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Multivariate analysis of community structure data 2001 Oct 2001 April 2001 Oct 2001 April 2001 April 2001 April 2001 April 2001 July 2001 July 2001 July 2000 Aug 2001 July 2001 Oct 2001 Oct 2001 Oct 2001 Oct 2000 May 2000 May 2000 Aug 2000 Aug 2000 Aug 2001 April 2001 Oct 2000 Aug 2000 Aug 2001 July 2001 July 2000 Aug 2001 July 2001 July 2001 April 2001 April 2000 Nov 2000 Nov 2000 Nov 2000 Nov 2001 Oct 2000 Aug 2000 Nov 2000 Nov 2000 Nov 2000 Nov 2000 May 2000 May 2000 May 2000 May 2000 May 2000 May 20 Colin Bates UBC 40 60 80 100 Bamfield Marine Sciences Centre Similarity Goals 1) To understand the ideas behind multivariate community structure analysis. 2) To understand how to perform these analyses in PRIMER. 3) To be prepared to analyse and interpret your class data later today. What are multivariate statistics? Statistics that allow us to look at how multiple variables change together What are multivariate statistics? Statistics that allow us to look at how multiple variables change together: EG: How do 50 species in a community react to an environmental perturbation? What are multivariate statistics? Statistics that allow us to look at how multiple variables change together: EG: How do 50 species in a community react to an environmental perturbation? 50 ANOVAs? What are multivariate statistics? Statistics that allow us to look at how multiple variables change together: EG: How do 50 species in a community react to an environmental perturbation? 50 ANOVAs? No… Multivariate stats allow us to “condense” information for simplicity When might I use this type of analysis? For a multi-species community, you may wish to: - pull order from complex systems - visualize these patterns - comparisons over time and space - test hypotheses The vehicle: Example: Seaweed Communities at Cape Beale - Is flora different at two close sites, each exposed to different wave intensity? Data collection: 2. Data Analysis Step 1: Entering your data into PRIMER How to analyze this type of data? 1. Diversity indices How to analyze this type of data? 1. Diversity indices Yet, most diversity indices do not consider species identity… How to analyze this type of data? 1. Diversity indices Yet, most diversity indices do not consider species identity… Multivariate community structure analyses Analysis flow samples species aa a b bb c sample similarities aa b a bb c cc are sites different? How? c c ordination Analysis flow samples species aa a b bb c sample similarities c c ordination Calculate Bray – Curtis Similarity gives a triangular similarity matrix within within between Analysis flow samples species aa a b bb c sample similarities aa b a bb c cc are sites different? How? c c ordination Visualizing similarities Ordination “maps” similarity relationships between samples a a b a b b c c c ordination nMDS ordination example nMDS ordination example Distance between points reflects relative similarity! Nonmetric multidimensional scaling (nMDS) “the future of ordination is in nonmetric multidimensional scaling” – McCune & Grace, 2002 Nonmetric: no axes Multidimensional: represents relationships between multiple variables in two or three dimensions Scaling: the ratio between reality and representation How does nMDS work? nMDS uses the RANK ORDER of similarity relationships between samples: Sample Sample rank A2 % similarity 99% A1 A1 A3 96% 2 A2 A3 95% 3 1 A1 is closer to A2 than it is to A3 How does nMDS work? Then, nMDS tries to place points in 2 (or 3) dimensional space to represent this ranked order: A3 A1 is closer to A2 than it is to A3 A1 A2 How does nMDS work? Then, nMDS tries to place points in 2 (or 3) dimensional space to represent this ranked order: A1 A2 A3 A1 is closer to A2 than it is to A3 How accurate is the nMDS map? - Sometimes the nMDS can’t represent all relationship accurately - this is reflected by a high STRESS value How accurate is the nMDS map? - Sometimes the nMDS can’t represent all relationship accurately similarity in sim. matrix - this is reflected by a high STRESS value . .. . .. . ... . . . . .. . .. . distance on nMDS If Stress Value = 0.0 : perfect map 0.1 : decent map 0.2 : ok map 0.3 : don’t bother Main points about ordination! - Ordination is a way to visualize how similar your samples are - nMDS tries to represent visually the rank order within the underlying similarity matrix - all that matters is the relative distance between points. - stress value allows you to estimate ‘quality’ of the nMDS’ aa a b bb c sample similarities c c ordination Obviously distinct groups Less obvious! Are they really different? Analysis flow samples species aa a b bb c sample similarities aa b a bb c cc are sites different? c c ordination Analysis flow samples species aa a b bb c sample similarities aa b a bb c cc are sites different? How? c c ordination Are groups different? Analysis of Similarities – a statistical approach exposed sheltered Are groups different? Analysis of Similarities – a statistical approach Ho = sites the same Ha = sites are different exposed sheltered If Ho (sites the same) = true Similarity within = Similarity between If Ha (sites different) = true Similarity within > Similarity between Are groups different? Analysis of Similarities – a statistical approach (rbetween - rwithin ) R= standardizing factor Are groups different? Analysis of Similarities – a statistical approach (rbetween - rwithin ) R= ~1 If Ho (sites the same) = true Similarity within = Similarity between (rbetween - rwithin ) R= ~1 ~0 If Ha (sites different) = true Similarity within > Similarity between (rbetween - rwithin ) R= ~1 ~1 To simulate null distribution To simulate null distribution Similarity within = Similarity between To simulate null distribution Similarity within = Similarity between Calculate R To simulate null distribution Similarity within = Similarity between Calculate R Phyc 2003 Practice data set 243 232 Frequency 189 109 .477 88 58 35 19 10 6 -0.20 9 1 -0.15 -0.10 -0.05 0.00 0.05 0.10 R 0.15 0.20 0.25 0.30 0.35 0.40 Phyc 2003 Practice data set 243 232 1 P= = 0.001 999 Frequency 189 109 .477 88 58 35 19 10 6 -0.20 9 1 -0.15 -0.10 -0.05 0.00 0.05 0.10 R 0.15 0.20 0.25 0.30 0.35 0.40 Analysis flow samples species aa a b bb c sample similarities aa b a bb c cc are sites different? How? c c ordination Sites are different – why? • We will use the SIMPER routine: - Similarity Percentages Basically indicates which species are responsible for the patterns that we see. Data analysis summary samples species aa a b bb c sample similarities are sites different? aa b a bb c cc ANOSIM How? SIMPER c nMDS c