Phylogenetic morphometrics (II): algorithms for landmark optimization

Goloboff, Pablo A.; Catalano, Santiago A.

doi:10.1111/j.1096-0031.2010.00318.x

Cited by 59 publications

(66 citation statements)

References 19 publications

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“…Finding the point positions that, for a given tree, minimize the total displacements between all ancestor/descendant points for the given landmark is considerably more difficult than for only three nodes, even for binary trees. Suffice it to say here that Goloboff and Catalano (in press) have developed and incorporated into TNT (Goloboff et al., 2003, 2008) heuristic methods (based on a Sankoff approximation as a first step, and a final iterative refinement), which produce a good approximation to the optimum. The problem is related to the problem of Euclidean Steiner trees.…”

Section: Description Of the Approachmentioning

confidence: 99%

“…Therefore the steps to perform a phylogenetic analysis from aligned specimens will be (i) optimize each landmark, finding optimal ancestral positions, (ii) calculate its score, (iii) divide the score of each landmark by the number of landmarks in the configuration, (iv) sum the scores of each configuration (possibly taking into account scale and/or units of measurement; see Goloboff and Catalano, in press), (v) sum this score with the remainder of the scores of other characters to obtain the final score of the tree.…”

Section: Description Of the Approachmentioning

confidence: 99%

“…To decrease the influence on tree choice of those configurations represented by many landmarks, configurations were down‐weighted in inverse proportion to the number of landmarks. Landmark rescaling and optimization was performed as described by Goloboff and Catalano (in press). Searches were done with TNT, using multiple random trees as starting points for tree bisection–reconnection (TBR).…”

Section: An Examplementioning

confidence: 99%

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Phylogenetic morphometrics (I): the use of landmark data in a phylogenetic framework

2010

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A method for the direct use of aligned landmark data (2D or 3D coordinates of comparable points) in phylogenetic analysis is described. The approach is based on finding, for each of the landmark points, the ancestral positions that minimize the distance between the ancestor ⁄ descendant points along the tree. Doing so amounts to maximizing the degree to which similar positions of the landmarks in different taxa can be accounted for by common ancestry, i.e. parsimony. This method requires no transformation of the aligned data or the results: the data themselves are the x, y, z coordinates of the landmarks, and the output of mapping a character onto a given tree is the x, y, z coordinates for the hypothetical ancestors. In the special case of collinear points, the results are identical to those of optimization of (continuous) additive characters.

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Section: Description Of the Approachmentioning

confidence: 99%

Section: Description Of the Approachmentioning

confidence: 99%

Section: An Examplementioning

confidence: 99%

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Phylogenetic morphometrics (I): the use of landmark data in a phylogenetic framework

2010

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“…Because GM deals with coordinate data as opposed to the interlandmark distances of standard morphometrics, it allows patterns of variation in shape to be easily visualized (Bookstein 1991;Zelditch et al 2004;Slice 2007). Certain kinds of GM data can be used under a parsimony framework (Catalano et al 2010;Goloboff and Catalano 2011;Catalano and Goloboff 2012), and we see this as a promising new avenue of research. However, as with any phylogenetic analysis, taxon construction remains a fundamental issue.…”

Section: Geometric Morphometricsmentioning

confidence: 97%

Design Space and Cultural Transmission: Case Studies from Paleoindian Eastern North America

O’Brien

Boulanger

Buchanan

et al. 2015

J Archaeol Method Theory

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Tool design is a cultural trait-a term long used in anthropology as a unit of transmittable information that encodes particular behavioral characteristics of individuals or groups. After they are transmitted, cultural traits serve as units of replication in that they can be modified as part of a cultural repertoire through processes such as recombination, loss, or partial alteration. Artifacts and other components of the archaeological record serve as proxies for studying the transmission (and modification) of cultural traits, provided there is analytical clarity in defining and measuring whatever it is that is being transmitted. Our interest here is in tool design, and we illustrate how to create analytical units that allow us to map tool-design space and to begin to understand how that space was used at different points in time. We first introduce the concept of fitness landscape and impose a model of cultural learning over it, then turn to four methods that are useful for the analysis of design space: paradigmatic classification, phylogenetic analysis, distance graphs, and geometric morphometrics. Each method builds on the others in logical fashion, which allows creation of testable hypotheses concerning cultural transmission and the evolutionary processes that shape it, including invention (mutation), selection, and drift. For examples, we turn to several case studies J Archaeol Method Theory

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“…Count us as fans of the new landmark optimization methods recently developed by Catalano et al. (2010) and Goloboff and Catalano (2010). These build on the retooling of TNT to handle continuous data (Goloboff et al., 2006, 2008), which we enthusiastically employed to give us phylogenetic hypotheses for species currently beyond the reach of molecular systematics and lacking many codable characters (Clouse et al., 2009; de Bivort et al., 2010).…”

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confidence: 99%