Continental-scale variation in otolith geochemistry of juvenile American shad (Alosa sapidissima)

We assembled a comprehensive atlas of geochemical signatures in juvenile American shad ( Alosa sapidissima ) to discriminate natal river origins on a large spatial scale and at a high spatial resolution. Otoliths and (or) water samples were collected from 20 major spawning rivers from Florida to Quebec and were analyzed for elemental (Mg:Ca, Mn:Ca, Sr:Ca, and Ba:Ca) and isotope (87Sr:86Sr and δ18O) ratios. We examined correlations between water chemistry and otolith composition for five rivers where both were sampled. While Sr:Ca, Ba:Ca, 87Sr:86Sr, and δ18O values in otoliths reflected those ratios in ambient waters, Mg:Ca and Mn:Ca ratios in otoliths varied independently of water chemistry. Geochemical signatures were highly distinct among rivers, with an average classification accuracy of 93% using only those variables where otolith values were accurately predicted from water chemistry data. The study represents the largest assembled database of otolith signatures from the entire native range of a species, encompassing approximately 2700 km of coastline and 19 degrees of latitude and including all major extant spawning populations. This database will allow reliable estimates of natal origins of migrating ocean-phase American shad from the 2004 annual cohort in the future.

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The Susceptibility of Juvenile American Shad to Rapid Decompression and Fluid Shear Exposure Associated with Simulated Hydroturbine Passage

Water ◽

10.3390/w12020586 ◽

2020 ◽

Vol 12 (2) ◽

pp. 586 ◽

Cited By ~ 1

Author(s):

Brett Pflugrath ◽

Ryan Harnish ◽

Briana Rhode ◽

Kristin Engbrecht ◽

Bernardo Beirão ◽

...

Keyword(s):

Dose Response ◽

Potential Method ◽

American Shad ◽

Native Range ◽

High Susceptibility ◽

Fluid Shear ◽

Negative Effects ◽

Alosa Sapidissima ◽

Response Models ◽

Rapid Decompression

Throughout many areas of their native range, American shad (Alosa sapidissima) and other Alosine populations are in decline. Though several conditions have influenced these declines, hydropower facilities have had significant negative effects on American shad populations. Hydropower facilities expose ocean-migrating American shad to physical stressors during passage through hydropower facilities, including strike, rapid decompression, and fluid shear. In this laboratory-based study, juvenile American shad were exposed separately to rapid decompression and fluid shear to determine their susceptibility to these stressors and develop dose–response models. These dose–response relationships can help guide the development and/or operation of hydropower turbines and facilities to reduce the negative effects to American shad. Relative to other species, juvenile American shad have a high susceptibility to both rapid decompression and fluid shear. Reducing or preventing exposure to these stressors at hydropower facilities may be a potential method to assist in the effort to restore American shad populations.

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Changes over three decades in feeding success of young American Shad Alosa sapidissima are influenced by invading zebra mussels Dreissena polymorpha

Marine Ecology Progress Series ◽

10.3354/meps13114 ◽

2019 ◽

Vol 628 ◽

pp. 141-153

Author(s):

ET Schultz ◽

MG Smircich ◽

DL Strayer

Keyword(s):

Dreissena Polymorpha ◽

Zebra Mussels ◽

American Shad ◽

Alosa Sapidissima ◽

Feeding Success

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Climate Change May Cause Shifts in Growth and Instantaneous Natural Mortality of American Shad Throughout Their Native Range

Transactions of the American Fisheries Society ◽

10.1002/tafs.10299 ◽

2021 ◽

Author(s):

Erin K. Gilligan‐Lunda ◽

Daniel S. Stich ◽

Katherine E. Mills ◽

Michael M. Bailey ◽

Joseph D. Zydlewski

Keyword(s):

Climate Change ◽

American Shad ◽

Natural Mortality ◽

Native Range

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Time–Frequency-Analysis-Based Blind Modulation Classification for Multiple-Antenna Systems

Sensors ◽

10.3390/s21010231 ◽

2021 ◽

Vol 21 (1) ◽

pp. 231

Author(s):

Weiheng Jiang ◽

Xiaogang Wu ◽

Yimou Wang ◽

Bolin Chen ◽

Wenjiang Feng ◽

...

Keyword(s):

Frequency Analysis ◽

Classification Accuracy ◽

Communication Systems ◽

Mimo Systems ◽

Decision Fusion ◽

Frequency Characteristics ◽

Modulation Classification ◽

Time Frequency Analysis ◽

Time Frequency ◽

Average Classification Accuracy

Blind modulation classification is an important step in implementing cognitive radio networks. The multiple-input multiple-output (MIMO) technique is widely used in military and civil communication systems. Due to the lack of prior information about channel parameters and the overlapping of signals in MIMO systems, the traditional likelihood-based and feature-based approaches cannot be applied in these scenarios directly. Hence, in this paper, to resolve the problem of blind modulation classification in MIMO systems, the time–frequency analysis method based on the windowed short-time Fourier transform was used to analyze the time–frequency characteristics of time-domain modulated signals. Then, the extracted time–frequency characteristics are converted into red–green–blue (RGB) spectrogram images, and the convolutional neural network based on transfer learning was applied to classify the modulation types according to the RGB spectrogram images. Finally, a decision fusion module was used to fuse the classification results of all the receiving antennas. Through simulations, we analyzed the classification performance at different signal-to-noise ratios (SNRs); the results indicate that, for the single-input single-output (SISO) network, our proposed scheme can achieve 92.37% and 99.12% average classification accuracy at SNRs of −4 and 10 dB, respectively. For the MIMO network, our scheme achieves 80.42% and 87.92% average classification accuracy at −4 and 10 dB, respectively. The proposed method greatly improves the accuracy of modulation classification in MIMO networks.

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Observations on the Food and Growth of Juvenile American Shad, Alosa Sapidissima

Transactions of the American Fisheries Society ◽

10.1577/1548-8659(1956)86[302:ootfag]2.0.co;2 ◽

1957 ◽

Vol 86 (1) ◽

pp. 302-306 ◽

Cited By ~ 2

Author(s):

Charles H. Walburg

Keyword(s):

American Shad ◽

Alosa Sapidissima

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Construction of Apple Leaf Diseases Identification Networks Based on Xception Fused by SE Module

Applied Sciences ◽

10.3390/app11104614 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4614

Author(s):

Xiaofei Chao ◽

Xiao Hu ◽

Jingze Feng ◽

Zhao Zhang ◽

Meili Wang ◽

...

Keyword(s):

Disease Control ◽

Classification Accuracy ◽

Mobile Terminal ◽

Disease Classification ◽

Memory Usage ◽

Compression Scheme ◽

Accurate Identification ◽

Average Classification Accuracy ◽

Network Compression ◽

Control And Management

The fast and accurate identification of apple leaf diseases is beneficial for disease control and management of apple orchards. An improved network for apple leaf disease classification and a lightweight model for mobile terminal usage was designed in this paper. First, we proposed SE-DEEP block to fuse the Squeeze-and-Excitation (SE) module with the Xception network to get the SE_Xception network, where the SE module is inserted between the depth-wise convolution and point-wise convolution of the depth-wise separable convolution layer. Therefore, the feature channels from the lower layers could be directly weighted, which made the model more sensitive to the principal features of the classification task. Second, we designed a lightweight network, named SE_miniXception, by reducing the depth and width of SE_Xception. Experimental results show that the average classification accuracy of SE_Xception is 99.40%, which is 1.99% higher than Xception. The average classification accuracy of SE_miniXception is 97.01%, which is 1.60% and 1.22% higher than MobileNetV1 and ShuffleNet, respectively, while its number of parameters is less than those of MobileNet and ShuffleNet. The minimized network decreases the memory usage and FLOPs, and accelerates the recognition speed from 15 to 7 milliseconds per image. Our proposed SE-DEEP block provides a choice for improving network accuracy and our network compression scheme provides ideas to lightweight existing networks.

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