Global Ecology and Biogeography · 2011 · 481 citations · 30 references
Life SciencesBiologyEcologyCommunity EcologyEvolutionary EcologySpeciationBiodiversity PatternsDiversity MetricsFunctional DiversitySpecies DiversitySpecies RichnessSpecies Richness PatternsBeta DiversityBeta Diversity AnalysisBeta Diversity PatternsEcological GradientsSpecies Diversity GradientsSpecies Diversity PatternsSpecies ReplacementSpecies Richness Gradients
ABSTRACT Aim To determine the relative contribution of species replacement and species richness differences to the emergence of beta‐diversity patterns. Innovation A novel method that disentangles all compositional differences (β cc , overall beta diversity) in its two components, species replacement (β ‐3 ) and species richness differences (β rich ) is proposed. The performance of the method was studied with ternary plots, which allow visualization of the influence of the relative proportions of shared and unique species of two sites over each metric. The method was also tested in different hypothetical gradients and with real datasets. The novel method was compared with a previous proposal based on the partitioning of overall compositional differences (β sor ) in replacement (β sim ) and nestedness (β nes ). The linear response of β cc contrasts with the curvilinear response of β sor to linear gradients of dissimilarity. When two sites did not share any species, β sim was always 1 and β ‐3 only reached 1 when the number of exclusive species of both sites was equal. β ‐3 remained constant along gradients of richness differences with constant replacement, while β sim decreased. β rich had a linear response to a linear gradient of richness differences with constant species replacement, whereas β nes exhibited a hump‐shaped response. Moreover, β sim > β nes when clearly almost all species of one site were lost, whereas β ‐3 < β rich in the same circumstances. Main conclusions The behaviour of the partition of β cc into β ‐3 and β rich is consistent with the variation of replacement and richness differences. The partitioning of β sor into β sim and β nes overestimates the replacement component and underestimates richness differences. The novel methodology allows the discrimination of different causes of beta‐diversity patterns along latitudinal, biogeographic or ecological gradients, by estimating correctly the relative contributions of replacement and richness differences.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
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R. H. Whittaker · Ecological Monographs · 1960 · 3.9K citations
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