1. Life style influence on trace element content in mushrooms sporocarps. Juan A. Campos and Rosario García-Moreno

2. 1 km 2

3. ELEMENTAL QUANTITATIVE AND QUALITATIVE ANALYSIS BY X RAY FLUORESCENCE MgCaScRbSnTa AlFeVSrCsW SiNiCrYBaPb PCuCoZrLaTh SZnGaNbCeU KClYMoHfNd L D L= 0.5 ppm Error= <2% in repetitive measurements Philips-PW2404 Panalytical Magic-Pro Model

4. PREVIOUS LITERATURE

5. Campos and Tejera, 2011. Biological Trace Elements Research PREVIOUS LITERATURE

6. Hypothesis The differences in the occurrence of trace elements in fungi biomass may reflects the different ecological niches in wich they live and hence their relation with the inorganic substrate.

7. ECTOMYCORRHIZAL SAPROBES EPIPHYTES 1 Amanita phalloides 2 Hebeloma sinapizans 3 Lactarius zugazae 4 Paxillus involutus 5 Russula delica 6 Suillus bellini 7 Clitocybe maxima 8 Entoloma lividum 9 Lepista inversa 10 Lepista nuda 11 Lycoperdon perlatum 12 Macrolepiota procera 13 Agrocybe aegerita 14 Armillaria mellea 15 Gymnopilus spectabilis 16 Hericium erinaceum 17 Inonotus hispidus 18 Meripilus giganteus

8. All data given in this work are in ppm dm (mg.kg -1 dry matter basis)

9. Amanita phalloides Lactarius zugazae Russula delica Lycoperdon perlatum Meripilus giganteus Clitocybe maxima Inonotus hispidus Paxillus involutus Suillus bellini Gymnopilus spectabilis Macrolepiota procera Entoloma lividum Hericium erinaceum Armillaria mellea Lepista inversa Lepista nuda Agrocybe aegerita Hebeloma sinapizans DENDROGRAM OF CLUSTER ANALYSIS (Nearest neighbor)

10. ANOVA F ratio = 1 P = 0.929 > 0.05 LDS= 15 COMPARISON BETWEEN SPECIES (All trace elements) Average content

11. ANOVA F ratio = 2 P value = 0.11 >0.05 LDS= 6 COMPARISON BETWEEN LIFE STYLES (All trace elements) EctomycorrhizasSaprobesEpiphytes Average content

12. Cu Zn Rb Ba COMPARISON BETWEEN ELEMENTS (All species) ANOVA F. ratio = 21 P. value = 0.00 <0.05 LDS= 11 Average content ELEMENTS

13. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 ELEMENTS Means and 95.0 Percent LSD Intervals CuRbZn COMPARISON BETWEEN DIFFERENT ELEMENTS FOR THE DIFFERENT HABITATS ANOVA F ratio = 10 P value = 0.00 < 0.05 LDS= 17

14. Ectomycorrhizas Epiphytes Saprobes Rb COMPARISON BETWEEN DIFFERENT ELEMENTS FOR THE DIFFERENT HABITATS Ectomycorrhizas Saprobes Epiphytes Cu Zn Ectomycorrhizas Saprobes Epiphytes ANOVA F ratio = 10 P value = 0.00 < 0.05 LDS= 17

15. PRINCIPAL COMPONENTS ANALYSIS

16. Tests for Normality TestStatisticP-Value Shapiro-Wilk W0.8 0.002 < 0.05 Normality rejected Density curve Summary Statistics for Cu Count 18 Average 26 Standard deviation 23 Coeff. of variation 91 % Minimum 4 Maximum 93 Range 89 Stnd. skewness3 > 2 Stnd. Kurtosis 3 Cu

17. 2.8 Std Dev. from the mean Clitocybe maxima Outliers Identification for Cu

18. Summary Statistics for Zn Count 18 Average 61 Standard deviation 30 Coeff. of variation 50 % Minimum 15 Maximum 122 Range 107 Stnd. skewness 1 < 2 Stnd. Kurtosis -1 Tests for Normality TestStatisticP-Value Shapiro-Wilk W0.9 0.7 > 0.05 Density Curve Normality assumed Zn

19. Outliers Identification for Zn No statistically supported outliers

20. Summary Statistics for Rb Count 18 Average 52 Standard deviation 55 Coeff. of variation 105 % Minimum 12 Maximum 221 Range 209 Stnd. Skewness 4 > 2 Stnd. kurtosis 4 Tests for Normality TestStatisticP-Value Shapiro-Wilk W0.708556 0.00 < 0.05 Density Curve Normality rejected Rb

21. Outliers Identification for Rb 3 Std Dev. from the mean Suillus bellini

22. CONCLUSIONS -Cu, Zn and Rb are the trace elements that showed significant differences among the different life styles - Cu and Zn are more accumulated in saprobes species whereas Rb is more accumulated in ectomycorrhizal species. -Clitocybe maxima has been indentified statistically as an outlier for Cu with a great accumulation for this element. - Suillus bellini has been identified statistically as an outlier for Rb with a great accumulation for this element.

23. PREVIOUS LITERATURE

24. Cu ZnRb Summary Statistics Cu Zn Rb Count 18 18 18 Average 26 61 52 Std. Dev. 23 30 55 Minimum 4 15 12 Maximum 93 122 221 Stnd. skewness3 1 4 Stnd. kurtosis3 -1 4

25. Principal Components Analysis ComponentPercent ofCumulative NumberEigenvalueVariancePercentage 14.6520631.01431.014 22.3485115.65746.670 32.0247213.49860.169 41.5543910.36370.531 51.343338.95679.487 60.8819015.87985.366 70.6424214.28389.649 80.5383753.58993.238 90.3387822.25995.497 100.3159612.10697.603 110.1380920.92198.524 120.1184490.79099.313 130.07621980.50899.821 140.01359090.09199.912 150.01320270.088100.000 The StatAdvisor This procedure performs a principal components analysis. The purpose of the analysis is to obtain a small number of linear combinations of the 15 variables which account for most of the variability in the data. In this case, 5 components have been extracted, since 5 components had eigenvalues greater than or equal to 1.0. Together they account for 79.4867% of the variability in the original data.