16 research outputs found

    Spearman correlations of CCA-axes and environmental variables.

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    <p>Spearman correlations of CCA-axes and environmental variables (n = 83). Only significant correlations are shown. Levels of significance:</p>**<p> = 0.0001*</p><p> = 0.01</p><p>Factors included in CCA factors are given in bold. Further details concerning single variables are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051520#pone-0051520-t001" target="_blank">Table 1</a>.</p

    Summaries of multiple regression analyses.

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    <p>Summaries of multiple regressions of species richness of acrocarpous, pleurocarpous and all bryophytes as well as bryophyte cover on intensities of land-use procedures (Model A); aboveground biomass and their nutrient content (Model B), and mean Ellenberg indicator values for vascular plants (Model C) in the two regions. Levels of significance:</p>***<p> = p<0.0001;</p>**<p> = 0.0001*</p><p> = 0.01</p><p>Further details concerning single variables are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051520#pone-0051520-t001" target="_blank">Table 1</a>.</p

    Summary about bryophyte, land-use intensity, productivity and indicator value data.

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    <p>Mean, minimum, maximum and SE of bryophyte diversity, vascular plant species, land-use measures, aboveground vascular plant biomass, nutrient content of biomass (Ca = calcium, K = potassium; Mg = magnesium, P = phosphorus; N = nitrogen), and mean Ellenberg indicator values for vascular plants for the two regions. Letters (<sup>a, b</sup>) indicate significant group differences between the regions.</p

    Frequency distribution of bryophyte species.

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    <p>Relative frequency distribution of the species richness of all, pleurocarpous, and acrocarpous bryophyte species per 16 m<sup>2</sup> plots in grasslands (<i>n</i> = 85).</p

    Relationships between bryophyte species richness and intensities of land-use and productivity.

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    <p>Relationships between total bryophyte species richness and intensities of land-use practices, mean annual amount of N fertilizer [kg*ha<sup>−1</sup>*year<sup>−1</sup>]; mean annual number of cuts [Cuts*year<sup>−1</sup>] from 2006–2008, aboveground community biomass of vascular plants [g*m<sup>−2</sup>], Nitrogen concentrations in biomass [[g/kg<sup>−1</sup>]], mean Ellenberg indicator values for vascular plants for nutrients (N) and for moisture (M) on 85 grassland plots.</p

    Relationship between species richness of bryophytes and vascular plants.

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    <p>Relationship between species richness of bryophytes and vascular plants (<i>n</i> = 85; y = 0.17x - 0.15; R<sup>2</sup> = 0.47; F = 74.1; P<0.0001).</p

    CCA-ordination of bryophyte species richness and environmental variables for stands (a) and species (b).

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    <p>CCA-ordination of bryophyte species and environmental factors in grasslands (n = 83). Stands and environmental factors (a) and species (b) of the same ordination are plotted separately to ease readability. Hainich-Dün: open circles; Schorfheide-Chorin: stars. Plots in the dotted circle are situated on either Gleyosols or Histisols. N and K are nutrient concentrations in aboveground vascular plant biomass and Ellenberg indicator values given are gained from vascular plant vegetation. Longer vectors indicate stronger correlations between variables and axes. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051520#pone-0051520-t001" target="_blank">Table 1</a> for further details on single variables.</p

    Calibration and validation statistics of partial least-squares regression models.

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    <p>Calibrations were evaluated as follows (Saeys et al (2005): excellent (R<sup>2</sup>/r<sup>2</sup> ≥ 0.9, RPD ≥ 3.0), reliable quantitative predictions (R<sup>2</sup>/r<sup>2</sup> ≥ 0.75 and <0.9, RPD ≥ 2.0 and <3.0), differentiation between high and low values (R<sup>2</sup>/r<sup>2</sup> ≥ 0.65 and <0.75, RPD ≥ 1.5 and <2.0, unsuccessful (R<sup>2</sup>/r<sup>2</sup> <0.65, RPD <1.5).</p><p>Transf: transformations for regression analyses.</p><p>Abs: Log1/R (R = reflectance).</p><p>1D: first derivative.</p><p>R<sup>2</sup>: coefficient of multiple determination (calibration).</p><p>SEC: standard error of calibration.</p><p>SECV: standard error of cross validation.</p><p>r<sup>2</sup>: regression coefficient NIRS predicted vs. observed values.</p><p>SEP: standard error of prediction (validation).</p><p>RPD: ratio of SD of reference values (validation) to SEP.</p><p>RPIQ: ratio of the interquartile distance IQ ( = Q3–Q1) of reference values (validation) to SEP.</p><p>Corr. OM: Pearson correlation with organic matter content.</p

    Results of quadratic discriminant analysis (QDA) of management types (organic vs. conventional) deduced from regionally standardized δ<sup>15</sup>N and δ<sup>13</sup>C isotopic abundances of soil and/or hay samples of grasslands.

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    <p>Results of quadratic discriminant analysis (QDA) of management types (organic vs. conventional) deduced from regionally standardized δ<sup>15</sup>N and δ<sup>13</sup>C isotopic abundances of soil and/or hay samples of grasslands.</p
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