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b. a. a. b. b. a. c. c. c. Visualizing sample similarities with nonmetric Multidimensional Scaling (nMDS). Colin Bates. Visualizing similarities. clustering. samples. a. c. b. species. b. a. a. b. b. a. Sample similarities. c. c. c. ordination. b. a. a. b. b. a.
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b a a b b a c c c Visualizing sample similarities with nonmetric Multidimensional Scaling (nMDS) Colin Bates
Visualizing similarities clustering samples a c b species b a a b b a Sample similarities c c c ordination
b a a b b a c c c ordination Why ordination? clustering Clustering dendrograms often don’t work well in ‘gradient’ situations. Ordination “maps” relationships between samples a c b
Bay of Fundy seaweeds - Clustering 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: 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
A2 A1 A3 How does nMDS work? Then, nMDS tries to place points in 2 (or 3) dimensional space to represent this ranked order: A1 is closer to A2 than it is to A3
BIOL 404 mite communities A B C wet dry Moisture gradient
BIOL 404 mite communities Abundance of X87
BIOL 404 mite communities - nMDS is a good exploratory tool
BIOL 404 mite communities - nMDS is a good exploratory tool
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 - this is reflected by a high STRESS value If Stress Value = 0.0 : perfect map 0.1 : decent map 0.2 : ok map 0.3 : don’t bother . . . . . . . . . . . . Distance in sim. matrix . . . . . . . . Distance on nMDS
nMDS notes • nMDS is simple in concept • nMDS maps can be rotated, scaled or inverted • any similarity measure can be used for underlying matrix • when stress is high, nMDS and clustering should be used together