17 research outputs found

    Density of all frugivorous Lepidoptera, and both specialist and generalists, per fruit.

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    <p>Host species are ranked from highest to lowest density for 326 plant species with samples of >1 kg and >50 fruits. Note that all plants to the right of each curve exhibited zero density for the herbivore category in question that cannot be shown on the log scale d y axis.</p

    Mean volume for whole fruit, mesocarp and seeds (a) and fleshiness (b) in plant species attacked and not attacked by Lepidoptera.

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    <p>The differences between attacked and non-attacked species are significant (whole fruit: U <sub>106,151</sub> = 5624, Z = 3.064, P = 0.002; mesocarp: U <sub>106,151</sub> = 5828, Z = 2.69, P = 0.007; seeds: U <sub>106,151</sub> = 5346, Z = 3.574, P < 0.0010), (b) Fleshiness (i.e. proportion of mesocarp in whole fruit) did not have significant effect on infestation (U <sub>106,151</sub> = 6839, Z = 0.83, P = 0.401).</p

    Overlap of Lepidoptera species in frugivorous (this study) and leaf-chewer (different study, [68]) guilds.

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    <p>Overlap of Lepidoptera species in frugivorous (this study) and leaf-chewer (different study, [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171843#pone.0171843.ref068" target="_blank">68</a>]) guilds.</p

    Effect of sampling scenario on FD index sensitivity.

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    <p>Barplots showing the results of linear mixed effects model, specifically the effect of the two sampling scenarios on the sensitivity of indices for three different types of organisms. The more negative the regression slope, the more sensitive the particular index is to missing trait information. The error bars denote the 95% confidence intervals. (A) plant community (n = 12 plots), (B) ant community (n = 58 plots), and (C) bird community (n = 8 plots).</p

    Plot-wise and pool-wise trait data thresholds.

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    <p>Schematic figure depicting plot-wise and pool-wise scenarios for setting the thresholds for trait data sampling. (A) species from all plots make up the pool of species; (B) species can be ordered by their abundance in each plot or in the whole pool; (C) the least abundant species in the whole pool of species are removed until reaching the desired threshold for trait sampling; (D) the least abundant species in each plot are removed until reaching the desired threshold for trait sampling.</p

    Effect of trait transformation on FD index sensitivity.

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    <p>The effect of trait transformation on the improvement in slope (transformed—untransformed trait data)—the bigger the improvement in slope, the more robust the index becomes to missing trait data (y axis). The right panels illustrate the different improvements in trait skewness, depicting examples of trait distribution before and after transformation, which correspond to the x axis of the main figure (matching colours).</p

    Effect of sampling method and abundance transformation on FD index sensitivity.

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    <p>Barplot depicting the results of linear mixed effects models, specifically the interaction between abundance transformation and the different abundance measures used in plant ecology (all three abundance measures were used for the same plant dataset in order to make their effects comparable). The effect of down-weighting the dominant species by log-transformation of their abundance was most pronounced in the biomass abundance measure. When log transformed, all three sampling methods have a very similar effect on the sensitivity of indices to missing trait data. Error bars denote the 95% confidence intervals.</p

    Flow diagram of the consecutive methodological steps.

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    <p>Upper left corner—in each plot species are ordered by their relative abundance and FD index is calculated for each plot of a community. Upper right corner—0.5% of the species relative abundance is removed in consecutive steps, starting with the least abundant species and FD index is then calculated again for each plot at each reduction step. Upper middle columns—plots are ranked based on the values of the FD index and the ranks of original data and data at each reduction step are correlated. Figure in the middle—regression slopes from fitting the linear model represent the robustness of FD index to missing trait data; in this example FD index is (A) less robust and (B) more robust to missing trait data (example RaoQ on head length of ants).</p
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