Biodiversity is a concept that plays a key role in both scientific theories such as the species-area law and conservation politics. Currently, however, little agreement exists on how biodiversity should be defined, let alone measured. This has led to suggestions that biodiversity is not a metaphysically robust concept, with major implications for its usefulness in formulating scientific theories and making conservation decisions. A general discussion of biodiversity is presented, highlighting its application both in scientific and conservation contexts, its relationship with environmental ethics, and existing approaches to its measurement. To overcome the limitations of existing biodiversity concepts, a new concept of biocomplexity is proposed. This concept equates the biodiversity of any biological system with its effective complexity. Biocomplexity is shown to be the only feasible measure of biodiversity that captures the essential features desired of a general biodiversity concept. In particular, it is a well-defined, measurable and strongly intrinsic property of any biological system. Finally, the practical application of biocomplexity is discussed.

Biodiversity is a concept that plays a key role in both scientific theories such as the species-area law and conservation politics. Currently, however, little agreement exists on how biodiversity should be defined, let alone measured. This has led to suggestions that biodiversity is not a metaphysically robust concept, with major implications for its usefulness in formulating scientific theories and making conservation decisions. A general discussion of biodiversity is presented, highlighting its application both in scientific and conservation contexts, its relationship with environmental ethics, and existing approaches to its measurement. To overcome the limitations of existing biodiversity concepts, a new concept of biocomplexity is proposed. This concept equates the biodiversity of any biological system with its effective complexity. Biocomplexity is shown to be the only feasible measure of biodiversity that captures the essential features desired of a general biodiversity concept. In particular, it is a well-defined, measurable and strongly intrinsic property of any biological system. Finally, the practical application of biocomplexity is discussed.

Thesis (Ph.D.) - University of St Andrews, May 2009. / Restricted until 29th May 2010.

Thesis (Ph. D.)--Australian National University, 2005. / Title from PDF title page (viewed on Oct. 6, 2006). Thesis is broken up into 12 separate PDF files, plus one PDF file consisting of the entire document. Includes bibliographical references (p. 178-200).

Until very recently, synthetic chemistry has focussed on the creation of chemical entities with desirable properties through the programmed application of isolated chemical reactions, either individually or in a cascade that afford a target compound selectively. By contrast, biological systems operate using a plethora of complex interconnected signaling and metabolic networks with multiple checkpoint controls and feedback loops allowing biological systems to adapt and respond rapidly to external stimuli. Systems chemistry attempts to capture the complexity and emergent phenomena prevalent in the life sciences within a wholly synthetic chemical framework. In this approach, complex phenomena are expressed by a group of synthetic chemical entities designed to interact and react with many partners within the ensemble in programmed ways. In this manner, it should be possible to create synthetic chemical systems whose properties are not simply the linear sum of the attributes of the individual components. Chapter 1 discusses the role of complex networks in various aspects of chemistry- related research from the origin of life to nanotechnology. Further, it introduces the concept of Systems chemistry, giving various examples of dynamic covalent networks, self-replicating systems and molecular logic gates, showing the applications of complex system research. Chapter 2 discusses the components of replicator design. Further, it introduces a network based on recognition mediated reactions that is implemented by length- segregation of the substrates and displays properties of self-sorting. Chapter 3 presents a fully addressable chemical system based on auto- and cross- catalytic properties of product templates. The system is described by Boolean logic operations with different template inputs giving different template outputs. Chapter 4 introduces a dynamic network which fate is determined by a single recognition event. The replicator is capable of exploiting and dominating the exchanging pool of reagents in order to amplify its own formation at the expense of other species through the non-linear kinetics inherent in minimal replication. Chapter 5 focuses on the development of complex dynamic systems from structurally simple molecules. The new approach allows creating multicomponent networks with many reaction pathways operating simultaneously from readily available substrates.

Shallow-water hydrothermal vents occur world-wide in regions of volcanic activity. The vents located at Tutum Bay, Ambitle Island, Papua New Guinea are unique in that the vent fluids and surrounding sediments contain some of the highest concentrations of arsenic in a natural system. This study addresses the effects of the vent system on the benthic communities, focusing on the eukaryotes, macrofauna, meiofauna and bacteria. Samples were collected in November 2003 and May/June 2005. Analysis of the 2003 macrofaunal samples indicated that pH, rather than arsenic was influencing the benthic community, and that the hydrothermal influence occurred at a greater distance than expected. Results of more intensive sampling carried out in 2005 are the primary focus of this dissertation. The pore water and sediment characteristics revealed distinct physical habitats corresponding with distance from the vent. There was a trend of decreasing temperature and arsenic concentration and increasing salinity and pH with distance from the vent. The vent sediment was poorly sorted volcanic gravel, while sediments along the transect showed a gradient from fine, well sorted volcanic sands to coarser carbonate sands farther away. The macrofauna showed a trend of increasing diversity with distance from the vent and similar taxa were present in both the 2003 and 2005 samples. The vent community was dominated by the polychaete Capitella cf. capitata. The inner transect from 30 m to 140 m had low diversity. Dominant taxa included thalassinid shrimp and the amphipod Platyischnopus sp.A. The 180 m to 300 m sites had significantly higher diversity. The Danlum Bay reference site had relatively higher diversity than the nearshore transect sites and was dominated by deposit feeding polychaetes. Macrofaunal community structure was influenced by the sediment characteristics, notably by CaCO3 content, sorting and median grain size. The meiofaunal community also showed changes with distance from the vent. Chromadorid nematodes were dominant at the vent site and were a major component of the meiofauna at most sites, along with copepods. The meiofaunal community at the reference site showed greater similarity to the vent community and both sites had low abundances. Nematodes were more abundant than copepods near the vent, but copepods were more abundant farther offshore and at the reference site. Meiofaunal community structure was influenced primarily by the pore water temperature and salinity. Biological interactions with the macrofaunal community through physical disturbance and predation may also influence the meiofaunal community.  The molecular analysis of eukaryotic and bacterial diversity also revealed changes with distance from the vent. The 0 m and reference sites grouped together due to the presence of fungal sequences and the 140 m and 300 m sites grouped together due to a common molluscan sequence. Metazoans and fungi dominated the eukaryote sequences. The most abundant eukaryotic OTUs included fungi matching Paecilomyces sp. and Cladosporium cladosporioides and metazoans matching Viscosia viscosa (Nematoda) and Astarte castanea represented by 24 phyla and was dominated by Actinobacteria and γ-Proteobacteria. More bacterial phyla were present near the vent, while more overall OTUs were found at the intermediate sites along the transect. The most distant site had much lower diversity dominated by Firmicutes. The macrofaunal community had the strongest correlation with environmental variables. Comparison between the meiofauna and the metazoan sequences showed the proportion of nematodes found in both datasets were comparable, but the meiofauna analysis found a higher proportion of arthropods, while the molecular results were disproportionally high for platyhelminthes. Overall, the vents increased the complexity of the system by creating unique habitats. The extreme environment created by the hydrothermal activity maintained the surrounding habitat at an early successional stage colonized by a few opportunistic species. There was a gradation in the benthic communities away from the vent towards a more carbonate based climax community. The low pH environment had an effect on the sediment composition, which in turn influenced the benthic community. These findings can serve as a model for studying the potential effects of ocean acidification and climate change on benthic communities and marine biocomplexity.

This dissertation is an attempt at establishing a bridge between biology and physics leading naturally from the field of phase transitions in physics to the cooperative nature of living systems. We show that this aim can be realized by supplementing the current field of evolutionary game theory with a new form of self-organized temporal criticality. In the case of ordinary criticality, the units of a system choosing either cooperation or defection under the influence of the choices done by their nearest neighbors, undergo a significant change of behavior when the intensity of social influence has a critical value. At criticality, the behavior of the individual units is correlated with that of all other units, in addition to the behavior of the nearest neighbors. The spontaneous transition to criticality of this work is realized as follows: the units change their behavior (defection or cooperation) under the social influence of their nearest neighbors and update the intensity of their social influence spontaneously by the feedback they get from the payoffs of the game (environment). If units, which are selfish, get higher benefit with respect to their previous play, they increase their interest to interact with other units and vice versa. Doing this, the behavior of single units and the whole system spontaneously evolve towards criticality, thereby realizing a global behavior favoring cooperation. In the case when the interacting units are oscillators with their own periodicity, homeodynamics concerns, the individual payoff is the synchronization with the nearest neighbors (i.e., lowering the energy of the system), the spontaneous transition to criticality generates fluctuations characterized by the joint action of periodicity and crucial events of the same kind as those revealed by the current analysis of the dynamics of the brain. This result is expected to explain the efficiency of enzyme catalyzers, on the basis of a new non-equilibrium statistical physics. We argue that the results obtained apply to sociological and psychological systems as well as to elementary biological systems.

The following thesis presents a computational framework that can capture inherently non-linear and emergent biocomplex phenomena. The main motivation behind the investigations undertaken was the absence of a suitable platform that can simulate, both the continuous features as well as the discrete, interaction-based dynamics of a given biological system, or in short, dynamic reciprocity. In order to determine the most powerful approach to achieve this, the efficacy of two modelling paradigms, transport phenomena as well as agent-based, was evaluated and eventually combined. Computational Fluid Dynamics (CFD) was utilised to investigate optimal boundary conditions, in terms of meeting cellular glucose consumption requirements and exposure to physiologically relevant shear fields, that would support mesenchymal stem cell growth in a 3-dimensional culture maintained in a commercially available bioreactor. In addition to validating the default bioreactor configuration and operational parameter ranges as suitable towards sustaining stem cell growth, the investigation underscored the effectiveness of CFD as a design tool. However, due to the homogeneity assumption, an untenable assumption for most biological systems, CFD often encounters difficulties in simulating the interaction-reliant evolution of cellular systems. Therefore, the efficacy of the agent-based approach was evaluated by simulating a morphogenetic event: development of in vitro osteogenic nodule. The novel model replicated most aspects observed in vitro, which included: spatial arrangement of relevant players inside the nodule, interaction-based development of the osteogenic nodules, and the dependence of nodule growth on its size. The model was subsequently applied to interrogate the various competing hypotheses on this process and identify the one that best captures transformation of osteoblasts into osteocytes, a subject of great conjecture. The results from this investigation annulled one of the competing hypotheses, which purported the slow-down in the rate of matrix deposition by certain osteoblasts, and also suggested the acquisition of polarity to be a non-random event. The agent-based model, however, due to being inherently computationally expensive, cannot be recommended to model bulk phenomena. Therefore, the two approaches were integrated to create a modelling platform that was utilised to capture dynamic reciprocity in a bioreactor. As a part of this investigation, an amended definition of dynamic reciprocity and its computational analogue, dynamic assimilation, were proposed. The multi-paradigm platform was validated by conducting melanoma chemotaxis under foetal bovine serum gradient. Due to its CFD and agent-based modalities, the platform can be employed as both a design optimisation as well as hypothesis testing tool.