Ecosystem-Oriented Distributed Evolutionary Computing

We create a novel optimisation technique inspired by natural ecosystems, where the optimisation works at two levels: a first optimisation, migration of genes which are distributed in a peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. We consider from the domain of computer science distributed evolutionary computing, with the relevant theory from the domain of theoretical biology, including the fields of evolutionary and ecological theory, the topological structure of ecosystems, and evolutionary processes within distributed environments. We then define ecosystem- oriented distributed evolutionary computing, imbibed with the properties of self-organisation, scalability and sustainability from natural ecosystems, including a novel form of distributed evolu- tionary computing. Finally, we conclude with a discussion of the apparent compromises resulting from the hybrid model created, such as the network topology.Comment: 8 pages, 5 figures. arXiv admin note: text overlap with arXiv:1112.0204, arXiv:0712.4159, arXiv:0712.4153, arXiv:0712.4102, arXiv:0910.067

Biology of Applied Digital Ecosystems

A primary motivation for our research in Digital Ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the biological processes that contribute to these properties have not been made explicit in Digital Ecosystems research. Here, we discuss how biological properties contribute to the self-organising features of biological ecosystems, including population dynamics, evolution, a complex dynamic environment, and spatial distributions for generating local interactions. The potential for exploiting these properties in artificial systems is then considered. We suggest that several key features of biological ecosystems have not been fully explored in existing digital ecosystems, and discuss how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, with measures originating from theoretical ecology, to confirm its likeness to a biological ecosystem. Including the responsiveness to requests for applications from the user base, as a measure of the 'ecological succession' (development).Comment: 9 pages, 4 figure, conferenc

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

Halting indigenous biodiversity decline: ambiguity, equity, and outcomes in RMA assessment of significance

In New Zealand, assessment of ‘significance’ is undertaken to give effect to a legal requirement for local authorities to provide for protection of significant sites under the Resource Management Act (1991). The ambiguity of the statute enables different interests to define significance according to their goals: vested interests (developers), local authorities, and non-vested interests in pursuit of protection of environmental public goods may advance different definitions. We examine two sets of criteria used for assessment of significance for biological diversity under the Act. Criteria adapted from the 1980s Protected Natural Areas Programme are inadequate to achieve the maintenance of biological diversity if ranking is used to identify only highest priority sites. Norton and Roper-Lindsay (2004) propose a narrow definition of significance and criteria that identify only a few high-quality sites as significant. Both sets are likely to serve the interests of developers and local authorities, but place the penalty of uncertainty on non-vested interests seeking to maintain biological diversity, and are likely to exacerbate the decline of biological diversity and the loss of landscape-scale processes required for its persistence. When adopting criteria for assessment of significance, we suggest local authorities should consider whose interests are served by different criteria sets, and who will bear the penalty of uncertainty regarding biological diversity outcomes. They should also ask whether significance criteria are adequate, and sufficiently robust to the uncertainty inherent in the assessment of natural values, to halt the decline of indigenous biological diversity

Diversity across Seasons of Culturable Pseudomonas from a Desiccation Lagoon in Cuatro Cienegas, Mexico.

Cuatro Cienegas basin (CCB) is a biodiversity reservoir within the Chihuahuan desert that includes several water systems subject to marked seasonality. While several studies have focused on biodiversity inventories, this is the first study that describes seasonal changes in diversity within the basin. We sampled Pseudomonas populations from a seasonally variable water system at four different sampling dates (August 2003, January 2004, January 2005, and August 2005). A total of 70 Pseudomonas isolates across seasons were obtained, genotyped by fingerprinting (BOX-PCR), and taxonomically characterized by 16S rDNA sequencing. We found 35 unique genotypes, and two numerically dominant lineages (16S rDNA sequences) that made up 64% of the sample: P. cuatrocienegasensis and P. otitidis. We did not recover genotypes across seasons, but lineages reoccurred across seasons; P. cuatrocienegasensis was isolated exclusively in winter, while P. otitidis was only recovered in summer. We statistically show that taxonomic identity of isolates is not independent of the sampling season, and that winter and summer populations are different. In addition to the genetic description of populations, we show exploratory measures of growth rates at different temperatures, suggesting physiological differences between populations. Altogether, the results indicate seasonal changes in diversity of free-living aquatic Pseudomonas populations from CCB

In silico transitions to multicellularity

The emergence of multicellularity and developmental programs are among the major problems of evolutionary biology. Traditionally, research in this area has been based on the combination of data analysis and experimental work on one hand and theoretical approximations on the other. A third possibility is provided by computer simulation models, which allow to both simulate reality and explore alternative possibilities. These in silico models offer a powerful window to the possible and the actual by means of modeling how virtual cells and groups of cells can evolve complex interactions beyond a set of isolated entities. Here we present several examples of such models, each one illustrating the potential for artificial modeling of the transition to multicellularity.Comment: 21 pages, 10 figures. Book chapter of Evolutionary transitions to multicellular life (Springer

The complex hybrid origins of the root knot nematodes revealed through comparative genomics

Meloidogyne root knot nematodes (RKN) can infect most of the world's agricultural crop species and are among the most important of all plant pathogens. As yet however we have little understanding of their origins or the genomic basis of their extreme polyphagy. The most damaging pathogens reproduce by mitotic parthenogenesis and are suggested to originate by interspecific hybridizations between unknown parental taxa. We sequenced the genome of the diploid meiotic parthenogen Meloidogyne floridensis, and use a comparative genomic approach to test the hypothesis that it was involved in the hybrid origin of the tropical mitotic parthenogen M. incognita. Phylogenomic analysis of gene families from M. floridensis, M. incognita and an outgroup species M. hapla was used to trace the evolutionary history of these species' genomes, demonstrating that M. floridensis was one of the parental species in the hybrid origins of M. incognita. Analysis of the M. floridensis genome revealed many gene loci present in divergent copies, as they are in M. incognita, indicating that it too had a hybrid origin. The triploid M. incognita is shown to be a complex double-hybrid between M. floridensis and a third, unidentified parent. The agriculturally important RKN have very complex origins involving the mixing of several parental genomes by hybridization and their extreme polyphagy and agricultural success may be related to this hybridization, producing transgressive variation on which natural selection acts. Studying RKN variation via individual marker loci may fail due to the species' convoluted origins, and multi-species population genomics is essential to understand the hybrid diversity and adaptive variation of this important species complex. This comparative genomic analysis provides a compelling example of the importance and complexity of hybridization in generating animal species diversity more generally