François-Joseph Lapointe

MODELING BRAIN EVOLUTION FROM BEHAVIOR: A PERMUTATIONAL REGRESSION APPROACH

This paper has two complementary purposes: first, to present a method to perform multiple regression on distance matrices, with permutation testing appropriate for path‐length matrices representing evolutionary trees, and then, to apply this method to study the joint evolution of brain, behavior and other characteristics in marsupials. To understand the computation method, consider that the dependent matrix is unfolded as a vector y; similarly, consider X to be a table containing the independent matrices, also unfolded as vectors. A multiple regression is computed to express y as a function of X. The parameters of this regression (R2 and partial regression coefficients) are tested by permutations, as follows. When the dependent matrix variable y represents a simple distance or similarity matrix, permutations are performed in the same manner as the Mantel permutational test. When it is an ultrametric matrix representing a dendrogram, we use the double‐permutation method (Lapointe and Legendre 1990, 1991). When it is a path‐length matrix representing an additive tree (cladogram), we use the triple‐permutation method (Lapointe and Legendre 1992). The independent matrix variables in X are kept fixed with respect to one another during the permutations. Selection of predictors can be accomplished by forward selection, backward elimination, or a stepwise procedure. A phylogenetic tree, derived from marsupial brain morphology data (28 species), is compared to trees depicting the evolution of diet, sociability, locomotion, and habitat in these animals, as well as their taxonomy and geographical relationships. A model is derived in which brain evolution can be predicted from taxonomy, diet, sociability and locomotion (R2 = 0.75). A new tree, derived from the “predicted” data, shows a lot of similarity to the brain evolution tree. The meaning of the taxonomy, diet, sociability, and locomotion predictors are discussed and conclusions are drawn about the evolution of brain and behavior in marsupials.

Congruence, Consensus, and the Comparative Phylogeography of Codistributed Species in California

Comparative phylogeography has emerged as a means of understanding the spatial patterns of genetic divergence of codistributed species. However, researchers are often frustrated because of the lack of appropriate statistical tests to assess concordancy of multiple phylogeographic trees. We develop a method for testing congruence across multiple species and synthesizing the data into a regional supertree. Nine phylogeographic data sets of species with different life histories and ecologies were statistically compared using maximum agreement subtrees (MAST) and showed a high degree of concordancy. A supertree combining the different phylogeographic trees was then computed using matrix representation with parsimony, and the groups defined by this supertree were tested against climatic data to investigate a potential mechanism driving divergence. Our data suggest that species and genetic lineages in California are shaped by climatic regimes. The supertree method in combination with MAST represents a new approach to test congruence hypotheses and detect common geographic signals in comparative phylogeography.

The Shape of Supertrees to Come: Tree Shape Related Properties of Fourteen Supertree Methods

Using a simple example and simulations, we explore the impact of input tree shape upon a broad range of supertree methods. We find that input tree shape can affect how conflict is resolved by several supertree methods and that input tree shape effects may be substantial. Standard and irreversible matrix representation with parsimony (MRP), MinFlip, duplication-only Gene Tree Parsimony (GTP), and an implementation of the average consensus method have a tendency to resolve conflict in favor of relationships in unbalanced trees. Purvis MRP and the average dendrogram method appear to have an opposite tendency. Biases with respect to tree shape are correlated with objective functions that are based upon unusual asymmetric tree-to-tree distance or fit measures. Split, quartet, and triplet fit, most similar supertree, and MinCut methods (provided the latter are interpreted as Adams consensus-like supertrees) are not revealed to have any bias with respect to tree shape by our example, but whether this holds more generally is an open problem. Future development and evaluation of supertree methods should consider explicitly the undesirable biases and other properties that we highlight. In the meantime, use of a single, arbitrarily chosen supertree method is discouraged. Use of multiple methods and/or weighting schemes may allow practical assessment of the extent to which inferences from real data depend upon methodological biases with respect to input tree shape or size.

The performance of the Congruence Among Distance Matrices (CADM) test in phylogenetic analysis

BackgroundCADM is a statistical test used to estimate the level of Congruence Among Distance Matrices. It has been shown in previous studies to have a correct rate of type I error and good power when applied to dissimilarity matrices and to ultrametric distance matrices. Contrary to most other tests of incongruence used in phylogenetic analysis, the null hypothesis of the CADM test assumes complete incongruence of the phylogenetic trees instead of congruence. In this study, we performed computer simulations to assess the type I error rate and power of the test. It was applied to additive distance matrices representing phylogenies and to genetic distance matrices obtained from nucleotide sequences of different lengths that were simulated on randomly generated trees of varying sizes, and under different evolutionary conditions.ResultsOur results showed that the test has an accurate type I error rate and good power. As expected, power increased with the number of objects (i.e., taxa), the number of partially or completely congruent matrices and the level of congruence among distance matrices.ConclusionsBased on our results, we suggest that CADM is an excellent candidate to test for congruence and, when present, to estimate its level in phylogenomic studies where numerous genes are analysed simultaneously.

A Generalized Permutation Model for the Analysis of Cross-Species Data

Many fields of biology employ cross-species comparisons. However, because species descend with modification from common ancestors, and rates of evolution may vary among branches of an evolutionary tree, problems of nonindependence and nonidentical distributions may occur in comparative data sets. Several phylogenetically based statistical methods have been developed to deal with these issues, but two are most commonly used. Independent contrasts attempts to transform the data to meet the i.i.d. assumption of conventional statistical methods. Monte Carlo computer simulations attempt to produce phylogenetically informed null distributions of test statistics. A disadvantage of the former is its ultimate reliance on conventional distributional assumptions, whereas the latter may require excessive information on biological parameters that are rarely known. We propose a phylogenetic permutation method that is akin to the simulation approach but requires less biological input information. We show that the conventional, equally likely (EL) randomization model is a special case of our phylogenetic permutations (PP). An application of the method is presented to test the correlation between two traits with cross-species data.

Climate change and habitat fragmentation drive the occurrence of Borrelia burgdorferi, the agent of Lyme disease, at the northeastern limit of its distribution

Lyme borreliosis is rapidly emerging in Canada, and climate change is likely a key driver of the northern spread of the disease in North America. We used field and modeling approaches to predict the risk of occurrence of Borrelia burgdorferi, the bacteria causing Lyme disease in North America. We combined climatic and landscape variables to model the current and future (2050) potential distribution of the black‐legged tick and the white‐footed mouse at the northeastern range limit of Lyme disease and estimated a risk index for B. burgdorferi from these distributions. The risk index was mostly constrained by the distribution of the white‐footed mouse, driven by winter climatic conditions. The next factor contributing to the risk index was the distribution of the black‐legged tick, estimated from the temperature. Landscape variables such as forest habitat and connectivity contributed little to the risk index. We predict a further northern expansion of B. burgdorferi of approximately 250–500 km by 2050 – a rate of 3.5–11 km per year – and identify areas of rapid rise in the risk of occurrence of B. burgdorferi. Our results will improve understanding of the spread of Lyme disease and inform management strategies at the most northern limit of its distribution.

A classification of pure malt Scotch whiskies

Single‐malt Scotch whiskies are produced by 109 distilleries in Scotland. The layman may wonder what are the major types of single malts that can be recognized, and what are their chief characteristics and best representatives, whether there is a geographical component in that classification and whether the various categories of characteristics lead to the same classification. This paper provides an answer to these questions, applying an array of statistical methods to a database derived from a connoisseurs description of these liquors. The tasters literary descriptions of Scotches were turned into a numerical database (109 Scotches × 68 binary variables). A first classification was produced by distance computation and hierarchical clustering. Since it was significantly related to the regions of Scotland, a second classification was computed with a spatial contiguity constraint, to divide Scotland into regions where Scotches are homogeneous in their organoleptic characteristics. to explore the congruence of the categories of characteristics, the five databases corresponding to nose, colour, body, palate and finish characteristics were compared by using statistical tests of significance: Among the raw data tables, among distance matrices and among classifications derived from these distance matrices. Most types of characteristic lead to congruent results, despite the loss of information that occurs when moving from one level to the next.

RAPD problems in phylogenetics

This paper is intended to clarify some of the questions related with the application of RAPD for phylogenetic reconstruction purposes. Using different specimens of mammals selected across various taxonomic levels, we assessed the validity of RAPD to recover a known phylogeny, using four distance coefficients (simple matching, Russell & Rao, Jaccard, and Dice). We assessed the minimum number of primers required in the computations to obtain stable results in terms of distance estimates and/or topologies of the derived trees. These results based on distance methods were compared with those obtained with parsimony analyses of RAPD markers. Both approaches have shown to be equally problematic for comparing taxa above the family level. On the basis of these comparisons among various indices and methods, we recommend the use of Jaccard or Dice coefficients, with no less than twelve primers. We also suggest validation of any phylogeny based on RAPD data with a resampling procedure (i.e. the bootstrap or the jackknife) before any sound conclusion can be drawn.

Properties of supertree methods in the consensus setting.

Supertree methods (SMs) are techniques for inferring (super)trees from sets of (input) trees. Classical consensus methods are SMs that were designed for the special case where input trees have identical leaf sets. The need for methods that can also combine information from input trees with nonidentical leaf sets has led to many alternative SMs. Some of these SMs are generalizations from conservative consensus methods (strict and semistrict) that do not resolve input tree conflicts (e.g., Gordon, 1986; Goloboff and Pol, 2002). Our focus here is on more liberal SMs, those capable of resolving conflicts among input trees. Liberal SMs comprise the majority of described methods and have been the most used in practice by biologists seeking well-resolved phylogenies. However, todays practitioners are confronted with choosing among a potentially bewildering array of liberal SM(s). Wilkinson et al. (2004) argued that nonarbitrary, rational choice among liberal SMs would best be guided by knowledge of the comparative accuracy of alternative methods. However, there have been few comparisons of accuracy using simulations (Bininda-Emonds and Sanderson, 2001; Chen et al., 2003; Eulenstein et al., 2004; Lapointe and Levasseur, 2004; Ross and Rodrigo, 2004) over a restricted range of conditions. Thus, Wilkinson et al. (2004) also discussed a number of properties that they suggested provide surrogates for accuracy and might therefore be expected of any SM. One of these, that input tree conflicts should be resolved independently of input tree shape, was investigated by Wilkinson et al. (2005a), who used a simple example (Fig. 1) and simulations to demonstrate input tree shape effects with 8 of the 14 methods they investigated, including the widely used matrix representation with parsimony (MRP) of Baum (1992) and Ragan (1992). Here we introduce a class of sub-Pareto properties that we argue constitute particularly weak expectations of how accurate SMs should handle consensus problems. We then use the same example to substantiate and extend results reported in Wilkinson et al. (2004) and to demonstrate that seven of the liberal SMs that are sensitive to input tree shape also lack some seemingly reasonable consensus properties. Lastly, we consider the relevance of these properties to choice and PRELIMINARIES

Comparison tests for dendrograms: A comparative evaluation

Classifications are generally pictured in the form of hierarchical trees, also called dendrograms. A dendrogram is the graphical representation of an ultrametric (=cophenetic) matrix; so dendrograms can be compared to one another by comparing their cophenetic matrices. Three methods used in testing the correlation between matrices corresponding to dendrograms are evaluated. The three permutational procedures make use of different aspects of the information to compare dendrograms: the Mantel procedure permutes label positions only; the binary tree methods randomize the topology as well; the double-permutation procedure is based on all the information included in a dendrogram, that is: topology, label positions, and cluster heights. Theoretical and empirical investigations of these methods are carried out to evaluate their relative performance. Simulations show that the Mantel test is too conservative when applied to the comparison of dendrograms; the methods of binary tree comparisons do slightly better; only the doublepermutation test provides unbiased type I error.RésuméLes arbres utilisés pour illustrés les groupements sont généralement représentés sous la forme de classifications hiérarchiques ou dendrogrammes. Un dendrogramme représente graphiquement l’information contenue dans la matrice ultramétrique (=cophénétique) correspondant à la classification. Dès ultramétriques correspondantes. Nous comparons trois méthodes permettant d’évaluer la signification statistique du coefficient de correlation mesuré entre deux matrices ultramétriques. Ces trois tests par permutations tiennent compte d’aspects différents pour comparer des dendrogrammes: le test de Mantel permute les feuilles de l’arbre, les méthodes pour arbres binaires permutent les feuilles et la topologie, alors que la procédure à double permutation permute les feuilles, la topologie et les niveaux de fusion des dendrogrammes comparés. L’efficacité relative des trois méthodes est évaluée empiriquement et théoriquement. Nos résultats suggèrent l’utilisation préférentielle du test à double permutation pour la comparaison de dendrogrammes: le test de Mantel s’avère trop conservateur, tandis que les méthodes pour arbres binaires ne sont pas toujours adéquates.