Community Ecology analysis using R: basic intro

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! Detrended Correspondence Analysis (DCA)! More robust than PCA! Solves problems associated to long gradients>DCAplot(DCA, display=“sites”)>plot(DCA, display=“species”)
! Mantel test è check correlation between two matrices! Using pearson or spearman correlation coefficients! Significance test (1000 permutations)! Let’s check the correlation between Bray-Curtis distancesobtained with raw and subsampled datasets>plot(OTU_ss.bray, OTU_all.bray)>abline(0,1)>mantel(OTU_ss.bray, OTU_all.bray)
Page 1 and 2: Community Ecology analysisusing R:
Page 3: ! Where to get R:! http://www.r-pro
Page 6 and 7: ! To see the variables that were de
Page 8 and 9: ! Working with tables:> getwd() #ge
Page 10 and 11: ! Analysis using Vegan (R functions
Page 12 and 13: owSums(OTU_table) # Find the sample
Page 14 and 15: ! Let’s get some richness estimat
Page 16 and 17: ! Accumulation curves (using Ugland
Page 18 and 19: ! We can also fit several rank-abun
Page 20 and 21: * Shannon H index (considers richne
Page 22 and 23: ! We use a subsampled OTU table in
Page 24 and 25: plot(OTU_ss_n.bray.nmds)>stressplot
Page 28 and 29: ! A linear regression model can be
Page 30 and 31: ! Other packages:! Labdsv (http://e

Community Ecology analysis using R: basic intro

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