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Supporting Information: Sedimentary events at the Jurassic–Cretaceous transition in the Slovenian Basin (Alpine Atlantic): further evidences for palaeoenvironmental record in pelagic sediments
<p>Dataset containing raw elemental geochemistry data (ICP-MS, pXRF and GRS measurements), stable carbon and oxygen isotopes, as well as rock magnetic data from the Tithonian-Berriasian of the Petrovo Brdo section (Slovenia). Supplementary information for the research entitled "The Jurassic-Cretaceous transition in the Slovenian Basin (Alpine Atlantic): further evidence for palaeoenvironmental record in pelagic sediments" published in <em>Geochemistry, Geophysics, Geosystems. </em></p>
TABLE 2 in Coexistence of two newt species in a transition zone of range overlap
<p>TABLE 2 Numbers of adult newts observed in the focal pond near Ambleteuse, Pas de Calais, France</p><table><tbody><tr><th><b>Year</b></th><th><b>Method</b></th><th><i>Ichthyosaura</i> <i>alpestris</i></th><th><i>Lissotriton</i> <i>helveticus</i></th><th><i>Lissotriton</i> <i>vulgaris</i></th></tr></tbody><tbody><tr><th>1975</th><td>Dipnet</td><td>3</td><td>31</td><td>10</td></tr><tr><th>1979</th><td>Dipnet</td><td>5</td><td>47</td><td>18</td></tr><tr><th>1980</th><td>Dipnet</td><td>4</td><td>68</td><td>38</td></tr><tr><th>1981</th><td>Dipnet</td><td>7</td><td>118</td><td>40</td></tr><tr><th>1982</th><td>Dipnet</td><td>2</td><td>15</td><td>13</td></tr><tr><th>1983 $</th><td>Dipnet</td><td>28</td><td>363</td><td>208</td></tr><tr><th>1984</th><td>Dipnet</td><td>13</td><td>172</td><td>82</td></tr><tr><th>1986 $</th><td>Dipnet</td><td>22</td><td>226</td><td>184</td></tr><tr><th>1986 #</th><td>Dipnet</td><td>23</td><td>731</td><td>192</td></tr><tr><th>1988 $</th><td>Dipnet</td><td>29</td><td>413</td><td>132</td></tr><tr><th>1989 $</th><td>Dipnet</td><td>100</td><td>396</td><td>228</td></tr><tr><th>1990 $</th><td>Dipnet</td><td>24</td><td>297</td><td>71</td></tr><tr><th>1991 $</th><td>Dipnet</td><td>71</td><td>251</td><td>115</td></tr><tr><th>1992 $</th><td>Dipnet</td><td>19</td><td>388</td><td>162</td></tr><tr><th>1993 $</th><td>Dipnet</td><td>44</td><td>193</td><td>111</td></tr><tr><th>1994 $</th><td>Dipnet</td><td>26</td><td>132</td><td>9</td></tr><tr><th>1995 $</th><td>Dipnet</td><td>91</td><td>570</td><td>52</td></tr><tr><th>2003 $</th><td>Dipnet</td><td>98</td><td>156</td><td>4</td></tr><tr><th>2012 $</th><td>Funnel trap</td><td>213</td><td>426</td><td>81</td></tr><tr><th>2021</th><td>Funnel trap</td><td>30</td><td>71</td><td>12</td></tr></tbody></table><p>$ = for population size estimates see table 3; # = including animals found dead.</p>
TABLE 1 in Coexistence of two newt species in a transition zone of range overlap
<p>TABLE 1 Numbers of adult <i>Lissotriton</i> newts observed over 105 ponds in the western part of the department Pas de Calais in the 1974 to 2021 period. <i>F</i> v = Lv /(Lh + Lv)</p><table><tbody><tr><th>Pond</th><th>Coordinates</th><th>Sample size for species</th><th><i>F</i> v</th></tr><tr><th><b>number</b></th><th>Northern latitude</th><th>Eastern longitude</th><th>Lissotriton <i>helveticus</i> (N)</th><th><i>Lissotriton</i> <b><i>vulgaris</i> (N)</b></th></tr></tbody><tbody><tr><th>1</th><td>50.770</td><td>1.772</td><td>21</td><td>1</td><td>0.05</td></tr><tr><th>2</th><td>50.871</td><td>1.617</td><td>194</td><td>175</td><td>0.47</td></tr><tr><th>3</th><td>50.902</td><td>1.679</td><td>223</td><td>9</td><td>0.04</td></tr><tr><th>4</th><td>50.901</td><td>1.678</td><td>126</td><td>7</td><td>0.05</td></tr><tr><th>5</th><td>50.870</td><td>1.606</td><td>580</td><td>24</td><td>0.04</td></tr><tr><th>6</th><td>50.902</td><td>1.680</td><td>233</td><td>6</td><td>0.03</td></tr><tr><th>7</th><td>50.869</td><td>1.608</td><td>34</td><td>1</td><td>0.03</td></tr><tr><th>8</th><td>50.869</td><td>1.609</td><td>20</td><td>0</td><td>0.00</td></tr><tr><th>9</th><td>50.875</td><td>1.656</td><td>26</td><td>2</td><td>0.07</td></tr><tr><th>10</th><td>50.855</td><td>1.666</td><td>410</td><td>149</td><td>0.27</td></tr><tr><th>11</th><td>50.854</td><td>1.664</td><td>188</td><td>96</td><td>0.34</td></tr><tr><th>12</th><td>50.839</td><td>1.672</td><td>108</td><td>10</td><td>0.08</td></tr><tr><th>13</th><td>50.837</td><td>1.675</td><td>29</td><td>5</td><td>0.15</td></tr><tr><th>14</th><td>50.820</td><td>1.631</td><td>65</td><td>41</td><td>0.39</td></tr><tr><th>15</th><td>50.858</td><td>1.630</td><td>26</td><td>6</td><td>0.19</td></tr><tr><th>16</th><td>50.861</td><td>1.610</td><td>92</td><td>34</td><td>0.27</td></tr><tr><th>17</th><td>50.860</td><td>1.606</td><td>43</td><td>0</td><td>0.00</td></tr><tr><th>18</th><td>50.849</td><td>1.597</td><td>186</td><td>87</td><td>0.32</td></tr><tr><th>19</th><td>50.853</td><td>1.595</td><td>27</td><td>11</td><td>0.29</td></tr><tr><th>20</th><td>50.866</td><td>1.608</td><td>107</td><td>46</td><td>0.30</td></tr><tr><th>21</th><td>50.844</td><td>1.590</td><td>104</td><td>76</td><td>0.42</td></tr><tr><th>22</th><td>50.844</td><td>1.598</td><td>26</td><td>16</td><td>0.38</td></tr><tr><th>23</th><td>50.844</td><td>1.599</td><td>83</td><td>66</td><td>0.44</td></tr><tr><th>24</th><td>50.845</td><td>1.599</td><td>812</td><td>182</td><td>0.18</td></tr><tr><th>25</th><td>50.845</td><td>1.599</td><td>45</td><td>16</td><td>0.26</td></tr><tr><th>26</th><td>50.845</td><td>1.599</td><td>53</td><td>40</td><td>0.43</td></tr><tr><th>27</th><td>50.845</td><td>1.599</td><td>86</td><td>35</td><td>0.29</td></tr><tr><th>28</th><td>50.845</td><td>1.600</td><td>41</td><td>16</td><td>0.28</td></tr><tr><th>29</th><td>50.845</td><td>1.600</td><td>79</td><td>33</td><td>0.29</td></tr><tr><th>30</th><td>50.845</td><td>1.600</td><td>70</td><td>17</td><td>0.20</td></tr><tr><th>31</th><td>50.845</td><td>1.601</td><td>51</td><td>45</td><td>0.47</td></tr><tr><th>32</th><td>50.846</td><td>1.600</td><td>1712</td><td>450</td><td>0.21</td></tr><tr><th>33</th><td>50.845</td><td>1.600</td><td>576</td><td>152</td><td>0.21</td></tr><tr><th>34</th><td>50.846</td><td>1.603</td><td>10</td><td>10</td><td>0.50</td></tr><tr><th>35</th><td>50.849</td><td>1.598</td><td>4</td><td>6</td><td>0.60</td></tr><tr><th>36</th><td>50.861</td><td>1.591</td><td>31</td><td>61</td><td>0.66</td></tr><tr><th>37</th><td>50.860</td><td>1.586</td><td>113</td><td>244</td><td>0.68</td></tr><tr><th>38</th><td>50.860</td><td>1.583</td><td>72</td><td>347</td><td>0.83</td></tr><tr><th>39</th><td>50.857</td><td>1.664</td><td>36</td><td>2</td><td>0.05</td></tr><tr><th>40</th><td>50.864</td><td>1.616</td><td>18</td><td>4</td><td>0.18</td></tr><tr><th>41</th><td>50.865</td><td>1.602</td><td>82</td><td>24</td><td>0.23</td></tr><tr><th>42</th><td>50.855</td><td>1.664</td><td>112</td><td>35</td><td>0.24</td></tr><tr><th>43</th><td>50.832</td><td>1.626</td><td>19</td><td>12</td><td>0.39</td></tr><tr><th>44</th><td>50.844</td><td>1.593</td><td>19</td><td>12</td><td>0.39</td></tr><tr><th>45</th><td>50.850</td><td>1.582</td><td>1</td><td>10</td><td>0.91</td></tr><tr><th>46</th><td>50.819</td><td>1.611</td><td>17</td><td>4</td><td>0.19</td></tr><tr><th>47</th><td>50.818</td><td>1.608</td><td>35</td><td>35</td><td>0.50</td></tr><tr><th>48</th><td>50.822</td><td>1.600</td><td>11</td><td>3</td><td>0.21</td></tr><tr><th>49</th><td>50.823</td><td>1.602</td><td>618</td><td>159</td><td>0.20</td></tr><tr><th>50</th><td>50.821</td><td>1.619</td><td>14</td><td>10</td><td>0.42</td></tr><tr><th>51</th><td>50.823</td><td>1.623</td><td>25</td><td>10</td><td>0.29</td></tr><tr><th>52</th><td>50.819</td><td>1.617</td><td>45</td><td>7</td><td>0.13</td></tr><tr><th>53</th><td>50.820</td><td>1.598</td><td>32</td><td>15</td><td>0.32</td></tr><tr><th>54</th><td>50.821</td><td>1.599</td><td>31</td><td>10</td><td>0.24</td></tr><tr><th>55</th><td>50.797</td><td>1.626</td><td>24</td><td>68</td><td>0.74</td></tr><tr><th>56</th><td>50.795</td><td>1.627</td><td>3</td><td>11</td><td>0.79</td></tr><tr><th>57</th><td>50.800</td><td>1.623</td><td>14</td><td>27</td><td>0.66</td></tr><tr><th>58</th><td>50.799</td><td>1.622</td><td>0</td><td>11</td><td>1.00</td></tr><tr><th>59</th><td>50.784</td><td>1.617</td><td>16</td><td>33</td><td>0.67</td></tr><tr><th>60</th><td>50.797</td><td>1.619</td><td>4</td><td>66</td><td>0.94</td></tr><tr><th>61</th><td>50.797</td><td>1.621</td><td>3</td><td>34</td><td>0.92</td></tr><tr><th>62</th><td>50.798</td><td>1.613</td><td>17</td><td>295</td><td>0.95</td></tr><tr><th>63</th><td>50.791</td><td>1.621</td><td>21</td><td>110</td><td>0.84</td></tr><tr><th>64</th><td>50.799</td><td>1.615</td><td>5</td><td>12</td><td>0.71</td></tr><tr><th>65</th><td>50.797</td><td>1.616</td><td>0</td><td>12</td><td>1.00</td></tr><tr><th>66</th><td>50.799</td><td>1.618</td><td>0</td><td>131</td><td>1.00</td></tr><tr><th>67</th><td>50.797</td><td>1.624</td><td>1</td><td>15</td><td>0.94</td></tr><tr><th>68</th><td>50.799</td><td>1.628</td><td>2</td><td>18</td><td>0.90</td></tr><tr><th>69</th><td>50.793</td><td>1.625</td><td>7</td><td>6</td><td>0.46</td></tr><tr><th>70</th><td>50.791</td><td>1.624</td><td>9</td><td>3</td><td>0.25</td></tr><tr><th>71</th><td>50.808</td><td>1.667</td><td>8</td><td>14</td><td>0.64</td></tr><tr><th>72</th><td>50.826</td><td>1.668</td><td>19</td><td>4</td><td>0.17</td></tr><tr><th>73</th><td>50.851</td><td>1.723</td><td>148</td><td>2</td><td>0.01</td></tr><tr><th>74</th><td>50.855</td><td>1.700</td><td>68</td><td>1</td><td>0.01</td></tr><tr><th>75</th><td>50.863</td><td>1.692</td><td>405</td><td>1</td><td>0.00</td></tr><tr><th>76</th><td>50.823</td><td>1.722</td><td>118</td><td>27</td><td>0.19</td></tr><tr><th>77</th><td>50.822</td><td>1.722</td><td>302</td><td>302</td><td>0.50</td></tr><tr><th>78</th><td>50.822</td><td>1.721</td><td>91</td><td>78</td><td>0.46</td></tr><tr><th>79</th><td>50.851</td><td>1.759</td><td>36</td><td>4</td><td>0.10</td></tr><tr><th>80</th><td>50.850</td><td>1.758</td><td>66</td><td>10</td><td>0.13</td></tr><tr><th>81</th><td>50.854</td><td>1.701</td><td>22</td><td>0</td><td>0.00</td></tr><tr><th>82</th><td>50.819</td><td>1.718</td><td>302</td><td>218</td><td>0.42</td></tr><tr><th>83</th><td>50.805</td><td>1.699</td><td>77</td><td>0</td><td>0.00</td></tr><tr><th>84</th><td>50.805</td><td>1.700</td><td>28</td><td>0</td><td>0.00</td></tr><tr><th>85</th><td>50.831</td><td>1.821</td><td>20</td><td>0</td><td>0.00</td></tr><tr><th>86</th><td>50.844</td><td>1.783</td><td>42</td><td>27</td><td>0.39</td></tr><tr><th>87</th><td>50.833</td><td>1.775</td><td>50</td><td>14</td><td>0.22</td></tr><tr><th>88</th><td>50.833</td><td>1.778</td><td>558</td><td>46</td><td>0.08</td></tr><tr><th>89</th><td>50.832</td><td>1.776</td><td>13</td><td>3</td><td>0.19</td></tr><tr><th>90</th><td>50.832</td><td>1.774</td><td>42</td><td>8</td><td>0.16</td></tr><tr><th>91</th><td>50.832</td><td>1.776</td><td>47</td><td>4</td><td>0.08</td></tr><tr><th>92</th><td>50.830</td><td>1.775</td><td>20</td><td>2</td><td>0.09</td></tr><tr><th>93</th><td>50.831</td><td>1.773</td><td>20</td><td>12</td><td>0.38</td></tr><tr><th>94</th><td>50.837</td><td>1.800</td><td>7</td><td>5</td><td>0.42</td></tr><tr><th>95</th><td>50.800</td><td>1.689</td><td>13</td><td>14</td><td>0.52</td></tr><tr><th>96</th><td>50.789</td><td>1.691</td><td>1883</td><td>6</td><td>0.00</td></tr><tr><th>97</th><td>50.778</td><td>1.679</td><td>66</td><td>1</td><td>0.01</td></tr><tr><th>98</th><td>50.779</td><td>1.659</td><td>13</td><td>0</td><td>0.00</td></tr><tr><th>99</th><td>50.771</td><td>1.666</td><td>327</td><td>3</td><td>0.01</td></tr><tr><th>100</th><td>50.774</td><td>1.673</td><td>20</td><td>0</td><td>0.00</td></tr><tr><th>101</th><td>50.779</td><td>1.606</td><td>87</td><td>50</td><td>0.36</td></tr><tr><th>102</th><td>50.807</td><td>1.690</td><td>32</td><td>0</td><td>0.00</td></tr><tr><th>103</th><td>50.797</td><td>1.688</td><td>27</td><td>1</td><td>0.04</td></tr><tr><th>104</th><td>50.801</td><td>1.690</td><td>17</td><td>1</td><td>0.06</td></tr><tr><th>105</th><td>50.789</td><td>1.690</td><td>13</td><td>0</td><td>0.00</td></tr></tbody></table>
TABLE 3 in Coexistence of two newt species in a transition zone of range overlap
<p>TABLE 3 Estimates on the total adult newt population size (N̂) composed of <i>Ichthyosaura alpestris</i>, <i>Lissotroton helveticus</i> and <i>L.vulgaris</i> in the focal pond near Ambleteuse, Pas de Calais, France, by a weighted mean capture-recapture method and a removal method (details see text)</p><table><tbody><tr><th><b>Year</b></th><th><b>Number</b> <b>of visits</b></th><th><b>Capture event</b></th><th><b>Weighted mean</b></th><th><b>Removal</b></th><th><b>Different</b> <b>individuals</b></th><th><b>Capture</b> <b>efficiency</b></th></tr><tr><th><b>First</b></th><th><b>Last</b></th><th>N̂</th><th><b>SE</b></th><th>N̂</th><th><b>SE</b></th><th><b>95% Confidence</b> <b>interval</b></th></tr><tr><th><b>Lower</b></th><th><b>Upper</b></th></tr></tbody><tbody><tr><th>1983</th><td>3</td><td>06-May</td><td>19-May</td><td>2828</td><td>459.0</td><td>840</td><td>29.0</td><td>789</td><td>902</td><td>560</td><td>0.67</td></tr><tr><th>1986</th><td>5</td><td>28-Mar</td><td>13-May</td><td>806</td><td>93.0</td><td>508</td><td>27.6</td><td>463</td><td>572</td><td>356</td><td>0.70</td></tr><tr><th>1986a</th><td>6</td><td>13-Mar</td><td>13-May</td><td>1320</td><td>93.0</td><td>1022</td><td>27.6</td><td>977</td><td>1086</td><td>870</td><td>0.85</td></tr><tr><th>1988</th><td>6</td><td>18-Mar</td><td>22-May</td><td>1051</td><td>110.1</td><td>834</td><td>32.5</td><td>776</td><td>903</td><td>482</td><td>0.58</td></tr><tr><th>1989</th><td>2</td><td>01-Apr</td><td>02-Apr</td><td>707</td><td>53.7</td><td>722</td><td>19.6</td><td>688</td><td>764</td><td>530</td><td>0.73</td></tr><tr><th>1990</th><td>2</td><td>05-May</td><td>06-May</td><td>426</td><td>45.4</td><td>420</td><td>15.3</td><td>394</td><td>454</td><td>303</td><td>0.72</td></tr><tr><th>1991</th><td>3</td><td>10-May</td><td>19-May</td><td>493</td><td>46.1</td><td>404</td><td>22.7</td><td>455</td><td>544</td><td>322</td><td>0.80</td></tr><tr><th>1992</th><td>7</td><td>21-Mar</td><td>10-May</td><td>477</td><td>33.9</td><td>406</td><td>12,0</td><td>390</td><td>438</td><td>370</td><td>0.91</td></tr><tr><th>1993</th><td>4</td><td>28-Apr</td><td>05-May</td><td>464</td><td>38.9</td><td>436</td><td>21.6</td><td>401</td><td>486</td><td>319</td><td>0.73</td></tr><tr><th>1994</th><td>4</td><td>07-Apr</td><td>10-Apr</td><td>370</td><td>75.6</td><td>217</td><td>17.3</td><td>190</td><td>259</td><td>142</td><td>0.65</td></tr><tr><th>1995</th><td>4</td><td>27-Apr</td><td>06-May</td><td>950</td><td>72.7</td><td>667</td><td>22.4</td><td>631</td><td>719</td><td>541</td><td>0.81</td></tr><tr><th>2003</th><td>4</td><td>13-Apr</td><td>26-May</td><td>255</td><td>47.4</td><td>154</td><td>9.8</td><td>142</td><td>181</td><td>130</td><td>0.84</td></tr><tr><th>2012</th><td>4</td><td>09-Mar</td><td>13-Apr</td><td>990</td><td>75.9</td><td>909</td><td>37.9</td><td>842</td><td>991</td><td>549</td><td>0.60</td></tr></tbody></table><p><sup>a</sup> Including animals found dead.</p>
Figures referring to the paper "Radii, masses, and transit-timing variations of the three-planet system orbiting the naked-eye star TOI-396" (Bonfanti et al.) accepted for publication in A&A on 20/11/2024
<p>Fig. A.1: ttv_pla1_2.pdf</p> <p>TTV amplitudes obtained for TOI-396 b (black markers) and TOI-396 c (red markers). This is a superposition of the first two panels of Figure 4 in the paper emphasising the anti-correlation pattern.</p> <p> </p> <p>Fig. A.2: lcGLS*.pdf</p> <p>First column: Generalised Lomb-Scargle periodograms of TESS Sector 3 (lcGLS_3.pdf), 4 (lcGLS_4RawFluxrm.pdf), 30 (lcGLS_30RawFlux.pdf), and 31 (lcGLS_31RawFlux.pdf) raw photometry. Second column: Generalised Lomb-Scargle periodograms of the residuals (lcGLSRaw_3noSine.pdf, lcGLSRaw_4noSinerm.pdf, lcGLSRaw_30noSine.pdf, lcGLSRaw_31noSine.pdf) after removing the best fitting sinusoidal signals at the most significant frequency identified in the periodograms of the corresponding TESS time series. The long dashed red line marks the FAP at 0.1\%. Significant peaks are detected in the 6---8 day range, which we attribute to the presence of active regions co-rotating with the star.</p>
Prefrontal Cortex Contribution in Transitive Inference
<p><span>Raw neural signals and event series were extracted, structured on a trial-by-trial basis, adapted for the analyses to be performed, and then stored as MATLAB files. The MATLAB files included in this repository contain behavioral and neural data structures and can be used by the analysis codes available at <span>https://doi.org/10.6084/m9.figshare.27951621.v1</span><br></span></p>
Data for: Carbon benefits through fallow agricultural land transitions: the case of multi-strata agroforestry in Hawaiʻi
<p>Bremer, L.L. (1,2), McGuire, G. (3,4), DeMaagd, N. (1,5), Trauernicht, C. (5)</p> <p><strong> </strong></p> <p>1 University of Hawaiʻi Economic Research Organization, University of Hawaiʻi at Mānoa, Honolulu, HI, 96822</p> <p>2 Water Resources Research Center, University of Hawaiʻi at Mānoa, Honolulu, HI, 96822</p> <p>3 Department of Geography and Environment, University of Hawaiʻi at Mānoa, Honolulu, HI, 96822</p> <p>4 Institute of Pacific Islands Forestry, USDA Forest Service, Hilo, HI, 96720</p> <p>5 Department of Natural Resources and Environmental Management, University of Hawaiʻi at Mānoa, Honolulu, HI, 96822</p> <p> </p> <p><strong>Bremer, L.L., McGuire, G., Hastings Silao, Z., Kurashima, N., Ticktin, T., Crow, S.E., Giardina, P.C., Winter, K.B., DeMaagd, N., and C. Trauernicht. Carbon benefits through fallow agricultural land transitions: the case of multi-strata agroforestry in Hawaiʻi</strong></p> <p> </p> <p>Multi-strata agroforestry land use scenarios were created using data from the: 2020 State of Hawaiʻi Agricultural Baseline (Perroy and Collier 2020), the Hawaiʻi Carbon Assessment (Jacobi et al. 2017), current (Giambelluca et al. 2013) and RCP 8.5 mid-century projected (Ellison-Timm et al. 2015) rainfall rasters, state land use zoning (SLUC, 2020), slope, elevation, and historical colluvial agroforestry maps (Kurashima et al. 2019). The following rasters display multi-strata agroforestry land-use scenarios. </p> <ul> <li> <p>“MS_currentclimate_landuse_scenario” represents potential multi-strata agroforestry under current rainfall.</p> </li> <li> <p>“MS_RCP85_midcentury_landuse_scenario” represents potential multi-strata agroforestry under projected RCP 8.5 mid-century rainfall. </p> </li> </ul> <p>For both scenarios: 1 = dry (550-1500 mm) multistrata agroforestry; 2 = mesic (1500-3000 mm) multi-strata agroforestry; 3 = wet (>3000 mm) multi-strata agroforestry.</p> <p>Estimates of projected changes in above-ground carbon were estimated by comparing modeled AGC in agroforestry scenarios to baseline AGC for current forest (Asner et al. 2016) and estimates of AGC in non-forest vegetation (Selmants et al. 2017). The following rasters display projected directional changes in soil carbon with agroforestry under current and RCP 8.5 mid century rainfall.</p> <ul> <li> <p>“AGC_change_currentclimate”</p> </li> <li> <p>“AGC_change_RCP85_midcentury”</p> </li> </ul> <p>For both scenarios: -2 = significant decrease (projected maximum < baseline); -1 = trend decrease (projected maximum > baseline > projected mean; 1 = weak increase (projected minimum < baseline < projected mean); 2 = strong increase (projected minimum > baseline).</p> <p>Estimates of projected changes in soil carbon under each scenario were estimated using global meta-analyses (Cardinael et al. 2018; Chaterjee et al. 2018; De Stefano and Jacobson 2017), studies of multi-strata agroforestry transitions in similar climates and soil types, and land-use change studies in Hawaiʻi. The following rasters display projected directional changes in soil carbon with agroforestry under current and RCP 8.5 mid-century rainfall. </p> <ul> <li> <p>“SoilC_currentclimate”</p> </li> <li> <p>“SoilC_RCP85_midcentury”</p> </li> </ul> <p>For both scenarios, 1 = increase low confidence; 10 = increase medium confidence; 100 = increase high confidence; 2 = no change low confidence; 20 = no change medium confidence; 200 = no change high confidence; 3 =unclear (insufficient data); 4 = unclear (mixed evidence).</p> <p>Projected synergies and tradeoffs in AGC and soil C under each scenario were estimated by combining the soil C and AGC results. The following rasters display projected synergies and tradeoffs in soil C and AGC under current and RCP 8.5 mid-century rainfall. </p> <ul> <li> <p>“AGC_Soil_Bivariate_currentclimate”</p> </li> <li> <p>“AGC_Soil_Bivariate_RCP85_midcentury”</p> </li> </ul> <p>For both scenarios: the first value is soil C category: 7 = unknown/uncertain; 8= increase; 9= no change; and the second value is AGC category: 0 = decrease; 1 = no change; 2 = increase.</p> <p><strong> </strong></p> <h2>References:</h2> <p>Asner, G. P., Sousan, S., Knapp, D. E., Selmants, P. C., Martin, R. E., Hughes, R. F., & Giardina, C. P. (2016). Rapid forest carbon assessments of oceanic islands: A case study of the Hawaiian archipelago. 11(1). <a href="https://doi.org/10.1186/s13021-015-0043-4">https://doi.org/10.1186/s13021-015-0043-4</a></p> <p>Cardinael, R., Umulisa, V., Toudert, A., Olivier, A., Bockel, L., & Bernoux, M. (2018). Revisiting IPCC Tier 1 coefficients for soil organic and biomass carbon storage in agroforestry systems. Environmental Research Letters, 13. <a href="https://doi.org/10.1088/1748-9326/aaeb5f/meta">https://doi.org/10.1088/1748-9326/aaeb5f/meta</a></p> <p>Chaterjee, N., Nair, P. K. R., Chakraborty, S., & Nair, V. D. (2018). Changes in soil carbon stocks across the forest-agrofoest-agriculture/pasture continuum in various agroecological regions: A meta-analysis. Agriculture, Ecosystems & Environment, 266, 55–67. <a href="https://doi.org/10.1016/j.agee.2018.07.014">https://doi.org/10.1016/j.agee.2018.07.014</a></p> <p>De Stefano, A., & Jacobson, M. G. (2017). soil carbon sequestration in agroforestry systems: A meta-analysis. Agroforestry Systems. <a href="https://doi.org/10.1007/s10457-017-0147-9">https://doi.org/10.1007/s10457-017-0147-9</a></p> <p>Elison Timm, O., Giambelluca, T. W., & Diaz, H. F. (2015). Statistical downscaling of rainfall changes in Hawaiʻi based on the CMIP5 global model projections. Journal of Geophysical Research: Atmospheres. <a href="https://doi.org/10.1002/2014JD22059">https://doi.org/10.1002/2014JD22059</a></p> <p>Giambelluca, T. W., Chen, Q., Frazier, A. G., Price, J. P., Chen, Y. L., Chu, P. S., Eischeid, J. K., & Delparte, D. M. (2013). Online Rainfall Atlas of Hawaiʻi. Bulletin Of the American Meteorological Society, 94, 313–316. <a href="https://doi.org/10.1175/BAMS-D-11-00228.1">https://doi.org/10.1175/BAMS-D-11-00228.1</a></p> <p>Jacobi, J. D., Price, J. P., Fortini, L. B., Gon III, S. M., & Berkowitz, P. (2017). Carbon Assessment of Hawaiʻi Land Cover Map [Map]. USGS. </p> <p><a href="https://www.sciencebase.gov/catalog/item/592dee56e4b092b266efeb6b">https://www.sciencebase.gov/catalog/item/592dee56e4b092b266efeb6b</a></p> <p>Kurashima, N., Fortini, L., & Ticktin, T. (2019). The potential of indigenous agricultural food production under climate change in Hawaiʻi. Nature Sustainability. <a href="https://doi.org/10.1038/s41892-019-0226-1">https://doi.org/10.1038/s41892-019-0226-1</a></p> <p>Selmants, P. C., Giardina, C. P., Sousan, S., Knapp, D. E., Kimball, H., Hawbaker, T. J., Moreno, A., Seirer, J., Running, S. W., Miura, T., Bergstrom, R., Hughes, R. F., Litton, C. M., & Asner, G. P. (2017). Baseline Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawaiʻi. USGS.</p> <p>State Land Use Commission. (2020). State Land Use District Boundaries [Map]. Hawaiʻi Statewide GIS Program.</p>
The role of atmospheric drivers in a sudden transition of California precipitation in the 2012/13 winter
<p>This contains the data, presented in a publication entitled "The role of atmospheric drivers in a sudden transition of California precipitation in the 2012/13 winter" (JGR: Atmospheres). See the paper for details. See 'Readme.pdf' for the file descriptions.</p>
Dataset: Magic in transition metal dichalcogenide bilayers
<p>Dataset for the paper "Magic in transition metal dichalcogenide bilayers" (arXiv:2106.11954). </p>
Large-scale eDNA metabarcoding survey reveals marine biogeographic break and transitions over tropical north-western Australia
<p><b>Aim:</b> Environmental DNA (eDNA) metabarcoding has demonstrated its applicability as a highly sensitive biomonitoring tool across small spatial and temporal scales in marine ecosystems. However, it has rarely been tested across large spatial scales, or biogeographical barriers. Here, we scale up marine eDNA metabarcoding, test its ability to detect a major marine biogeographic break, and evaluate its use as a regional biomonitoring tool in Australia.</p> <p><b>Location:</b> North-western Australia (NWA)</p> <p><b>Methods:</b> We applied metabarcoding assays targeting the mitochondrial 16S rRNA and CO1 genes to 284 surface seawater eDNA samples collected from 71 mid-shelf, inshore, coastal and nearshore estuarine sites over 700 km of the NWA coastline.</p> <p><b>Results:</b> Metabarcoding detected a wide range of bony fish (404 taxa), elasmobranchs (44) and aquatic reptiles (5). We detected bioregional and depth differentiation within inshore bony fish communities. These findings support the presence of a marine biogeographic break, which is purported to occur in the vicinity of Cape Leveque, demarcating the border between the Kimberley and Canning bioregions. Inshore bony fish and elasmobranch communities, as well as coastal bony assemblages, were additionally found to differ between the South and North Kimberley regions <span><span>suggesting</span></span> previously unrecognised subregional differentiation among these taxa. The overall compositional data has been used to update distribution information for a number of endangered, elusive and data-deficient taxa, including sawfish (family: Pristidae), northern river shark (<i>Glyphis garricki</i>) and wedgefish (genus: <i>Rhynchobatus</i>).</p> <p><b>Main conclusions</b>: eDNA metabarcoding demonstrated a high level of sensitivity that was able to discern fine-scale patterns across the large-scale, remote and oceanographically complex region of North-western Australia. Importantly, this study highlights the potential of integrating broad-scale eDNA metabarcoding alongside other baseline surveys and long-term monitoring approaches, which are crucial for the sustainable management and conservation of marine biodiversity in this unique marine region.</p>
HD118203 transit analysis
Analysis of the transits of HD118203 in TESS based on https://gallery.exoplanet.codes/tutorials/quick-tess/ and https://arxiv.org/abs/1911.05150.<br><br>Created using <a href="https://github.com/rodluger/showyourwork">showyourwork</a> from <a href="https://github.com/rodluger/showyourwork-paper/tree/3b41b07849677bb7c0d89c6c04652944de20669e">this GitHub repo</a> using the following command: <pre><code class="language-bash">cd src/figures && python src/analysis/HD118203.py</code></pre>
Bizarre tail weaponry in a transitional ankylosaur from subantarctic Chile
<p>Armoured dinosaurs are well known for their evolution of specialized tail weapons— paired tail spikes in stegosaurs and heavy tail clubs in advanced ankylosaurs1. Armoured dinosaurs from southern Gondwana are rare and enigmatic, but probably include the earliest branches of Ankylosauria2–4. Here we describe a mostly complete, semi-articulated skeleton of a small (approximately 2 m) armoured dinosaur from the late Cretaceous period of Magallanes in southernmost Chile, a region that is biogeographically related to West Antarctica5. Stegouros elengassen gen. et sp. nov. evolved a large tail weapon unlike any dinosaur: a flat, frond-like structure formed by seven pairs of laterally projecting osteoderms encasing the distal half of the tail. Stegouros shows ankylosaurian cranial characters, but a largely ancestral postcranial skeleton, with some stegosaur-like characters. Phylogenetic analyses placed Stegouros in Ankylosauria; specifically, it is related to Kunbarrasaurus from Australia6 and Antarctopelta from Antarctica7, forming a clade of Gondwanan ankylosaurs that split earliest from all other ankylosaurs. The large osteoderms and specialized tail vertebrae in Antarctopelta suggest that it had a tail weapon similar to Stegouros. We propose a new clade, the Parankylosauria, to include the first ancestor of Stegouros— but not Ankylosaurus—and all descendants of that ancestor.</p>
Bizarre tail weaponry in a transitional ankylosaur from subantarctic Chile
<p>Armoured dinosaurs are well known for their evolution of specialized tail weapons— paired tail spikes in stegosaurs and heavy tail clubs in advanced ankylosaurs1. Armoured dinosaurs from southern Gondwana are rare and enigmatic, but probably include the earliest branches of Ankylosauria2–4. Here we describe a mostly complete, semi-articulated skeleton of a small (approximately 2 m) armoured dinosaur from the late Cretaceous period of Magallanes in southernmost Chile, a region that is biogeographically related to West Antarctica5. Stegouros elengassen gen. et sp. nov. evolved a large tail weapon unlike any dinosaur: a flat, frond-like structure formed by seven pairs of laterally projecting osteoderms encasing the distal half of the tail. Stegouros shows ankylosaurian cranial characters, but a largely ancestral postcranial skeleton, with some stegosaur-like characters. Phylogenetic analyses placed Stegouros in Ankylosauria; specifically, it is related to Kunbarrasaurus from Australia6 and Antarctopelta from Antarctica7, forming a clade of Gondwanan ankylosaurs that split earliest from all other ankylosaurs. The large osteoderms and specialized tail vertebrae in Antarctopelta suggest that it had a tail weapon similar to Stegouros. We propose a new clade, the Parankylosauria, to include the first ancestor of Stegouros— but not Ankylosaurus—and all descendants of that ancestor.</p>
Seismic Anisotropy in the Lower Mantle Transition Zone Induced by Lattice Preferred Orientation of Akimotoite-Dataset
<p>The dataset includes the lattice preferred orientation data of akimotoite aggregates obtained through EBSD and transmitted two-dimensional (2D) X-ray diffraction method at BL04B1 of synchrotron facility of SPring-8, Hyogo, Japan. The employed conditions of 2D X-ray diffraction measurements are also available.</p>
caneill et al. The polar transition from alpha to beta regions set by a surface buoyancy flux inversion.
<p>NEMO outputs used for the paper Caneill, R., Roquet, F., Madec, G., and Nycander, J. (2022). The polar transition from alpha to beta regions set by a surface buoyancy flux inversion. Journal of Physical Oceanography.</p> <p><a href="https://doi.org/10.1175/JPO-D-21-0295.1">https://doi.org/10.1175/JPO-D-21-0295.1</a></p> <p>Abstract:</p> <p>The stratification is primarily controlled by temperature in subtropical regions (alpha-ocean), and by salinity in subpolar regions (beta-ocean). Between these two regions lies a transition zone, often characterized by deep mixed layers in winter and responsible for the ventilation of intermediate or deep layers. While of primary interest, no consensus on what controls its position exists yet. Amongst the potential candidates, we find the wind distribution, air-sea fluxes or the nonlinear cabbeling effect. Using an ocean general circulation model in an idealized basin configuration, a sensitivity analysis is performed testing different equations of state. More precisely, the thermal expansion coefficient (TEC) temperature dependence is explored, changing the impact of heat fluxes on buoyancy fluxes in a series of experiments. The transition zone is found to be located at the position where the sign of the surface buoyancy flux reverses to become positive, in the subpolar region, while wind or cabbeling are found of secondary importance. This inversion becomes possible because the TEC is reducing at low temperature, enhancing in return the relative impact of freshwater fluxes on the buoyancy forcing at high latitudes. When the TEC is made artificially larger at low temperature, the freshwater flux required to produce a positive buoyancy flux increases and the transition zone moves poleward. These experiments demonstrate the important role of competing heat and freshwater fluxes in setting the position of the transition zone. This competition is primarily influenced by the spatial variations of the TEC linked to meridional variations of the surface temperature.</p> <p> </p> <p>Download data:</p> <p>Due to their large size, the data have been split into multiple zip files. To extract them, follow the following commands:</p> <pre><code class="language-bash">zip -s 0 EXP_main.zip --out out.zip unzip out.zip</code></pre> <p> </p>
Different molecular changes underlie the same phenotypic transition: Origins and consequences of independent shifts to homostyly within species
<p>The repeated transition from outcrossing to selfing is a key topic in evolutionary biology. However, the molecular basis of such shifts has been rarely examined due to lack of knowledge of the genes controlling these transitions. A classic example of mating system transition is the repeated shift from heterostyly to homostyly. Occurring in 28 angiosperm families, heterostyly is characterized by the reciprocal position of male and female sexual organs in two (or three) distinct, usually self-incompatible floral morphs. Conversely, homostyly is characterized by a single, self-compatible floral morph with reduced separation of male and female organs, facilitating selfing. Here, we investigate the origins of homostyly in <i>Primula vulgaris </i>and its microevolutionary consequences by integrating surveys of the frequency of homostyles in natural populations, DNA sequence analyses of the gene controlling the position of female sexual organs (<i>CYPᵀ</i>), and microsatellite genotyping of both progeny arrays and natural populations characterized by varying frequencies of homostyles. As expected, we found that homostyles displace short-styled individuals, but long-style morphs are maintained at low frequencies within populations. We also demonstrated that homostyles repeatedly evolved from short-styled individuals in association with different types of loss-of-function mutations in <i>CYPᵀ</i>. Additionally, homostyly triggers a shift to selfing, promoting increased inbreeding within and genetic differentiation among populations. Our results elucidate the causes and consequences of repeated transitions to homostyly within species, and the putative mechanisms precluding its fixation in <i>P. vulgaris</i>. This study represents a benchmark for future analyses of losses of heterostyly in other angiosperms.</p>
A critical review of 'just transition' publications using Google and Google Scholar
<p>This dataset offers the list of sources included in our critical review of the term 'just transition' (in English), from 1990 to 2021 in the Global North and South Africa, using Google and Google Scholar as search engines. The publications retrieved include both peer-reviewed literature and publicly available reports and documents. Results (with full citations) are categorized by actor group and type, location, and year of publication.</p>
FIG. 13 in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 13. — Bathymetric reconstruction and correlations between sections.
Dataset for "Ancient whale rhodopsin reconstructs dim-light vision over a major evolutionary transition: Implications for ancestral diving behaviour"
<p>Dataset files include:</p> <p>- Alignment of rhodopsin (Rh1) sequences formatted for PAML</p> <p>- Corresponding species tree in Newick format for PAML</p> <p>- Ancestral Rh1 amino acid sequences (for Cetacean and Whippomorpha nodes) estimated with PAML (random sites, clade, and amino acid models), Datamonkey, and ProtASR</p>
Dataset for paper entitled 'Microstructure transition gradients in titanium dissimilar alloy (Ti-5Al-5V-5Mo-3Cr/Ti-6Al-4V) tailored wire-arc additively manufactured components'
<p>Dataset for paper entitled 'Microstructure transition gradients in titanium dissimilar alloy (Ti-5Al-5V-5Mo-3Cr/Ti-6Al-4V) tailored wire-arc additively manufactured components'. doi: <a href="https://doi.org/10.1016/j.matchar.2021.111577">https://doi.org/10.1016/j.matchar.2021.111577</a></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.