Diversité et structure du zooplancton : importance pour la conservation de la biodiversité aquatique en zone urbaine

L'écologie urbaine est un nouveau champ de recherche qui cherche à comprendre les structures et les patrons des communautés et des écosystèmes situés dans des paysages urbains. Les petits plans d’eau sont connus comme des écosystèmes aquatiques qui peuvent contenir une biodiversité considérable pour plusieurs groupes taxonomiques (oiseaux, amphibiens, macroinvertébrés), ce qui en fait des écosystèmes intéressants pour les études de conservation. Cependant, la biodiversité du zooplancton, un élément central des réseaux trophiques aquatiques, n’est pas entièrement connue pour les plans d’eaux urbains et devrait être mieux décrite et comprise. Cette étude a évalué les patrons de biodiversité des communautés zooplanctoniques dans des plans d’eau urbains sur l’Ile de Montréal et leurs sources de variation. Des suggestions pour l’évaluation et la conservation de la biodiversité sont aussi discutées. La biodiversité zooplanctonique des plans d’eaux urbains s’est avérée être assez élevée, avec les cladocères et les rotifères montrant les contributions à la diversité gamma et bêta les plus élevées. Sur l’ensemble des plans d’eau, il y avait une corrélation négative entre les contributions à la bêta diversité des cladocères et des rotifères. Au niveau de chaque plan d'eau, la zone littorale colonisée par des macrophytes s'est avérée être un habitat important pour la biodiversité zooplactonique, contribuant considérablement à la richesse en taxons, souvent avec une différente composition en espèces. Les communautés zooplanctoniques répondaient aux facteurs ascendants et descendants, mais aussi aux pratiques d’entretien, car le fait de vider les plans d’eau en hiver affecte la composition des communautés zooplanctoniques. Les communautés de cladocères dans ces plans d’eau possédaient des quantités variables de diversité phylogénétique, ce qui permet de les classer afin de prioriser les sites à préserver par rapport à la diversité phylogénétique. Le choix des sites à préserver afin de maximiser la diversité phylogénétique devrait être correctement établi, afin d’eviter de faire des choix sous-optimaux. Cependant, pour des taxons tels que les cladocères, pour lesquels les relations phylogénétiques demeurent difficiles à établir, placer une confiance absolue dans un seul arbre est une procédure dangereuse. L’incorporation de l’incertitude phylogénétique a démontré que, lorsqu’elle est prise en compte, plusieurs différences potentielles entre la diversité phylogenétique ne sont plus supportées. Les patrons de composition des communautés différaient entre les plans d’eau, les mois et les zones d’échantillonnage. Etant donné les intéractions sont significatives entres ces facters; ceci indique que tous ces facteurs devraient êtres considérés. L’urbanisation ne semblait pas sélectionner pour un type unique de composition des groupes alimentaires, étant donné que les communautés pouvaient changer entres des assemblages de types alimentaires différents. Les variables environnementales, surtout la couverture du plan d’eau en macrophytes, étaient des facteurs importants pour la biodiversité zooplanctonique, affectant la richesse spécifique de divers groupes taxonomiques et alimentaires. Ces variables affectaient aussi la composition des communautés, mais dans une moindre mesure, étant des variables explicatives modestes, ce qui indiquerait le besoin de considérer d’autres processus.

Validating planning heritage : evidence and reasoning for national heritage recognition of the 'City of Adelaide Plan' and park lands

The Adelaide Park Lands and the ‘City of Adelaide Plan’ (1837), as prepared by Colonel William Light, have long been held up as an international precedent in town planning literature. The celebrated model, embraced by Ebenezer Howard to describe his Garden City theory, has several layers of cultural landscape heritage. The ‘Plan’, in recent years, has been subject to a rigorous investigation of its Indigenous and colonization evolutionary layers to inform moves to list the landscape as possessing national heritage status under relevant Australian heritage regimes, and more recently under the National Heritage List regime, as a pre-emptive strategy towards an eventual World Heritage nomination of the cultural landscape and ‘Plan’.

The evolutionary relationships and age of Homo naledi : an assessment using dated Bayesian phylogenetic methods

Acknowledgements We wish to express our gratitude to the National Geographic Society and the National Research Foundation of South Africa for funding the discovery, recovery, and analysis of the H. naledi material. The study reported here was also made possible by grants from the Social Sciences and Humanities Research Council of Canada, the Canada Foundation for Innovation, the British Columbia Knowledge Development Fund, the Canada Research Chairs Program, Simon Fraser University, the DST/NRF Centre of Excellence in Palaeosciences (COE-Pal), as well as by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada, a Young Scientist Development Grant from the Paleontological Scientific Trust (PAST), a Baldwin Fellowship from the L.S.B. Leakey Foundation, and a Seed Grant and a Cornerstone Faculty Fellowship from the Texas A&M University College of Liberal Arts. We would like to thank the South African Heritage Resource Agency for the permits necessary to work on the Rising Star site; the Jacobs family for granting access; Wilma Lawrence, Bonita De Klerk, Merrill Van der Walt, and Justin Mukanku for their assistance during all phases of the project; Lucas Delezene for valuable discussion on the dental characters of H. naledi. We would also like to thank Peter Schmid for the preparation of the Dinaledi fossil material; Yoel Rak for explaining in detail some of the characters used in previous studies; William Kimbel for drawing our attention to the possibility that there might be a problem with Dembo et al.’s (2015) codes for the two characters related to the articular eminence; Will Stein for helpful discussion about the Bayesian analyses; Mike Lee for his comments on this manuscript; John Hawks for his support in organizing the Rising Star workshop; and the associate editor and three anonymous reviewers for their valuable comments. We are grateful to S. Potze and the Ditsong Museum, B. Billings and the School of Anatomical Sciences at the University of the Witwatersrand, and B. Zipfel and the Evolutionary Studies Institute at the University of the Witwatersrand for providing access to the specimens in their care; the University of the Witwatersrand, the Evolutionary Studies Institute, and the South African National Centre of Excellence in PalaeoSciences for hosting a number of the authors while studying the material; and the Western Canada Research Grid for providing access to the high-performance computing facilities for the Bayesian analyses. Last but definitely not least, we thank the head of the Rising Star project, Lee Berger, for his leadership and support, and for encouraging us to pursue the study reported here.

A generative design system based on evolutionary and mathematical functions

Previous work by Professor John Frazer on Evolutionary Architecture provides a basis for the development of a system evolving architectural envelopes in a generic and abstract manner. Recent research by the authors has focused on the implementation of a virtual environment for the automatic generation and exploration of complex forms and architectural envelopes based on solid modelling techniques and the integration of evolutionary algorithms, enhanced computational and mathematical models. Abstract data types are introduced for genotypes in a genetic algorithm order to develop complex models using generative and evolutionary computing techniques. Multi-objective optimisation techniques are employed for defining the fitness function in the evaluation process.

An evolutionary framework for enhancing design

A computational framework for enhancing design in an evolutionary approach with a dynamic hierarchical structure is presented in this paper. This framework can be used as an evolutionary kernel for building computer-supported design systems. It provides computational components for generating, adapting and exploring alternative design solutions at multiple levels of abstraction with hierarchically structured design representations. In this paper, preliminary experimental results of using this framework in several design applications are presented.

A natural model for architecture : the nature of the evolutionary model 1995

John Frazer's architectural work is inspired by living and generative processes. Both evolutionary and revolutionary, it explores informatin ecologies and the dynamics of the spaces between objects. Fuelled by an interest in the cybernetic work of Gordon Pask and Norbert Wiener, and the possibilities of the computer and the "new science" it has facilitated, Frazer and his team of collaborators have conducted a series of experiments that utilize genetic algorithms, cellular automata, emergent behaviour, complexity and feedback loops to create a truly dynamic architecture. Frazer studied at the Architectural Association (AA) in London from 1963 to 1969, and later became unit master of Diploma Unit 11 there. He was subsequently Director of Computer-Aided Design at the University of Ulter - a post he held while writing An Evolutionary Architecture in 1995 - and a lecturer at the University of Cambridge. In 1983 he co-founded Autographics Software Ltd, which pioneered microprocessor graphics. Frazer was awarded a person chair at the University of Ulster in 1984. In Frazer's hands, architecture becomes machine-readable, formally open-ended and responsive. His work as computer consultant to Cedric Price's Generator Project of 1976 (see P84)led to the development of a series of tools and processes; these have resulted in projects such as the Calbuild Kit (1985) and the Universal Constructor (1990). These subsequent computer-orientated architectural machines are makers of architectural form beyond the full control of the architect-programmer. Frazer makes much reference to the multi-celled relationships found in nature, and their ongoing morphosis in response to continually changing contextual criteria. He defines the elements that describe his evolutionary architectural model thus: "A genetic code script, rules for the development of the code, mapping of the code to a virtual model, the nature of the environment for the development of the model and, most importantly, the criteria for selection. In setting out these parameters for designing evolutionary architectures, Frazer goes beyond the usual notions of architectural beauty and aesthetics. Nevertheless his work is not without an aesthetic: some pieces are a frenzy of mad wire, while others have a modularity that is reminiscent of biological form. Algorithms form the basis of Frazer's designs. These algorithms determine a variety of formal results dependent on the nature of the information they are given. His work, therefore, is always dynamic, always evolving and always different. Designing with algorithms is also critical to other architects featured in this book, such as Marcos Novak (see p150). Frazer has made an unparalleled contribution to defining architectural possibilities for the twenty-first century, and remains an inspiration to architects seeking to create responsive environments. Architects were initially slow to pick up on the opportunities that the computer provides. These opportunities are both representational and spatial: computers can help architects draw buildings and, more importantly, they can help architects create varied spaces, both virtual and actual. Frazer's work was groundbreaking in this respect, and well before its time.

Creative design and the generative evolutionary paradigm

Design as seen from the designer's perspective is a series of amazing imaginative jumps or creative leaps. But design as seen by the design historian is a smooth progression or evolution of ideas that they seem self-evident and inevitable after the event. But the next step is anything but obvious for the artist/creator/inventor/designer stuck at that point just before the creative leap. They know where they have come from and have a general sense of where they are going, but often do not have a precise target or goal. This is why it is misleading to talk of design as a problem-solving activity - it is better defined as a problem-finding activity. This has been very frustrating for those trying to assist the design process with computer-based, problem-solving techniques. By the time the problem has been defined, it has been solved. Indeed the solution is often the very definition of the problem. Design must be creative-or it is mere imitation. But since this crucial creative leap seem inevitable after the event, the question must arise, can we find some way of searching the space ahead? Of course there are serious problems of knowing what we are looking for and the vastness of the search space. It may be better to discard altogether the term "searching" in the context of the design process: Conceptual analogies such as search, search spaces and fitness landscapes aim to elucidate the design process. However, the vastness of the multidimensional spaces involved make these analogies misguided and they thereby actually result in further confounding the issue. The term search becomes a misnomer since it has connotations that imply that it is possible to find what you are looking for. In such vast spaces the term search must be discarded. Thus, any attempt at searching for the highest peak in the fitness landscape as an optimal solution is also meaningless. Futhermore, even the very existence of a fitness landscape is fallacious. Although alternatives in the same region of the vast space can be compared to one another, distant alternatives will stem from radically different roots and will therefore not be comparable in any straightforward manner (Janssen 2000). Nevertheless we still have this tantalizing possibility that if a creative idea seems inevitable after the event, then somehow might the process be rserved? This may be as improbable as attempting to reverse time. A more helpful analogy is from nature, where it is generally assumed that the process of evolution is not long-term goal directed or teleological. Dennett points out a common minsunderstanding of Darwinism: the idea that evolution by natural selection is a procedure for producing human beings. Evolution can have produced humankind by an algorithmic process, without its being true that evolution is an algorithm for producing us. If we were to wind the tape of life back and run this algorithm again, the likelihood of "us" being created again is infinitesimally small (Gould 1989; Dennett 1995). But nevertheless Mother Nature has proved a remarkably successful, resourceful, and imaginative inventor generating a constant flow of incredible new design ideas to fire our imagination. Hence the current interest in the potential of the evolutionary paradigm in design. These evolutionary methods are frequently based on techniques such as the application of evolutionary algorithms that are usually thought of as search algorithms. It is necessary to abandon such connections with searching and see the evolutionary algorithm as a direct analogy with the evolutionary processes of nature. The process of natural selection can generate a wealth of alternative experiements, and the better ones survive. There is no one solution, there is no optimal solution, but there is continuous experiment. Nature is profligate with her prototyping and ruthless in her elimination of less successful experiments. Most importantly, nature has all the time in the world. As designers we cannot afford prototyping and ruthless experiment, nor can we operate on the time scale of the natural design process. Instead we can use the computer to compress space and time and to perform virtual prototyping and evaluation before committing ourselves to actual prototypes. This is the hypothesis underlying the evolutionary paradigm in design (1992, 1995).