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  • 1
    Language: English
    In: Ecological Modelling, 2004, Vol.174(1), pp.25-35
    Description: Ecological indices are used to provide summary information about a particular aspect of ecosystem behavior. Many such indices have been proposed and here we investigate two: exergy and Fisher Information. Exergy, a thermodynamically based index, is a measure of the maximum amount of useable work that can be extracted when a system is brought into equilibrium with a reference state. The measure for exergy used herein, also includes a factor to weigh the “complexity” of the ecological species. Fisher Information is an old statistical measure that has recently been applied as a way to detect change in system regime and as a measure of system order. These two indices are compared on a 10-compartment food web model undergoing five different perturbation scenarios. This food web model, although simple, allows for some interesting insight into the two indices. The results show that generally, although not always, exergy and Fisher Information respond differently, such that when one increases due to a perturbation the other decreases and vice versa. We provide a discussion as to the usefulness of these metrics as ecological indices and as their potential use as ecological goal functions in light of these findings.
    Keywords: Ecological Indices ; Ecological Goal Functions ; Ecological Modeling ; Exergy ; Fisher Information ; Food Webs ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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  • 2
    Language: English
    In: Journal of Theoretical Biology, 2003, Vol.222(4), pp.517-530
    Description: 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.
    Keywords: Fisher Information ; Information Theory ; Predator–Prey Models ; Ecological Models ; Biology
    ISSN: 0022-5193
    E-ISSN: 1095-8541
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  • 3
    Language: English
    In: Fluid Phase Equilibria, 2002, Vol.194, pp.3-14
    Description: While there is tremendous interest in sustainability, a fundamental theory of sustainability does not exist. We present our efforts at constructing a theory from Information Theory and Ecological Models. We discuss the state of complex systems that incorporate ecological and other components in terms of dynamic behavior in a phase space defined by the system state variables. From sampling the system trajectory, a distribution function for the probability of observing the system in a given state is constructed, and an expression for the Fisher information is derived. Fisher information is the maximum amount of information available from a set of observations, in this case, states of the system. Fisher information is a function of the variability of the observations such that low variability leads to high Fisher information and high variability leads to low Fisher information. Systems in stable dynamic states have constant Fisher information. Systems losing organization migrate toward higher variability and lose Fisher information. Self-organizing systems decrease their variability and acquire Fisher information. These considerations lead us to propose a sustainability hypothesis: “sustainable systems do not lose or gain Fisher information over time.” We illustrate these concepts using simulated ecological systems in stable and unstable states, and we discuss the underlying dynamics.
    Keywords: Fisher Information ; Information Theory ; Predator–Prey Models ; Sustainability ; Ecological Models ; Engineering ; Chemistry
    ISSN: 0378-3812
    E-ISSN: 1879-0224
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  • 4
    Language: English
    In: Energy, 2005, Vol.30(8), pp.1221-1231
    Description: We explore the use of Fisher Information as a basis for an index of sustainability. Sustainability of an ecosystem refers to the robustness of a preferred dynamic regime to human and natural disturbances. Ecosystems under perturbations of varying regularity and intensity can either remain within the current regime or transition into the neighbourhood of a regime with different (viz. less desirable) characteristics. The Fisher Information index we develop is based on the probability of finding the system in a particular state. We apply the index to a 10-compartment food web model with five functional groups: detritus, primary producers, herbivores, carnivores, and an omnivore. Fisher Information is shown to be sensitive to transients in model generated data. Such transients can be indicative of a transition to a new dynamic regime. Early detection of transitions to undesirable regimes may permit management intervention.
    Keywords: Environmental Sciences ; Economics
    ISSN: 0360-5442
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  • 5
    Language: English
    Description: All organisms alter their surroundings, and humans now have the ability to affect environments at increasingly larger temporal and spatial scales. Indeed, mechanical and engineering advances of the twentieth century greatly enhanced the scale of human activities. Among these are the use and redistribution of natural resources. Unfortunately, these activities can have unexpected and unintended consequences. Environmental systems often respond to these activities with diminished or lost capacity of natural function. Fortunately, environmental management can play an important role in ameliorating these negative effects. The aim is to promote sustainable development, i.e., enrichment of the lives of the majority of people without seriously degrading the diversity and richness of the environment. However, the management tools themselves often fall prey to the same narrow levels of perspective that generated the negative conditions. The challenge is to develop a system-level index, one that indicates the organization and direction of ecological system dynamics. This index could detect when the system is changing its configuration to a new, perhaps less desirable, dynamic regime and may be incorporated into a sustainable management plan for the system. In this chapter, we demonstrate the use of Fisher information (FI) as such an environmental system index.
    Keywords: Computer Science ; Information Systems Applications (Incl.Internet) ; Models and Principles ; Data Structures, Cryptology and Information Theory ; Pattern Recognition ; Computer Appl. in Social and Behavioral Sciences ; Probability and Statistics in Computer Science ; Engineering ; Computer Science
    ISBN: 9781846285066
    ISBN: 1846285062
    Source: SpringerLink Books
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