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The process of phylogenetic analysis inherently consists of two phases. First a data matrix is assembled, and then a phylogenetic tree is inferred from that matrix. There is obviously some feedback between these two phases, yet they remain logically distinct parts of the overall process. One could easily argue that the first phase of phylogenetic analysis is the most important: the tree is basically just a re-representation of the data matrix with no value added. This is especially true from a parsimony viewpoint, the point of which is to maintain an isomorphism between a data matrix and a cladogram. Paradoxically, despite the logical preeminence of data matrix construction in phylogenetic analysis, by far the greatest effort in phylogenetic theory has been directed at the second phase of analysis, the question of how to turn a data matrix into a tree. This chapter deals with logical issues involving the elements of the data matrix in light of the nested and interrelated nature of terminal units (‘twigs’ of the tree) and characters. It is argued that if care is taken to construct an appropriate data matrix to address a particular question of relationships at a given level, then simple parsimony analysis is all that is needed to transform that matrix into a tree. Debates over more complicated models for tree-building may then be seen for what they are: attempts to compensate for marginal data.

Molecular evolution is the study of the process of evolution at the level of DNA, RNA, and proteins, in which the neutral or nearly neutral evolution model has provided the theoretical basis. Yet, the role of positive selection at the molecular level remains a controversial issue. Recent advances in genomics, including whole-genome sequencing, high-throughput protein characterization, and bioinformatics have led to a dramatic increase in studies in comparative and evolutionary genomics. This chapter introduces some widely-used methods in genomic analysis. These include distance method, parsimony methods, maximum-likelihood methods, Bayesian methods, and ancestral sequence inference.

This chapter rebuts irreducible complexity and creationism by explaining the reliability of dating techniques as well as sophisticated laboratory techniques that allow researchers to synthesize extinct genes (genetic archaeology, gene resurrection) and study their homology to other genes. These techniques clearly demonstrate that the irreducible complexity of the eye, the immune system, and the bacterial flagellum are subjective impressions. On the contrary, phylogenetic trees based on gene homology show a deep evolutionary link between simple life-forms and complex ones. Finally, the chapter gives several examples of “poor design” that cast doubt on the principle of Intelligent Design.

A probabilistic sequence (PS) is a sequence in which each position instead of having a single character (amino acid, nucleotide, or codon), has a vector describing the probability of each symbol being the character at that position. A probabilistic ancestral sequence (PAS) is a reconstructed PS for the common ancestor of several sequences. This chapter presents a formalism to compute the probabilities of each character at each position of the biological sequence for the internal nodes in a given phylogenetic tree using a Markov model of evolution. From this model, the probability of an evolutionary configuration can be computed. In addition, efficient algorithms for computing the likelihood score of aligning a character with a character, a character with a probabilistic character, or two probabilistic characters are derived. These scores can then be used in direct string matching or dynamic programming alignments of probabilistic sequences with insertions and deletions. Applications for these alignments, including long-distance homology searching and multiple sequence alignment construction, are shown.

This chapter explains how to build a phylogeny for a certain set of species. A phylogenetic tree is a representation of species interrelatedness and conveys information about which taxa share recent common ancestors, which evolutionary groups (clades) species belong to, and the distances (time, genetic, or character differences) separating species. The chapter first considers two R packages called ape and picante for use in analysis of the R phylogenetic object (referred to as a phylo object type), along with a few other packages, before discussing the steps in reconstructing phylogenetic relationships. It also evaluates some tree-building approaches that are easily implemented in R, including distance-based methods and maximum likelihood methods. Finally, it describes ways of finding and adapting available phylogenetic trees, together with tree scaling and rate smoothing.

This concluding chapter discusses the various issues raised in the course of the book and suggests a way forward for readers attempting ancestral sequence reconstruction. Ancestral sequence reconstruction can be used for testing general hypotheses about the environment and lifestyles of extinct species, general hypotheses about the processes driving gene and genome evolution, specific hypotheses about the evolution of gene function in individual gene families, and ultimately the it can be used for the generation of an understanding of the mapping between sequence (and substitution) to molecular function. A consideration of alternative phylogenetic tree topologies and their effects on ancestral sequence reconstruction is recommended. For smaller data-sets, integrated methods that combine multiple sequence alignment and phylogenetic tree construction in one step are slow, but may provide a better assessment of homology and the evolutionary history of any given amino acid position. Readers may also consider starting with precalculated gene families that already contain multiple sequence alignments and phylogenetic trees for families of interest. Such families can be modified with detailed knowledge and expanded to include new sequences, as available and desired.

Engaging in tree thinking (using phylogenetic diagrams to interpret and infer historical processes) is a prerequisite for understanding macroevolution. Tree thinking has become increasingly important in biology, with important ramifications for applied fields such as genomics, conservation, epidemiology, and pharmacology. Focusing on what is currently known about cognitive and perceptual constraints on students' tree-thinking skills the chapter reports on the effectiveness of business-as-usual instructional units on tree-thinking concepts in two upper-level classes for Biology majors and discussing how this knowledge can be used to inform curriculum development. The chapter argues for a paradigm shift in the way evolution is taught — from a strong focus on natural selection to a model that visualizes evolution as a broad hierarchical continuum which integrates both micro and macro processes with critical scientific reasoning skills.

Each species can be considered to possess a set of unique characters which comprise its feature diversity — the diversity that would be lost when that species goes extinct. Biodiversity is unevenly distributed across the tree of life; if distinctive species become extinct, more of the tree (more unique features) is lost than if we prune less distinctive species. Studying how feature diversity is distributed across biodiversity, using taxonomies and supertrees, allows us to assess the impacts of historically and prehistorically recent extinctions on this distribution. Roughly twice as many higher mammal and bird taxa than expected under a random extinction scenario have been lost throughout the Holocene. Smaller taxa were more likely to lose species to extinction, but there has also been ‘selectivity by taxon’ not predicted by taxon size. The Holocene mammalian phylogeny appears imbalanced, most likely due to non-random losses from species-poor clades over the course of the Holocene.

This article reviews basic techniques of Fourier analysis on a finite abelian group Q, with subsequent applications in graph theory. These include evaluations of the Tutte polynomial of a graph G in terms of cosets of the Q-flows of G. Other applications to spanning trees of Cayley graphs and to group-valued models on phylogenetic trees are also presented to illustrate methods.

This chapter provides an overview of phylogeny reconstruction methods. It introduces some basic concepts used to describe trees and discusses general features of tree-reconstruction methods. Distance and parsimony methods are also discussed.

This chapter examines the logic of null modeling for phylogenetic tests. Developing null expectations for community phylogenetic patterns from randomization procedures is the cornerstone for many ecophylogenetic analysis. The chapter advocates an approach that explicitly considers multiple randomizations to better understand what aspects of community and phylogenetic structure determine observed patterns. It first provides a brief historical overview of randomization tests in ecology, focusing on two important academic conflicts that highlight the need for using randomizations in ecological analysis: the first relates to species–genus ratios and competition between close relatives, and the second deals with co-occurrence patterns and competitive coexistence. It then explains how community data and phylogenetic data can be randomized, taking into account randomizations to test trait data, altering the phylogenetic tree, and other randomizations and inference issues. It also discusses some important considerations for constructing the species pool to be used in the randomization tests.

This chapter focuses on cladistics and addresses questions of tempo and mode of evolution. Do phylogenetic trees reflect or direct our views of Earth history, either regarding the quality of the fossil record or the implication for palaeobiogeographic inference? Can phylogenetic trees imply anything about the rate of taxic diversity through time? Can phylogenetic trees imply anything about the rate of morphological evolution through time? To exemplify the use to which phylogenetic trees may be put, this chapter looks at the evolution of lower teleost fishes through the Cretaceous. The majority of teleosts (16,000 modern species) belong in the clade Acanthomorpha. There were clear vicariant events during late Jurassic times between Northern and Southern Hemisphere continents, and these imposed a geographic pattern reaching from Mexico in the west, along the northern edge of Tethys to North Africa in the east. For some clades of lower teleosts, there is concordance between phylogeny and palaeogeography. This chapter also discusses the distributions of three groups of teleosts: aspidorhynchids, ellimichthyiforms, and chanoids.

The eucalypt group (Myrtaceae) totals seven genera, including small rain forest genera, and species-rich sclerophyll genera that dominate Australian vegetation. Macrofossils of eucalypts extend this range to South America (Early Eocene) and New Zealand (Early Miocene). Subgenus Eucalyptus (the “monocalypts”), with 111 species, is well supported as a monophyletic group. A comprehensive phylogenetic analysis of the monocalypt group has the potential to contribute not only to improved classification and taxonomy, but to an understanding of the evolution of Australian continental bioregions and ecology of the flora, particularly the history of the southwestern sclerophyll biome, which is a recognized region of high endemism and biodiversity, and its disjunction from eastern Australia. This chapter presents a comprehensive phylogenetic tree for subgenus Eucalyptus for the first time, allowing assessment of the biogeographic history and age of a plant group that shows strong east-west disjunction across the Australian continent.

Charles Darwin revolutionised biological thought by suggesting that the origins of species were the result of ‘descent with modification’. His theory of evolution gave the word ‘homology’ its present meaning and importance. The first phylogenetic tree was created based on Darwin’s ideas about evolution, speciation, and natural selection. This book focuses on the origin of the living phyla, which are now separated from each other by distinct morphological gaps, and uses phylogenetic/cladistic principles to infer the topology of the basal metazoan radiation.

So far in this volume we have considered the nature of living things and some of their key building blocks and capabilities. This has set the stage for the current section and the next where we will describe some exemplar integrated biomimetic and biohybrid systems—living machines. To place these contributions in some additional context this introduction briefly reviews the history of life and of its variety, noting some of the critical branching points in the phylogenetic tree, identifying some of the organisms that have been the focus of research on biomimetic systems, and exploring why they might be seen to be important or pivotal. We begin with the first replicators, then consider bacterial colonies, the emergence of multicellularity and of bilateral symmetry, and conclude with a brief discussion of biomimetics applied to vertebrate brain and body plans including those of humans.

The earlier chapters in this book could be thought of as travel notes from an intellectual journey across the landscape of ecological science. In particular, the previous five chapters, 10–14, implicitly or explicitly indicate some of the unintended consequences of the growth in numbers of people and in their environmental impacts. In this final chapter, I begin with a survey of some quantitative measures of the scale of human impacts. Emphasizing the many lamentable uncertainties in our knowledge base, I focus especially on the rising rates of extinction of plant and other animal species. Why should we care about such impoverishment of our planet’s biological diversity? I outline three kinds of possible reasons, under the headings of narrowly utilitarian, broadly utilitarian, and ethical. Each of these is then discussed, with emphasis on ways in which current lack of knowledge—lack of data and/or lack of theoretical understanding—is a handicap. In places, this carries the discussion into areas not commonly found in ecology texts (ethical, economic, and political questions, for instance). In other places, there is the more familiar exhortation for more research on this or that topic. Contrary to some impressions, human population growth has been far from simply exponential. Broadly speaking, humans have been around for a couple of hundred thousand years (Deevey, 1960; Cohen, 1995). For essentially all this time, they were small bands of hunter-gatherers, with the total human population being variously estimated at around 5–20 million people. With the benefits of the invention of agriculture, roughly simultaneously in various parts of the world around 10 000 years ago, things started to change. Denser aggregations of people became possible, and villages began their journey to cities. Following the advent of this agricultural revolution, human populations arguably grew more rapidly in the first 5000 years than in the more recent 5000, up to the beginning of the Scientific- Industrial Revolution around the 1600s. This relative slowing of population growth is almost surely associated with infectious diseases which were not sustainable at the low population densities associated with hunter-gatherers.