Geology topics

John Plumb

Publications and source records attributed to John Plumb.

9 recordsLinked to original sources

USGS2026

Differences among runs of Chinook Salmon in routing probability at the Georgiana Slough-Sacramento River junction

The survival of juvenile Chinook Salmon ( Oncorhynchus tshawytscha ) depends on the specific migration route they take through the Sacramento–San Joaquin Delta. Factors such as flow magnitude, flow direction, and distribution of fish across the channel significantly affect the likelihood of their entering routes with lower survival probabilities. Management strategies to mitigate the entry of endangered winter-run and threatened spring-run Chinook Salmon into the interior Delta—particularly through Georgiana Slough—involve flow regulation and the installation of a bioacoustic fish fence. Monitoring the effectiveness of these measures has primarily relied on acoustically-tagged, juvenile, hatchery-reared, late-fall-run Chinook Salmon, which are easier to obtain and can accommodate larger tags compared to other runs. Previous studies explored how flow dynamics affect routing probabilities of late-fall-run Chinook Salmon, but there is a lack of understanding about how routing probabilities vary among runs. We leveraged data from 15 previous studies comprising 3,004 acoustically-tagged fish across all four runs, over a 12-year period, to assess the effects of run on routing probability into Georgiana Slough, while accounting for variation in flow dynamics. We employed logistic regression to model the influence of tidal flow metrics, time of day (day and night), and run type on the probability of juvenile Chinook Salmon being routed into Georgiana Slough. Our analysis revealed that reverse flow during incoming tides influenced the routing probabilities of all runs. An increased proportion of flow into Georgiana Slough, meant an increased probability for all runs to be routed into Georgiana Slough. Late-fall-run Chinook Salmon also showed a greater probability of routing into Georgiana Slough during the night than during the day, whereas the opposite was true for other runs. These differences in routing probability affect our understanding of how management actions intended to reduce routing into Georgiana Slough may differentially affect the four runs of Chinook Salmon in the Sacramento River.

Callifornia↗

USGS2025

Behavioral responses of Silver Carp to underwater acoustic deterrent sounds

Objective Invasive carps continue to spread across the Mississippi River basin, posing significant ecological risk. Identifying technologies to slow their dispersal is critical. The use of sound has been proposed as a method to modify the behavior of Silver Carp Hypophthalmichthys molitrix , offering a nonstructural deterrent strategy. Methods Silver Carp implanted with acoustic transmitters were released into earthen ponds equipped with telemetry arrays. The fish were exposed to a 30-min playback of three underwater sounds (chirp saw, chirp square, and 100-hp boat motor). Movement trajectories were analyzed using a two-state hidden Markov model to estimate the effects of environmental and experimental variables on fish behavior. Results The results of the hidden Markov model supported two behavioral states. State 1 was characterized by longer step lengths (distance between positions) and greater directional persistence in turning angle (change in direction between two intervals), indicative of heighted activity. State 2 was defined by shorter step lengths and less directional persistence, suggesting reduced activity. Silver Carp that were exposed to the chirp square sound had an increased likelihood of entering state 1, whereas the 100-hp boat motor sound promoted transitions to state 2. Conclusions Underwater sounds distinctly influenced the movement of Silver Carp in earthen ponds. The chirp square sound elicited heightened activity levels, demonstrating potential for use in acoustic deterrent applications. However, the response of Silver Carp to these sounds may be influenced by the size of the study environment or the absence of natural drivers of fish behavior, such as food or reproduction. This study contributes to the development of nonstructural, species-specific deterrent systems by identifying sounds that influence the behavior of invasive carps. The application of sound-based methods may play a critical role in integrated pest management strategies for invasive carps, potentially limiting their spread while minimizing effects on native species.

Transactions of the American Fisheries Society↗

USGS2025

Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington

Restoration of salmon populations in the upper Lewis River Basin depends on a trap-and-haul program owing to the Lewis River Hydroelectric Project (Project) operated by PacifiCorp and Cowlitz PUD (Utilities), which has been a barrier to salmon passage since the 1930s. Thus, sustaining the Coho salmon ( Oncorhynchus kisutch ) population upstream of the Project currently depends on two fundamental factors: (1) the collection of upstream migrating adult Coho salmon at Merwin Dam, the lower most dam within the Project, and transporting them by truck to spawn above Swift Dam, the upper most 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 life cycle model for Lewis River anadromous fish was identified by the Lewis River Aquatic Technical Subgroup, with the understanding that many years (>15) of data collection are needed to adequately measure the life cycle production of coho salmon. Use of past data to construct models could help inform future data collection and provide a framework that can be updated annually to measure trap and haul program performance within a life cycle context (Note: Data are not currently available from PacifiCorp. Contact organization Chris Karchesky for further information). Because Coho salmon can live as long as five years, estimating demographic parameters for Coho salmon populations over their life cycle 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, providing sufficient data to formulate a life cycle model that can guide future data collection efforts and provide preliminary information to resource managers The goal of the statistical life cycle model was to estimate annual production and survival during two critical life-stage transitions (1) the freshwater production from escapement of adults released upstream of Swift Dam, and the collection of downstream migrating juveniles at the 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. 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 of 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 life cycle 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 (IPM) to the data, and (4) summarize our findings, identify data gaps, and identify potential opportunities for future studies that could provide information used to 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% and ranging as high as 12.9%, and (3) juvenile capacity upriver of 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 this two-stage life cycle model partitions factors that affect fish production in river versus the ocean, the model estimates should 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 can assist in the evaluation and continued improvement of the current trap and haul program to support anadromous fishes in the Lewis River Basin.

BioRxiv↗

USGS2024

Snake River Fall Chinook Salmon research and monitoring

In Chapter 1, we report on development and application of an integrated population model (IPM) for the natural-origin fall Chinook salmon population upstream of Lower Granite Dam. This year’s efforts represent the third update to the model. Initial efforts focused on generating juvenile and adult abundance estimates, with estimates of uncertainty, for informing the life-cycle model and estimating the effects of covariates on key demographic parameters. The goals of this year’s report are to 1) describe the modifications and advances made since the previous report, 2) to annually update and report the abundance estimates and other quantities used in the model, 3) to provide annual estimates of population parameters estimated by the IPM, and 4) to outline the next year’s tasks for advancing and/or applying the model. Since our last report on the life-cycle model, we have made a number of changes including: 1) incorporating jack abundance and age-structure data into the observation model, 2) changing smolt-to-adult survival (SAR) for subyearling and yearling to partial SARs that represent the joint probability surviving and entering the ocean at a given juvenile age, 3) combining age categories for rarely observed ages, 4) using scale data from unmarked fish to estimate age structure, and 5) generating composite life-cycle demographic parameters (cumulative capacity and productivity) from stage-specific parameters. We also generated juvenile abundance estimates, extended the model to include three additional brood years (1992– 2021), and ran the model to forecast returns to Lower Granite in 2022. For posterior medians of life stage-specific parameters, we estimated a mean productivity of 438 natural-origin juvenile recruits per female spawner, a capacity of 1.36 million juveniles, and a mean smolt-to-adult survival (SAR) of 1.2%. We detected strong density-dependent regulation, with juvenile recruits per spawner declining to about 50 juvenile recruits per female spawner at high spawner abundance. Across the entire life cycle, these stage-specific parameters resulted in a median cumulative intrinsic productivity of 1.93 adult female recruits per female spawner and a median equilibrium abundance of 2,851 female spawners (7,842 total spawners). Annual juvenile productivity varied from about 250–1,000 juveniles per spawner but displayed no temporal trends or patterns. For the three most recent brood years added to the model, recruits per spawner were higher than average but well within the range of uncertainty observed over the entire time series. In contrast to juvenile recruitment variability, SAR varied considerably among years and exhibited two periods of high survival (1996–2001 and 2007–2012) when SAR ranged from 2% to 6% and cumulative productivity ranged from 2 to 8 recruits per spawner. Partial SARs revealed that yearling outmigrants contributed substantially to the high SARs in the first high-survival period, but the second period was dominated by subyearlings. Yearlings contributed >30% to SAR in most years prior to 2007, and <30% since 2007. Our two-stage IPM provides a wealth of information about population dynamics affecting two key life-stage transitions (spawner to juvenile, and juvenile to spawner) centered on passage at Lower Granite Dam. By summarizing these stage-specific demographic parameters across the entire life cycle, this information will be useful for informing the recovery status of this threatened population. Whereas previous versions introduced hydrosystem and ocean covariates into the model, this phase of model development focused on solidifying the underlying model structure by introducing the concept of partial SARs and developing composite productivity and capacity as a function of underlying stage-specific parameters. Given this advancement, our next steps are to re-incorporate covariates into the model, specifically to understand how different factors affect partial SARs of subyearling and yearlings. Longer term model developments include:1) incorporating hatchery fish to explicitly estimate their survival as an alternative method for estimating natural-origin age composition, 2) expanding the model’s structure to include the three major spawning aggregates, 3) more explicitly modeling hydrosystem effects including transportation, and 4) using the model to assess retrospective and prospective management actions. In 2022, the U.S. Geological Survey (USGS) focused adult salmon survey efforts in the Snake River on deepwater redd searches and fish collection for parentage-based tagging (PBT) analyses. We use used a boat-mounted underwater video camera to count 99 deepwater redds at 16 of the 29 sites surveyed. Redd depths averaged 4.4 m. In conjunction with the Idaho Power Company, we collected genetic samples from 318 live fall Chinook salmon (Oncorhynchus tshawytscha) and 19 carcasses at 40 unique geographic locations that spanned 91 river kilometers. Eighty fish were collected at three sites (High Range [rkm 332.3], Dug Bar [rkm 315.4], and Three Creek [rkm 384.0]), which accounted for 23% of all collected fish in 2022. Most (333 fish) post-spawned salmon were collected from early to mid-November just after the peak of spawning. A summary of 2021 PBT results produced by the Idaho Power Company can be found in Appendix A.2. Beach seining and PIT tagging of subyearling fall Chinook salmon was conducted in Snake and Salmon rivers to obtain information on population metrics and growth as well as to provide data for ongoing life-cycle modeling. In the Snake River, we collected 7,496 subyearlings, tagged 4,139, and recaptured 502 (12.1%). Using 8-mm tags in 45–49-mm fish allowed us to represent an additional 25% of the juvenile population through PIT tagging beyond just using standard 9- and 12-mm tags. In the Salmon River, we captured 206 natural subyearlings with the majority (52%) of fish being captured at two sites: rkm 20 and 26. We tagged 145 subyearlings and recaptured 9 fish. Many of the subyearlings we tagged in the Snake River were detected passing Lower Granite Dam, but only 4 fish tagged in the Salmon River were detected. In total we detected 484 (11.3%) tagged fish at Lower Granite Dam, and detection rates varied by tag size and passage route. More subyearlings were detected passing via the removable spill weir (RSW) earlier in the season while more fish were detected passing through the juvenile fish bypass system (JBS) earlier in the season while more fish were detected passing via the removable spill weir (RSW) later in the season. In general, fish tagged with 12-mm PIT tags had higher detection rates than fish tagged with smaller tags. Survival to Lower Granite Dam was low and ranged from 0.22 to 0.36. Season-wide, growth of subyearlings was higher in the lower reach than in the upper reach of the Snake River.

Idaho, Oregon, Washington↗

USGS2023

Movement and behavioral states of common carp (Cyprinus carpio) in response to a behavioral deterrent in a navigational lock

Freshwater ecosystems are some of the most affected by biological invasions due, in part, to the introduction of invasive carp worldwide. Where carp have become established, management programs often seek to limit further range expansion into new areas by reducing their movement through interconnected rivers and waterways. Lock and dams are important locations for non-physical deterrents, such as carbon dioxide (CO 2 ), to reduce unwanted fish passage without disrupting human use. The purpose of this study was to evaluate the behavioral responses of common carp ( Cyprinus carpio ) to non-physical deterrents within a navigation structure on the Fox River, Wisconsin. Acoustic telemetry combined with hidden Markov models (HMMs) was used to analyze variation in carp responses to treatments. Outcomes may inform CO 2 effectiveness at preventing invasive carp movement through movement pinch-points.

Wisconsin↗

USGS2019

A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals

Understanding drivers of temporal variation in demographic parameters is a central goal of mark‐recapture analysis. To estimate the survival of migrating animal populations in migration corridors, space‐for‐time mark–recapture models employ discrete sampling locations in space to monitor marked populations as they move past monitoring sites, rather than the standard practice of using fixed sampling points in time. Because these models focus on estimating survival over discrete spatial segments, model parameters are implicitly integrated over the temporal dimension. Furthermore, modeling the effect of time‐varying covariates on model parameters is complicated by unknown passage times for individuals that are not detected at monitoring sites. To overcome these limitations, we extended the Cormack–Jolly–Seber (CJS) framework to estimate temporally stratified survival and capture probabilities by including a discretized arrival time process in a Bayesian framework. We allow for flexibility in the model form by including temporally stratified covariates and hierarchical structures. In addition, we provide tools for assessing model fit and comparing among alternative structural models for the parameters. We demonstrate our framework by fitting three competing models to estimate daily survival, capture, and arrival probabilities at four hydroelectric dams for over 200 000 individually tagged migratory juvenile salmon released into the Snake River, USA.

Biometrics↗

USGS2019

Movement and apparent survival of acoustically tagged juvenile late-fall run chinook salmon released upstream of Shasta Reservoir, California

Stakeholder interests have spurred the reintroduction of the critically endangered populations of Chinook Salmon to tributaries upstream of Shasta Dam, in northern California. We released two groups of acoustically tagged, juvenile hatchery, late-fall Chinook Salmon to determine how juvenile salmon would distribute and survive. We measured travel times to Shasta Dam, and the number of fish that moved between locations within Shasta Reservoir. We used mark-recapture methods to determine detection and apparent survival probabilities of the tagged fish as they traveled through five reaches of the Sacramento River from the McCloud River to San Francisco Bay (~590 km) over the two 3-month observation periods. After our first (February) release of 262 tagged fish, 182 fish (70%) were detected at least once at the dam, 41 (16%) were detected at least once downstream of Shasta Dam, and 3 (1%) traveled as far as San Francisco Bay. After the second (November) release of 355 tagged fish, only 4 (1%) were detected at Shasta Dam. No fish were detected below Shasta Dam, so we could not estimate survival for this second release group. The first release of fish was fortuitously exposed to exceptionally high river flows and dam discharges, which may have contributed to the more distant downstream migration and detection of these fish — though other factors such as season, diploid versus triploid, and fish maturation and size may have also contributed to release differences. The reported fish travel times as well as detection and survival rates are the first estimates of juvenile salmon emigration from locations above Shasta Dam in more than 70 years. This information should help inform resource managers about how best to assess juvenile winter-run Chinook Salmon and assist in their reintroduction to watersheds upstream of Shasta Dam.

California↗

USGS2019

A natural‐origin steelhead population's response to exclusion of hatchery fish

It is asserted that reduction or elimination of hatchery stocking will increase natural‐origin salmon Oncorhynchus spp. and steelhead O. mykiss production. We conducted an analysis of steelhead population census data (1958–2017) to determine whether elimination of summer steelhead stocking in the upper Clackamas River in 1998 increased the productivity of natural‐origin winter steelhead. A Bayesian state–space stock–recruitment model was fitted to the adult steelhead data set, and productivity was estimated as a function of hatchery‐origin spawner abundance as well as other environmental factors. When used as a predictive variable in our model, the abundance of hatchery summer steelhead spawners (1972–2001) did not have a negative effect on winter steelhead recruitment. However, spill at North Fork Dam (the gateway to the upper Clackamas River basin) and the Pacific Decadal Oscillation (an index of ocean conditions) were both negatively associated with winter steelhead recruitment. Moreover, winter steelhead abundance in the upper Clackamas River basin failed to rebound to abundances observed in years prior to the hatchery program, and fluctuations in winter steelhead abundance were correlated with those of other regional winter steelhead stocks. Our assessment underscores the need for studies that (1) directly quantify the effects of hatchery fish on the production of natural‐origin salmon and steelhead, (2) empirically test published theories about mechanisms of hatchery fish impacts on natural‐origin populations, and (3) document population responses to major changes in hatchery programs.

Oregon↗

USGS2017

Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon

In 1992, Snake River basin fall Chinook salmon (Oncorhynchus tshawytscha) were listed for protection under the U.S. Endangered Species Act (NMFS 1992) and the population remained below 1000 individuals until 2000. Since then, returns from natural production has rebounded to over 20,000 spawners owing to a host of factors including reduced harvest (Peters et al. 2001), stable minimum spawning flows (Groves and Chandler 1999), summer flow augmentation (Connor et al. 2003), predator control (Beamesderfer et al. 1996), hatchery supplementation (Rosenberger et al. 2017), improved juvenile passage structures (Adams et al. 2014), summer spill operations (Perry et al. 2006; Adams et al. 2008), and periods of favorable ocean conditions and food availability (Logerwell et al. 2003; Peterson et al. 2014). Given this change in abundance coincident with numerous management actions and fluctuation in environmental drivers, quantifying which factors contributed to the observed rebound in natural production can provide critical insights into future management actions for this at-risk population. Multistage life cycle models provide a powerful analytical framework for understating how each life stage of a population contributes to population growth rate (Moussalli and Hilborn 1986; Greene and Beechie 2004). Multistage models may also be used as an analytical framework to explicitly estimate demographic parameters of a population model. This approach has an advantage over single-stage stock-recruitment models by allowing population growth rates to be partitioned among life stages rather than aggregated over an entire life cycle. Such partitioning allows for estimating 1) stage-specific density dependence, and 2) stage-specific effects of environmental factors or management actions. For example, Zabel et al. (2006) estimated parameters of a multistage model used in the context of a population viability analysis for spring/summer Chinook salmon in the Snake River, but such an approach has yet to be applied to fall Chinook salmon in the Snake River basin. Typically, data informing estimates of abundance at particular “check points” in the life cycle determines the complexity of the multistage model that can be fit to the data. For fall Chinook salmon, we are developing a two-stage model that encompasses: 1) upstream passage of spawners at Lower Granite Dam (LGR) to the subsequent downstream passage of their progeny at the dam, and 2) downstream passage of juveniles at LGR to their subsequent return from the ocean and passage at the Dam 2‒6 years later. This approach partitions the life cycle of fall Chinook salmon both spatially and temporally, which allows us to fit and compare alternative models with covariates specific to each stage. Our previous report to the ISAB (Zabel et al. 2013) detailed methods for estimating abundance of naturally produced adults and juveniles passing Lower Granite Dam, which provides the requisite data for fitting a two-stage model. The intent of this report is to describe the structure of the two-stage life cycle model, present preliminary results from fitting the model to data, and outline future directions and developments. As is clear from the diversity of models presented in this report, “life cycle models” range from very simple theoretically based population models (e.g., the Beverton-Holt stock- recruitment model) to very complex spatially explicit simulation models linked to hydrosystem hydrodynamic models (e.g., the COMPASS model for a single transition in a life cycle model, Zabel et al. 2008). We chose to develop a model of intermediate complexity that casts the two- stage life cycle model in a state-space framework (Newman et al. 2014). We chose to use a state-space framework implemented in a Bayesian framework because: • It provides both a statistical estimation framework for retrospective statistical analysis and a stochastic simulation framework for prospective analysis to evaluate alternative management actions. • Abundance estimates are uncertain. A state-space framework accounts for observation uncertainty in the abundance estimates and other data (e.g., age structure) while simultaneously estimating process uncertainty. • It allows for missing data. By drawing missing data from an appropriate probability model, uncertainty owing to missing data can be propagated without having to omit data or assume fixed values for missing data. Thus, a two-stage state-space life cycle model for fall Chinook salmon strikes an appropriate balance between model complexity, tractability, and applicability given the goals of performing both retrospective and prospective analysis to guide future management of this population.

Idaho, Oregon, Washington, Wyoming↗