Robustness of statistical tests for multiplicative terms in the additive main effects and multiplicative interaction model for cultivar trials

The additive main effects multiplicative interaction model is frequently used in the analysis of multilocation trials. In the analysis of such data it is of interest to decide how many of the multiplicative interaction terms are significant. Several tests for this task are available, all of which assume that errors are normally distributed with a common variance. This paper investigates the robustness of several tests (Gollob, F _GH1, F_GH2, F_R)to departures from these assumptions. It is concluded that, because of its better robustness, the F _Rtest is preferable. If the other tests are to be used, preliminary tests for the validity of assumptions should be performed.     

Using Confidence Set Heuristics During Topology Search Improves the Robustness of Phylogenetic Inference

We examine the impact of likelihood surface characteristics on phylogenetic inference. Amino acid data sets simulated from topologies with branch length features chosen to represent varying degrees of difficulty for likelihood maximization are analyzed. We present situations where the tree found to achieve the global maximum in likelihood is often not equal to the true tree. We use the program covSEARCH to demonstrate how the use of adaptively sized pools of candidate trees that are updated using confidence tests results in solution sets that are highly likely to contain the true tree. This approach requires more computation than traditional maximum likelihood methods, hence covSEARCH is best suited to small to medium-sized alignments or large alignments with some constrained nodes. The majority rule consensus tree computed from the confidence sets also proves to be different from the generating topology. Although low phylogenetic signal in the input alignment can result in large confidence sets of trees, some biological information can still be obtained based on nodes that exhibit high support within the confidence set. Two real data examples are analyzed: mammal mitochondrial proteins and a small tubulin alignment. We conclude that the technique of confidence set optimization can significantly improve the robustness of phylogenetic inference at a reasonable computational cost. Additionally, when either very short internal branches or very long terminal branches are present, confident resolution of specific bipartitions or subtrees, rather than whole-tree phylogenies, may be the most realistic goal for phylogenetic methods. [Reviewing Editor: Dr. Nicolas Galtier]     

Evolutionary coupling between the deleteriousness of gene mutations and the amount of non-coding sequences

The phenotypic effects of random mutations depend on both the architecture of the genome and the gene-trait relationships. Both levels thus play a key role in the mutational variability of the phenotype, and hence in the long-term evolutionary success of the lineage. Here, by simulating the evolution of organisms with flexible genomes, we show that the need for an appropriate phenotypic variability induces a relationship between the deleteriousness of gene mutations and the quantity of non-coding sequences maintained in the genome. The more deleterious the gene mutations, the shorter the intergenic sequences. Indeed, in a shorter genome, fewer genes are affected by rearrangements (duplications, deletions, inversions, translocations) at each replication, which compensates for the higher impact of each gene mutation. This spontaneous adjustment of genome structure allows the organisms to retain the same average fitness loss per replication, despite the higher impact of single gene mutations. These results show how evolution can generate unexpected couplings between distinct organization levels.     

Evolvability and Robustness in Color Displays: Bridging the Gap between Theory and Data

Evolution of diet-derived sexual ornaments—some of the most spectacular and diverse traits in the living world—highlights the gap between modern evolutionary theory and empirical data on the origin and inheritance of complex environment-dependent traits. Specifically, current theory offers little insight into how strong environmental contingency of diet-dependent color biosynthesis and environmental variability in precursor supply can be reconciled with extensive evolutionary elaboration, diversification, and convergence of diet-dependent displays among animal taxa. Moreover, biosynthetic pathways of diet-derived displays combine seemingly irreconcilable robustness, lability, and modularity to facilitate elaboration under variable environmental conditions. Here I show that an ontogenetic decrease in the predictability of an association between organismal and environmental components of color biosynthesis and the corresponding evolutionary transition from short-term epigenetic inheritance of peripheral biosynthetic components to genetic inheritance of the most reliable upstream components link the causes of developmental variation with the causes of inheritance in diet-derived displays. Using carotenoid-based colors as an empirical model, I outline general principles of a testable evolutionary framework of diversification and functional robustness of diet-derived displays, and suggest that such a framework provides insight into the foundational question of evolutionary biology—how to connect causes of within-generation developmental variation with causes of among-generation and among-taxa variation and thus with causes of evolution?     

The uniqueness of biological self-organization: challenging the Darwinian paradigm

Here we discuss the challenge posed by self-organization to the Darwinian conception of evolution. As we point out, natural selection can only be the major creative agency in evolution if all or most of the adaptive complexity manifest in living organisms is built up over many generations by the cumulative selection of naturally occurring small, random mutations or variants, i.e., additive, incremental steps over an extended period of time. Biological self-organization—witnessed classically in the folding of a protein, or in the formation of the cell membrane—is a fundamentally different means of generating complexity. We agree that self-organizing systems may be fine-tuned by selection and that self-organization may be therefore considered a complementary mechanism to natural selection as a causal agency in the evolution of life. But we argue that if self-organization proves to be a common mechanism for the generation of adaptive order from the molecular to the organismic level, then this will greatly undermine the Darwinian claim that natural selection is the major creative agency in evolution. We also point out that although complex self-organizing systems are easy to create in the electronic realm of cellular automata, to date translating in silico simulations into real material structures that self-organize into complex forms from local interactions between their constituents has not proved easy. This suggests that self-organizing systems analogous to those utilized by biological systems are at least rare and may indeed represent, as pre-Darwinists believed, a unique ascending hierarchy of natural forms. Such a unique adaptive hierarchy would pose another major challenge to the current Darwinian view of evolution, as it would mean the basic forms of life are necessary features of the order of nature and that the major pathways of evolution are determined by physical law, or more specifically by the self-organizing properties of biomatter, rather than natural selection.     

Bayesian Insight Into a Robust Two-sample t-Test Based on Asymmetric Censored Samples

A robust two-sample Student t-type procedure based on symmetrically censored samples proposed by Tiku (1980, 1982a, b) is studied from the Bayesian point of view. The effect of asymmetric censoring on this procedure is investigated and a good approximation to its posterior distribution in this case is worked out. An illustrative example is also presented.