Geology topics

Song S. Qian

Publications and source records attributed to Song S. Qian.

At least 19 recordsLinked to original sources

USGS2026

Bayesian hierarchical model of lake whitefish cohort strength from sparse trawl data

Recruitment indices for rare or intermittently recruiting fishes are needed to compare year classes and evaluate recruitment drivers, but sparse trawl data with many zero-catch observations complicate estimation. We used fall bottom trawl data from New York, Pennsylvania, and Ohio surveys in Lake Erie's central and eastern basins to estimate annual relative cohort strength of age-0 lake whitefish ( Coregonus clupeaformis ) from 1992 to 2021 and evaluate whether a Bernoulli-Bernoulli presence-absence model retained enough information for an annual relative cohort strength index compared with a Binomial-Poisson count model. We fixed detection probability at 0.31 in the primary analysis and refit both models using alternative fixed values in sensitivity analyses. Among 2879 tows, 173 were positive and 368 fish were collected, with positive catches ranging from 1 to 20 fish. Annual catch per unit area and both models recovered a similar recruitment pattern, with variable recruitment from 1992 to 2005, little to no recruitment from 2006 to 2014, and renewed recruitment in most years from 2015 to 2021. Cohort rank order was stable across fixed detection values (Spearman r s = 0.996 to 1.000), and annual median estimates maintained high agreement with the primary analysis (Pearson r = 0.966 to 1.000). However, Bernoulli-Bernoulli estimates were not one-to-one with Binomial-Poisson estimates, and relative magnitude depended on assumed detection probability. These results indicate that the Bernoulli-Bernoulli simplification is adequate for recovering cohort strength patterns, but the Binomial-Poisson model is more appropriate for distinguishing relative cohort strength among years.

New York, Ohio, Pennsylvania↗

USGS2026

Identifying overlap between native fish movements and a possible seasonal Grass Carp deterrent in the Sandusky River, Ohio, USA

Riverine fishes are vulnerable to habitat fragmentation caused by interrupted access to vital habitats. Fragmentation using artificial structures can be used to limit the spread of invasive fishes by inhibiting movement between critical habitats. Thus, tradeoffs exist between maintaining connectivity for native species and restricting movement of invasive fishes. A nonphysical deterrent has been proposed to prevent invasive Grass Carp ( Ctenopharyngodon idella ) from reaching spawning habitats in the Sandusky River, a tributary to Lake Erie, during late spring–summer. However, this timing overlaps with spawning periods of a suite of native fishes. We used acoustic telemetry and ichthyoplankton surveys to examine movement and spawning activity of multiple native species and to assess potential impacts of deterrent operation on reproduction. All species used the proposed deterrent location during the Grass Carp spawning period, and their movements corresponded with larval fish collections, indicating upstream spawning. These findings suggest the deterrent could unintentionally restrict native species’ access to essential habitats. Balancing habitat connectivity and invasive species control will likely depend on species-specific responses and careful timing of deterrent operation.

Ohio↗

USGS2026

On the importance of ichthyoplankton monitoring for invasive grass carp control in the Laurentian Great Lakes

Grass carp ( Ctenopharyngodon idella ) is an invasive herbivore observed in small numbers in the Laurentian Great Lakes since the 1980 s with records from all lakes except Lake Superior. Identification of diploid, age-1 + grass carp from the Sandusky River, a Lake Erie tributary, in 2012, prompted targeted efforts to evaluate the status of grass carp reproduction in the Lake Erie Basin. In 2014, researchers from the U.S. Geological Survey and University of Toledo began surveys to assess grass carp spawning in the Great Lakes, with the first fertilized eggs discovered in 2015 in the Sandusky River. Eight Great Lakes tributaries in the United States have been surveyed for evidence of grass carp spawning, identifying three confirmed spawning tributaries (Sandusky, Maumee, and Huron Rivers in Ohio). Initial work identified specific flow and temperature conditions that likely stimulate spawning. Egg and larval drift modeling estimated spawning locations based on egg development and flow characteristics, which helped removal crews locate and target spawning fish in the Sandusky River and later, the Maumee River. The research synthesized herein demonstrates the value of ichthyoplankton research to inform control of emerging invasive species and could inform management of other invasive carps with similar reproductive life histories, should they enter the Great Lakes.

Michigan, Ohio↗

USGS2026

A Bayesian hierarchical modeling approach for species diversity in ecology

Species diversity is the foundation of many ecological disciplines. This metric is often approximated using species richness and evenness, even though actual richness likely exceeds observations due to imperfect sampling methods. Estimating the “true” species richness, which includes identifying the number of missing species, has intrigued ecologists for decades. We adopted a parametric model that appeared in Fisher et al. (1943), which models the numbers of individuals from different species as random samples from a negative binomial distribution, and developed a Bayesian computational approach to directly estimate the distribution model parameters. The model parameters represent species abundance and evenness, and can be used to derive species richness. We evaluated our parametric approach using (1) a simulation study and (2) three historical data sets. Furthermore, we illustrated the hierarchical modeling approach to combine data from multiple parallel studies using a biannual fishery survey data set. Our parametric model formulation is computationally efficient, and the hierarchical structure facilitates embedding diversity estimation into broader application, such as assessing spatial and temporal trends in species diversity associated with environmental stressors. Additionally, because the two parameters of the negative binomial distribution model represent species abundance and evenness of a community, this parametric approach facilitates a deeper understanding of the ecological systems under study. The negative binomial distribution model works with a wide range of species frequency distribution types. As a result, our emphasis on a parametric model can help us characterize the structure of an ecosystem and provide a greater depth of ecologically meaningful information.

Ecological Informatics↗

USGS2025

Dead giveaway: Rising mortality rates suggest effectiveness of Lake Erie grass carp (Ctenopharyngodon idella) response

Grass carp ( Ctenopharyngodon idella ) are large, invasive fish that threaten Lake Erie’s economy and ecosystem. Incidental catches of grass carp have occurred since the 1980s in Lake Erie, while multi-day removal events were carried out in 2014 and 2017. To mitigate ecosystem impacts, a large-scale, multi-agency response to remove as many grass carp as possible from the Lake Erie basin (“strike teams”) began in 2018 and has increased every year. To date, total annual removals of fish has been the primary measure of progress; however, total annual removals do not indicate how efforts are affecting the grass carp population. Population vital rates, such as mortality rate, can indicate population demographic changes and may provide an alternative approach to measure how removals have impacted the grass carp population. We estimated annual mortality rates using 553 grass carp, representing 82.9 % of all grass carp removed in the Lake Erie basin, using a hierarchical catch-curve model and catch-at-age data from 2014 to 2022. Annual average mortality rates were initially low (4.3 %) and increased between 2017 and 2022 with the highest mortality (13.6 %) observed in 2021. Positive correlations between mortality and the number of fish harvested per year suggest that removals may be driving increases in the grass carp mortality rate. This increase in mortality rate shows promise for controlling the spread of grass carp within the Lake Erie ecosystem. This research supports the needs of fishery managers to better understand grass carp population dynamics and the adaptive management framework identified in the Lake Erie Grass Carp Adaptive Response Strategy.

Lake Erie↗

USGS2025

Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River

Natural resources management is often concerned with conserving rare-native or controlling rare-invasive fishes. Informing and assessing conservation and control efforts frequently requires information from captures. When little is understood about spatial and temporal fish distributions, captures can be infrequent and costly. If successful management depends on effective management response, optimizing for efficiency may be the difference between success and failure. We compared per vessel hour capture efficiencies for invasive grass carp ( Ctenopharyngodon idella ) between two methods: electrofishing-only (electrofishing) and in combination with a trammel net (combination). Capture and effort information including 174 captures from 1853 capture attempts from 1706 total hours of effort in the Sandusky River, OH, USA from 2020–2023 was used to fit a generalized linear model. Captures were allowed to vary by river kilometer, month, and year to account for unequal capture rates and effort. Captures were offset by total vessel hours or the count of independent efforts to compare methods that prioritize detection at a single location (e.g., combination) to methods that prioritize exploiting more locations (e.g., electrofishing). Including trammel nets was intended to increase single site detection, but we found that electrofishing-only was at least 2.4x more efficient (catch per vessel hour) than when combined with a trammel net with no significant difference in catch per removal effort. Complex methods intended to increase single site detection may reduce the number of efforts completed. Therefore, overall capture efficiency and total capture numbers for rare fish may be increased through methods that prioritize per-hour efficiency.

Ohio↗

USGS2024

Assessing the probability of grass carp (Ctenopharyngodon idella) spawning in the Sandusky River using discharge and water temperature

Grass carp ( Ctenopharyngodon idella , Val.) is an invasive species in the Laurentian Great Lakes region with the potential for damaging the lake ecosystem and harming the region's economy. Grass carp spawning was documented in the Sandusky River, Ohio, in 2015 through targeted egg sampling. Continued egg sampling in the Sandusky River suggested that grass carp spawning is related to discharge and water temperature. We used egg sampling data from 2014 to 2021 to develop a Bayesian model to understand the likely conditions related to grass carp spawning in the Lake Erie watershed. The resulting model estimates the likelihood of spawning as a function of discharge and water temperature. The results suggest that spawning is most likely to occur when discharge is above 10 m 3 /s and water temperature is below 25 ℃. The model provides a tool for setting research and management priorities to develop management strategies to reduce the grass carp population in Lake Erie. Furthermore, the Bayesian nature of the model makes the model updatable when new data are available, whether from the same river or from another river, to incorporate river-specific features to identify likely spawning rivers.

Ohio↗

USGS2024

Reproduction of grass carp (Ctenopharyngodon idella) in the Maumee River, Ohio: Part 1—Spawning area identification using bidirectional drift modeling

Control of invasive grass carp ( Ctenopharyngodon idella ) populations in the Western Lake Erie Basin merits adaptive management guided by the best available science. Presently (2024), capture of mature grass carp in rivers during spawning season is most efficient, so knowing when and where grass carp are spawning is essential information for natural resource agencies. Using bidirectional drift modeling and grass carp ichthyoplankton samples captured in the Maumee River during the 2017–2019 spawning seasons, this study identified 12 probable grass carp spawning areas in the lower 96.5-kilometers of the Maumee River. These spawning areas were located both above and below the Grand Rapids/Providence low-head dams. Three areas showed evidence of multiyear use, while nine had multi-event use. Spawning activity had no definitive diel variation and occurred at an average photoperiod of 15.15 h. The maturation metric ADD15, or annual degree days above 15 degrees Celsius, generally exceeded the 655 threshold for spawning; however, some spawning occurred when ADD15 ≤235, indicating spawners likely matured in a warmwater discharge. The probable spawning areas were generally characterized by mean velocities between 0.4 and 2.1 m per second (with locally higher velocities possible), areas of high turbulence produced by dam spillways or bedrock outcroppings, channel constrictions, confluences, islands, and bridges with piers in the water. Spawning suitability indices (SSI), based on velocity, varied considerably between spawning areas and SSI models. These results could be used to inform control efforts and predict potential grass carp spawning locations in other rivers under threat of invasion.

Ohio↗

USGS2024

First documentation of grass carp spawning in Lake Erie’s Central Basin

Grass carp ( Ctenopharyngodon idella ) are non-indigenous to North America having been translocated to the United States in the 1960s as a potential non-chemical solution for nuisance aquatic vegetation. Reproductively viable grass carp now exist in many watersheds in the United States. In the Great Lakes basin, grass carp were first discovered in the 1980s with direct confirmation of successful reproduction in 2015 via collection of fertilized grass carp eggs in the Sandusky River. Early life stage monitoring also confirmed reproduction in the Maumee River in 2017. During 2018–2021, no new spawning tributaries were discovered (18 total sampling events in five Great Lakes tributaries). In 2022, fourteen eggs with characteristics similar to grass carp were identified from the Huron River which is a tributary to Lake Erie’s Central Basin. Eggs were identified to species via DNA sequencing and were determined to be grass carp eggs. The confirmation of spawning in the Huron River represents a third spawning tributary in the Lake Erie basin and expands eastward the geographic extent of known grass carp spawning locations. Presently, the ability of the Huron River to support hatching and survival of larval grass carp is unknown. Discovery of the Huron River as a grass carp spawning tributary identifies the value of continued surveillance in Great Lakes tributaries for early life stages and conducting scientific inquiries evaluating the consistency of tributary use and survival of early life stages.

Ohio↗

USGS2024

Capturing potential: Leveraging grass carp behavior Ctenopharyngodon idella for enhanced removal

Effective management of invasive species benefits from a comprehensive understanding of the species’ behavior and interactions with the invaded system. We investigated temporal dynamics of telemetry detections and the potential utility of a traitor approach for informing response efforts to the invasive grass carp ( Ctenopharyngodon idella ) population in the Sandusky River, a major tributary to Lake Erie. Telemetered grass carp exhibited heightened activity at night and early morning, suggesting that capture and removal be more effective during these time periods. Analysis of catch per unit effort (CPUE) across different removal methods, trammel nets, electrofishing, and hoop nets. suggested that incorporating the traitor approach could improve capture. Low catchability values (<0.026), based on the number of telemetered grass carp present in the river on a weekly basis and the number of those telemetered fish captured, suggest the species is difficult to capture. Optimizing response effort efficiency is important and refining catchability estimates will lessen errors in population models and improve interpretation of low CPUE data. Results from generalized additive models suggest capture could be improved using telemetry data, night removals, and by attempting exploratory removal efforts in fall and winter months. By incorporating telemetry data and acknowledging the complexities of grass carp behavior and ecology, we found that a multifaceted and data-driven approach to invasive species control could be beneficial, ultimately promoting conservation and sustainability in dynamic ecosystems like Lake Erie.

Ohio↗

USGS2024

Electrofishing Sandusky River grass carp spawning grounds may disrupt spawning

Invasive grass carp Ctenopharyngodon idella spawning was confirmed in Lake Erie with the collection of fertilized eggs in the Sandusky River, Ohio in 2015. Managers responded with initiation of adult grass carp removal in 2017. Hydrodynamic modeling revealed a potential spawning location in downtown Fremont, Ohio (41.3455; −83.1110), which was supported by the presence of sexually mature adults. Egg detection and adult removals appear to coincide with periods of elevated discharge and suitable water temperatures. Electrofishing is the primary method for removing adults during spawning, however, it is unknown if this has indirect effects such as disruption of grass carp spawning; thereby lowering egg presence in ichthyoplankton samples. We used a binomial generalized linear model to predict the probability of grass carp egg presence (≥ 1 egg) in a paired ichthyoplankton net based on the presence of electrofishing in the spawning grounds and net depth using 2017–2022 data. Further, we carried out a field experiment to isolate the effect of electrofishing by sampling eggs at two sites before and during electrofishing in the spawning grounds in 2022. Analysis of 2017–2022 egg and electrofishing data suggested that grass carp egg presence in a paired ichthyoplankton net was significantly higher without electrofishing and in nets towed at a depth of 1.5 m compared to surfacetowed nets. Data analysis from the field experiment revealed a significant negative relationship between electrofishing in the spawning grounds and grass carp egg collections downstream. Both analyses suggested lower egg capture rates associated with electrofishing in the spawning grounds, although other factors should be further quantified. Consequently, electrofishing may cause a short-term disruption in grass carp spawning in the Sandusky River and could reduce spawning during preferred conditions.

Ohio↗

USGS2023

Evaluating population trends of juvenile Atlantic Sturgeon at low abundance in a dynamic estuarine environment (Hudson River, New York)

Evaluating population trends in dynamic estuarine environments can be challenging, especially when survey data include a high percentage of zero observations. In fishery-independent surveys, zeros that come from reduced susceptibility to sample gears and reduced availability of the population to the survey impact survey catchability and negatively bias relative abundance indices. A zero-inflated negative binomial model was used to standardize a juvenile Atlantic Sturgeon ( Acipenser oxyrinchus oxyrinchus ) relative abundance index (Hudson River, New York) that included a high proportion (42%) of zero observations and intra- and interannually variable covariates. Reduced susceptibility was related to low water temperature, with the percentage of zeroes increasing rapidly below 7°C. Availability was influenced by temperature and distance to salt front, as catch rates increased with temperature and peaked in mesohaline waters ~27 km downstream of the predicted salt front. An alternative index suggested significant population growth ( r = 0.15; p -value = 0.007) occurred from 2004 to 2015. The zero-inflated model helped better understand Hudson River juvenile Atlantic Sturgeon ecology and relative trends in abundance, to better inform future management and monitoring decisions along the Atlantic Coast.

New York↗

USGS2023

Estimating phosphorus retention capacity of flow-through wetlands

A Bayesian hierarchical modeling approach is introduced to pool data properly from multiple flow-through wetlands to estimate wetland-specific long-term phosphorus retention capacity. By pooling data from multiple wetlands, we overcome the difficulties in estimating the effectiveness of using constructed and natural wetlands for nutrient reduction. The Bayesian hierarchical modeling approach reduces estimation uncertainty by shrinking wetland-specific estimates towards the overall average of the same quantity from multiple wetlands, facilitating information sharing across sites, thereby reducing the demand on sample sizes from individual wetlands and avoiding several common pitfalls of using large data (i.e., from multiple systems) induced by Simpson's paradox. In this paper, we develop a sequential updating framework to alleviate the computational burden of compiling and modeling data from multiple wetlands. We then demonstrate the sequential updating process to estimate retention capacity of a suite of wetlands in Ohio, USA. A total of four wetlands, representing both natural and constructed wetlands, were used. The estimated total phosphorus retention capacities range less than 0.01 to well over 1 ton per year per system. As wetland restoration initiatives expand around the Laurentian Great Lakes and nationally, this model serves as an important initial step in developing tools to meet nutrient reduction goals and standards. Extending this work, we have developed a publicly accessible on-line open computation platform that can help natural resource specialists better plan for wetland efficacy in the future.

Ecological Engineering↗

USGS2022

Bayesian applications in environmental and ecological studies with R and Stan

Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. Bayesian Applications in Evnironmental and Ecological Studies with R and Stan provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data. Features: An accessible overview of Bayesian methods in environmental and ecological studies Emphasizes the hypothetical deductive process, particularly model formulation Necessary background material on Bayesian inference and Monte Carlo simulation Detailed case studies, covering water quality monitoring and assessment, ecosystem response to urbanization, fisheries ecology, and more Advanced chapter on Bayesian applications, including Bayesian networks and a change point model Complete code for all examples, along with the data used in the book, are available via GitHub The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.

Book↗

USGS2021

Validation of the model-predicted spawning area of grass carp Ctenopharyngodon idella in the Sandusky River

Spawning of grass carp, Ctenopharyngodon idella, in the Great Lakes basin was verified when eight fertilized eggs were collected in the Sandusky River, a tributary to Lake Erie, in 2015. Using a fluvial drift model (FluEgg) and simulation modeling, researchers predicted the fertilization location for those eggs was 3.8 ± 1 km (95% credible interval, CI) downstream of Ballville Dam. In June 2018, simultaneous collection of fertilized eggs and adults within the model-predicted spawning area provided the opportunity to verify the fertilization location. We used estimated developmental time (Dt) of eggs calculated from developmental stages, water temperature, and an equation that predicts Dt from cumulative thermal units experienced by developing eggs, in two analyses. First, we regressed Dt versus location of capture and solved that equation for developmental time of 0 hrs (Dt 0 ) to estimate fertilization location. Second, we used Dt in the Fluvial Drift Simulator (FluEgg) to simulate 23 scenarios representative of drift conditions throughout the spawning event using the model-predicted spawning area and the site of Ballville Dam as potential spawning locations. Regression analysis placed the mean fertilization location 3.36 km (95% CI 2.27, 4.24) downstream of the site of Ballville Dam, within the model-predicted spawning area. Drift models demonstrated the model-predicted spawning area was best supported. Histograms of fertilization times overlapped with capture times by boat electrofishing of diploid adult grass carp in the model-predicted spawning area. This suite of analyses confirms the model-predicted spawning area and validates the methodology used to locate it.

Ohio↗

USGS2021

Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach

A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics , and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.

North Carolina, South Carolina, Virginia↗

USGS2020

Evaluating catchability in a large-scale gillnet survey using hydroacoustics: Making the case for coupled surveys

Abundance estimates facilitate successful fisheries management. Fisheries agencies often monitor abundance through fishery independent standardized protocols generating relative measures such as catch-per-unit-effort (CPUE), where CPUE is assumed proportional to true abundance. Unfortunately, this assumption is rarely met as fish behavior and environmental conditions influence catchability and sample gear efficiency. We used paired gillnet and hydroacoustic samples and a catchability equation ( U i = q N i β "> U i =qN i β ) to assess the correspondence between gillnet CPUE ( U i "> U i ) and hydroacoustic abundance estimates ( N i "> N i ). We found that gill nets were hyperstable (i.e., β < 1) and efficiency declined along environmental gradients. These gradients, such as increased depths, and decreased turbidity and water temperatures, likely influenced fish behavior, and encounter and gear saturation rates. As a result, catchability declined with increasing abundance qacross survey regions. Finally, simulations showed that catchability gradients and variable migratory patterns can contribute to annual variation in CPUE indices regardless of changes in abundance. Surveys plagued by varying catchability could benefit from coupling with hydroacoustics, a sample gear less subject to gear efficiency and catchability issues.

Fisheries Research↗

USGS2019

Modeling framework to estimate spawning and hatching locations of pelagically-spawned eggs

Identifying spawning and hatching locations is vital to controlling invasive fish and conserving imperiled fish, which can be difficult for pelagically-spawning species with semi-buoyant eggs. In freshwater systems, this reproductive strategy is common among cyprinid species, such as Chinese carp species currently threatening the Great Lakes. Following the confirmation that one of these species, Grass Carp (Ctenopharyngodon idella), was spawning in a Great Lakes tributary, we developed a modeling framework to combine field data with hydraulic models to calculate the most probable spawning and hatching locations for collected eggs. Our results indicate that the estimated spawning location encompassed habitat consistent with spawning sites in Grass Carp’s native range. Additionally, all eggs were identified to have hatched in the river, increasing the likelihood of successful recruitment. This modeling framework can be used to estimate spawning and hatching locations for Chinese carp species, as well as all pelagic, riverine spawners. Spawning and hatching locations provide key information to researchers about the reproductive requirements of species and to agencies about how best to manage populations for control or restoration.

Canadian Journal of Fisheries and Aquatic Sciences↗