Detecting a nearshore fish parade using the adaptive resolution imaging sonar (ARIS): An automated procedure for data analysis

Shahrestani, Suzan; Bi, Hongsheng; Lyubchich, Vyacheslav; Boswell, Kevin M.

doi:10.1016/j.fishres.2017.03.013

Cited by 37 publications

(29 citation statements)

References 32 publications

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“…Recorded depths of an individual were accurate to 0.1 m. Using interpolated transect tracks (s −1 ), we estimated the latitude and longitude of all counted C. chesapeakei . Sample volume and sample depth were calculated for each recorded frame using image analysis methods adapted from Shahrestani et al (2017). Frames were aggregated to standardize jellyfish counts to metric units, whereby C. chesapeakei medusa occurrence was summed within cubic meter bins (Fig.…”

Section: Methodsmentioning

confidence: 99%

Multi‐scale spatial dynamics of the Chesapeake Bay nettle, Chrysaora chesapeakei

Shahrestani

Liang

et al. 2020

Ecosphere

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Untangling organisms' multi-scale spatial distributions is challenging due to their interactions with environments at multiple spatial and temporal scales. We deployed an Adaptive Resolution Imaging Sonar (ARIS) in a Chesapeake Bay sub-estuary to investigate multi-scale spatial distributions of the bay nettle (Chrysaora chesapeakei) in May-September of 2016 and 2017. Nettles were found to be dispersed in aggregations of multiple individuals. The average density of bay nettles in 2017 was higher than in 2016. Small aggregations (<5 m) were persistent in both years but only contributed <10% of total observed nettles. Large patches (>30 m) contributed~40% of the total observed nettles. Large patches were more common in creek habitat where nettle density was higher. Nettle density was found to hit a peak value once in 2016, while there were two density peaks in 2017. Different aggregation patterns were observed during the second peak period in 2017 in which the number of large patches increased dramatically. Within the surveyed waterscape, the spatial patterns were consistent over time with higher abundance in the source creek than in the river channel, which underscores that C. chesapeakei requires hard substrate in shallow creeks for its benthic polyp stage. Using the ratio between nettles in the creek and near creek mouth as a proxy for dispersal rate, more nettles were transported out of the creek in 2017 than in 2016. The increase in patch size and high dispersion rate in peak periods in 2017 suggests that individuals were moving out of the creek habitat as density increased. Results highlight the complex spatial structure of bay nettles, which has major impacts on density estimates and subsequently affects our understanding of jellyfish population dynamics and long-term trends.

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Section: Methodsmentioning

confidence: 99%

Multi‐scale spatial dynamics of the Chesapeake Bay nettle, Chrysaora chesapeakei

Shahrestani

Liang

et al. 2020

Ecosphere

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“…This segmentation technique was utilized by Shahrestani et al (2017) to analyze sonar footage of swimming fish and improve estimations of fish abundance at a fixed location. Cheng et al (2019) drew upon the technique to develop and test an enhanced convolutional neural network for improved plankton image recognition that can be applied to images acquired from different systems.…”

Section: Advancements In Studying Oil Particle and Microbial Interactionsmentioning

confidence: 99%

Technological Developments Since the Deepwater Horizon Oil Spill

Dannreuther¹,

Halpern²,

Rullkötter³

et al. 2021

Oceanog

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The Gulf of Mexico Research Initiative (GoMRI) program funded research for 10 years following the Deepwater Horizon incident to address five themes, one of which was technology developments for improved response, mitigation, detection, characterization, and remediation associated with oil spills and gas releases. This paper features a sampling of such developments or advancements, most of which cite studies funded by GoMRI, but we also include several developments that occurred outside this program. We provide descriptions of new techniques or the novel application or enhancement of existing techniques related to studies on the evolution of the subsurface oil plume, the collection of data on ocean currents to support oil transport modeling, and oil spill modeling. We also feature developments related to the interactions of oil with particulate matter and microbial organisms, sampling for studies and analysis of biogeochemical processes related to oil fate, human health risks from inhalation of oil spill chemicals, impacts on marine life, and alternative dispersant technologies to Corexit®. Many of the techniques featured here have contributed to complementary or subsequent research and have applications beyond oil spill research that can contribute to a wide range of scientific endeavors.

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“…The technology is most commonly used in dark and turbid waters where optical systems cannot capture meaningful data. Their applications are diverse and allow for the direct observation and recording of fish migration, fish behavior near migratory barriers, cooling water withdrawals, hydroelectric plants, bypass systems, spawning grounds, natural and artificial structures and fishing equipment [9,[36][37][38][39][40][41].…”

Section: Detailed Investigation Of Fish Behaviormentioning

confidence: 99%

Hydroacoustic and Pressure Turbulence Analysis for the Assessment of Fish Presence and Behavior Upstream of a Vertical Trash Rack at a Run-of-River Hydropower Plant

2018

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The spatial distribution of fish upstream of a vertical trash rack was investigated at the hydropower plant Kirchbichl in the alpine River Inn (Tyrol, Austria). The objective of the research project “FIDET” was to establish a non-invasive methodology to study fish presence and flow characteristics at large hydro power sites. A new monitoring approach was developed combining hydroacoustic observations of fish locations with multivariate hydrodynamic data. This was accomplished by utilizing complementary observations from multiple underwater sensor technologies: First, an array of echosounders were deployed at a fixed cross-section upstream of the trash rack for long-term monitoring. Afterwards, detailed underwater surveys with “acoustic cameras” (DIDSON and ARIS) revealed that the spatial distributions of fish in front of the trash rack were highly heterogeneous. The spatial distribution of the flow field was assessed via the time-averaged velocity fields from acoustic Doppler current profiler (ADCP). Finally, a custom pressure-based flow turbulence probe was developed, providing spatial estimates of flow turbulence immediately upstream of the trash rack. The significant contribution of this work is to provide a multi-modal monitoring approach incorporating both fish position data and hydrodynamic information. This forms the starting point for a future objective, namely to create an automated, sonar-based detection and control systems to assist and monitor fish protection operations in near real-time.

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Detecting a nearshore fish parade using the adaptive resolution imaging sonar (ARIS): An automated procedure for data analysis

Cited by 37 publications

References 32 publications

Multi‐scale spatial dynamics of the Chesapeake Bay nettle, Chrysaora chesapeakei

Multi‐scale spatial dynamics of the Chesapeake Bay nettle, Chrysaora chesapeakei

Technological Developments Since the Deepwater Horizon Oil Spill

Hydroacoustic and Pressure Turbulence Analysis for the Assessment of Fish Presence and Behavior Upstream of a Vertical Trash Rack at a Run-of-River Hydropower Plant

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