Syst. Biol. 50(3) 2001

*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]