–2020 in response to U.S. Endangered Species Act recovery efforts and other federally mandated actions. This annual report focuses on changes in population abundance and habitat use by natural- and hatchery-origin spawners. Typically, we also report on population attributes of natural-origin juveniles, but data on juveniles were not collected in 2020 due to Covid-19. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching the point that no more redds can be supported. Timing of spawning and fry emergence have been relatively stable, but effects of density dependence are evident in juvenile life stages. Apparent abundance of juvenile fall Chinook salmon has increased and we noted the following changes: parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier; growth rate (g/d) and dispersal size of parr has declined; and passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate has increased. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir resulting from the expansion of the recovery program. The long-term goal is to use this information in a comprehensive modeling effort to conduct action-effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management Research, Monitoring, and Evaluation (RM&E) programs. In 2020, the U.S. Geological Survey (USGS) focused survey efforts in the Snake River on deepwater redd searches and fish collection for parentage-based tagging (PBT) analyses. We use a boat-mounted underwater video camera to count 170 deepwater redds at 19 of the 28 sites surveyed. Redd depths averaged 4.2 m. We collected genetic samples from 297 live fall Chinook salmon and 16 carcasses at 44 unique geographic locations that spanned 89 river kilometers. Seventy-two fish were recovered at Eureka Bar (rkm 307.1) and Corral Creek (rkm 349.7), which accounted for 23% of all collected fish in 2020. Most (238 fish) post-spawned salmon were collected from early to mid-November just after peak spawning. A summary of 2019 PBT results can be found in Appendix A.1. In 2020, we PIT tagged subyearling fall Chinook salmon in the Clearwater River to obtain population and growth data. In the Clearwater River, we tagged 2,192 subyearlings and recaptured 79 (3.6%) fish in the river and 187 fish (78 tagged by the U.S. Geological Survey, 109 tagged by the Nez Perce Tribe) at Lower Granite Dam during October which provided information for growth estimation. Within riverine habitats, growth in both length and mass were higher for fish tagged with 8-mm tags than with 9- and 12-mm tags. Estimated growth in length and mass of subyearlings was generally lower in Lower Granite Reservoir than in riverine habitats. Information on prey resources and juvenile fall Chinook salmon prey consumption was collected to better understand the growth opportunity of late-migrating fish in Lower Granite Reservoir. Zooplankton and surface drifting prey were collected from three reservoir locations from July through October during 2019 and 2020. Fall Chinook salmon diet data were collected from angled fish using gastric lavage. Cladocera and Copepoda were the most abundant zooplankton taxa collected while Diptera was the most common invertebrate taxon collected in surface drift samples. Totals of 49 and 94 juvenile fall Chinook salmon were captured in 2019 and 2020, respectively, and most fish were caught in the lower reach of the reservoir in October of each year. Juvenile fall Chinook salmon consumed mainly dipterans in July and October 2019 and mainly Daphnia during August–October in 2020. Fish showed selection mainly for dipterans in 2019 but strong selection for Daphnia during October 2020. Stomach fullness values were relatively low (<1.1%) during both years. Results show that prey resources are adequate in Lower Granite Reservoir to support positive fish growth during late summer and early autumn.

Idaho, Oregon, Washington↗
USGS2020

Development of a two-stage life cycle model for Oncorhynchus kisutch (coho salmon) in the upper Cowlitz River Basin, Washington

Recovery of salmon populations in the upper Cowlitz River Basin depends on trap-and-haul efforts owing to impassable dams. Therefore, successful recovery depends on the collection of out-migrating juvenile salmon at Cowlitz Falls Dam (CFD) for transport below downstream dams, as well as the collection of adults for transport upstream from the dams. Tacoma Power began downstream fish collection efforts at CFD in the mid-1990s and has been working consistently since then to improve collection efficiency to support self-sustaining salmon and steelhead ( Onchorhynchus spp.) populations in the upper Cowlitz River Basin. Although much work has focused on estimating fish collection efficiency (FCE), there has been relatively little focus on modeling population dynamics to understand how fish collection efficiency and other factors drive production of both juvenile and adult salmon over their life cycle. As a first step towards understanding the factors affecting population dynamics of Oncorhynchus kisutch (coho salmon) in the upper Cowlitz River Basin, we developed a statistical life cycle model using adult escapement and age structure data, juvenile collection data, and juvenile fish collection efficiency estimates. The goal of the statistical life cycle model is to estimate annual production and survival during two critical life-stage transitions: the freshwater production from escapement of adults upstream from CFD to collection of juveniles at CFD, and the juvenile-to-adult survival from the time of collection at the dam to the return of adults. To structure the life cycle model, we used the Ricker stock-recruitment model to estimate juvenile production from the number of parent spawners. This approach allowed us to account for density dependence at high spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. We then expressed productivity as a function two key variables affecting the number of juveniles collected and transported at CFD: (1) annual FCE, and (2) the annual number of days that spill occurred at CFD from September 1 to April 30. Our key findings were as follows: FCE was the primary factor affecting productivity of coho salmon upstream from CFD because FCE affects the number of juveniles that survive to continue downstream migration; Juvenile-to-adult return (JAR) rates were relatively high considering that harvest was included in the estimate, averaging about 3.6 percent and ranging as high as 9.1 percent, suggesting that adult coho salmon may be able to return to CFD at sustainable population sizes; and Much variation in the estimates of juvenile fish production upriver of CFD was unexplained even after adult escapement and FCE were accounted for, suggesting that the model may be improved by exploring different covariates and model structures for juvenile production as well as JAR rates. Additionally, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE=1, was 108.4 juveniles per spawner. Because this two-stage life cycle model partitions factors that affect fish production in river compared to the ocean environment and fish life stages, the model estimates should help inform fishery managers about the overall role that fish collection at CFD may have on the recovery and sustainability of coho salmon populations.

Washington↗
USGS2019

Using the stream salmonid simulator (S3) to assess juvenile Chinook salmon (Oncorhynchus tshawytscha) production under historical and proposed action flows in the Klamath River, California

Executive Summary The production of Klamath River fall Chinook salmon ( Oncorhynchus tshawytscha ) in northern California and southern Oregon is thought to be limited by poor survival during freshwater juvenile life stages, in part a result of Ceratonova shasta —a highly infectious disease that can lead to high fish mortality. Higher flushing river flows are thought to affect the concentration of C. shasta spores, and in turn, juvenile salmon infection and mortality. The Stream Salmonid Simulator (S3) model was built to simulate the spatiotemporal dynamics of the growth, movement, and survival of juvenile salmon from spawning through migration to the Pacific Ocean in response to river flow, habitat availability, water temperature, and C. shasta spore concentrations. The S3 model has been calibrated to juvenile fall Chinook salmon abundances at a trap site within the Klamath River, and was specifically designed to provide objective predictions of juvenile salmon abundance and survival in relation to proposed flow management alternatives and resulting fish infection and mortality by C. shasta . Infection by C. shasta in the Klamath River is location specific, occurring in a “disease zone” with high spore concentrations. The spatial extent of this disease zone (from river kilometer 289.6 to 212.9) has been incorporated in the S3 model for the Klamath River, enabling the assessment of disease effects on fish at specific spatial locations such as the trap sampling sites, and for fish that were or were not exposed to the disease zone as they emigrate the Klamath River to the Pacific Ocean. Given the information gained from field observations on spore concentrations in relation to river flow, deliberations by resource managers resulted in the incorporation of springtime flushing flows in a Proposed Action (PA) scenario developed in part to lower spore concentrations within the disease zone. A Historical (HI) scenario based on the observed flows, temperatures, and spore concentrations from 2004 to 2016 was used to compare and contrast the potential benefits to juvenile salmon from PA flows in relation to the HI conditions.

California↗
USGS2019

Application of the Stream Salmonid Simulator (S3) to Klamath River fall Chinook salmon (Oncorhynchus tshawytscha), California—Parameterization and calibration

Executive Summary In this report, we describe application of the Stream Salmonid Simulator (S3) to Chinook salmon ( Oncorhynchus tshawytscha ) in the Klamath River between Keno Dam in southern Oregon and the ocean in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. It can track different source populations or species, such as major tributary populations that enter a river like the Klamath River. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit affect survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the Klamath River was formed by classifying the river into 2,635 mesohabitat units composed of runs, riffles, and pools. This template enabled modeling of the unimpounded Klamath River between the Keno Dam (the uppermost of four dams) and Iron Gate Dam (the lowermost dam) to address dam-removal scenarios. However, in this report, our focus was on parameterizing and calibrating the model under existing conditions, which included 1,706 discrete habitat units over the 312-kilometer (km) section of river between Iron Gate Dam and the ocean. For each habitat unit, we developed a time series of daily flow, water temperature, and amount of available habitat (weighted usable habitat area [WUA]) for spawners, fry, and parr. WUA time series were constructed using habitat suitability criteria for Chinook salmon applied to eight two-dimensional (2-D) hydrodynamic models that represented the geomorphic variability in habitat across the Klamath River. Results from the 2-D models were then extrapolated to unmodeled habitat units by scaling WUA curves for changes in habitat unit length and width. These variables were then used to drive population dynamics such as egg development and survival and juvenile movement, growth, and survival.

California, Oregon↗
USGS2019

Juvenile Chinook salmon (Oncorhynchus tshawytscha) survival in Lookout Point Reservoir, Oregon, 2018

A field study was conducted to estimate survival of juvenile Chinook salmon ( Oncorhynchus tshawytscha ) in Lookout Point Reservoir, Oregon, during 2018. The study consisted of releasing three groups of genetically-marked fish into the reservoir, and sampling them monthly. Juveniles were released during April 10–13 (116,708 fish), May 15–18 (31,911 fish), and June 19–20 (11,758 fish). Reservoir sampling began in May and occurred monthly through October, consisting of 5-day events where juvenile Chinook salmon were collected using electrofishing, shoreline traps, and gill nets. Data were analyzed using a staggered release-recovery model and a parentage-based tagging (PBT) N-mixture model. The staggered release-recovery model provided survival estimates from three periods: mid-April to mid-May (SSRRM1); mid-May to mid-June (SSRRM2); and mid-April to mid-June (SSRRM12). Multiple estimates of survival were possible for each period using different combinations of recovery data from the three groups of fish that were released. Survival probability estimates for SSRRM1 ranged from 0.98520 to 0.98954; estimates for SSRRM2 ranged from 0.09338 to 0.62142; and the estimate for cumulative survival from mid-April to mid-June (SSRRM12) were 0.75211. We suspect that issues with release groups in May ( R 2 ) and June ( R 3 ) led to biased survival results using the staggered release-recovery model. The PBT N-mixture model provided survival estimates from six periods: mid-April to mid-May (SNMIX1); mid-May to mid-June (SNMIX2), mid-June to mid-July (SNMIX3), mid-July to mid-August (SNMIX4), mid-August to mid-September (SNMIX5); and mid-September to mid-October (SNMIX6). Survival estimates from the PBT N-mixture model were lowest for SNMIX6 (0.41620) and highest for SNMIX1 (0.79587). These results differed from those in 2017 when monthly survival increased across months. This suggests that one or more factors could have affected juvenile Chinook salmon survival in Lookout Point Reservoir. One possible factor could be copepods (which were highly prevalent on juvenile Chinook salmon during summer 2018), but environmental factors such as reserveroir elevation, discharge at Lookout Point Dam, and fish distributions within the reservoir differed between study years. Two PBT N-mixture models provided cumulative survival estimates from mid-April to mid-October. Estimates from the two models were 0.061 and 0.039, which suggests that survival of subyearling Chinook salmon in Lookout Point Reservoir was very low in 2018. Additional research is recommended to better understand inter-annual variability of subyearling Chinook salmon in the reservoir and to gain insights into factors that affect their survival.

Oregon↗
USGS2019

Evaluation of Chinook salmon (Oncorhynchus tshawytscha) fry survival at Lookout Point Reservoir, western Oregon, 2017

A field study was conducted to estimate survival of fry-sized juvenile Chinook salmon ( Oncorhynchus tshawytscha ) in Lookout Point Reservoir, western Oregon, during 2017. The field study consisted of releasing three groups of genetically marked fish in the reservoir and monthly fish sampling. Fish were released during April 18–19 (43,950 fish), May 30–June 2 (44,145 fish), and on June 28, 2017 (3,920 fish). Reservoir sampling began in May and occurred monthly through October, consisting of 5-day events where juvenile Chinook salmon were collected using various gear types (electrofishing, shoreline traps, gill nets). Data were analyzed using two models: (1) a staggered release-recovery model (SRRM), and (2) a parentage-based tagging (PBT) N -mixture model. The SRRM provided survival estimates from two periods: (1) mid-April to late May (S SRRM1 ), and (2) late May to late June (S SRRM2 ). Multiple estimates of survival were possible for each period using different combinations of recovery data from the three groups of fish that were released. Survival estimates for S SRRM1 ranged from 0.470 to 0.520. Estimates for S SRRM2 ranged from 0.968 to 0.969; cumulative survival from mid-April to late June (S SRRM2 ) was estimated at 0.870. We suspect that issues with the third release group led to biased survival results using the SRRM. The PBT N -mixture model provided survival estimates from six periods: (1) mid-April to mid-May (S NMIX1 ), (2) mid-May to mid-June (S NMIX2 ), (3) mid-June to mid-July (S NMIX3 ), (4) mid-July to mid-August (S NMIX4 ), (5) mid-August to mid-September (S NMIX5 ), and (6) mid-September to mid-October (S NMIX6 ). Survival estimates from the PBT N -mixture model were lowest for S NMIX1 (0.461) and increased monthly to a high of 0.970 for S NMIX6 . Cumulative survival from mid-April to mid-July was 0.233 and overall survival from mid-April to mid-October was 0.188. This suggests that most mortality occurred early in the study when juvenile Chinook salmon were small. This could be because these fish were most vulnerable to predation in the reservoir at that time. We determined that mortality of juvenile Chinook salmon was high in the reservoir during this study and similar estimates of parr-to-smolt survival have been observed in other systems. Additional analyses are required, including results from the second year of study (2018), and potentially similar evaluations will need to be made at other locations to determine if reservoir mortality is a limiting survival factor for Chinook salmon in the Middle Fork Willamette River.

Oregon↗
USGS2019

Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook Salmon ESU

The portion of the Snake River fall Chinook Salmon Oncorhynchus tshawytscha ESU that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 1992–2018 in association with U.S. Endangered Species Act recovery efforts and other federally mandated actions. This annual report focuses on (1) numeric and habitat use responses by natural- and hatchery-origin spawners, (2) phenotypic and numeric responses by natural-origin juveniles, and (3) use of a small unmanned aerial system (sUAS) to search for fall Chinook salmon redds and carcasses. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching redd capacity. Timing of spawning and fry emergence has been relatively stable, but effects of density dependence are evident in juvenile life stages. Apparent abundance of juvenile fall Chinook salmon has increased and we noted the following responses: parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier; growth rate (g/d) and dispersal size of parr declined; and passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate faster. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir that was influenced by the expansion of the recovery program. The long-term goal is to use this information in a comprehensive modeling effort to conduct action-effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management Research, Monitoring, and Evaluation (RM&E). In 2018, the U.S. Geological Survey (USGS) searched 10 shallow-water spawning sites and 25 deepwater spawning sites in conjunction with the Idaho Power Company (IPC). A total of 103 redds were counted at shallow-water sites and 61 redds were counted at deepwater sites. We recovered 17 carcasses and 13 live fish, which were spawned out, and collected biological information and tissue samples that are currently being analyzed for parentage to determine the percentage of hatchery-origin spawners on the spawning grounds.

Idaho, Oregon, Washington↗
USGS2018

Fish behavior and abundance monitoring near a floating surface collector in North Fork Reservoir, Clackamas River, Oregon, using multi-beam acoustic imaging sonar

An imaging sonar was used to assess the behavior and abundance of fish sized the same as salmonid smolt and bull trout ( Salvelinus confluentus ) at the entrance to the juvenile fish floating surface collector (FSC) at North Fork Reservoir, Oregon. The purpose of the FSC is to collect downriver migrating juvenile salmonids (Chinook salmon [ Oncorhynchus tshawytscha ], Coho salmon [ Oncorhynchus kisutch ], and steelhead [ Oncorhynchus mykiss ]) at the North Fork Dam and to safely route them around the hydroelectric projects. The objective of the imaging sonar component of this study was to assess the behaviors of both smolt and predator-size fish (smolt [60–250 millimeter] and predator 350–650 [millimeter]) observed near the FSC and to determine if the presence of predator-size fish influenced the abundance of smolt-size fish. An imaging sonar was deployed near the entrance to the FSC during the spring smolt out-migration period. The imaging sonar technology was an informative tool for assessing abundance and spatial and temporal behaviors of both smolt and predator-size fish near the entrance of the FSC. Both smolt and predator-size fish were regularly observed near the entrance, with greater abundances observed during day than during night. Behavioral differences were also observed between the two fish-size classes, with smolt-size fish traveling straighter with more directed movement, and predator-size fish generally showing more milling behavior. Additionally, the presence of predator-size fish may be effecting the abundance and direction of travel of smolt-size fish, as counts of smolt-size fish were reduced in conjunction with the presence of predator-size fish and a greater proportion of smolt-size fish were observed traveling away from the FSC when predator-size fish were present than when predator-size fish were absent. Results of modeling potential predator-prey interactions and influences indicated that both the number of juvenile fish tracks and photoperiod had the strongest effects on the number of predator fish tracks, with more predator-size fish tracks observed as the number of smolt-size fish tracks increased. Overall, the results indicate that predator-size fish are present near the entrance of the FSC, concomitant with smolt-size fish, and their abundances and behaviors indicate that they may be drawn to the entrance of the FSC because of the abundance of prey-sized fish found there.

Oregon↗
USGS2018

Application of the Stream Salmonid Simulator (S3) to the restoration reach of the Trinity River, California—Parameterization and calibration

Executive Summary In this report, we constructed and parameterized the Stream Salmonid Simulator (S3) for the 64-kilometer “Restoration Reach” of the Trinity River, just downstream of Lewiston Dam in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the Restoration Reach was formed by classifying the river into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily flow, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg growth and survival and juvenile movement, growth, and survival.

California↗