Abstract.— Advocates of cladistic parsimony methods have invoked the philosophy of Karl Popper in an attempt to argue for the superiority of those methods over phylogenetic methods based on Ronald Fisher’s statistical principle of likelihood. We argue that the concept of likelihood in general, and its application to problems of phylogenetic inference in particular, are highly compatible with Popper’s philosophy. Examination of Popper’s writings reveals that his concept of corroboration is, in fact, based on likelihood. Moreover, because probabilistic assumptions are necessary to calculate the probabilities that define Popper’s corroboration, likelihood methods of phylogenetic inference--with their explicit probabilistic basis--are easily reconciled with that concept. In contrast, cladistic parsimony methods, at least as described by certain advocates of those methods, are less easily reconciled with Popper’s concept of corroboration. If those methods are interpreted as lacking probabilistic assumptions, then they are incompatible with corroboration. Conversely, if parsimony methods are to be considered compatible with corroboration, then they must be interpreted as carrying implicit probabilistic assumptions. Thus, the non-probabilistic interpretation of cladistic parsimony favored by some advocates of those methods is contradicted by an attempt by the same authors to justify parsimony methods in terms of Popper’s concept of corroboration. In addition to being compatible with Popperian corroboration, the likelihood approach to phylogenetic inference permits researchers to test the assumptions of their analytical methods (models) in a way that is consistent with Popper’s ideas about the provisional nature of background knowledge. [Assumptions, corroboration, likelihood, parsimony, philosophy, phylogeny, Karl Popper, probability]
Abstract.— We defend and expand on our earlier proposal for an inclusive philosophical framework for phylogenetics, based on an interpretation of Popperian corroboration that is de-coupled from the popular falsificationist interpretation of Popperian philosophy. Any phylogenetic inference method can provide Popperian "evidence" or "test statements" based on the method’s goodness-of–fit values for different tree hypotheses. Corroboration, or the severity of that test, requires that the evidence is improbable without the hypothesis, given only background knowledge that includes elements of chance. This framework contrasts with attempted Popperian justifications for cladistic parsimony in which evidence is the data, background knowledge is restricted to descent with modification, and "corroboration", as a by-product of non-falsification, is to be measured by cladistic parsimony. Recognition that cladistic "corroboration" reflects only goodness-of-fit, not corroboration/severity, makes it clear that standard cladistic prohibitions, such as restrictions on the evolutionary models to be included in "background knowledge", have no philosophical status. The capacity to assess Popperian corroboration neither justifies nor excludes any phylogenetic method, but it does provide a framework in phylogenetics for learning from errors – cases where apparent good evidence is probable even without the hypothesis. We explore these issues in the context of corroboration assessments applied to likelihood methods and to a new form of parsimony. These different forms of evidence and corroboration assessment point also to a new way to combine evidence, not at the level of overall fit, but at the level of overall corroboration/severity. We conclude that progress in an inclusive phylogenetics will be well-served by the rejection of cladistic philosophy. [Popper; PTP; corroboration; severe test; philosophy of science; likelihood; parsimony]
Abstract.— A number of methods have been proposed to infer the states at the ancestral nodes on a phylogeny. These methods assume a specific tree and set of branch lengths when estimating the ancestral character state. Inferences of the ancestral states, then, are conditioned on the tree and branch lengths being true. We develop a hierarchical Bayes method for inferring the ancestral states on a tree. The method integrates over uncertainty in the tree, branch lengths, and substitution model parameters using Markov chain Monte Carlo. We compare the hierarchical Bayes inferences of ancestral states to inferences of ancestral states made under the assumption that a specific tree is correct. We find that the methods are correlated, but that accommodating uncertainty in parameters of the phylogenetic model can make inferences of ancestral states even more uncertain than they would be in an empirical Bayes analysis. [Ancestral state reconstruction; Bayesian estimation; empirical Bayes; hierarchical Bayes]
Abstract.— A shift from a traditional biogeographical paradigm in cladistic biogeography to a chronobiogeographical paradigm is proposed. The chronobiogeographical paradigm aims to utilize temporal data in conjunction with spatial data in the detection of discrete historical events, such as vicariance and vicariant speciation, on cladograms. The concepts of primary and secondary congruency are introduced in relation to the distinction between repeated area relationships (primary congruency) and common extrinsic causality (secondary congruency). Simple hypothetical examples demonstrate that area cladograms cannot be safely interpreted purely as representing the sequence of area fragmentation: rather they reflect recency of biotic interaction. Temporal data are shown to have a direct and potentially profound influence on the results of traditional cladistic biogeographical analyses, indicating the necessity of developing a chronobiogeographical approach. The implementation of the paradigm is considered, first from a theoretical viewpoint, and then in the context of the type of empirical data that are usually available. An as yet undevised "time/space algorithm" is deemed necessary for the latter. Guidelines are then presented for the development of such an algorithm. Finally, it is concluded that the most rigorous and philosophically justified approach to the detection of phylogenetic causal events can only be found when temporal and spatial data are considered simultaneously. Consequently, the chronobiogeographical paradigm is seen as a logical elaboration of, and not a replacement for, the biogeographical paradigm. [biogeography, chronobiogeography, cladistic biogeography, phylogenetics, vicariance, Component Analysis, area cladograms]
Abstract.— Sir Karl Popper is well known for explicating science
in falsificationist terms, and for which his degree of corroboration formalism,
C(h,e,b), has become little more than a symbol. For example, de Queiroz
and Poe (2001) argue that C(h,e,b) reduces to a single relative (conditional)
probability, p(e,hb), the likelihood of evidence e, given both hypothesis
h and background knowledge b, and in reaching that conclusion,
without stating or expressing it, they render Popper a verificationist. The
contradiction they impose is easily explained — de Queiroz and Poe fail
to take account of the fact that Popper derived C(h,e,b) from absolute
(logical) probability and severity of test, S(e,h,b), where critical
evidence, p(e,b), is fundamental. Thus, de Queiroz and Poe’s
conjecture that p(e,hb) = C(h,e,b) is refuted.
Falsificationism, not verificationism, remains a fair description of the parsimony method of inference employed in phylogenetic systematics, not withstanding de Queiroz and Poe’s mistaken understanding that "statistical" probability justifies that method. While de Queiroz and Poe assert that maximum likelihood has the power "to explain data", they do not successfully demonstrate how causal explanation is achieved, or what it is that is being explained. This is not surprising, bearing in mind that what is assumed about character evolution in the accompanying likelihood model M cannot then be explained by the results of a maximum likelihood analysis. [absolute (logical) probability; critical evidence; corroboration; explanation; falsificationism; maximum likelihood; relative (conditional) probability; severity of test; verificationism]
Abstract.— A total of 7806 nucleotide positions derived from one mitochondrial and eight nuclear DNA segments were used to provide a robust phylogeny for members of the order Artiodactyla. Twenty-four artiodactyl and two cetacean species were included and the horse, order Perissodactyla, was used as the outgroup. Limited rate heterogeneity was observed among the nuclear genes. The partition homogeneity tests indicated no conflicting signal among the nuclear gene fragments and the sequence data were analyzed together and as separate loci. Analyses based on the individual nuclear DNA fragments, and 34 unique indels, all produced phylogenies largely congruent with the topology from the combined data set. In sharp contrast to the nuclear DNA data, the mtDNA cytochrome b sequence data showed high levels of homoplasy, failed to produce a robust phylogeny, and were remarkably sensitive to taxon sampling. The nuclear DNA data clearly support the paraphyletic nature of the Artiodactyla. Additionally, the family Suidae is diphyletic and the non-ruminating pigs and peccaries (Suiformes) were the most basal cetartiodactyl group. The morphologically derived Ruminantia was always monophyletic and within this group all taxa with paired bony structures on their skulls clustered together. The nuclear DNA data suggested that the Antilocaprinae comprise a unique evolutionary lineage, the Cervidae and Bovidae are sister taxa while the Giraffidae is more primitive. [Artiodactyla; Cetacea; Ruminantia; Nuclear DNA; cytochrome b; indels]
Abstract.— Tests for incongruence as an indicator of among data partition conflict have played an important role in conditional data combination. When such tests reveal significant incongruence, this has been interpreted as rationale for not combining data in a single phylogenetic analysis. In this study of lorisiform phylogeny, we employ the incongruence length difference (ILD) test to assess conflict among three independent data sets. A large morphological data set and two unlinked molecular data sets, the mitochondrial cytochrome b gene and the nuclear interphotoreceptor retinoid binding protein (exon 1), are analyzed with various optimality criteria and weighting mechanisms in order to determine the phylogenetic relationships among slow lorises (Primates, Loridae). When analyzed separately, the morphological data show impressive statistical support for a monophyletic Loridae. Both molecular data sets resolve the Loridae as paraphyletic, though with different branching order depending on optimality criterion and/or character weighting employed. When the three data partitions are analyzed in various combinations, an inverse relationship between congruence and phylogenetic accuracy is observed. Nearly all combined analyses that recover monophyly indicate strong data partition incongruence (p = 0.00005, in the most extreme case) whereas all analyses that recover paraphyly indicate lack of significant incongruence. Numerous lines of evidence verify that monophyly is the accurate phylogenetic result. Therefore, this study contributes to a growing body of information that affirms that measures of incongruence should not be employed as indicators of data set combinability. [Partition homogeneity test; incongruence length difference; lorises; galagos; conditional data combination; molecules and morphology]
Abstract.— The Conditional Probability of Reconstruction is a measure of the robustness of cladogram internodes, and unlike Bremer support and bootstrapping values, directly gauges probability. The new method compares the three putative branch lengths (the optimal and two alternatives) obtained through branch recalculation after nearest neighbor interchange. With rooted trees, this involves switching the three free subclades attached at the distal and basal ends of an internal branch. Probabilistic reconstruction of a branch for small data sets (e.g., morphological) is defined as no contrary support for the two alternative branches, and, when sufficient data is available (e.g., molecular studies), as a selected confidence limit met in chi-squared analysis. The exact probability that the internal branch is reconstructed is the same as that obtained by the chi-squared analysis, or otherwise it is a simple calculation of the length of the optimal branch divided by the sum of the lengths of all three putative branches. This new measure of robustness allows calculation of summary probabilities of subclade and tree reconstruction. The measure is conditional on a particular data set and optimization method. Examples are provided by a morphological data set (the bryophyte Didymodon) and a molecular data set (primates). [branch length; chi-squared; Didymodon; primates; probabilistic reconstruction; support]