Investigating biocomplexity through the agent-based paradigm.

Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex

Biodiversity and Ecosystem Informatics - BDEI - Planning Workshop on Biodiversity and Ecosystem Informatics for the Indian River Lagoon, Florida

This proposal solicits funding to organize and conduct a planning workshop that will establish and facilitate research on the informatics needed to address complex issues of biodiversity and ecosystem processes within the Indian River Lagoon. This workshop will provide the opportunity and resources for collaboration and discussion among scientists from diverse fields of biodiversity, ecological sciences, remote sensing, geographic information systems, computer science and intelligent systems. The topics to be discussed will include investigation of novel computational intelligence techniques for modeling, prediction, analysis and database management of the disparate and complex data for the Indian River Lagoon. The explicit products of the proposed workshop will be a white paper and technical report, a formal research agenda that incorporates informatics into existing and planned research, and preparation of a competitive proposal based on the recommendations and preliminary work defined by the workshop

Predicting Water Availability in the Antarctic Dry Valleys using Geographic Information Systems and Remote Sensing

Water is one of the most important ingredients for life on Earth. The presence or absence of biologically available water determines whether or not life will exist. Antarctica is an environment where abiotic constraints, particularly water, strongly influence the distribution and diversity of biota. As Antarctic biology is relatively simple when compared to more temperate climates, it is a prime location for researching constraints on biodiversity, and what may be the impacts of changes to these constraints resulting from climate change and human disturbance. This research uses Geographic Information Systems (GIS) and remote sensing to develop a relative water availability index of three Dry Valleys in Southern Victoria Land, Antarctica. This study area is being used for the IPY Terrestrial Biocomplexity project, an international collaboration researching the distribution, diversity and complexity of biology in the Dry Valleys. The development of a predictive water availability model will contribute greatly to their research goals. This thesis describes the sources of biologically available water in the Dry Valleys and its interaction with biota. Remotely sensed data of these sources is gathered and various methods of analysing the data are explored. This includes creating a mean snow cover distribution model from MODIS data over 4 summer seasons, and Landsat7 ETM+ surface temperature data. These data sets, combined with a high resolution LIDAR Digital Elevation Model and glacier and lake locations, are then analysed with GIS to produce a Compound Topographic Index (CTI), a model showing the likely accumulation and dispersal of liquid water given the spatial distribution of water sources and the flow of water over the terrain according to the influence of gravity. Visualisation techniques are used to validate the resulting model, including the use of 3D visualisation and comparison of drainage patterns using overlays of a high resolution ALOS image. This research concludes that GIS and remote sensing are valuable tools for predicting water distribution in Antarctica. Although cloud cover, varied illumination and differing spatial resolutions can create limitations, remote sensing's cost effective and environmentally sound method of data capture and the computational and spatial modelling capabilities of GIS make their use well suited to the Antarctic environment

Eurythermalism of a deep-sea symbiosis system from an enzymological aspect

The recently proposed and experimentally validated Equilibrium Model provides the most detailed description of temperature's effect on enzyme catalytic activity to date. By introducing an equilibrium between Eact, the active form of enzyme, and Einact, a reversibly inactivated form of enzyme, the Equilibrium Model explains apparent enzyme activity loss at high temperatures that cannot be accounted for by irreversible thermal denaturation. The Equilibrium Model describes enzyme behavior in the presence of substrates and under assay conditions; thus its associated parameters, deltaHeq and Teq, may have physiological significance. The Equilibrium Model parameters have been determined for twenty-one enzymes of diverse origins. The results demonstrated the wide applicability of the Equilibrium Model to enzymes of different types and temperature affinity. The study has also established deltaHeq as the first quantitative measure of enzyme eurythermalism and demonstrated the relationship between Teq and optimal growth temperature of organisms. The Equilibrium Model is therefore a useful tool for studying enzyme temperature adaptation and its role in adaptations to thermophily and eurythermalism. Moreover, it potentially enables a description of the originating environment from the properties of the enzymes. The Equilibrium Model has been employed to characterize enzymes isolated from bacterial episymbionts of Alvinella pompejana. A. pompejana inhabits one of the most extreme environments known to science and has been proposed as an extremely eurythermal organism. A metagenomic study of the A. pompejana episymbionts has unveiled new information related to the adaptive and metabolic properties of the bacterial consortium; the availability of metagenomic sequences has also enabled targeted retrieval and heterologous expression of A. pompejana episymbiont genes. By inspecting enzymes derived from the unique episymbiotic microbial consortium intimately associated with A. pompejana, the study has shed light on temperature adaptations in this unique symbiotic relationship. The findings suggested that eurythermal enzymes are one of the mechanisms used by the microbial consortium to achieve its adaptations. By combining metagenomic and enzymological studies, the research described in this thesis has lead to insights on the eurythermalism of a complex microbial system from an enzymological aspect. The findings have enhanced our knowledge on how life adapts to extreme environments, and the validation of the Equilibrium Model as a tool for studying enzyme temperature adaptation paves the way for future studies

Monitoring and prediction of natural disasters

The problems of natural disaster predicting and accomplishing a synthesis of environmental monitoring systems to collect, store, and process relevant information for their solution are analyzed. A three-level methodology is proposed for making decisions concerning the natural disaster dynamics. The methodology is based on the assessment of environmental indicators and the use of numerical models of the environment

Small-scale biocomplexity in coastal Atlantic cod supporting a Darwinian perspective on fisheries management

Harvesting of marine resources raises concerns about how to identify and preserve biocomplexity, including the diversity of life histories found within and among wild populations of a species. In order to fully accomplish this, there is a need to elucidate the underlying causes of phenotypic variation, and how this variation responds to environmental changes. In general, both evolutionary (genetic) and nonevolutionary (plastic) responses may occur. Plastic responses to environmental change are expected to shift the phenotype along a reaction norm, while an evolutionary response is expected to shift the reaction norm itself. Here, we assess the maturation patterns of coastal Atlantic cod (Gadus morhua) in Skagerrak, where studies using neutral markers have revealed genetically differentiated populations of this harvested fish within tens of kilometres of coastline. Our results suggest that physiological state prior to the spawning season, as well as juvenile growth, both influence the probability of completing sexual maturation at a given age. Furthermore, our results point towards a spatial structuring of this plasticity (i.e. the maturation reaction norms) comparable with population connectivity inferred from neutral markers. We argue that such fine-scale biocomplexity calls for a Darwinian approach to fisheries management