Biomedical subjects

Brian D Fath

Publications and source records attributed to Brian D Fath.

3 recordsLinked to original sources

PubMed2006

Functional integration of ecological networks through pathway proliferation.

Large-scale structural patterns commonly occur in network models of complex systems including a skewed node degree distribution and small-world topology. These patterns suggest common organizational constraints and similar functional consequences. Here, we investigate a structural pattern termed pathway proliferation. Previous research enumerating pathways that link species determined that as pathway length increases, the number of pathways tends to increase without bound. We hypothesize that this pathway proliferation influences the flow of energy, matter, and information in ecosystems. In this paper, we clarify the pathway proliferation concept, introduce a measure of the node-node proliferation rate, describe factors influencing the rate, and characterize it in 17 large empirical food-webs. During this investigation, we uncovered a modular organization within these systems. Over half of the food-webs were composed of one or more subgroups that were strongly connected internally, but weakly connected to the rest of the system. Further, these modules had distinct proliferation rates. We conclude that pathway proliferation in ecological networks reveals subgroups of species that will be functionally integrated through cyclic indirect effects.

Animals↗

PubMed2004

Ecosystem growth and development.

One of the most important features of biosystems is how they are able to maintain local order (low entropy) within their system boundaries. At the ecosystem scale, this organization can be observed in the thermodynamic parameters that describe it, such that these parameters can be used to track ecosystem growth and development during succession. Thermodynamically, ecosystem growth is the increase of energy throughflow and stored biomass, and ecosystem development is the internal reorganization of these energy mass stores, which affect transfers, transformations, and time lags within the system. Several proposed hypotheses describe thermodynamically the orientation or natural tendency that ecosystems follow during succession, and here, we consider five: minimize specific entropy production, maximize dissipation, maximize exergy storage (includes biomass and information), maximize energy throughflow, and maximize retention time. These thermodynamic orientors were previously all shown to occur to some degree during succession, and here we present a refinement by observing them during different stages of succession. We view ecosystem succession as a series of four growth and development stages: boundary, structural, network, and informational. We demonstrate how each of these ecological thermodynamic orientors behaves during the different growth and development stages, and show that while all apply during some stages only maximizing energy throughflow and maximizing exergy storage are applicable during all four stages. Therefore, we conclude that the movement away from thermodynamic equilibrium, and the subsequent increase in organization during ecosystem growth and development, is a result of system components and configurations that maximize the flux of useful energy and the amount of stored exergy. Empirical data and theoretical models support these conclusions.

Animals↗

PubMed2003

Regime changes in ecological systems: an information theory approach.

We present our efforts at developing an ecological system index using information theory. Specifically, we derive an expression for Fisher Information based on sampling of the system trajectory as it evolves in the space defined by the state variables of the system, i.e. its state space. The Fisher Information index, as we have derived it, is a measure of system order, and captures the characteristic variation in speed and acceleration along the system's periodic steady-state trajectories. When calculated repeatedly over the system period, this index tracks steady states and transient behavior. We believe that such an index could be useful in detecting system 'flips' associated with a regime change, i.e. determining when systems are in a transient between one steady state and another. We illustrate the concepts using model ecosystems.

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