Evol Ecol Res 10: 787-796 (2008) Full PDF if your library subscribes.
On comparative analyses involving non-heritable traits: why half a loaf is sometimes worse than none
William E. Kunin
Earth & Biosphere Institute and Institute for Integrative and Comparative Biology, University of Leeds, Leeds, UK
Correspondence: W.E. Kunin, Earth & Biosphere Institute and Institute for Integrative and Comparative Biology, University of Leeds, Leeds LS2 9JT, UK.
Question: Should phylogenetically informed (PI) analyses be used when not all variables in an analysis are heritable?
Methods: I simulated phylogenetic trees, with randomized traits (1) inherited with variation, (2) assigned directly to extant species, or (3) made partially dependent on a heritable variable, testing the frequency of ‘significant’ correlations between variables using conventional and two different PI techniques.
Results: ‘Significance’ was inflated in analyses of heritable variables, and this was corrected by both PI methods. However, where one variable was heritable and the other not, conventional analyses provided unbiased probability estimates. Modelled correlations between heritable and non-heritable traits were more readily detected by conventional analyses, but analyses involving ‘incorrect’ heritable traits sometimes showed spurious correlations.
Conclusions: The results suggest that PI analyses are inappropriate when only one of a pair of variables displays phylogenetic pattern. Where intrinsically non-heritable traits display phylogenetic pattern, conventional analyses are appropriate as an initial approach, but residuals should be tested for phylogenetic patterning.
Keywords: abundance, comparative method, correlated traits, distribution, heritability, independent contrasts, phylogenetic analyses.
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