Paralogy and the Centre of Origin Concept

Ancestral area methodology, applied to finding the centre of origin, conflicts with most cladistic biogeographic methods since it uses, not reduces, paralogy. A new term, area cladistics, is herein proposed as an efficient paralogy-free (or reduced) method under the three-item philosophy that currently exists with other methods under the broad term cladistic biogeography.     

Extrapolating Cladistic Biogeography: A Brief Comment on van Veller et al. (1999, 2000, 2001)

Cladistic biogeography aims to find congruence (common patterns among area relationships) among taxon-area cladograms. Not all areagrams are congruent, and ambiguity needs to be either reduced or resolved in order for a common biogeographic pattern to emerge. Recent papers by van Veller et al. (1999, Cladistics 15, 393–406; van Veller et al. 2000, Cladistics 16, 319–345; van Veller et al. 2001, Cladistics ) suggest that ambiguity is the result of isolation mechanisms other than vicariance. That is, identifying such mechanisms in a monophyletic group or areagram and by combining two or more areagrams using assumptions 0, 1, or 2 may result in common patterns. Under such a hypothesis van Veller et al. (1999, 2000, 2001) suggest that ambiguity is congruent and removal of it decreases explanatory power. Assumption 0 differs in all other approaches as it resolves ambiguity using taxon and not area relationships , contrary to the aims of cladistic biogeography.     

Critique of parsimony analysis of endemicity as a method of historical biogeography

Aim Assess the value of parsimony analysis of endemism as either an a priori (cladistic) and an a posteriori (phylogenetic) method of historical biogeography. Location World‐wide. Methods Parsimony analysis of endemicity (PAE) and Brooks parsimony analysis (BPA). Results Parsimony analysis of endemicity is capable of finding correct and unambiguous area relationships only under scenarios of vicariance in combination with non‐response to vicariance or extinction. An empirical comparison between PAE and BPA, using the poeciliid fish genera Heterandria and Xiphophorus, demonstrates that PAE fails to document much of the historical complexity in this relatively simple system. Main conclusions The a priori assumptions of PAE are far more restrictive than those made by other a priori methods, limiting its utility as a method of cladistic biogeography. The inability of PAE to detect perfect vicariance or biogeographical histories involving dispersal, renders it unsuitable as a method of phylogenetic biogeography.     

Cladistic and phylogenetic biogeography: the art and the science of discovery

All methods used in historical biogeographical analysis aim to obtain resolved area cladograms that represent historical relationships among areas in which monophyletic groups of taxa are distributed. When neither widespread nor sympatric taxa are present in the distribution of a monophyletic group, all methods obtain the same resolved area cladogram that conforms to a simple vicariance scenario. In most cases, however, the distribution of monophyletic groups of taxa is not that simple. A priori and a posteriori methods of historical biogeography differ in the way in which they deal with widespread and sympatric taxa. A posteriori methods are empirically superior to a priori methods, as they provide a more parsimonious accounting of the input data, do not eliminate or modify input data, and do not suffer from internal inconsistencies in implementation. When factual errors are corrected, the exemplar presented by M.C. Ebach & C.J. Humphries (Journal of Biogeography, 2002, 29 , 427) purporting to show inconsistencies in implementation by a posteriori methods actually corroborates the opposite. The rationale for preferring a priori methods thus corresponds to ontological rather than to epistemological considerations. We herein identify two different research programmes, cladistic biogeography (associated with a priori methods) and phylogenetic biogeography (associated with a posteriori methods). The aim of cladistic biogeography is to fit all elements of all taxon–area cladograms to a single set of area relationships, maintaining historical singularity of areas. The aim of phylogenetic biogeography is to document, most parsimoniously, the geographical context of speciation events. The recent contribution by M.C. Ebach & C.J. Humphries (Journal of Biogeography, 2002, 29 , 427) makes it clear that cladistic biogeography using a priori methods is an inductivist/verificationist research programme, whereas phylogenetic biogeography is hypothetico‐deductivist/falsificationist. Cladistic biogeography can become hypothetic‐deductive by using a posteriori methods of analysis.     

When phylogenetics met biogeography: Willi Hennig,Lars Brundin and the roots of phylogenetic and cladistic biogeography

Willi Hennig's (Beitr. Ent. 1960, 10, 15) Die Dipteren-Fauna von Neuseeland als systematisches und tiergeographisches Problem applied a phylogenetic approach to examine the distributional patterns exhibited by the Diptera of New Zealand. Hennig showed how phylogenetic trees may be used to infer dispersal, based on the progression and deviation rules, and also discussed the existence of vicariance patterns. The most important author who applied Hennig's phylogenetic biogeography was Lars Brundin, when analysing the phylogenetic relationships of two taxa of Chironomidae (Diptera) and using them to examine the biogeographic relationships of Australia, New Zealand, South America and South Africa. The relevance of Brundin's contribution was noted by several authors, as it began the cladistic or vicariance approach to biogeography, that implies the discovery of vicariance events shared by different monophyletic groups. Both phylogenetic and cladistic biogeography have a place in contemporary biogeography, the former for analysing taxon biogeography and the latter when addressing Earth or biota biogeography. The recent use of the term “phylogenetic biogeography” to refer to a posteriori methods of cladistic biogeography is erroneous and should be avoided.     

Primary classification and phylogeny of the Polemoniaceae, with comments on molecular cladistics

The system of classification of the Polemoniaceae currently in use was published by Grant in 1959. Much new evidence concerning relationships in the family has been obtained by numerous workers since 1959, and the old system is in need of revision. A revised system down to the genus level, based on conventional and unconventional characters, including molecular evidence, is presented here. Nineteen genera are grouped into eight tribes and two subfamilies. Three new tribes are described: Acanthogilieae, Loeselieae, and Leptodactyloneae. Several genera are transferred to new groups. The phylogeny of the family is discussed in the light of both the older and new evidence. The approach used in constructing both the 1959 and new systems is that of evolutionary systematics. Two recent (1996, 1997) family-wide surveys of cpDNA and rDNA use cladistic methods of analysis to arrive at sets of major groups. Some of this molecular evidence has been adopted for the present revised system. However, much incongruence still exists between the new sets of clades, on the one hand, and the present revised system or the still-viable parts of the 1959 system on the other hand. The incongruences call for an examination and comparison of the contrasting methods of evolutionary systematics and molecular cladistics. A fundamental flaw in the 1996 and 1997 treatments is the attempt to classify plants on the basis of single-gene gene trees.     

Assumption 2: opaque to intuition?

Aim The aim of this paper was to revise the historical biogeographical method for resolving complicated distribution patterns through a technique that has come to be called assumption 2. Assumption 2 was used to resolve multiple areas on a single terminal branch (masts) as well as paralogous and missing areas in two or more areagrams. Recent examples, however, have shown that assumption 2 may be using rather than resolving paralogy. The paper attempts to resolve this problem by formulating a separate procedure to avoid using paralogous (redundant) area data in area cladistic analyses. Method The revision results in a new derivative method, the transparent method, to replace assumptions 1 and 2. It separates the procedures for resolving paralogy and for solving distribution patterns that occur in more than one area (masts). Results Several hypothetical examples show how the transparent method reduces paralogy and masts. The results show that paralogy can be reduced if the paralogy subtree method is applied after uncovering all possible relationships as single components on the terminals of areagrams. Conclusion The transparent method is a significant step forward in cladistic biogeography as it utilizes area relationships rather than generating general areagrams based on paralogous data.     

Panbiogeography: Its origin,metamorphosis and decline

From the viewpoint of 2007, one can trace the history of an interesting and contentious trend in biogeography and evolution that began with Croizat’s concept of panbiogeography in 1958. After a quiescent period of about 16 years, some young biologists in New York and in New Zealand read Croizat’s books and became enthusiastic supporters of his ideas. In New York, in the early 1970s, panbiogeography was combined with a part of Hennig’s phylogenetic method to create vicariance biogeography. In 1986, the name of the latter was changed to cladistic biogeography. In the meantime, Croizat’s followers in New Zealand sought to maintain panbiogeography in its original form without reference to phylogeny. This idea reached its peak of popularity in 1989–1990 and then began to fade. In comparison, cladistic biogeography became much more widespread, especially when its followers began publishing laudatory books and papers. Its decline became noticeable after the turn of the century as the dispersal counterrevolution began to have its effect. It served a useful purpose by engaging the interest of young biologists who otherwise may not have become aware of biogeography.     

Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray experiments

MOTIVATION: An important goal in analyzing microarray data is to determine which genes are differentially expressed across two kinds of tissue samples or samples obtained under two experimental conditions. Various parametric tests, such as the two-sample t-test, have been used, but their possibly too strong parametric assumptions or large sample justifications may not hold in practice. As alternatives, a class of three nonparametric statistical methods, including the empirical Bayes method of Efron et al. (2001), the significance analysis of microarray (SAM) method of Tusher et al. (2001) and the mixture model method (MMM) of Pan et al. (2001), have been proposed. All the three methods depend on constructing a test statistic and a so-called null statistic such that the null statistic's distribution can be used to approximate the null distribution of the test statistic. However, relatively little effort has been directed toward assessment of the performance or the underlying assumptions of the methods in constructing such test and null statistics. RESULTS: We point out a problem of a current method to construct the test and null statistics, which may lead to largely inflated Type I errors (i.e. false positives). We also propose two modifications that overcome the problem. In the context of MMM, the improved performance of the modified methods is demonstrated using simulated data. In addition, our numerical results also provide evidence to support the utility and effectiveness of MMM.     

Biogeography of Southeast Asia and the West Pacific

The biogeography of Southeast Asia and the West Pacific is complicated by the fact that these are regions on the border of two palaeocontinents that have been separated for a considerable period of time. Thus, apart from any patterns of vicariance, two general patterns relating to dispersal can be expected: a pattern of Southeast Asian elements, perhaps of Laurasian origin, expanding into Australian areas, and a reverse pattern for Australian elements, perhaps of Gondwanan origin. On top of this, both Australian and Southeast Asian elements occur in the Pacific. They dispersed there as the Pacific plate moved westward, bringing the different islands within reach of Southeast Asia and Australia. In order to reconstruct the biotic history of these areas, two large data sets consisting of both plants and animals were generated, one for each pattern, which were analysed using cladistic methods. The general patterns that emerged were weakly supported and do not allow general conclusions.     

Philosophy and phylogenetic inference: a comparison of likelihood and parsimony methods in the context of Karl Popper's writings on corroboration

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 for calculating the probabilities that define Popper's corroboration, likelihood methods of phylogenetic inference--with their explicit probabilistic basis--are easily reconciled with his 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.     

Spatial analysis of vicariance: a method for using direct geographical information in historical biogeography

Based on Hovenkamp’s ideas on historical biogeography, we present a method for analysis of taxon history, spatial analysis of vicariance, which uses observed distributions as data, thus requiring neither predefined areas nor assumptions of hierarchical relations between areas. The method is based on identifying sister nodes with disjunct (allopatric/vicariant) distributions. To do this across the tree, internal nodes are assigned distributions (as the sum of the distributions of the descendant nodes). When distributions are less than ideal, ignoring the distribution of the problematic node(s) when assigning a distribution to their ancestors may allow us to consider additional sister nodes (i.e. those resulting from splits basal to the problematic node) as having disjunct distributions. The optimality criterion seeks to find the best (possibly weighted) compromise between the maximum possible number of disjunct sister nodes and the minimum number of eliminated distributions. The method can also take overlap into account. The methodology presented is implemented in VIP, a computer program available at http://www.zmuc.dk/public/phylogeny/vip . © The Willi Hennig Society 2011.     

Recent developments in the analysis of comparative data

Comparative methods can be used to test ideas about adaptation by identifying cases of either parallel or convergent evolutionary change across taxa. Phylogenetic relationships must be known or inferred if comparative methods are to separate the cross-taxonomic covariation among traits associated with evolutionary change from that attributable to common ancestry. Only the former can be used to test ideas linking convergent or parallel evolutionary change to some aspect of the environment. The comparative methods that are currently available differ in how they manage the effects brought about by phylogenetic relationships. One method is applicable only to discrete data, and uses cladistic techniques to identify evolutionary events that depart from phylogenetic trends. Techniques for continuous variables attempt to control for phylogenetic effects in a variety of ways. One method examines the taxonomic distribution of variance to identify the taxa within which character variation is small. The method assumes that taxa with small amounts of variation are those in which little evolutionary change has occurred, and thus variation is unlikely to be independent of ancestral trends. Analyses are then concentrated among taxa that show more variation, on the assumption that greater evolutionary change in the character has taken place. Several methods estimate directly the extent to which ancestry can predict the observed variation of a character, and subtract the ancestral effect to reveal variation of phylogeny. Yet another can remove phylogenetic effects if the true phylogeny is known. One class of comparative methods controls for phylogenetic effects by searching for comparative trends within rather than across taxa. With current knowledge of phylogenies, there is a trade-off in the choice of a comparative method: those that control phylogenetic effects with greater certainty are either less applicable to real data, or they make restrictive or untestable assumptions. Those that rely on statistical patterns to infer phylogenetic effects may not control phylogeny as efficiently but are more readily applied to existing data sets.     

LisBeth: New cladistics for phylogenetics and biogeography

Within phylogenetics, two methods are known to implement cladistics: parsimony or maximum parsimony (MP) and three-item analysis (3ia). Despite the lack of suitable software, 3ia is occasionally used in systematic, and more regularly, in historical biogeography. Here, we present LisBeth, the first and only phylogenetic/biogeographic program freely available that uses the 3ia approach and offer some insights into its theoretical propositions. LisBeth does not rely on the conventional taxon/character matrix. Instead, characters are represented as rooted trees. LisBeth performs 3ia analyses based on maximum congruence of three-item statements and calculates the intersection tree (which differs from usual consensus). In biogeography, it applies the transparent method to handle widespread taxa and implements paralogy-free subtree analysis to remove redundant distributions. For the sake of interoperability, LisBeth may import/export characters from/to matrix in NEXUS format, allowing comparison with other cladistic programs. LisBeth also imports phylogenetic characters from Xper² knowledge bases.     

New Guinea: A Correlation between Accreting Areas and Dispersing Sapindaceae

A correlation between accreting (hybridizing) areas and dispersing taxa (several genera of Southeast Asian/Australian Sapindaceae) is theoretically impossible in cladistic biogeography. However, in particular circumstances (primitive absence followed by colonization and speciation) cladistic methods can reconstruct (part of) the historical sequence of accretion. In this example, the phases in the accretion history of more than 30 terranes of the northern half of New Guinea correspond reasonably well with the generalized area cladogram of the Sapindaceae.     

A data based parsimony method of cophylogenetic analysis

Phylogenies of closely interacting groups, such as hosts and parasites, are seldom completely congruent. Incongruence can arise from biologically meaningful differences in the histories of the two groups, or can be generated by artifactual differences that are merely the result of incorrect phylogenies with weakly supported nodes. We present a method that distinguishes between these sources of incongruence and identifies lineages that are responsible for significant differences between phylogenies. We use the logic of conditional combination in that we first test for statistically significant incongruence using the partition homogeneity test. Then we remove all possible combinations of taxa until a non-significant result of this test is achieved. Finally, we construct a 'combined evidence' phylogeny and then reposition the incongruent taxa. This method produces trees for final comparison using reconciliation methods, but it includes only as many incongruence events as can be statistically justified from the data sets. We apply this method to a host–parasite (gopher–louse) data set and identify many fewer incongruence events than do topology based analyses alone. Our method is broadly applicable to comparisons of phylogenies of interacting taxa, such as hosts and parasites, or mutualists. The method should also be useful for other problems involving comparisons of phylogenies, such as multiple gene trees or cladistic biogeography.     

A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments

MOTIVATION: A common task in analyzing microarray data is to determine which genes are differentially expressed across two kinds of tissue samples or samples obtained under two experimental conditions. Recently several statistical methods have been proposed to accomplish this goal when there are replicated samples under each condition. However, it may not be clear how these methods compare with each other. Our main goal here is to compare three methods, the t-test, a regression modeling approach (Thomas et al., Genome Res., 11, 1227-1236, 2001) and a mixture model approach (Pan et al., http://www.biostat.umn.edu/cgi-bin/rrs?print+2001,2001a,b) with particular attention to their different modeling assumptions. RESULTS: It is pointed out that all the three methods are based on using the two-sample t-statistic or its minor variation, but they differ in how to associate a statistical significance level to the corresponding statistic, leading to possibly large difference in the resulting significance levels and the numbers of genes detected. In particular, we give an explicit formula for the test statistic used in the regression approach. Using the leukemia data of Golub et al. (Science, 285, 531-537, 1999), we illustrate these points. We also briefly compare the results with those of several other methods, including the empirical Bayesian method of Efron et al. (J. Am. Stat. Assoc., to appear, 2001) and the Significance Analysis of Microarray (SAM) method of Tusher et al. (PROC: Natl Acad. Sci. USA, 98, 5116-5121, 2001).     

An evaluation of fitting methods for the sum of two hyperbolas: application to uptake studies

Analysis of data in terms of the sum of two rectangular hyperbolas is frequently required in solute uptake studies. Four methods for such analysis have been compared. Three are based on least-squares fitting whereas the fourth (partition method I) is an extension of a single hyperbola fitting procedure based on non-parametric statistics. The four methods were tested using data sets which had been generated with two primary types of random, normal error in the dependent variable: one of constant error variance and the other of constant coefficient of variation. The methods were tested on further data sets which were obtained by incorporating single 10% bias errors at different positions in the original two sets. Partition method I consistently gave good estimates for the four parameters defining the double hyperbola and was highly insensitive to the bias errors. The least-squares procedures performed well under conditions satisfying the least-squares assumptions regarding error distribution, but frequently gave poor estimates when these assumptions did not hold. Our conclusion is that in view of the errors inherent in many solute uptake experiments it would usually be preferable to analyse data by a method such as partition method I rather than to rely on a least-squares procedure.     

A priori assumptions about characters as a cause of incongruence between molecular and morphological hypotheses of primate interrelationships

When molecules and morphology produce incongruent hypotheses of primate interrelationships, the data are typically viewed as incompatible, and molecular hypotheses are often considered to be better indicators of phylogenetic history. However, it has been demonstrated that the choice of which taxa to include in cladistic analysis as well as assumptions about character weighting, character state transformation order, and outgroup choice all influence hypotheses of relationships and may positively influence tree topology, so that relationships between extant taxa are consistent with those found using molecular data. Thus, the source of incongruence between morphological and molecular trees may lie not in the morphological data themselves but in assumptions surrounding the ways characters evolve and their impact on cladistic analysis. In this study, we investigate the role that assumptions about character polarity and transformation order play in creating incongruence between primate phylogenies based on morphological data and those supported by multiple lines of molecular data. By releasing constraints imposed on published morphological analyses of primates from disparate clades and subjecting those data to parsimony analysis, we test the hypothesis that incongruence between morphology and molecules results from inherent flaws in morphological data. To quantify the difference between incongruent trees, we introduce a new method called branch slide distance (BSD). BSD mitigates many of the limitations attributed to other tree comparison methods, thus allowing for a more accurate measure of topological similarity. We find that releasing a priori constraints on character behavior often produces trees that are consistent with molecular trees. Case studies are presented that illustrate how congruence between molecules and unconstrained morphological data may provide insight into issues of polarity, transformation order, homology, and homoplasy.     

Misconceptions about parsimony analysis of endemicity

Parsimony analysis of endemicity (PAE) has been widely criticized in the recent literature based on methodology rather than on theory. Here I argue that most of the criticisms of PAE result from confusion between the dynamic and static approaches of PAE, by both users and critics of the method. Originally, PAE (the dynamic approach) was proposed primarily for historical comparisons of biotic distributions based on geological and stratigraphical information; that is, the stratigraphical record of the biota within two or more horizons was used to evaluate changes (layer by layer) in their distributional patterns. This led to an analysis of the biota throughout space and through time. On the other hand, the static approach excluded the temporal component and based the analysis on a single geological horizon. Most problems exemplified and discussed in the literature refer to the static approach. In addition to this defence of the original PAE, I present some new criticisms regarding the application of PAE using artificially delimited areas (for example areas defined by geopolitical boundaries), which may lead to incorrect interpretations. Recently, several variations of static PAE have appeared: some designed to accommodate ecological data (e.g. parsimony analysis of distributions – PAD); others that incorporate phylogenetic content (e.g. cladistic analysis of distributions and endemism – CADE); and some that have been integrated with other historical methods (e.g. panbiogeography) in order to detect and evaluate hypotheses of biogeographical homologies. Biogeographers, both ecological and historical, should be aware of the problems and limitations of both dynamic and static PAE and evaluate new variations of PAE (PAD, CADE, etc.). Finally, I argue in favour of an independent and pluralist discipline of biogeography that treats biogeography as related to systematics but not dependent on it, as some scholars have assumed.