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Phylogeny and Morphometrics G562 Geometric Morphometrics Phylogeny, trees and morphospace Hierarchical patterns in morphometric data WALLABY Node 0 HUMAN LEOPARD Node 1 Node 3 FOSSA Node 2 DOG Node 4 OTTER 0 20 40 60 80 Cottonwood tree (Populus deltoides), New Harmony, Indiana Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Most phenotypic data have a phylogenetic component Evolution - descent with modification (and diversification) Marmota) Consequence: organisms that share a common ancestor are expected to share similarities that are not shared with distantly related organisms. Apodemus) Spermophilus) In such a situation, evolution introduces a hierarchical structure to morphometric data. Thus: whenever three or more OTUs* are involved – regardless of whether they are populations, stratigraphic samples, species, genera, families, or whatever – their phylogenetic links introduce some degree of autocorrelation between the more closely related taxa. * OTU – Operational Taxonomic Unit, shorthand for “group in question” Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Approaches to hierarchy in morphometric data 1. Building trees from morphometric data to show hierarchical similarity (hierarchical clustering) 2. Finding groupings in morphometric data (non-hierarchical clustering) 3. Mapping morphometric data onto hierarchical structure derived from an independent source (e.g., phylogenetic tree) 4. Using phylogenetic statistical methods to account for (or remove) effects of hierarchy in statistical tests Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Controversies about phylogenetic signal in morphometric data Some researchers, usually parsimony-based phylogeneticists, have argued that morphometric data do not have “phylogenetic signal” because they measure “overall similarity” Others have argued that morphometric data do not have phylogenetic signal because they are mostly “adaptive” And yet others argue that morphometric data do not have phylogenetic signal because they are mostly “non-genetic” And a few have argued that morphometric data do not have phylogenetic signal because they are merely morphological, not molecular.... Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Examples of evidence offered against “phylogenetic signal” 1. A UPGMA tree whose topology does not agree with the author’s conception of phylogeny; 2. Correlation of morphometric data with a factor such as diet; 3. A two-dimensional PCA plot whose pattern of scatter does not appear to reflect phylogenetic relationships; 4. A parsimony tree based on gap-coded morphometric data that does not correspond to the author’s conception of phylogeny; 5. A morphological tree that does not correspond to a molecular tree. Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Under what conditions would morphometric data not have a phylogenetic component? 1. If the phenotypes are non-genetic, entirely environmentally plastic responses to local conditions met by an organism during its lifetime 2. If morphometric variation is non-existent 3. If morphometric variation is entirely due to measurement error 4. If species were specially created and have no evolutionary history 5. If phylogenetic history is completely erased by other factors, such as homoplasy due to parallel functional adaptations in different clades Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics The issues at stake: 1. Can phylogenetic relationships be reconstructed from morphometric data? 2. Do morphometric patterns reflect adaptation (e.g., diet) or phylogeny or something else? 3. Are observations based on morphometrics related to evolution or chance or environmental plasticity? Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics The scientific solution: 1. Measure the contribution of potential factors, don’t assume that one factor is or is not important 2. Evaluate with hypothesis-driven tests for association between morphometric data and all relevant factors 3. Synthesize findings to describe the scope of each factor for explaining morphometric variation (i.e., under what conditions is the factor likely to be important and under what conditions is it not) How much of morphometric variation can be explained by phylogenetic history? Under what circumstances phylogenetic history be recovered from morphometric data? With what accuracy can phylogenetic history be recovered from morphometric data? When does phylogenetic history interfere with recovering other relationships? Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics “Factor thinking” in morphometrics Many factors, not just one, contribute to morphometric similarities and differences (variance). Phylogenetic Functional Environmental History Role Interactions The question is often not whether a factor does or does not contribute, but rather how much does it contribute. Morphometric Data MANOVA and regression are two methods for partitioning variance among factors. R2 is one metric for measuring the association of a factor with the total variance. Measurement Sample Unconsidered Error Choice Factors Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Empirical study of factors in morphometric variation Caumul, R and PD Polly. 2005. Phylogenetic and environmental components of morphological variation: skull, mandible, and molar shape in marmots (Marmota, Rodentia). Evolution, 59: 2460-2472. Three phenotypic structures, each with different expectations for functional role, genetic vs. environmental contributions, and complexity, from the same populations and, thus, with the same phylogenetic history. 1. M. marmota 2. M. caudata caudata 100.0 3. M. caudata aurea 4. M. baibacina 83.0 5. M. himalayana robusta 88.0 6. M. sibirica sibirica 0.01 Caumul and Polly, 2005 Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Path analysis (controlled multiple regression) Path coefficients (square to get R2) Proportion unexplained (no need to square) Caumul and Polly, 2005 Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Proportion of morphometric variation explained by phylogeny and other factors Caumul and Polly, 2005 Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Trees recovered from morphometric data “Real” phylogeny Phylo signal=15%: Good recovery Phylo signal=7%: Poor recovery Phylo signal=5%: Good recovery Caumul and Polly, 2005 Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics What do we actually know about phylogenetic signal in morphometrics? 1. Morphometric variation is largely, but not entirely heritable. Typical heritability studies put the value at 40%-70% heritable (percentage of variation that is passed from parent to offspring), high for traits that are measured by geneticists. 2. Morphometric traits evolve quickly. Compared to the gain and loss of structures (i.e., cladistic state changes of the ideal type), the size and shape of structures changes rapidly. (Something that ought to be obvious based on logic alone). 3. Size and shape of homologous structures are often constrained by common ‘homologous’ functions. Once a structure has arisen, it often maintains a similar function throughout phylogenetic history (though there are notable exceptions). Thus the size and shape of that structure have functional constraints imposed on them. And morphometric comparisons are normally limited to structures that are found in all the OTUs being studied. 4. Traits have a window of time when they are likely to be phylogenetically informative. The window depends on the rate of evolution in the trait, the degree of functionality, and the degree of heritability. Within that window, phylogeny is likely to be recovered with a suitable methodology (e.g., Maximum-likelihood); outside that window, phylogeny is unlikely to be recovered. Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Populations versus collections of populations Variation within populations is largely free of phylogenetic effects and so is an appropriate system for measuring relationship of shape to factors such as body size, latitude, etc. Variation between populations (or other OTUs) is normally influenced both by phylogenetic history and adaptive selection. The two may be difficult to disentangle (indeed, the two are themselves related). Among species in a appropriate system to measure disparity, adaptive similarity, etc. Department of Geological Sciences | Indiana University (c) 2012, P. David Polly G562 Geometric Morphometrics Tree building: advantages 1. Trees summarize similarities and differences in shape across the whole shape (i.e., across all dimensions of morphospace) in a single, intuitive diagram 2. For biological data drawn from more than one species, the null assumption is that shape differences should be distributed in a tree-like hierarchy because of phylogeny 3. Morphometric trees can easily be compared
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