21 research outputs found

    Sensitivity of the immigration parameter <i>I˜</i>, as predicted from Gaussian and Cauchy dispersal kernels, to dispersal distance and local community radius.

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    <p>Isolines of are functions of the community radius <i>R<sub>c</sub></i> (10<<i>R<sub>c</sub></i> <600 m) and of the 95% quantile, (1<<600 m), for the Gaussian (left) and Cauchy (right) dispersal kernels. The null isoline of <i>x</i> represents the limit (equal sensitivity to the variation in <i>R<sub>c</sub></i> and ) between the dispersal dependent (DD, <i>x</i><0) and size dependent (SD, <i>x</i> > 0) zones (see main text). We displayed field plot locations (using the codes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0072497#pone-0072497-t001" target="_blank">Table 1</a>) by calculating the values corresponding to each plot size. Most of the plots fall into the DD and SD zones for the Gaussian Cauchy kernel, respectively.</p

    Isolines of the dispersal kernel-based analogue <i>I˜</i> of the immigration parameter (Eq. 1) computed as a function of the community radius <i>R<sub>c</sub></i> (1<<i>R<sub>c</sub></i><600 m) and of the 95% quantile (1<<600 m) of the Gaussian (left) and Cauchy (right) dispersal kernels.

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    <p>The dispersal dependent (DD) regime encompasses situations when <i>I˜</i> is mostly sensitive to (vertical portion of the isolines), while the size dependent (SD) regime sets in when <i>I˜</i> is mostly sensitive to <i>R<sub>c</sub></i> (horizontal portion of the isolines).</p

    Some orders of magnitude of seed dispersal distances of tree species in tropical rainforests, as estimated from field studies (extracted from [18]).

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    <p>Some orders of magnitude of seed dispersal distances of tree species in tropical rainforests, as estimated from field studies (extracted from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0072497#pone.0072497-Turner1" target="_blank">[18]</a>).</p

    Published estimates of the immigration parameter <i>I</i> in rainforest tree communities, using Spatially Implicit Neutral Models (SINMs).

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    <p>The corresponding 95% quantile dispersal distances, , are given under the assumption of pure dispersal limitation using the Gaussian and Cauchy kernels (see main text). <i>A</i> is the sample area in ha and <i>J<sub>s</sub></i> corresponds to the sample size in number of individuals above 10 cm dbh. <i>S</i> indicates the respective species richness of the sample plots. Bold/normal values respectively denote the published/transformed parameter values of Hubbell's <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0072497#pone.0072497-Hubbell1" target="_blank">[2]</a> migration rate <i>m</i> or the corresponding immigration parameter, <i>I</i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0072497#pone.0072497-Etienne6" target="_blank">[21]</a>. <i>m</i>/<i>I</i> and are calculated here for the case when the forest plots represent complete communities (i.e. sample size  =  community size in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0072497#pone-0072497-g001" target="_blank">Figure 1</a>). values have been rounded to the nearest metre.</p

    Predicted species growth response shapes and amplitudes to competition, tree size and aspect.

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    <p>Predicted growth at standardized conditions with respect to competition (A), tree size (B) and aspect (C), i.e. with the other covariates fixed at their observed means. The 6 most abundant species are in bold in top panels. Bottom panels represent the distribution of species signed sensitivity to covariates, as defined in section Analysis.</p

    Observed and fitted growth variability according to species maximum growth.

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    <p>Variance of observed growth within each species according to species maximum growth (A).Proportion of this intraspecific variability captured by the model for each species (R<sub>i</sub>²) according to species maximum growth (B). The lines represent fitted relationships with a power (A) and a linear function (B).</p
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