Geology topics

Song Qian

Publications and source records attributed to Song Qian.

4 recordsLinked to original sources

USGS2019

Effectiveness of shallow water habitat remediation for improving fish habitat in a large temperate river

Loss of shallow water riparian zones in the St. Clair River has reduced availability of nursery areas and refuge for fishes. To remediate habitat losses and provide fish nursery areas, five remediation projects were carried out along the river’s United States bank from 2012 to 2014, replacing seawalls with sloping banks and adding in-stream structure (e.g., root wads and boulders). Project evaluation is necessary to determine success, however there is no standard sampling protocol for shallow habitat in large rivers, especially when both adults and juvenile fishes should be targeted. Therefore, to assess remediation effectiveness and suggest appropriate sampling techniques for large river shorelines, we employed a multi-gear sampling strategy targeting multiple fish species and life history stages at five shoreline remediation and four control sites. We collected juvenile fishes with minnow traps and backpack electrofishing and adult fishes with gillnets. Poisson models were used to evaluate catch per unit effort (CPUE) differences between remediation and control sites for species of management priority (e.g., game fishes and rare species) and taxonomic groups. Model estimates were then used to calculate proportional abundances and compare species composition between site types. Results indicated that electrofishing CPUEs of Darters, mottled sculpin Cottus bairdi , rare threatened and endangered species, and juvenile and adult Centrarchidae were higher at remediation sites than at control sites. Additionally, juvenile Centrarchidae and mottled sculpin had a higher proportional abundance in electrofishing collections at remediation sites than at control sites. In contrast, CPUEs and proportional abundances were similar for all taxonomic and management priority groups of fish collected in minnow traps and gillnets. Electrofishing captured more species and more individuals and is therefore a valuable sampling technique for large river shorelines. Nevertheless, addition of minnow traps and gillnets allowed for a more comprehensive assessment of fish assemblages. Overall, this multi-faceted survey approach demonstrates that shoreline remediation projects were beneficial to recreational and ecologically important species in the St. Clair River.

Michigan, Ontario↗

USGS2017

Sparse targets in hydroacoustic surveys: Balancing quantity and quality of in situ target strength data

Hydroacoustic sampling of low-density fish in shallow water can lead to low sample sizes of naturally variable target strength (TS) estimates, resulting in both sparse and variable data. Increasing maximum beam compensation (BC) beyond conventional values (i.e., 3 dB beam width) can recover more targets during data analysis; however, data quality decreases near the acoustic beam edges. We identified the optimal balance between data quantity and quality with increasing BC using a standard sphere calibration, and we quantified the effect of BC on fish track variability, size structure, and density estimates of Lake Erie walleye ( Sander vitreus ). Standard sphere mean TS estimates were consistent with theoretical values (−39.6 dB) up to 18-dB BC, while estimates decreased at greater BC values. Natural sources (i.e., residual and mean TS) dominated total fish track variation, while contributions from measurement related error (i.e., number of single echo detections (SEDs) and BC) were proportionally low. Increasing BC led to more fish encounters and SEDs per fish, while stability in size structure and density were observed at intermediate values (e.g., 18 dB). Detection of medium to large fish (i.e., age-2+ walleye) benefited most from increasing BC, as proportional changes in size structure and density were greatest in these size categories. Therefore, when TS data are sparse and variable, increasing BC to an optimal value (here 18 dB) will maximize the TS data quantity while limiting lower-quality data near the beam edges.

Ohio↗

USGS2016

First direct confirmation of grass carp spawning in a Great Lakes tributary

Grass carp ( Ctenopharyngodon idella ), an invasive species of Asian carp, has been stocked for many decades in the United States for vegetation control. Adult individuals have been found in all of the Great Lakes except Lake Superior, but no self-sustaining populations have yet been identified in Great Lakes tributaries. In 2012, a commercial fisherman caught four juvenile diploid grass carp in the Sandusky River, a major tributary to Lake Erie. Otolith microchemistry and the capture location of these fish permitted the conclusion that they were most likely produced in the Sandusky River. Due to this finding, we sampled ichthyoplankton using paired bongo net tows and larval light traps during June–August of 2014 and 2015 to determine if grass carp are spawning in the Sandusky River. From the samples collected in 2015, we identified and staged eight eggs that were morphologically consistent with grass carp. Five eggs were confirmed as grass carp using quantitative Polymerase Chain Reaction for a grass carp-specific marker, while the remaining three were retained for future analysis. Our finding confirms that grass carp are naturally spawning in this Great Lakes tributary. All eggs were collected during high-flow events, either on the day of peak flow or 1–2 days following peak flow, supporting an earlier suggestion that high flow conditions favor grass carp spawning. The next principal goal is to identify the spawning and hatch location(s) for the Sandusky River. Predicting locations and conditions where grass carp spawning is most probable may aid targeted management efforts.

Lake Erie, Sandusky River↗

USGS2012

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

Urban development alters important physical, chemical, and biological processes that define urban stream ecosystems. An approach was developed for quantifying the effects of these processes on aquatic biota, and then linking those effects to endpoints that can be used for environmental management. These complex, interacting systems are challenging to model from a scientific standpoint. A desirable model clearly shows the system, simulates the interactions, and ultimately predicts results of management actions. Traditional regression techniques that calculate empirical relations between pairs of environmental factors do not capture the interconnected web of multiple stressors, but urban development effects are not yet understood at the detailed scales required to make mechanistic modeling approaches feasible. Therefore, in contrast to a fully deterministic or fully statistical modeling approach, a Bayesian network model provides a hybrid approach that can be used to represent known general associations between variables while acknowledging uncertainty in predicted outcomes. It does so by quantifying an expert-elicited network of probabilistic relations between variables. Advantages of this modeling approach include (1) flexibility in accommodating many model specifications and information types; (2) efficiency in storing and manipulating complex information, and to parameterize; and (3) transparency in describing the relations using nodes and arrows and in describing uncertainties with discrete probability distributions for each variable. In realization of the aforementioned advantages, a Bayesian network model was constructed to characterize the effect of urban development on aquatic macroinvertebrate stream communities through three simultaneous, interacting ecological pathways affecting stream hydrology, habitat, and water quality across watersheds in the Northeastern United States. This model incorporates both empirical data and expert knowledge to calculate the probabilities of attaining desired aquatic ecosystem conditions under different urban stress levels, environmental conditions, and management options. Ecosystem conditions are characterized in terms of standardized Biological Condition Gradient (BCG) management endpoints. This approach to evaluating urban development-induced perturbations in watersheds integrates statistical and mechanistic perspectives, different information sources, and several ecological processes into a comprehensive description of the system that can be used to support decision making. The completed model can be used to infer which management actions would lead to the highest likelihood of desired BCG tier achievement. For example, if best management practices (BMP) were implemented in a highly urbanized watershed to reduce flashiness to medium levels and specific conductance to low levels, the stream would have a 70-percent chance of achieving BCG Tier 3 or better, relative to a 24-percent achievement likelihood for unmanaged high urban land cover. Results are reported probabilistically to account for modeling uncertainty that is inherent in sources such as natural variability and model simplification error.

Scientific Investigations Report↗