Michael J. Sanderson

Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.

SUMMARY: Estimating divergence times and rates of substitution from sequence data is plagued by the problem of rate variation between lineages. R8s version 1.5 is a program which uses parametric, nonparametric and semiparametric methods to relax the assumption of constant rates of evolution to obtain better estimates of rates and times. Unlike most programs for rate inference or phylogenetics, r8s permits users to convert results to absolute rates and ages by constraining one or more node times to be fixed, minimum or maximum ages (using fossil or other evidence). Version 1.5 uses truncated Newton nonlinear optimization code with bound constraints, offering superior performance over previous versions. AVAILABILITY: The linux executable, C source code, sample data sets and user manual are available free at http://ginger.ucdavis.edu/r8s.

Bruce G. Baldwin, Michael J. Sanderson, J. Mark Porter, Martin F. Wojciechowski, Christopher S. Campbell, Michael J. Donoghue, The its Region of Nuclear Ribosomal DNA: A Valuable Source of Evidence on Angiosperm Phylogeny, Annals of the Missouri Botanical Garden, Vol. 82, No. 2 (1995), pp. 247-277

A new method for estimating divergence times when evolutionary rates are variable across lineages is proposed. The method, called nonparametric rate smoothing (NPRS), relies on minimization of ancestor-descendant local rate changes and is motivated by the likelihood that evolutionary rates are autocorrelated in time. Fossil information pertaining to minimum and/or maximum ages of nodes in a phylogeny is incorporated into the algorithms by constrained optimization techniques. The accuracy of NPRS was examined by comparison to a clock-based maximum-likelihood method in computer simulations. NPRS provides more accurate estimates of divergence times when (1) sequence lengths are sufficiently long, (2) rates are truly nonclocklike, and (3) rates are moderately to highly autocorrelated in time. The algorithms were applied to estimate divergence times in seed plants based on data from the chloroplast rbcL gene. Both constrained and unconstrained NPRS methods tended to produce divergence time estimates more consistent with paleobotanical evidence than did clock-based estimates.

Abstract The classification of the legume family proposed here addresses the long‐known non‐monophyly of the traditionally recognised subfamily Caesalpinioideae, by recognising six robustly supported monophyletic subfamilies. This new classification uses as its framework the most comprehensive phylogenetic analyses of legumes to date, based on plastid matK gene sequences, and including near‐complete sampling of genera (698 of the currently recognised 765 genera) and ca. 20% (3696) of known species. The matK gene region has been the most widely sequenced across the legumes, and in most legume lineages, this gene region is sufficiently variable to yield well‐supported clades. This analysis resolves the same major clades as in other phylogenies of whole plastid and nuclear gene sets (with much sparser taxon sampling). Our analysis improves upon previous studies that have used large phylogenies of the Leguminosae for addressing evolutionary questions, because it maximises generic sampling and provides a phylogenetic tree that is based on a fully curated set of sequences that are vouchered and taxonomically validated. The phylogenetic trees obtained and the underlying data are available to browse and download, facilitating subsequent analyses that require evolutionary trees. Here we propose a new community‐endorsed classification of the family that reflects the phylogenetic structure that is consistently resolved and recognises six subfamilies in Leguminosae: a recircumscribed Caesalpinioideae DC., Cercidoideae Legume Phylogeny Working Group (stat. nov.), Detarioideae Burmeist., Dialioideae Legume Phylogeny Working Group (stat. nov.), Duparquetioideae Legume Phylogeny Working Group (stat. nov.), and Papilionoideae DC. The traditionally recognised subfamily Mimosoideae is a distinct clade nested within the recircumscribed Caesalpinioideae and is referred to informally as the mimosoid clade pending a forthcoming formal tribal and/or clade‐based classification of the new Caesalpinioideae. We provide a key for subfamily identification, descriptions with diagnostic charactertistics for the subfamilies, figures illustrating their floral and fruit diversity, and lists of genera by subfamily. This new classification of Leguminosae represents a consensus view of the international legume systematics community; it invokes both compromise and practicality of use.