Evolutionary biology : mass survivals

The conclusion that the primary divergences of the modern groups of mammals occurred in the mid-Cretaceous requires fresh thinking about this facet of evolutionary history — especially in ecological terms.

Review ["Telling the Evolutionary Time : Molecular Clocks and the Fossil Record" edited by Philip C. J. Donoghue and M. Paul Smith]

Determining the temporal scale of biological evolution has traditionally been the preserve of paleontology, with the timing of species originations and major diversifications all being read from the fossil record. However, the ages of the earliest (correctly identified) records will underestimate actual origins due to the incomplete nature of the fossil record and the necessity for lineages to have evolved sufficiently divergent morphologies in order to be distinguished. The possibility of inferring divergence times more accurately has been promoted by the idea that the accumulation of genetic change between modern lineages can be used as a molecular clock (Zuckerkandl and Pauling, 1965). In practice, though, molecular dates have often been so old as to be incongruent even with liberal readings of the fossil record. Prominent examples include inferred diversifications of metazoan phyla hundreds of millions of years before their Cambrian fossil record appearances (e.g., Nei et al., 2001) and a basal split between modern birds (Neoaves) that is almost double the age of their earliest recognizable fossils (e.g., Cooper and Penny, 1997).

Accounting for calibration uncertainty in phylogenetic estimation of evolutionary divergence times

The estimation of phylogenetic divergence times from sequence data is an important component of many molecular evolutionary studies. There is now a general appreciation that the procedure of divergence dating is considerably more complex than that initially described in the 1960s by Zuckerkandl and Pauling (1962, 1965). In particular, there has been much critical attention toward the assumption of a global molecular clock, resulting in the development of increasingly sophisticated techniques for inferring divergence times from sequence data. In response to the documentation of widespread departures from clocklike behavior, a variety of local- and relaxed-clock methods have been proposed and implemented. Local-clock methods permit different molecular clocks in different parts of the phylogenetic tree, thereby retaining the advantages of the classical molecular clock while casting off the restrictive assumption of a single, global rate of substitution (Rambaut and Bromham 1998; Yoder and Yang 2000).

The evolutionary history of the extinct ratite moa and New Zealand Neogene paleogeography

The ratite moa (Aves: Dinornithiformes) were a speciose group of massive graviportal avian herbivores that dominated the New Zealand (NZ) ecosystem until their extinction �600 years ago. The phylogeny and evolutionary history of this morphologically diverse order has remained controversial since their initial description in 1839. We synthesize mitochondrial phylogenetic information from 263 subfossil moa specimens from across NZ with morphological, ecological, and new geological data to create the first comprehensive phylogeny, taxonomy, and evolutionary timeframe for all of the species of an extinct order. We also present an important new geological/paleogeographical model of late Cenozoic NZ, which suggests that terrestrial biota on the North and South Island landmasses were isolated for most of the past 20–30 Ma. The data reveal that the patterns of genetic diversity within and between differentmoaclades reflect a complex history following a major marine transgression in the Oligocene, affected by marine barriers, tectonic activity, and glacial cycles. Surprisingly, the remarkable morphological radiation of moa appears to have occurred much more recently than previous early Miocene (ca. 15 Ma) estimates, and was coincident with the accelerated uplift of the Southern Alps just ca. 5–8.5 Ma. Together with recent fossil evidence, these data suggest that the recent evolutionary history of nearly all of the iconic NZ terrestrial biota occurred principally on just the South Island.

The evolutionary history of cockatoos (Aves: Psittaciformes: Cacatuidae)

Cockatoos are the distinctive family Cacatuidae, a major lineage of the order of parrots (Psittaciformes) and distributed throughout the Australasian region of the world. However, the evolutionary history of cockatoos is not well understood. We investigated the phylogeny of cockatoos based on three mitochondrial and three nuclear DNA genes obtained from 16 of 21 species of Cacatuidae. In addition, five novel mitochondrial genomes were used to estimate time of divergence and our estimates indicate Cacatuidae diverged from Psittacidae approximately 40.7 million years ago (95% CI 51.6–30.3 Ma) during the Eocene. Our data shows Cacatuidae began to diversify approximately 27.9 Ma (95% CI 38.1–18.3 Ma) during the Oligocene. The early to middle Miocene (20–10 Ma) was a significant period in the evolution of modern Australian environments and vegetation, in which a transformation from mainly mesic to xeric habitats (e.g., fire-adapted sclerophyll vegetation and grasslands) occurred. We hypothesize that this environmental transformation was a driving force behind the diversification of cockatoos. A detailed multi-locus molecular phylogeny enabled us to resolve the phylogenetic placements of the Palm Cockatoo (Probosciger aterrimus), Galah (Eolophus roseicapillus), Gang-gang Cockatoo (Callocephalon fimbriatum) and Cockatiel (Nymphicus hollandicus), which have historically been difficult to place within Cacatuidae. When the molecular evidence is analysed in concert with morphology, it is clear that many of the cockatoo species’ diagnostic phenotypic traits such as plumage colour, body size, wing shape and bill morphology have evolved in parallel or convergently across lineages.

Evolutionary relationships and divergence times among the native rats of Australia

Background The genus Rattus is highly speciose and has a complex taxonomy that is not fully resolved. As shown previously there are two major groups within the genus, an Asian and an Australo-Papuan group. This study focuses on the Australo-Papuan group and particularly on the Australian rats. There are uncertainties regarding the number of species within the group and the relationships among them. We analysed 16 mitochondrial genomes, including seven novel genomes from six species, to help elucidate the evolutionary history of the Australian rats. We also demonstrate, from a larger dataset, the usefulness of short regions of the mitochondrial genome in identifying these rats at the species level. Results Analyses of 16 mitochondrial genomes representing species sampled from Australo-Papuan and Asian clades of Rattus indicate divergence of these two groups ~2.7 million years ago (Mya). Subsequent diversification of at least 4 lineages within the Australo-Papuan clade was rapid and occurred over the period from ~ 0.9-1.7 Mya, a finding that explains the difficulty in resolving some relationships within this clade. Phylogenetic analyses of our 126 taxon, but shorter sequence (1952 nucleotides long), Rattus database generally give well supported species clades. Conclusions Our whole mitochondrial genome analyses are concordant with a taxonomic division that places the native Australian rats into the Rattus fuscipes species group. We suggest the following order of divergence of the Australian species. R. fuscipes is the oldest lineage among the Australian rats and is not part of a New Guinean radiation. R. lutreolus is also within this Australian clade and shallower than R. tunneyi while the R. sordidus group is the shallowest lineage in the clade. The divergences within the R. sordidus and R. leucopus lineages occurring about half a million years ago support the hypotheses of more recent interchanges of rats between Australia and New Guinea. While problematic for inference of deeper divergences, we report that the analysis of shorter mitochondrial sequences is very useful for species identification in rats.

A hierarchical evolutionary algorithmic design (HEAD) system for generating and evolving building design models

This thesis develops a detailed conceptual design method and a system software architecture defined with a parametric and generative evolutionary design system to support an integrated interdisciplinary building design approach. The research recognises the need to shift design efforts toward the earliest phases of the design process to support crucial design decisions that have a substantial cost implication on the overall project budget. The overall motivation of the research is to improve the quality of designs produced at the author's employer, the General Directorate of Major Works (GDMW) of the Saudi Arabian Armed Forces. GDMW produces many buildings that have standard requirements, across a wide range of environmental and social circumstances. A rapid means of customising designs for local circumstances would have significant benefits. The research considers the use of evolutionary genetic algorithms in the design process and the ability to generate and assess a wider range of potential design solutions than a human could manage. This wider ranging assessment, during the early stages of the design process, means that the generated solutions will be more appropriate for the defined design problem. The research work proposes a design method and system that promotes a collaborative relationship between human creativity and the computer capability. The tectonic design approach is adopted as a process oriented design that values the process of design as much as the product. The aim is to connect the evolutionary systems to performance assessment applications, which are used as prioritised fitness functions. This will produce design solutions that respond to their environmental and function requirements. This integrated, interdisciplinary approach to design will produce solutions through a design process that considers and balances the requirements of all aspects of the design. Since this thesis covers a wide area of research material, 'methodological pluralism' approach was used, incorporating both prescriptive and descriptive research methods. Multiple models of research were combined and the overall research was undertaken following three main stages, conceptualisation, developmental and evaluation. The first two stages lay the foundations for the specification of the proposed system where key aspects of the system that have not previously been proven in the literature, were implemented to test the feasibility of the system. As a result of combining the existing knowledge in the area with the newlyverified key aspects of the proposed system, this research can form the base for a future software development project. The evaluation stage, which includes building the prototype system to test and evaluate the system performance based on the criteria defined in the earlier stage, is not within the scope this thesis. The research results in a conceptual design method and a proposed system software architecture. The proposed system is called the 'Hierarchical Evolutionary Algorithmic Design (HEAD) System'. The HEAD system has shown to be feasible through the initial illustrative paper-based simulation. The HEAD system consists of the two main components - 'Design Schema' and the 'Synthesis Algorithms'. The HEAD system reflects the major research contribution in the way it is conceptualised, while secondary contributions are achieved within the system components. The design schema provides constraints on the generation of designs, thus enabling the designer to create a wide range of potential designs that can then be analysed for desirable characteristics. The design schema supports the digital representation of the human creativity of designers into a dynamic design framework that can be encoded and then executed through the use of evolutionary genetic algorithms. The design schema incorporates 2D and 3D geometry and graph theory for space layout planning and building formation using the Lowest Common Design Denominator (LCDD) of a parameterised 2D module and a 3D structural module. This provides a bridge between the standard adjacency requirements and the evolutionary system. The use of graphs as an input to the evolutionary algorithm supports the introduction of constraints in a way that is not supported by standard evolutionary techniques. The process of design synthesis is guided as a higher level description of the building that supports geometrical constraints. The Synthesis Algorithms component analyses designs at four levels, 'Room', 'Layout', 'Building' and 'Optimisation'. At each level multiple fitness functions are embedded into the genetic algorithm to target the specific requirements of the relevant decomposed part of the design problem. Decomposing the design problem to allow for the design requirements of each level to be dealt with separately and then reassembling them in a bottom up approach reduces the generation of non-viable solutions through constraining the options available at the next higher level. The iterative approach, in exploring the range of design solutions through modification of the design schema as the understanding of the design problem improves, assists in identifying conflicts in the design requirements. Additionally, the hierarchical set-up allows the embedding of multiple fitness functions into the genetic algorithm, each relevant to a specific level. This supports an integrated multi-level, multi-disciplinary approach. The HEAD system promotes a collaborative relationship between human creativity and the computer capability. The design schema component, as the input to the procedural algorithms, enables the encoding of certain aspects of the designer's subjective creativity. By focusing on finding solutions for the relevant sub-problems at the appropriate levels of detail, the hierarchical nature of the system assist in the design decision-making process.

Evolutionary design of bone scaffolds with reference to material selection

The favourable scaffold for bone tissue engineering should have desired characteristic features, such as adequate mechanical strength and three-dimensional open porosity, which guarantee a suitable environment for tissue regeneration. In fact, the design of such complex structures like bone scaffolds is a challenge for investigators. One of the aims is to achieve the best possible mechanical strength-degradation rate ratio. In this paper we attempt to use numerical modelling to evaluate material properties for designing bone tissue engineering scaffold fabricated via the fused deposition modelling technique. For our studies the standard genetic algorithm was used, which is an efficient method of discrete optimization. For the fused deposition modelling scaffold, each individual strut is scrutinized for its role in the architecture and structural support it provides for the scaffold, and its contribution to the overall scaffold was studied. The goal of the study was to create a numerical tool that could help to acquire the desired behaviour of tissue engineered scaffolds and our results showed that this could be achieved efficiently by using different materials for individual struts. To represent a great number of ways in which scaffold mechanical function loss could proceed, the exemplary set of different desirable scaffold stiffness loss function was chosen. © 2012 John Wiley & Sons, Ltd.

Composite SaaS placement and resource optimization in Cloud computing using evolutionary algorithms

Software as a Service (SaaS) is gaining more and more attention from software users and providers recently. This has raised many new challenges to SaaS providers in providing better SaaSes that suit everyone needs at minimum costs. One of the emerging approaches in tackling this challenge is by delivering the SaaS as a composite SaaS. Delivering it in such an approach has a number of benefits, including flexible offering of the SaaS functions and decreased cost of subscription for users. However, this approach also introduces new problems for SaaS resource management in a Cloud data centre. We present the problem of composite SaaS resource management in Cloud data centre, specifically on its initial placement and resource optimization problems aiming at improving the SaaS performance based on its execution time as well as minimizing the resource usage. Our approach differs from existing literature because it addresses the problems resulting from composite SaaS characteristics, where we focus on the SaaS requirements, constraints and interdependencies. The problems are tackled using evolutionary algorithms. Experimental results demonstrate the efficiency and the scalability of the proposed algorithms.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.

A human-simulated immune evolutionary computation approach

Premature convergence to local optimal solutions is one of the main difficulties when using evolutionary algorithms in real-world optimization problems. To prevent premature convergence and degeneration phenomenon, this paper proposes a new optimization computation approach, human-simulated immune evolutionary algorithm (HSIEA). Considering that the premature convergence problem is due to the lack of diversity in the population, the HSIEA employs the clonal selection principle of artificial immune system theory to preserve the diversity of solutions for the search process. Mathematical descriptions and procedures of the HSIEA are given, and four new evolutionary operators are formulated which are clone, variation, recombination, and selection. Two benchmark optimization functions are investigated to demonstrate the effectiveness of the proposed HSIEA.