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Forecasting model of seasonal dynamics of boll weevil Anthonomus grandis grandis (Coleoptera: Curculionidae) in cotton crops using artificial neural networks
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Dataset - "An Adaptive Multi-Seasonal ARIMA Approach for Domestic Hot Water Load Forecasting: A Pilot Study"
<p>The description of the data is in README.txt.</p>
Seasonal Changes of Mélange Thickness Coincide With Greenland Calving Dynamics
<p>Supp_dataset.docx lists the ArcticDEM tiles, ICESat-2, Landsat, Sentinel-1 and Sentinel-2 Imagery files used in this study. </p> <p>Figures_MainText.zip contains the source data and MATLAB codes to reproduce Figure 1 to Figure 8 presented in the main text. The ReadMe.txt file in each folder includes instructions on how to reproduce the corresponding figure. </p> <p>demo_codes_CodeOcean.zip contains the sample code and data file to reproduce Figure 13(a)(d) in the supplemental material (Melange surface elevation profile at Jakobshavn on 19 Apr 2014, from ArcticDEM). User can run the Hx_distribution.m file, which calls peakFit.m function and dpROI_Jakob_20140419.mat data file, and to obtain the figure. This folder has been uploaded to code ocean portal as well (https://codeocean.com/capsule/4948451/tree). </p> <p>Termini_offset_tide.xlsx contains the elevation offsets applied on the 108 ArcticDEM strips for the 32 Greenland glacier termini, with corresponding ArcticDEM strip acquisition dates and Mosaic DEM tiles for coregistration.</p> <p>GlacierID_GlacierName.zip folders contain two types of files: 1) points_yymmdd.csv contains point ID, x and y coordinates in polar stereographic projection (EPSG: 3413). The first and second points (ID=1, 2) delineate the glacier terminus segment, and the third to the last points (ID=3, N) delineate the region of interest of proglacial melange from the corresponding ArcticDEM strip acquired on the same date (yymmdd); 2) dpROI_yymmdd.mat contains all data points from the ArcticDEM strip cropped by the melange region of interest. Every row represents one data point from ArcticDEM, the first to fourth column corresponds to i) x coordinate in polar stereographic projection (EPSG: 3413); ii) y coordinate in polar stereographic projection (EPSG: 3413); iii) elevation above mean sea level in meters before coregistration; and iv) distance of the data point from the terminus segment in meters. Column iii) and iv) are used to plot the melange surface elevation (or thickness) profile as a function of distance from terminus. </p> <p>Hx_distribution.m is the MATLAB file (calling the function peakFit.m) that plots the melange surface elevation profile as a function of distance from terminus (Z(x)), providing the dpROI_yymmdd.mat file.</p> <p>ICESat-2_allData.zip folder contains the ICESat-2 data presented in Figure 2 in the main text (seasonal melange surface elevation profiles for Jakobshavn, Kangerlussuaq, and Store glaciers). Figure 2 in the main text can be reproduced by running the MATLAB code inside the folder (Fig_H_x_disToTerm.m), which includes the geoid and tidal corrections on the ICESat-2 raw data files. </p> <p> </p> <p> </p> <p> </p>
Figure 1 in SEASONAL VARIATION IN THE CHIRONOMIDAE (DIPTERA) COMMUNITIES OF TWO FAROESE STREAMS Abstract
Figure 1. Map of the Faroe Islands with the location of the two sampled streams, Matará and Sundsá.
Supporting data: Human-induced weakening of subsurface ocean temperature seasonality
<p>CESM1 ocean-only experiments for analysis:</p> <p>Liu et al., 2024: <span>Human-induced weakening of subsurface ocean temperature seasonality, in preparation. </span></p>
The Seasonality of the Heat Budget on the Ross Sea Continental Shelf in a Coupled Regional Ocean-Sea Ice-Ice Shelf Model
<p>This dataset includes the model data used in our paper entitled 'The Seasonality of the Heat Budget on the Ross Sea Continental Shelf in a Coupled Regional Ocean-Sea Ice-Ice Shelf Model'</p>
Table 1 in Seasonal mite population distribution on Caryocar brasiliense trees in the Cerrado domain
<p><b>Table 1.</b> Number of mites (cm 2 of leaf) or per fruit, diversity and species richness (cm 2 of leaf/tree), temperature (°C), rainfall (mm), relative humidity of air (%), sunlight (h), and velocity of wind (m/sec) (average ± SE) according to the season of the year on <i>Caryocar brasiliense</i>. Montes Claros, Minas Gerais State, Brazil.</p><table><tbody><tr><th></th><th></th><th><b>Season of the year</b></th><th></th></tr></tbody><tbody><tr><th><b>Mites/cm</b> <b>2</b> <b>of leaf</b></th><td></td><td></td><td></td><td></td></tr><tr><th></th><td><b>Summer</b></td><td><b>Autumn</b></td><td><b>Winter</b></td><td><b>Spring</b></td></tr><tr><th>Acari n.s.</th><td>0.0019 ± 0.0007A</td><td>0.0066 ± 0.0018A</td><td>0.0019 ± 0.0009A</td><td>0.0000 ± 0.0000A</td></tr><tr><th><i>Agistemus</i> sp. *</th><td>0.0086 ± 0.0021AB</td><td>0.0139 ± 0.0032A</td><td>0.0019 ± 0.0011B</td><td>0.0026 ± 0.0014B</td></tr><tr><th><i>Eutetranychus</i> sp. n. s.</th><td>0.0000 ± 0.0000A</td><td>0.0013 ± 0.0007A</td><td>0.0008 ± 0.0008A</td><td>0.0000 ± 0.0000A</td></tr><tr><th><i>Histiostoma</i> sp. **</th><td>0.0376 ± 0.0094C</td><td>0.0834 ± 0.0094A</td><td>0.0675 ± 0.0093B</td><td>0.0598 ± 0.0157B</td></tr><tr><th><i>Proctolaelaps</i> sp. **</th><td>0.0010 ± 0.0007B</td><td>0.0156 ± 0.0061A</td><td>0.0022 ± 0.0012B</td><td>0.0000 ± 0.0000B</td></tr><tr><th><i>Tetranychus</i> sp.1 **</th><td>0.0059 ± 0.0018AB</td><td>0.0150 ± 0.0034A</td><td>0.0124 ± 0.0041A</td><td>0.0000 ± 0.0000B</td></tr><tr><th><i>Tetranychus</i> sp.2 n.s.</th><td>0.0017 ± 0.0010A</td><td>0.0060 ± 0.0018A</td><td>0.0038 ± 0.0016A</td><td>0.0011 ± 0.0008A</td></tr><tr><th><b>Mites/fruit</b></th></tr><tr><th><i>Histiostoma</i> sp. *</th><td>76.76 ± 18.67A</td><td>0.00 ± 0.00B</td><td>0.00 ± 0.00B</td><td>0.00 ± 0.00B</td></tr><tr><th><i>Proctolaelaps</i> sp. *</th><td>2.80 ± 0.79A</td><td>0.00 ± 0.00B</td><td>0.00 ± 0.00B</td><td>0.00 ± 0.00B</td></tr><tr><th><b>Ecological indices</b></th></tr><tr><th>Diversity**</th><td>3.82 ± 1.02AB</td><td>5.19 ± 1.36A</td><td>3.54 ± 0.87AB</td><td>1.96 ± 0.32B</td></tr><tr><th>Species richness*</th><td>2.70 ± 0.65AB</td><td>3.60 ± 0.71A</td><td>2.70 ± 0.73AB</td><td>1.60 ± 0.26B</td></tr><tr><th><b>Variables</b></th></tr><tr><th>Temperature**</th><td>24.10 ± 0.11B</td><td>22.16 ± 0.30C</td><td>22.78 ± 0.23C</td><td>25.05 ± 0.27A</td></tr><tr><th>Rainfall**</th><td>5.15 ± 0.73B</td><td>1.04 ± 0.35B</td><td>1.03 ± 0.40B</td><td>22.48 ± 7.59A</td></tr><tr><th>Humidity*</th><td>75.80 ± 1.21A</td><td>64.31 ± 1.51B</td><td>52.36 ± 0.98C</td><td>63.97 ± 2.80B</td></tr><tr><th>Sunlight**</th><td>5.98 ± 0.32B</td><td>8.33 ± 0.16A</td><td>8.06 ± 0.20A</td><td>6.84 ± 0.56B</td></tr><tr><th>Wind**</th><td>2.48 ± 0.29A</td><td>1.80 ± 0.02B</td><td>2.30 ± 0.06A</td><td>2.12 ± 0.03AB</td></tr></tbody></table><p>Means followed by the same letter (average ± SE) in each row are not different by the test of Tukey (* = P<0.01 and ** = P <0.05).Freedom degree: mites/leaf = 5281, mites/fruit = 2184, ecological indices = 27, and climatic data = 72, “n.s.” = non-significant data.</p>
Table 2 in Oviposition of AedeS japoNiCUS japoNiCUS (Diptera: Culicidae) and associated native species in relation to season, temperature and land use in western Germany
<p><b>Table 2</b> Maximum temperature of water (°C) in the mosquito-positive ovitraps during the field studies at the different study sites</p><table><tbody><tr><th>Study</th><th>Site</th><th><i>Ae. japonicus japonicus</i></th><th><i>Cx.pipiens</i> s.l.</th><th><i>An. plumbeus</i></th><th><i>Ae. geniculatus</i></th></tr></tbody><tbody><tr><th>2017</th><td>Alfter</td><td>26.8</td><td>34.7</td><td>31.3</td><td>20.3</td></tr><tr><th></th><td>Dormagen</td><td>22.1</td><td>27.2</td><td>17.3</td><td>21.7</td></tr><tr><th>2018</th><td>Alfter</td><td>22.6</td><td>19.8</td><td>20.6</td><td>n.n.</td></tr><tr><th></th><td>Bonn SÜd</td><td>24.7</td><td>24</td><td>17.3</td><td>n.n.</td></tr><tr><th></th><td>Heimerzheim</td><td>24.3</td><td>24.6</td><td>23.2</td><td>22.7</td></tr><tr><th></th><td>Lohmar</td><td>28.6</td><td>25.8</td><td>28.6</td><td>16.6</td></tr><tr><th></th><td>Siegburg</td><td>25.8</td><td>30</td><td>27</td><td>23.1</td></tr><tr><th></th><td>Troisdorf</td><td>26.8</td><td>27.7</td><td>25.2</td><td>n.n.</td></tr></tbody></table><p><i>n.n.</i> Species not present</p>
Table 1 in Oviposition of AedeS japoNiCUS japoNiCUS (Diptera: Culicidae) and associated native species in relation to season, temperature and land use in western Germany
<p><b>Table 1</b> Total number and percentages of positive samples and occurrence of mosquito species per trap</p><table><tbody><tr><th>Study</th><th></th><th><i>Aedes japonicus japonicus</i></th><th><i>Culex pipiens</i> s.l.</th><th><i>Anopheles plumbeus</i></th><th><i>Aedes geniculatus</i></th><th>Total</th></tr></tbody><tbody><tr><th>2017</th><td>Total positive traps (<i>n</i>)</td><td>97</td><td>199</td><td>47</td><td>38</td><td>381</td></tr><tr><th></th><td>Positive traps/analysable traps (%)</td><td>15.4</td><td>31.7</td><td>7.5</td><td>6.1</td><td>60.7</td></tr><tr><th></th><td>Traps multiple species (<i>n</i>)</td><td>56</td><td>58</td><td>39</td><td>25</td><td>80</td></tr><tr><th></th><td>Multiple species/positive traps (%)</td><td>57.7</td><td>29.1</td><td>83</td><td>65.8</td><td>21</td></tr><tr><th>2018</th><td>Total positive traps (<i>n</i>)</td><td>441</td><td>285</td><td>137</td><td>19</td><td>882</td></tr><tr><th></th><td>Positive traps/analysable traps (%)</td><td>20.3</td><td>13.1</td><td>6.3</td><td>0.9</td><td>40.7</td></tr><tr><th></th><td>Traps multiple species (<i>n</i>)</td><td>180</td><td>139</td><td>113</td><td>11</td><td>206</td></tr><tr><th></th><td>Multiple species/positive traps (%)</td><td>40.8</td><td>48.8</td><td>82.5</td><td>57.9</td><td>23.4</td></tr></tbody></table><p>Calculations based on a total of 628 samples in 2017 and 2168 samples in 2018.The number of positive ovitraps with more than one species divided by the total number of positive ovitraps represents the portion of positive ovitraps with multiple species.See Additional file 1: Table S1 for all combinations of species and Additional file 2: dataset S1 for all samplings</p>
Table 3 in Oviposition of AedeS japoNiCUS japoNiCUS (Diptera: Culicidae) and associated native species in relation to season, temperature and land use in western Germany
<p><b>Table 3</b> Coefficients and statistically significant output of predictor variables as calculated by the generalised linear model</p><table><tbody><tr><th></th><th>Estimate</th><th>SE</th><th><i>Z</i> -value</th><th><i>P</i></th></tr></tbody><tbody><tr><th>(Intercept)</th><td>− 29.890</td><td>15.100</td><td>− 19.790</td><td>0.0478*</td></tr><tr><th>Temp_mean</th><td>0.2126</td><td>0.0933</td><td>22.800</td><td>0.0226*</td></tr><tr><th>Cxbin</th><td>0.2732</td><td>0.3148</td><td>0.868</td><td>0.3854</td></tr><tr><th>Plbbin</th><td>0.5999</td><td>0.2253</td><td>26.630</td><td>0.0077*</td></tr><tr><th>F100</th><td>0.4931</td><td>0.4826</td><td>10.220</td><td>0.3068</td></tr><tr><th>F10</th><td>0.7486</td><td>0.4127</td><td>18,140</td><td>0.0697</td></tr><tr><th>F/S</th><td>0.8715</td><td>0.3728</td><td>23.380</td><td>0.0194*</td></tr><tr><th>S10</th><td>10.770</td><td>0.3347</td><td>32.170</td><td>0.0013*</td></tr><tr><th>Ngbi</th><td>0.0412</td><td>0.1157</td><td>0.356</td><td>0.722</td></tr><tr><th>Nhbu</th><td>0.0001</td><td>0.0251</td><td>0.003</td><td>0.9972</td></tr><tr><th>Ngki</th><td>0.0295</td><td>0.0432</td><td>0.684</td><td>0.4941</td></tr><tr><th>Nsei</th><td>− 0.0362</td><td>0.0609</td><td>− 0.594</td><td>0.5528</td></tr><tr><th>Ntei</th><td>− 0.0845</td><td>0.0917</td><td>− 0.922</td><td>0.3566</td></tr><tr><th>Ngfi</th><td>0.1002</td><td>0.0832</td><td>12.050</td><td>0.2283</td></tr><tr><th>Nrbu</th><td>0.0648</td><td>0.0456</td><td>14.200</td><td>0.1557</td></tr></tbody></table><p>Characteristics:negative binomial,link = log, <i>z</i> -values calculated by Wald-test. Response variable:total of <i>Ae. japonicus japonicus</i> -positive ovitraps per location Predictors:Temp_mean = Mean water temperature,binary native taxa occurrence:Cxbin = <i>Cx. pipiens</i> s.l., <i>Plbbin An. plumbeus</i>, land use data: percentage forest:F100 = 100% forest,F10 = 60% forest,F/S = 50% forest,S10 = 40% forest,number of tree species in a 10 m radius of the trap locations (the tree species occurred in more than five transects):Nrbu: <i>Fagus sylvatica</i>, Nhbu: <i>Carpinus betulus</i>, Ngbi: <i>Betula pendula</i>, Nsei: <i>Quercus robur</i>, Ntei: <i>Quercus petreae</i>, Ngfi: <i>Picea abies</i>, Ngki: Pinus sylvestris</p>
Table 2 in Circulating dengue virus serotypes and vertical transmission in AEdES larvae during outbreak and inter-outbreak seasons in a high dengue risk area of Sri Lanka
<p><b>Table 2</b> Distribution of DENV serotypes in patients with suspected dengue and in <i>Aedes</i> mosquito larvae</p><table><tbody><tr><th>Patient no.</th><th><i>Ae. aegypti</i></th><th><i>Ae. albopictus</i></th><th>DENV serotype identified in mosquito pools</th><th>DENV serotype identified in patients</th></tr></tbody><tbody><tr><th>1</th><td>Detected</td><td>ND</td><td>DENV-3</td><td>DENV-3</td></tr><tr><th>2</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>DENV-1</td></tr><tr><th>3</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>DENV-3</td></tr><tr><th>4</th><td>ND</td><td>Detected</td><td>DENV-4</td><td>ND</td></tr><tr><th>5</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>ND</td></tr><tr><th>6</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>ND</td></tr><tr><th>7</th><td>Detected</td><td>ND</td><td>DENV-2</td><td>ND</td></tr><tr><th>8</th><td>Detected</td><td>ND</td><td>DENV-1</td><td>ND</td></tr><tr><th>9</th><td>Detected</td><td>ND</td><td>DENV-1</td><td>ND</td></tr><tr><th>10</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>ND</td></tr><tr><th>11</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>ND</td></tr><tr><th>12</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>DENV-1</td></tr><tr><th>13</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>ND</td></tr><tr><th>14</th><td>ND</td><td>Detected</td><td>DENV-4</td><td>ND</td></tr><tr><th>15</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>ND</td></tr><tr><th>16</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>DENV-2</td></tr></tbody></table><p><i>ND</i> Not detected</p>
Table 1 in Circulating dengue virus serotypes and vertical transmission in AEdES larvae during outbreak and inter-outbreak seasons in a high dengue risk area of Sri Lanka
<p><b>Table 1</b> Distribution of <i>Aedes</i> mosquito larvae in and around residences of patients with suspected dengue in Mawanella from December 2015 to March 2017</p><table><tbody><tr><th>Period</th><th>Month and year of sample collection</th><th>Total no. of vector pools collected in entomological survey</th><th>No. of <i>Aedes</i> mosquito pools identified</th></tr><tr><th><i>Ae. aegypti</i></th><th><i>Ae. albopictus</i></th></tr></tbody><tbody><tr><th>Epidemic</th><td>12/2015</td><td>18</td><td>3</td><td>15</td></tr><tr><th></th><td>1/2016</td><td>22</td><td>8</td><td>14</td></tr><tr><th>Inter-epidemic</th><td>2/2016</td><td>5</td><td>0</td><td>5</td></tr><tr><th></th><td>3/2016</td><td>3</td><td>1</td><td>2</td></tr><tr><th></th><td>4/2016</td><td>4</td><td>1</td><td>3</td></tr><tr><th></th><td>5/2016</td><td>12</td><td>1</td><td>11</td></tr><tr><th></th><td>6/2016</td><td>15</td><td>9</td><td>6</td></tr><tr><th>Epidemic</th><td>7/2016</td><td>7</td><td>1</td><td>6</td></tr><tr><th></th><td>8/2016</td><td>5</td><td>2</td><td>3</td></tr><tr><th></th><td>9/2016</td><td>5</td><td>2</td><td>3</td></tr><tr><th>Inter-epidemic</th><td>10/2016</td><td>6</td><td>1</td><td>5</td></tr><tr><th></th><td>11/2016</td><td>6</td><td>1</td><td>5</td></tr><tr><th>Epidemic</th><td>12/2016</td><td>14</td><td>3</td><td>11</td></tr><tr><th></th><td>1/2017</td><td>23</td><td>8</td><td>15</td></tr><tr><th>Inter-epidemic</th><td>2/2017</td><td>1</td><td>0</td><td>1</td></tr><tr><th></th><td>3/2017</td><td>25</td><td>8</td><td>17</td></tr><tr><th>Total</th><td></td><td>171</td><td>49</td><td>122</td></tr></tbody></table>
Seasonality and inter-annual stability in the population genetic structure of Batrachospermum gelatinosum (Rhodophyta)
<p>Data used for Shainker-Connelly et al. in biorxiv: https://www.biorxiv.org/content/10.1101/2024.09.20.614195v1</p>
Spatial and seasonal distribution of selected nitrogen cycle genes in deep waters of the Baltic Proper
<p>The dataset provides information on nitrogen cycle related bins and gene characteristics across selected depths within the IDEAL, P1, and BY15 sites in the Baltic Sea. The dataset includes details such as gene spans, gene lengths, gene names, and the processes to which each gene is assigned. Additionally, it contains raw read counts, RPKM (reads per kilobase of transcript, per million mapped reads), family, phylum, bin, site, common bin identifiers for sites, and seasonal variations. Bin parameters, along with lineage-specific markers, are included to estimate the completeness of the bins. We focused on nitrogen loss processes (denitrification, anammox), reduction processes (dissimilatory nitrate reduction (DNR), dissimilatory nitrate reduction to ammonium (DNRA)), and oxidation (nitrification). <span>The reported results were obtained within the framework of the statutory activities of the Institute of Oceanology of the Polish Academy of Sciences and the following research project: 2019/34/E/ST10/00217 funded by the Polish National Science Centre.</span></p>
Coopetition as an ecological dynamic: interactions between dense seasonal macroalgal mats and oysters on temperate shellfish reefs
<p>We document the proliferation of dense algal mats on intertidal oyster reefs in the Southeastern USA. We also use data from a small field experiment to understand the effects that oysters have on macroalgae. The data and code included here can be used to replicate all analyses and figures in the manuscript.</p>
Table 1 in Proximate composition and its seasonal variations of the muscle tissue of Channa striata from Krishna river, Andhra Pradesh
<p><b>Table 1:</b> Variations of biochemical composition of muscle. <i>C</i>. <i>striata</i> (females)</p><table><tbody><tr><th><b>Seasons</b></th><th><b>Months Protein 2021-2022</b></th><th><b>Fat</b></th><th><b>Moisture</b></th><th><b>Ash</b></th></tr></tbody><tbody><tr><th>South West Monsoon</th><td>June</td><td>22.9</td><td>5.1</td><td>81.5</td><td>1.75</td></tr><tr><td>July</td><td>23.5</td><td>4.9</td><td>82.6</td><td>1.87</td></tr><tr><td>August</td><td>24.3</td><td>4.3</td><td>83.8</td><td>1.99</td></tr><tr><td>September</td><td>23.8</td><td>4.5</td><td>83.4</td><td>2.03</td></tr><tr><th>Post Monsoon</th><td>October November</td><td>22.8 21.5</td><td>4.8 5.2</td><td>83 82</td><td>2.12 2.19</td></tr><tr><th>North East Monsoon</th><td>December January February</td><td>20.4 21.5 21.2</td><td>5.4 4.9 4.6</td><td>82.1 82.3 82.2</td><td>2.01 1.96 1.81</td></tr><tr><th>Summer</th><td>March</td><td>21.8</td><td>4.5</td><td>80.2</td><td>1.79</td></tr><tr><td>April</td><td>22.3</td><td>4.6</td><td>81.5</td><td>1.61</td></tr><tr><td>May</td><td>22.4</td><td>5.2</td><td>80.5</td><td>1.75</td></tr><tr><th></th><td>Min.</td><td>20.4</td><td>4.3</td><td>80.2</td><td>1.61</td></tr><tr><th></th><td>Max.</td><td>24.3</td><td>5.4</td><td>83.8</td><td>2.19</td></tr><tr><th></th><td>Avg. 22.36±2.24.83±0.582.09±5.91.90±0.06</td></tr></tbody></table>
Table 2 in Proximate composition and its seasonal variations of the muscle tissue of Channa striata from Krishna river, Andhra Pradesh
<p><b>Table 2:</b> Variations of biochemical composition of muscle. <i>C</i>. <i>striata</i> (males)</p><table><tbody><tr><th><b>Seasons</b></th><th><b>Months Protein 2021-2022</b></th><th><b>Fat</b></th><th><b>Moisture</b></th><th><b>Ash</b></th></tr></tbody><tbody><tr><th>South West Monsoon</th><td>June</td><td>23.7</td><td>5.4</td><td>82.4</td><td>1.79</td></tr><tr><td>July</td><td>23.8</td><td>5.1</td><td>83.1</td><td>1.65</td></tr><tr><td>August</td><td>25.2</td><td>4.5</td><td>84.2</td><td>2.05</td></tr><tr><td>September</td><td>25.1</td><td>4.7</td><td>83.8</td><td>2.14</td></tr><tr><th>Post Monsoon</th><td>October November</td><td>24.2 23.5</td><td>4.9 5.3</td><td>82.9 83.2</td><td>2.1 2.25</td></tr><tr><th>North East Monsoon</th><td>December January February</td><td>22.4 22.3 23.2</td><td>5.5 4.6 4.4</td><td>81.2 81.5 80.5</td><td>1.96 1.85 1.72</td></tr><tr><th>Summer</th><td>March</td><td>22.6</td><td>3.8</td><td>80.4</td><td>1.65</td></tr><tr><td>April</td><td>23.5</td><td>3.6</td><td>81.5</td><td>1.84</td></tr><tr><td>May</td><td>22.5</td><td>4.8</td><td>80.6</td><td>1.89</td></tr><tr><th></th><td>Min.</td><td>22.3</td><td>3.6</td><td>80.4</td><td>1.72</td></tr><tr><th></th><td>Max.</td><td>25.2</td><td>5.5</td><td>84.2</td><td>2.25</td></tr><tr><th></th><td>Avg. 23.5±2.54.71±0.582.10±5.81.90±0.05</td></tr></tbody></table>
Sensitivity of M2 tidal magnetic signals to seasonal and spatial variations of ocean electric conductivity
<p>Gijm_fwd</p> <p>SH coefficients of M2 induced field for monthly conductivities.</p> <p>WOA03: March; WOA06: June; WOA09: September; WOA12: December</p> <p>Schmidt semi-normalization, complex; ordering g10,g11,h11,g20,g21,h21,g22,h22,...</p> <p>Snm</p> <p>relative differences between SH coefficients</p> <p>same ordering as Gijm_fwd</p> <p>Inversion</p> <p>result of synthetic inversion</p> <p>longitude,latitude,conductivity in S/m</p> <p> </p> <p> </p> <p> </p>
Seasonality of cyanobacteria and eukaryotes in Lake Geneva and the impacts of cyanotoxins on growth of the model ciliate Tetrahymena pyriformis
<p><span>Toxic cyanobacteria are likely to be favored by global warming and other human impacts, posing significant threats to aquatic ecosystems. While cyanobacterial blooms in eutrophic lakes are widely investigated, the dynamics of cyanobacteria and the effects of their toxins and bioactive metabolites on the plankton communities in mesotrophic and oligotrophic lakes are less well understood. Here we investigated seasonal dynamics of cyanobacteria, eukaryotic algae and cyanotoxins in oligo-mesotrophic Lake Geneva—the largest and deepest lake in western Europe. High-throughput sequencing of the 16S rRNA genes in 143 samples along a water column revealed that Lake Geneva hosts diverse, co-dominant cyanobacterial genera, including <em>Planktothrix</em>, <em>Cyanobium</em>, <em>Pseudanabaena</em>, and <em>Aphanizomenon. </em>The abundance of the <em>mcyA</em> gene marker for microcystin production was highly correlated with total cyanobacteria abundance, obtained from qPCR of the 16S rRNA genes. Targeted LC-HRMS/MS analysis demonstrated peak concentrations of cyanotoxins in September and December 2021 at the deep chlorophyll-a maximum layer, reaching up to 1474 ng/l for anabaenopeptins and 144 ng/l for microcystins. The toxin peaks did not correlate with the abundance or variations in the cyanobacteria or eukaryote community, but they were correlated in time with seasonal lows in the abundances of ciliates (18S rRNA analysis). Laboratory exposure tests demonstrated that growth of the model ciliate <em>Tetrahymena pyriformis </em>was inhibited by Microcystin-RR and Anabaenopeptin A at environmentally relevant concentrations in the ng/l-range, in natural lake water, </span><span>synthetic freshwater, and growth media spiked with the cyanotoxins. Our findings suggest that even low concentrations (in the ng/l-range) of microcystins and anabaenopeptins, reduce growth of ciliates such as <em>T. pyriformis</em> and can be expected to have wider impacts on the eukaryote communities. </span></p>
Vertical assemblage of the holoplanktonic mollusks (Pteropoda and Pterotracheoidea) in the Campeche Canyon, southern Gulf of Mexico, during a "Nortes" season
<p>Data: Vertical assemblage of the holoplanktonic mollusks (Pteropoda and<br>Pterotracheoidea) in the Campeche Canyon, southern Gulf of Mexico,<br>during a “Nortes” season</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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