Can otolith chemistry be used for identifying essential seagrass habitats for juvenile spotted seatrout, Cynoscion nebulosus, in Chesapeake Bay?

2005 ◽  
Vol 56 (5) ◽  
pp. 645 ◽  
Author(s):  
Emmanis Dorval ◽  
Cynthia M. Jones ◽  
Robyn Hannigan ◽  
Jacques van Montfrans
Keyword(s):  
Trace Elements ◽  
Chesapeake Bay ◽  
Classification Accuracy ◽  
Spatial Scales ◽  
Juvenile Fish ◽  
Spotted Seatrout ◽  
Otolith Chemistry ◽  
Seagrass Beds ◽  
Cynoscion Nebulosus ◽  
High Classification Accuracy

We investigated the variability of otolith chemistry in juvenile spotted seatrout from Chesapeake Bay seagrass habitats in 1998 and 2001, to assess whether otolith elemental and isotopic composition could be used to identify the most essential seagrass habitats for those juvenile fish. Otolith chemistry (Ca, Mn, Sr, Ba, and La; δ13C, δ18O) of juvenile fish collected in the five major seagrass habitats (Potomac, Rappahannock, York, Island, and Pocomoke Sound) showed significant variability within and between years. Although the ability of trace elements to allocate individual fish may vary between years, in combination with stable isotopes, they achieve high classification accuracy averaging 80–82% in the Pocomoke Sound and the Island, and 95–100% in the York and the Potomac habitats. The trace elements (Mn, Ba, and La) provided the best discrimination in 2001, a year of lower freshwater discharge than 1998. This is the first application of a rare earth element measured in otoliths (La) to discriminate habitats, and identify seagrass habitats for juvenile spotted seatrout at spatial scales of 15 km. Such fine spatial scale discrimination of habitats has not been previously achieved in estuaries and will distinguish fish born in individual seagrass beds in the Bay.

Relating otolith chemistry to surface water chemistry in a coastal plain estuary

2007 ◽  
Vol 64 (3) ◽  
pp. 411-424 ◽  
Author(s):  
Emmanis Dorval ◽  
Cynthia M Jones ◽  
Robyn Hannigan ◽  
Jacques van Montfrans
Keyword(s):  
Water Chemistry ◽  
Juvenile Fish ◽  
Spotted Seatrout ◽  
Otolith Chemistry ◽  
Cynoscion Nebulosus ◽  
Environmental Tracers ◽  
Surface Water Chemistry ◽  
Water Composition ◽  
Temperature Exposure ◽  
The Relationship

Although laboratory studies confirm that otoliths incorporate trace elements and stable isotopes from surrounding waters, few studies explore the relationship of otolith chemistry to water chemistry in the field and none include a larger suite of environmental tracers, such as rare earth elements. Using spotted seatrout (Cynoscion nebulosus) as model species, we tested the hypothesis that otoliths record the water chemistry of seagrass habitats in Chesapeake Bay. In summer 2001, we sampled water and juvenile fish in seagrass beds of the bay. Weighted linear regressions showed that [Ba/Ca]otolith and [La/Ca]otolith were best predicted by salinity and were modeled as [Ba/Ca]otolith (µmol·mol–1) = –2.25 ± 0.35 × salinity + 59.47 ± 7.01) and [La/Ca]otolith (pmol·mol–1) = –8.71 ± 0.65 × salinity + 243.87 ± 12.52. [Ba/Ca]otolith increased with [Ba/Ca]water, but the relationship was nonlinear. Salinity did not influence [Mn/Ca]otolith, but this ratio was positively correlated with [Mn/Ca]water. Although the partition coefficient of Sr (DSr = 0.23 ± 0.019) was similar to that in laboratory experiments, [Sr/Ca] in waters and otoliths was decoupled despite equal temperature exposure, suggesting that [Sr/Ca]otolith concentration may not be a simple function of water composition. However, there was a predictive relationship between [δ18O]otolith and [Sr/Ca]water ([δ18O]otolith = 1.18 ± 0.09 × [Sr/Ca]water (mmol·mol–1) – 14.286 ± 0.78) resulting from mixing between fluvial and oceanic waters. Water chemistry showed mixed values as a proxy for otolith chemistry and may not be a surrogate for otolith chemistry in wide estuaries.

scholarly journals Acoustic monitoring indicates a positive relationship between calling frequency and spawning in captive spotted seatrout (Cynoscion nebulosus)

2016 ◽  
Author(s):  
Eric W Montie ◽  
Matt Hoover ◽  
Chris Kehrer ◽  
Justin Yost ◽  
Karl Brenkert ◽  
...  
Keyword(s):  
Sound Production ◽  
Spatial Scales ◽  
Reproductive Activity ◽  
Acoustic Monitoring ◽  
Spotted Seatrout ◽  
Light Cycle ◽  
Cynoscion Nebulosus ◽  
Underwater Sound ◽  
Spawning Period ◽  
Spawning Aggregations

Background: Fish sound production is widespread throughout many families. Agonistic and courtship behaviors are the most common reasons for fish sound production. Yet, there is still some debate on how sound production and spawning are correlated in many soniferous fish species. In the present study, our aim was to determine if a quantitative relationship exists between calling and egg deposition in captive spotted seatrout (Cynoscion nebulosus). This type of data is essential if scientists and managers plan to use acoustic metrics to identify spawning aggregations over large spatial scales and monitor reproductive activity over annual and decadal timeframes.Methods: Wild caught spotted seatrout were held in three laboratory tanks equipped with long-term acoustic loggers (i.e., DSG-Oceans) to record underwater sound throughout an entire, simulated reproductive season. Acoustic monitoring occurred from April 13 to December 19, 2012 for Tank 1 and from April 13 to November 21, 2012 for Tanks 2 and 3. DSG-Oceans were scheduled to record sound for 2 min every 20 min. We enumerated the number of calls, calculated the received sound pressure level (SPL in dB re 1 µPa; between 50 and 2000 Hz) of each 2 min ‘wav file’, and counted the number of eggs every morning in each tank.Results: Spotted seatrout produced three distinct call types characterized as “drums”, “grunts”, and “staccatos”. Spotted seatrout calling increased as the light cycle shifted from 13.5 to 14.5 h of light, and the temperature increased to 27.7oC. Calling began to decrease once the temperature fell below 27.7 oC, and the light cycle shifted to 12 h of light. These captive settings are similar to the amount of daylight and water temperatures observed during the summer, which is the primary spawning period of spotted seatrout. Spotted seatrout exhibited daily patterns of calling. Sound production began once the lights turned off, and calling reached maximum activity approximately 3 h later. Spawning occurred only on evenings in which spotted seatrout were calling. Significantly more calling and higher mean SPLs occurred on evenings in which spawning occurred as compared to evenings in which spawning did not occur. Spawning was more productive when spotted seatrout produced more calls. For all tanks, more calling and higher SPLs were associated with more eggs released by females.Discussion: The fact that more calling and higher SPLs were associated with spawns that were more productive indicates that acoustic metrics can provide quantitative information on spotted seatrout spawning in the wild. These findings will help us to identify spawning aggregations over large spatial scales and monitor the effects of noise pollution, water quality, and climatic changes on reproductive activity using acoustic technology.

scholarly journals Regional Patterns in the Otolith Chemistry of Juvenile Spotted Seatrout (Cynoscion nebulosus) Differ under Contrasting Hydrological Regimes

2015 ◽  
Vol 8 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Chet F. Rakocinski ◽  
Bruce H. Comyns ◽  
Mark S. Peterson ◽  
Alan M. Shiller
Keyword(s):  
Geographic Distance ◽  
Specific Effect ◽  
Local Effect ◽  
Spotted Seatrout ◽  
Otolith Chemistry ◽  
Cynoscion Nebulosus ◽  
Regional Patterns ◽  
Source Regions ◽  
Source Contributions ◽  
Hydrological Regimes

The value of using otolith chemistry to characterize recruitment in terms of natal source regions depends on how consistently spatio-temporal variation can be resolved. The objective of this study was to compare regional classification patterns in the otolith chemistry of juvenile Spotted Seatrout (Cynoscion nebulosus) between two years experiencing disparate hydrological regimes, and separated by a five year interlude. Spatial patterns in the whole-otolith chemistry of juveniles of this estuarine-dependent species were compared between years using five otolith elements and two stable isotopes. Consistent size-related trends in uptake and deposition were evidenced by parallel ontogenetic relationships for six otolith variables. Nine natal regions were discerned equally well in both years; and region accounted for similar overall amounts of variation in the seven otolith variables in both years. However, the otolith variables did not distinguish the nine regions in the same manner in both years, and natal regions varied in how similar they were in otolith chemistry between years. Consequently, between-year cross-classification accuracy varied widely among regions, and geographic distance per se was unimportant for explaining regional patterns in otolith chemistry. Salinity correlated significantly with regional patterns in otolith chemistry in 2001, but not at all in 2006 when conditions were much drier. Regional patterns in individual otolith variables reflected either a general trend based on hydrology, a regional-local effect whereby geographically closer regions exhibited similar otolith chemistry, or a location-specific effect for which there was either no correlation in otolith concentration among regions between years, or a significant but individualistic relationship. In addition to elucidating limitations of using otolith chemistry to identify natal source regions or for tracking fish movements, knowing more about how and why otolith chemistry varies could be used to address specific questions about early recruitment dynamics, or to aid in the development of more reliable instruments for discerning natal source contributions.

scholarly journals Acoustic monitoring indicates a correlation between calling and spawning in captive spotted seatrout (Cynoscion nebulosus)

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e2944 ◽  
Author(s):  
Eric W. Montie ◽  
Matt Hoover ◽  
Christopher Kehrer ◽  
Justin Yost ◽  
Karl Brenkert ◽  
...  
Keyword(s):  
Sound Production ◽  
Spatial Scales ◽  
Maximum Activity ◽  
Reproductive Season ◽  
Spotted Seatrout ◽  
Light Cycle ◽  
Cynoscion Nebulosus ◽  
Underwater Sound ◽  
Passive Acoustics ◽  
Acoustic Signaling

BackgroundFish sound production is widespread throughout many families. Territorial displays and courtship are the most common reasons for fish sound production. Yet, there is still some questions on how acoustic signaling and reproduction are correlated in many sound-producing species. In the present study, our aim was to determine if a quantitative relationship exists between calling and egg deposition in captive spotted seatrout (Cynoscion nebulosus). This type of data is essential if passive acoustics is to be used to identify spawning aggregations over large spatial scales and monitor reproductive activity over annual and decadal timeframes.MethodsAcoustic recorders (i.e., DSG-Oceans) were placed in three laboratory tanks to record underwater sound over an entire, simulated reproductive season. We enumerated the number of calls, calculated the received sound pressure level, and counted the number of eggs every morning in each tank.ResultsSpotted seatrout produced three distinct call types characterized as “drums,” “grunts,” and “staccatos.” Spotted seatrout calling increased as the light cycle shifted from 13.5 to 14.5 h of light, and the temperature increased to 27.7 °C. Calling decreased once the temperature fell below 27.7 °C, and the light cycle shifted to 12 h of light. These temperature and light patterns followed the natural reproductive season observed in wild spotted seatrout in the Southeast United States. Spotted seatrout exhibited daily rhythms in calling. Acoustic signaling began once the lights turned off, and calling reached maximum activity approximately 3 h later. Eggs were released only on evenings in which spotted seatrout were calling. In all tanks, spotted seatrout were more likely to spawn when male fish called more frequently. A positive relationship between SPL and the number of eggs collected was found in Tanks 1 and 3.DiscussionOur findings indicate that acoustic metrics can predict spawning potential. These findings are important because plankton tows may not accurately reflect spawning locations since egg capture is likely affected by predator activity and water currents. Instead, passive acoustics could be used to monitor spotted seatrout reproduction. Future studies can use this captive study as a model to record the estuarine soundscape precisely over long time periods to better understand how human-made stressors (e.g., climate change, noise pollution, and chemical pollutants) may affect spawning patterns.

Trash or treasure? Use of sagittal otoliths partially composed of vaterite for hatchery stock discrimination in steelhead

2020 ◽  
Vol 77 (2) ◽  
pp. 276-284
Author(s):  
Richard R. Budnik ◽  
John R. Farver ◽  
Joel E. Gagnon ◽  
Jeffrey G. Miner
Keyword(s):  
Classification Accuracy ◽  
Lake Erie ◽  
Juvenile Fish ◽  
Otolith Chemistry ◽  
Elemental Concentrations ◽  
Stock Discrimination ◽  
Quadratic Discriminant Function ◽  
Hatchery Stock ◽  
Similar Classification ◽  
Discriminant Function Analyses

Sagittal otoliths are normally deposited as the CaCO3 polymorph aragonite; however, a proportion of otoliths transitions to vaterite during growth. This transition can complicate otolith chemistry analyses, as differences in the crystalline structure (aragonite or vaterite) of otoliths causes variation in otolith chemistry signatures. To address this issue, we introduce a method to utilize sagittal otoliths partially composed of vaterite for stock discrimination. Using this method, we determined the hatchery origins of yearlings from five Lake Erie hatcheries by using Ba, Mg, Mn, and Sr concentrations in vaterite sections of steelhead (Oncorhynchus mykiss) otoliths. We then compared the classification accuracy of our vaterite method with a method in which otoliths composed entirely of aragonite were used. Overall, quadratic discriminant function analyses revealed similar classification success when elemental concentrations from vaterite (95% accuracy) and aragonite (94% accuracy) otolith regions were used. The methods introduced here could likely be used for other fish species that have otoliths that transition to vaterite as long as an adequate number of juvenile fish are available to develop vaterite otolith chemistry signatures.

scholarly journals Acoustic monitoring indicates a positive relationship between calling frequency and spawning in captive spotted seatrout (Cynoscion nebulosus)

2016 ◽  
Author(s):  
Eric W Montie ◽  
Matt Hoover ◽  
Chris Kehrer ◽  
Justin Yost ◽  
Karl Brenkert ◽  
...  
Keyword(s):  
Sound Production ◽  
Spatial Scales ◽  
Reproductive Activity ◽  
Acoustic Monitoring ◽  
Spotted Seatrout ◽  
Light Cycle ◽  
Cynoscion Nebulosus ◽  
Underwater Sound ◽  
Spawning Period ◽  
Spawning Aggregations

Background: Fish sound production is widespread throughout many families. Agonistic and courtship behaviors are the most common reasons for fish sound production. Yet, there is still some debate on how sound production and spawning are correlated in many soniferous fish species. In the present study, our aim was to determine if a quantitative relationship exists between calling and egg deposition in captive spotted seatrout (Cynoscion nebulosus). This type of data is essential if scientists and managers plan to use acoustic metrics to identify spawning aggregations over large spatial scales and monitor reproductive activity over annual and decadal timeframes.Methods: Wild caught spotted seatrout were held in three laboratory tanks equipped with long-term acoustic loggers (i.e., DSG-Oceans) to record underwater sound throughout an entire, simulated reproductive season. Acoustic monitoring occurred from April 13 to December 19, 2012 for Tank 1 and from April 13 to November 21, 2012 for Tanks 2 and 3. DSG-Oceans were scheduled to record sound for 2 min every 20 min. We enumerated the number of calls, calculated the received sound pressure level (SPL in dB re 1 µPa; between 50 and 2000 Hz) of each 2 min ‘wav file’, and counted the number of eggs every morning in each tank.Results: Spotted seatrout produced three distinct call types characterized as “drums”, “grunts”, and “staccatos”. Spotted seatrout calling increased as the light cycle shifted from 13.5 to 14.5 h of light, and the temperature increased to 27.7oC. Calling began to decrease once the temperature fell below 27.7 oC, and the light cycle shifted to 12 h of light. These captive settings are similar to the amount of daylight and water temperatures observed during the summer, which is the primary spawning period of spotted seatrout. Spotted seatrout exhibited daily patterns of calling. Sound production began once the lights turned off, and calling reached maximum activity approximately 3 h later. Spawning occurred only on evenings in which spotted seatrout were calling. Significantly more calling and higher mean SPLs occurred on evenings in which spawning occurred as compared to evenings in which spawning did not occur. Spawning was more productive when spotted seatrout produced more calls. For all tanks, more calling and higher SPLs were associated with more eggs released by females.Discussion: The fact that more calling and higher SPLs were associated with spawns that were more productive indicates that acoustic metrics can provide quantitative information on spotted seatrout spawning in the wild. These findings will help us to identify spawning aggregations over large spatial scales and monitor the effects of noise pollution, water quality, and climatic changes on reproductive activity using acoustic technology.

Infection dynamics of Kudoa inornata (Cnidaria: Myxosporea) in spotted seatrout Cynoscion nebulosus (Teleostei: Sciaenidae)

2017 ◽  
Vol 127 (1) ◽  
pp. 29-40 ◽  
Author(s):  
I de Buron ◽  
KM Hill-Spanik ◽  
L Haselden ◽  
SD Atkinson ◽  
SL Hallett ◽  
...  
Keyword(s):  
Spotted Seatrout ◽  
Cynoscion Nebulosus ◽  
Infection Dynamics

A visual terrain classification method for mobile robots’ navigation based on convolutional neural network and support vector machine

2021 ◽  
pp. 014233122098791
Author(s):  
Wanli Wang ◽  
Botao Zhang ◽  
Kaiqi Wu ◽  
Sergey A Chepinskiy ◽  
Anton A Zhilenkov ◽  
...  
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Mobile Robots ◽  
Convolutional Neural Network ◽  
Hybrid Method ◽  
Classification Accuracy ◽  
Support Vector ◽  
High Classification Accuracy ◽  
Enhance Efficiency ◽  
Multi Class Classification

In this paper, a hybrid method based on deep learning is proposed to visually classify terrains encountered by mobile robots. Considering the limited computing resource on mobile robots and the requirement for high classification accuracy, the proposed hybrid method combines a convolutional neural network with a support vector machine to keep a high classification accuracy while improve work efficiency. The key idea is that the convolutional neural network is used to finish a multi-class classification and simultaneously the support vector machine is used to make a two-class classification. The two-class classification performed by the support vector machine is aimed at one kind of terrain that users are mostly concerned with. Results of the two classifications will be consolidated to get the final classification result. The convolutional neural network used in this method is modified for the on-board usage of mobile robots. In order to enhance efficiency, the convolutional neural network has a simple architecture. The convolutional neural network and the support vector machine are trained and tested by using RGB images of six kinds of common terrains. Experimental results demonstrate that this method can help robots classify terrains accurately and efficiently. Therefore, the proposed method has a significant potential for being applied to the on-board usage of mobile robots.

scholarly journals Privacy-Preserving Deep Neural Network Methods: Computational and Perceptual Methods—An Overview

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1367
Author(s):  
Raghida El El Saj ◽  
Ehsan Sedgh Sedgh Gooya ◽  
Ayman Alfalou ◽  
Mohamad Khalil
Keyword(s):  
Neural Networks ◽  
Classification Accuracy ◽  
Deep Neural Networks ◽  
Privacy Preserving ◽  
Sensitive Data ◽  
Encrypted Data ◽  
High Classification Accuracy ◽  
Hide Information ◽  
Network Methods ◽  
Cloud Environments

Privacy-preserving deep neural networks have become essential and have attracted the attention of many researchers due to the need to maintain the privacy and the confidentiality of personal and sensitive data. The importance of privacy-preserving networks has increased with the widespread use of neural networks as a service in unsecured cloud environments. Different methods have been proposed and developed to solve the privacy-preserving problem using deep neural networks on encrypted data. In this article, we reviewed some of the most relevant and well-known computational and perceptual image encryption methods. These methods as well as their results have been presented, compared, and the conditions of their use, the durability and robustness of some of them against attacks, have been discussed. Some of the mentioned methods have demonstrated an ability to hide information and make it difficult for adversaries to retrieve it while maintaining high classification accuracy. Based on the obtained results, it was suggested to develop and use some of the cited privacy-preserving methods in applications other than classification.

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