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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>
Trophic resource partitioning drives fine-scale coexistence in cryptic bat species
Understanding the processes that enable species coexistence has important implications for assessing how ecological systems will respond to global change. Morphology and functional similarity increase the potential for competition, and therefore, co-occurring morphologically similar but genetically unique species are a good model system for testing coexistence mechanisms. We used DNA metabarcoding and High Throughput Sequencing to characterise for the first time the trophic ecology of two recently-described cryptic bat species with parapatric ranges, Myotis escalerai and Myotis crypticus. We collected faecal samples from allopatric and sympatric regions and from syntopic and allotopic locations within the sympatric region to describe the diets both taxonomically and functionally and compare prey consumption with prey availability. The two bat species had highly similar diets characterised by high arthropod diversity, particularly Lepidoptera, Diptera and Araneae, and a high proportion of prey that is not volant at night, which points to extensive use of gleaning. Diet overlap at the prey-item level was lower in syntopic populations, supporting trophic shift under fine-scale co-occurrence. Furthermore, the diet of M. escalerai had a marginally lower proportion of not nocturnally volant prey in syntopic populations, suggesting that the shift in diet may be driven by a change in foraging mode. Our findings suggest that fine-scale coexistence mechanisms can have implications for maintaining broad-scale diversity patterns. This study highlights the importance of including both allopatric and sympatric populations and choosing meaningful spatial scales for detecting ecological patterns. We conclude that a combination of high taxonomic resolution with a functional approach helps identify patterns of niche shift.
Preferential allocation of benefits and resource competition among recipients allows coexistence of symbionts within hosts
<p>Functionally variable symbionts commonly co-occur including within the roots of individual plants, in spite of arguments from simple models of the stability of mutualism that predict competitive exclusion among symbionts. We explore this paradox by evaluating the dynamics generated by symbiont competition for plant resources, and the plant's preferential allocation to the most beneficial symbiont, using a system of differential equations representing the densities of mutualistic and non-mutualistic symbionts and the level of preferentially allocated and non-preferentially allocated resources for which the symbionts compete. We find that host preferential allocation and costs of mutualism generate resource specialization that makes the coexistence of beneficial and non-beneficial symbionts possible. Furthermore, coexistence becomes likely due to negative physiological feedbacks in host preferential allocation. We find that biologically realistic models of plant physiology and symbiont competition predict that the coexistence of beneficial and non-beneficial symbionts should be common in root symbioses, and that the density and relative abundance of mutualists should increase in proportion to the needs of the host.</p>
Coexisting multi-states in catalytic hydrogen oxidation on rhodium - Supplementary Database 1
<p>Supplementary Database 1 to the associated article in Nature Communications (DOI: <a href="https://doi.org/10.1038/s41467-021-26855-y">10.1038/s41467-021-26855-y</a>) containing the raw data for the results shown in the display items. Experimental conditions, parameters and evaluation procedures are given in the corresponding figure captions and the Methods section of the associated article.</p>
Functional niche constraints on carnivore assemblages (mammalia: carnivora) in the Americas: What facilitates coexistence through space and time?
<p><b>Aim:</b> Mammalian carnivores are among the best studied groups in terms of evolutionary history. However, the effects of species interactions in shaping community assemblages remain poorly understood. We hypothesize that indirect interactions via ecological trait filtering play a key role in structuring carnivoran assemblages, mediate coexistence, and thus should show high functional diversity in space and time at continental scales.</p> <p><b>Location:</b> Americas.</p> <p><b>Taxon:</b> Mammalian carnivores (Mammalia: Carnivora).</p> <p><b>Methods:</b> We followed a macroecological perspective via ecological networks analyses for indirect interactions, and assessed the underlying functional diversity (FD) across space and from the Last Interglacial to the present in the Americas. We analyzed the potential distributions and six ecological traits of 88 species to establish possible mechanisms that enables species to coexist and the underlying diversity patterns. We compared the empirical results with two null models, and two sensitivity analyses.</p> <p><b>Results:</b> Co-occurring carnivore species presented ecological segregation driven mainly by a size ratio (S <sub>R</sub>) relationship, called here the body-size spatial anti-clustering effect. The underlying FD patterns showed low redundancy towards the tropics and the poles during the times evaluated. However, during the LGM, shifts occurred primarily at high latitudes in North America. This shift affected the S <sub>R</sub> relationship and therefore changed functional diversity patterns. These local-to-continental interactions mediated by the S <sub>R</sub> are significant from an ecological and biogeographic perspective, suggesting a robust and consistent trend in which carnivore species of similar size have a lower probability of occupying the same area unless they differentiate in other ecological trait spaces.</p> <p><b>Main conclusions:</b> The S <sub>R</sub> relationship is potentially a primary mechanism limiting carnivore coexistence, reflecting functional filtering. The S <sub>R</sub> tends to be conservative across different ecological trait groups and through time and space. We propose that the body-size spatial anti-clustering effect can directly measure species' coexistence and mediate FD patterns in the Americas.</p>
A quantitative synthesis of soil microbial effects on plant species coexistence: code and data
<p>This release contains data and code to conduct all analyses in Yan et al. "A quantitative synthesis of soil microbial effects on plant species coexistence".</p>
Data from: Stochasticity leads to coexistence of generalists and specialists in assembling mutualistic communities
<p>Previous models for assembling ecological networks did not include stochasticity at the level of population dynamics (e.g., demographic noise, environmental noise) and focused mainly on food webs. Here, we present a model for the assembly of mutualistic bipartite networks, such as plant-pollinator networks, and examine the influence of demographic noise on the trajectory of species and strategy diversity, i.e., the range of present strategies from specialism to generalism. We find that assembled communities show at intermediate assembly stages a maximum of species diversity and of average generalization. Our model thus provides a mechanism for non-linear, hump-shaped diversity trajectories at intermediate succession, consistent with the intermediate disturbance hypothesis. Long-term coexistence of specialists and generalists emerges only in the presence of demographic noise and is due to a persistent species turnover. These findings highlight the importance of stochasticity for maintaining long-term diversity.</p>
Positive allometric growth explains the positive effect of foliar fungal pathogens on plant coexistence
<p><span>The data was collected in the northeastern Qinghai-Tibetan Plateau, Qinghai Province, China (101° 18′ 57</span>″ <span>E, 37° 36′ 50</span>″ <span>N; 3 221 m a.s.l.) in 2019 and 2020, including t</span>he species-specific growth allometry (scaling exponent and intercept) fitted by the allometric equation under each treatment in a population-level experiment, i.e., control, fungicide application, neighbor removal (removal), fungicide application × neighbor removal, and the community-level mean and dispersion of the growth allometry (CWM and FDis of growth scaling exponent and intercept, respectively) weighted by the species cover for each plot in a community-level fungicide application experiment.</p>
The expression of demographic costs of reproduction varies among coexisting plants with different life history traits
<p><span>1. </span><span>Demographic costs of reproduction in flowering plants should depend on life history and reproductive effort, but how the expression of costs varies with life history traits is poorly understood.</span></p> <p><span>2. </span><span>We experimentally increased and reduced reproductive effort (fruit production) to quantify demographic costs of reproduction in four coexisting species with contrasting growth forms (clonal vs. nonclonal) and flower production (single- vs. multi-flowered). We repeated the experiment in three years, and measured demographic rates the year after treatment. In two years, we also quantified costs of flower maintenance by contrasting the performance of nonfruiting plants with intact flowers and plants with their flowers removed.</span></p> <p><span>3. </span><span>Costs varied among species, in both magnitude and demographic rate affected. Costs of natural reproduction were expressed as reductions in size and fecundity next year, whereas increased reproduction additionally reduced sprouting probability. The magnitude of demographic costs of both reproduction and flower maintenance was highest in the nonclonal, multi-flowered species, and costs were more frequently detected in the two multi-flowered species than in the single-flowered ones. This may be explained by higher biomass allocation to reproductive parts and a longer flowering period in the former. Demographic costs of reproduction did not depend on clone size.</span></p> <p><span>4. </span><span>These results document that demographic costs vary among coexisting species sharing similar niches, and are associated with divergence in life history traits. Such trait-dependent variation in costs may reduce competition among coexisting species and facilitate diversity.</span></p>
Understanding farmers' reasons behind mitigation decisions is key in supporting their coexistence with wildlife
<p>1. Coexistence between wildlife and farmers can be challenging and can endanger the lives of both, prompting the provisioning of mitigation methods by governments and non-governmental organisations (NGOs). However, provision of materials, demonstration of the effectiveness of methods or willingness to uptake a method do not predict uptake of methods.</p> <p>2. We used Ethnographic Decision Models to understand how farmers' work through the decisions of uptake or non-uptake of methods to mitigate crop consumption by elephants, and how the government and NGOs can either enable or impede the ability of farmers to protect themselves and their crops.</p> <p>3. While farmers were motivated to use methods if they received or could afford to buy materials and they believed in the effectiveness of the methods, they still did not use them if they considered a method to be dangerous, or issues with elephants not to be severe enough, or when the supply of materials or income was not sufficient. Methods were not even considered by farmers if they lacked awareness or knowledge of the method. Government departments and NGOs enabled farmers to mitigate elephant crop consumption by providing opportunities for cash income, and providing materials and knowledge. Yet, there was disparity between the materials farmers received and methods they wished to adopt.</p> <p>4. One-off inputs of materials did not result in sustainable use of mitigation methods. We see an opportunity for governmental departments or NGOs to stimulate logistics (e.g. roads and retail) to increase availability of mitigation materials since this promoted farmer autonomy. We also highlight the importance of empowering farmers by facilitating within community sharing of mitigation ideas and increasing knowledge about the effectiveness of promising wildlife conscious farming, as despite promising farmer testimonies, only a few farmers used these techniques.</p>
Figures 3-4 in Coexistence of Asemonea cf. tenuipes (Araneae: Salticidae: Asemoneinae) with Crematogaster ants (Formicidae: Myrmicinae) and a mealybug (Hemiptera: Pseudococcidae)
Figures 3-4. Penultimate male Asemonea cf. tenuipes in shelter under a leaf of a teak tree, Tectona grandis, with ants (Crematogaster sp.) tending to a mealybug.
Figures 1-2 in Coexistence of Asemonea cf. tenuipes (Araneae: Salticidae: Asemoneinae) with Crematogaster ants (Formicidae: Myrmicinae) and a mealybug (Hemiptera: Pseudococcidae)
Figures 1-2. Penultimate male Asemonea cf. tenuipes in shelter under a leaf of a teak tree, Tectona grandis, with ants (Crematogaster sp.) tending to a mealybug.
Datasets for Twort et al. Signals of positive selection in Palearctic bat species coexisting with a fungal pathogen
<p>Datasets used in Twort et al: Signals of positive selection in Palearctic bat species coexisting with a fungal pathogen</p> <p>Included are final gene alignments and tree files from the Phylogenetic Dataset (2515 genes) and the curated dataset (300 genes).</p> <p>Phylogenetic Dataset Files:</p> <ul> <li>BUSCO Dataset: 2515 genes extracted from the Mammalia_odb10 BUSCO database. This dataset was used for phylogeney construction and branch tests</li> <li>Align_BUSCO: Contains the final cleaned alignments used for the 2515 Phylogenetic dataset genes (after gblocks) in fasta format</li> <li>Contree_BUSCO.zip: Contains the consensus tree constructed with IQ-Tree for the 2,515 phylogenetic gene dataset (used as input for ASTRAL,and for branch tests) </li> <li>Ufboot_BUSCO.zip: Contains the bootstrap trees from IQ-Tree for the 2,515 gene dataset</li> <li>Branch_Myoluc_labelled_BUSCO.zip: Final labelled trees, with Myotis lucifugus labelled as foreground branch from the 2,515 gene dataset used for PAML branch tests, all bootstrap values and branch lengths have been removed.</li> <li>Branch_Myomyo_labelled_BUSCO.zip: Final labelled trees, with Myotis myotis labelled as foreground branch from the 2,515 gene dataset used for PAML branch tests, all bootstrap values and branch lengths have been removed.</li> </ul> <p>Curated Dataset Files:</p> <ul> <li>PAML Dataset - 300 gene set, This dataset was used for codon tests (PAML)</li> <li>Align_Paml: Contains the final cleaned alignments for the 300 gene dataset (after gblocks) in fasta format</li> <li>Contree_PAML: Contains the consensus trees constructed with IQ-Tree for the 300 gene dataset </li> </ul> <p>Version 2 corrects a sample labelling mistake present in Version 1.</p>
Fig. 1 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 1. Beach profile showing the burrow zones of Ocypode gaudichaudii at Culebra Beach.
Fig. 1. A in Tolerance to Anhydrobiotic Conditions Among Two Coexisting Tardigrade Species Differing in Life Strategies.
Fig. 1. A simple schematic illustration of the experiments.
ML-Optimized QKD Frequency Assignment for Efficient Quantum-Classical Coexistence in Multi-Band EONs
<p>Abstract: Quantum key distribution (QKD) represents a cutting-edge technology that ensures unbreakable security. Coexisting quantum and classical signals on a multi-band (O+E+S+C+L-band) system offer a viable solution for secure, high-rate networks amidst growing classical traffic and address quantum signal sensitivity. In this study, we assume a dynamic classical traffic load and varying configurations of classical channels (CChs). Considering the varying behavior of Secure Key Rate (SKR) under different classical conditions, solving the integral noise equations are crucial for optimizing QKD implementation and enhancing resource efficiency. The complexity and time-consuming nature of this process challenge infrastructure providers in determining the optimal quantum channel (QCh) frequency in real time. To tackle these challenges, we propose a machine learning (ML) algorithm. By leveraging ML, QKD can be implemented efficiently, optimizing resource utilization while significantly reducing computation and processing time in dynamic classical traffic. We implement three ML algorithms at various fiber intervals, all of which estimate the optimal frequency for QCh with 99\% accuracy and perform computations on average in 0.09 seconds, which is significantly faster compared to integral computational methods that have a mean time of 637 seconds.<br><br>Information: In this file, the Excel sheet contains data for each fiber interval, including inputs such as fiber length in each interval, the overall classical loading factor percentage, the C-band loading factor percentage, the L-band loading factor percentage, the highest active classical frequency (which serves as input to the machine learning model), and the QCh frequency that resulted in the highest SKR.</p>
Data and codes for "Habitat structural complexity increases age-class coexistence and population growth rate through relaxed cannibalism in medaka fish"
<p>The zip file contains readme files, as well as data and codes to reproduce results and figures from the paper.</p>
Fragmentation in trader preferences among multiple markets: Market coexistence versus single market dominance
<p>Technological advancement has lead to an increase in number and type of trading venues and diversification of goods traded. These changes have re-emphasized the importance of understanding the effects of market competition: does proliferation of trading venues and increased competition lead to dominance of a single market or coexistence of multiple markets? In this paper, we address these questions in a stylized model of Zero Intelligence traders who make repeated decisions at which of three available markets to trade. We analyse the model numerically and analytically and find that parameters that govern traders' decisions--memory length and intensity of choice, e.g. how strongly decisions are based on past success--make the key distinctions between consolidated and fragmented steady states of the population of traders. All three markets coexist with equal shares of traders only when either learning is too weak and traders choose randomly, or when markets are identical. In the latter case, the population of traders is fragmented across the markets. For the more general case of markets with different biases, we note that market dominance is the more typical scenario. These results are interesting because previously either strong differentiation of markets or heterogeneity in the needs of traders was found to be a necessary condition for market coexistence. We show that, in contrast, these states can emerge simply as a consequence of co-adaptation of an initially homogeneous population of traders.</p>
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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.