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A traditional presupposition in science is that nature ultimately is simple and comprehensible. Accordingly, theory reduction is a primary goal in much of ecosystems science the belief, for example, that ecosystem development can be described by a single covering principle. Recently, however, the theory of complex adaptive systems has challenged th...
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... A corollary to the action of selection pressure is a tendency to reward and support any changes that serve to bring ever more resources into B. Because this circumstance pertains to any and all members of the feedback loop, an autocatalytic cycle becomes, ipso facto, the epicenter of a centripetal pattern of flows upon which resources converge (Fig. 3). Thus, without having to possess any visible integument, an autocatalytic loop can define its own selfhood as the focus of centripetal ...
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... Materially, the global capitalist economy is a complex living system where limited energy and natural resources support agents' activity, similar to ecosystems. We base our theoretical perspective on "process ecology," which emphasizes self-entailing configurations of processes that engender positive feedback or autocatalysis that imparts structure and regularity to ecosystems, as opposed to entropic tendencies toward disorganization and decay (Ulanowicz, 1997(Ulanowicz, , 2006(Ulanowicz, , 2009. The concept of autocatalysis offers a comprehensive framework for theorizing on economic growth and development. ...
... Materially, the global capitalist economy is a complex living system where limited energy and natural resources support agents' activity, similar to ecosystems. We base our theoretical perspective on "process ecology," which emphasizes self-entailing configurations of processes that engender positive feedback or autocatalysis that imparts structure and regularity to ecosystems, as opposed to entropic tendencies toward disorganization and decay (Ulanowicz, 1997(Ulanowicz, , 2006(Ulanowicz, , 2009. The concept of autocatalysis offers a comprehensive framework for theorizing on economic growth and development. ...
... The concept of autocatalysis offers a comprehensive framework for theorizing on economic growth and development. First, the autocatalytic dynamics operate with concepts like competition, selection, organization, and efficiency (Ulanowicz, 1997), which can straightforwardly apply to economic contexts (Matutinović, 2020). Second, it explicitly introduces specific negative feedbacks that are instrumental in stabilizing exponential growth resulting from the interplay of positive feedbacks, which is the central theme of this work. ...
We use a simulation model to explore the theoretical impact of technology, recycling, household propensity for material consumption, and nature conservation policies on economic growth and possible stabilization of the global economy within biophysical boundaries. The model dynamics, which arise from the autocatalytic loop between production and household sectors that deplete finite natural resources, qualitatively reproduce historically observed global GDP growth. The simulation results show that a sustainable but unstable steady-state can be reasonably reached only by the simultaneous application of policies that increase nature conservation and promote environmentally efficient technologies, a circular economy, and less-intensive material lifestyles. These policy measures, if realized, would reflect the anticipatory behavior of the human system to prevent future hazards by taking adequate actions in the present. The unstable steady-state suggests long-term sustainability would depend on continuous behavioral, institutional, and policy adjustments rooted in anticipatory behavior.
... In short, ecosystems are inherently unpredictable. This is only stressed from the works of Ulanowicz and the phenomenological behaviour based on diversity and importance of flows (Ulanowicz, 1986(Ulanowicz, , 1997(Ulanowicz, , 2006(Ulanowicz, , 2009. ...
Complexity in ecology arises not merely from number of components and the direct interactions - such as flows - between them alone. We may talk transactions in general and consider that they may be both material and immaterial in character. Our concerns here simply will be of the latter kind. Ecological sciences of today have troubles in coming together to find ways to address the fact that we do not really understand how to tackle the issues treated under the term of complexity and how properties arise. At the same time biological system at all levels of hierarchy are ontic open, which means that the number of possible combinations of their components at any level reaches numbers that exceeds what can possibly be realized in time or space even if considering the total number of particles in the universe. This means that the very character of this sort of complexity alone provides a feature that ensure development and evolution that at low level of hierarchy is entirely random, indeterminate and non-directional (Nielsen and Ulanowicz, 2011. Ecological Modelling, 222, 2908) but simply inherent in a heterogenous system together with its extrinsic relations in terms of hierarchical organisation, thermodynamics and informational dependencies (Nielsen, 2000. Ecol. Modelling, 135: 279; Nielsen, 2007. Ecol. Complexity, 4, 93; Nielsen, 2009. Cybern. Hum. Knowing, 16, (1-2), 27). At higher levels of hierarchy biological systems are still ontic open but are met with different and increasingly stronger, more specific constrains. Biological systems are not only formed and shaped by constraints from the inside-outward but external constrains are also imposed by imperatives set by the surrounding environment. Thus they are not truly autonomous but are rather systems that receives a strong influence of outside-inward gradients what can be considered a downward causation. A great part of realisation and more important the cybernetics of these forms of existence involves transfer and decoding of information and in the end that the system exhibit adequate responses to a given situation. Such phenomena are widely known as biosemiotics processes. The same is valid to ecosystems as long as we consider conditions that allow us to interpret them as embedded forms. For some other focal levels - like that of population - the semiotics seems to take over a great deal of the cybernetics, but due to the autonomous part of the steering we have to deal with these systems within a framework of seconder order cybernetics. As we move up ro another form of hierarchy - namely that of more and more advanced organisms - it seem that the semiotics adds up to yet another type of ontic opennes that involves a second order, cyber-semiotic system (Brier, 1996. Syst. Res., 13, (3), 229; Brier, 2013a. Toronto Studies in Semiotics and Communication. University of Toronto Press, 498 pages). At the uppermost levels we find advanced structural societies, not only the well know examples of ants nests, bee hives but also large scales ecosystems like the Serengeti that seem to be more or less driven by interpretational processes, such as for instance the yearly cycle of wandering of the gnu/wildebeest. It is therefore likely that we need to integrate semiotics in our existing scientific models but only a few modelling approaches if any include this type of transactions in them not to say the possibility to do so. A framework to assist in the development of such type of model is presented.
... Ecosystems are of course ontic open too (Jørgensen et al. 2007). In general, as pointed out by Ulanowicz, it takes no more for a system than to be composed of around 75 distinguishable components (or tokens) for it to be ontic open (Ulanowicz 2006). It is quite a task to analyze and fully understand an ecosystem. ...
The heterogenic character of biological systems has as a consequence that calculations of their possible combinatorial constellations very soon run into numerical explosions. This means, that the resulting numbers—so-called immense numbers—exhibit orders of magnitude beyond any physical meaning. Such a high number of possibilities cause another property—named ontic openness by the physicist W. M. Elsasser—to emerge within such systems. All biological systems possess the feature of being ontic open and this is of great importance to evolution, as ontic openness not only guarantees a development of the system to take place, but also interferes with our chances to fully comprehend this evolutionary processes sensu lato. Thus ontic openness implies an extremely high level of uncertainty and unpredictability. On the one hand, we have a certainty that “something” is bound to happen within the system—on the other hand, we can be totally sure that we will never be able to forecast exactly whatever that “something” will be. At lower levels of biological hierarchy, e.g., the molecular level represented by molecules like DNA, RNA, and proteins, ontic openness seems pretty easy to comprehend. When it comes to more aggregate and even conglomerate systems, i.e., at higher levels of biological hierarchy, the emergence as well as the expression of this property becomes increasingly obscure. Although definitely present, the property at superior levels tends to be overlooked or neglected. Although the calculations may take different forms—and in spite of finding different causes—the property penetrates through all levels of biological hierarchy. To prevent systems from ending up in a situation where the evolutionary state described by calculations that are incomprehensible or even intractable constraints of the systems are needed. From the different levels some systematic patterns seem to be recognizable. Whereas lower levels find causes inside–upwards to be dominating, at upper levels causes become dominated by outside–inwards interactions. Eventually, the ontic openness is likely to be limited not only by physical dimensions but is also constrained by downward acting factors. One reason for this is that space and time scales are well-known to be tightly coupled throughout the biological hierarchy—smaller scales have fast reaction rates as opposed to large scale with slower functions. Thus, space and time scales become important to the realization of ontic openness. At the same time, a shift occurs that stresses information exchange and treatment together with cognitive processes to be increasingly dominant in the biosemiotics of the ongoing processes. The whole leads to a shift from dominance of objective factors to more subjective ones in the process of evolution. Viewing evolutionary systems as ontic openness systems and pursuing the constraints influencing them may turn out to be a fruitful strategy to the investigation of all developmental processes.
... In fact, the legitimity of discussions around teleology aspects of nature disappeared from Western Science with the decline and submission of the Hellenist society. The philosophical views of Greek philosophers such as Aristotle involved final goals which made up an essential metaphysical part of his four forms of causality (for a discussion on this see for instance Ulanowicz, 2006). This has partly been due to the almost total dominance of Christianity and its various adjacent creeds in Europe. ...
... Both the concept and the argumentation around it have been further developed over the years. A condensed presentation of the evolution of the ascendency concept may be found in three books by Ulanowicz (1986Ulanowicz ( , 1997Ulanowicz ( , 2006 see also Patricio et al. (2004). ...
For more than two millenniums it has been almost impossible to address the issue of teleology in Western world science. Meanwhile, after the introduction of a systems view in ecology it has been clearly demonstrated that when attempting to understand nature as ecosystems, we deal with structures organized in a hierarchy and with a very high complexity. Many unexpected properties emerge from the constituent components and the interactions among them. The processes result in an intricate behaviour that can only be understood and explained within the realm of some degree of goal oriented behaviour of the systems. The use of the term goal function proper implies that a full teleological perspective is included in our perception of the systems. However, lately we have tended use more vague concepts like orientors and indicators. This paper argues that such a division makes sense, only we need in the future to be more clear and consistent in our use of the concepts. The term goal functions should be reserved to functions that are given final extremum states alone. Orientors should be used for localized directional behaviour in time and space. Indicators should be used where isolated time/space information exists. It may be used for monitoring changes in systems without giving any directional cause to development. The exact role among the concepts of being either a goal function, orientor or indicator is not always clearly defined. In many cases because the concepts are often used outside their original domains. Three types of original domains are clearly distinguishable, a biotic, a network and a thermodynamical direction. The strengths and weaknesses within the areas are discussed. Biotic concepts share the advantage of being close to established biological views and traditional ecology. They tell little about functionality, directionality and consequences of interactions. This is opposed to the two other directions that find their background in network analysis, information theory, and various domains of thermodynamics. As derived from physics the latter two areas achieve some scientific credibility, but suffer from problems of definition already inherent in the scientific sub-disciplines. Concerning the acceptance of ecosystem theory to ecologists it is also clear that approaches close to traditional biology such as the energetics of eco-physiology and diversity are much more accepted than any of the others leading to an overwhelming number of isolated and non-aggregated indices in the area of indicators. Indices that demand multidisciplinary insights such as goal functions and orientors are found to be less popular and deserve to receive much more attention in the future.
... Each response behaviour is a singularity, a unique behavioural trajectory, shaped by the contingencies of circumstances (Bernstein, 1967). A response outcome does not distinguish an organism from its environment, however, because the organism's surroundings are entwined with the production of the response, its functionality, and consequences (Ulanowicz, 2006). A measurement outcome that could distinguish an organism from its surroundings would be additive effects of crossed environmental factors, as in multifactorial ANOVA, indicating that effects of environmental factors are independent of the organism's history (cf. ...
Observations of ultrafast cognition in human performance challenge intuitive information processing and computation metaphors of cognitive processing. Instances of ultrafast cognition are marked by ultrafast response times of reliable, accurate responses to a relatively complex stimulus. Ultrafast means response times that are as fast as a single feedforward burst of activity across the nervous system connecting eye to hand. Thus the information processing and computation metaphors in question are those in which some amount of time is required to decide and initiate a response, over and above the minimum time required, physiologically, for the eye-hand chain of action potentials—these are metaphors in which the brain does work that has a measurable duration in time. Ultrafast cognition can be explained by synergies spanning the mind and body. Synergies are temporary dynamical structures that anticipate context-appropriate behaviour. An anticipatory state poises the mind and body in symmetry among equivalent options for behaviour, and only a minimal change in context, favouring one option over any other, is sufficient to break symmetry and enact an ultrafast cognitive response
... He also has argued strongly for a non-mechanistic approach to life science and suggests that " process ecology " provides a better basis for a paradigm of science than Newtonian mechanics or even Darwinian evolutionary theory. His process ecology (Ulanowicz, 2006: Taken as a whole, his work forms an " ecological metaphysic " (Ulanowicz, 1999) that he sees as general and robust enough to be valid for many scientific fields even beyond ecology. His parsimonious ecological metaphysic is based on three main tenets (Ulanowicz, 2009): 1) systems are vulnerable to disruption by chance events, 2) a process, mediated by other processes, is capable of influencing itself, and 3) systems have different histories, and some aspects of unique histories are recorded in material configurations. ...
We present a conceptual synthesis to address the global ecological crisis. The current paradigm underlying life science appears insufficient to enable a solution to the crisis and may be part of the cause of the crisis. We develop a distinct "sustained life" to complement the current paradigm based solely on "discrete life". We present a three-model, multi-scale characterization of the original and fundamental nature of life. The multi-model, expressed as a hyperset formalism, is: life = {environment{ecosystems{organisms{environment}}}} This self-referential, closed loop hierarchy explicitly prohibits fragmentation of sub-units of life and prohibits separation of life from its essential environmental life support context. We integrate work of 1) Ulanowicz and Patten, 2) Rosen amd Kercel and 3) Lovelock and Vernadsky who developed holistic characterizations of life at ecosystemic, organismic and biospheric organization levels, respectively. This paradigm could enable actualization of a mutualistic win-win relation between humans and environment and long-term environmental sustainability.
... On the one hand they are not simple, low-numbered, enough, and not complex, high-numbered enough, to be reduced to simple equations, for example, through Newtonian or statistical mechanics, respectively. Recently, it has been argued that ecosystems with only 75 components or slightly more easily will reach a number of combinatorial possibilities that exceeds 10 100 (Googol) which in short means that unpredictability (emergence), surprise and uniqueness should be expected to dominate in these systems (Ulanowicz, 2006). ...
The final decades of the last century saw the introduction of several new ways of thinking about biology, and ecology in particular. Firstly, through the development of non-equilibrium thermodynamics it was suggested that it is possible to understand and interpret biological systems and phenomena within a thermodynamic framework. This view has been extended to the ecosystem level and has been applied to a wide range of ecosystems. The view is considered a more useful way of presenting the energetic balances of biological systems than the various forms of 1st Law analysis normally carried out in ecology. This is in spite of the fact that approaches using like doing 2nd Law analysis for instance, will inevitably run into problems of definition as well as epistemology.due to various concepts, for example, entropy, not having a strict definition in domains removed as far from equilibrium as biological systems. Secondly, hierarchical thinking has found widespread use in the fields of biology and ecology. The hierarchical arrangement is a construct and hence often phenomenologically based and epistemological rather than ontological in nature. Thus, it is highly dependent on subjective views. An important problem arises from this, as controversies with the science of theoretical ecology often use arguments from hierarchical constructs that are of a quite different ontological nature. The statements of this paper are based on hierarchies that are physically embedded in each other. Merging thermodynamic and hierarchical views, putting the ecosystem, or any biological system for that matter, with its components at the focal level makes it possible to de-construct the systems and create a connection to the four Aristotelian causes: material cause refers to system components, efficient cause to internal interactions, flows as well as other semiotic processes, and formal cause to its relationship to the immediate environment. Final cause is seen as the function of the whole. A whole that has to obey the 2nd Law, and at the same time make the system survive and grow under far-from-equilibrium conditions. Interpreted in this manner the thermodynamic relationship to the surroundings at least comes to act as weak downward causation of the system. This is considered to be an important exterior constrain on the emergence of first biological structures, as well as evolution, and the existence of life. At the same time, thermodynamic efficiency and a continuous evaluation of the system on the basis of this efficiency--at any time considering the interior and exterior constraints on the system--provides a materialist explanation, i.e. building on physically existing, ontological units, of the Aristotelian final cause or telos of the system and how it can explain ecosystem behavior.
A New Ecology presents an ecosystem theory based on the following ecosystem properties: physical openness, ontic openness, directionality, connectivity, a complex dynamic for growth and development, and a complex dynamic response to disturbances. Each of these properties is developed in detail to show that these basic and characteristic properties can be applied to explain a wide spectrum of ecological obsevations and convections. It is also shown that the properties have application for environmental management and for assessment of ecosystem health. * Demonstrates an ecosystem theory that can be applied to explain ecological observations and rules * Presents an ecosystem theory based upon a systems approach * Discusses an ecosystem theory that is based on a few basic properties that are characteristic for ecosystmes.
Decades of research and discussion have shown that the human population growth and our increased consumption of natural resources cannot continue - there are limits to growth. This volume demonstrates how we might modify and revise our economic systems using nature as a model. The book describes how nature uses three growth forms: biomass, information, and networks, resulting in improved overall ecosystem functioning and co-development. As biomass growth is limited by available resources, nature uses the two other growth forms to achieve higher resource use efficiency. Through a universal application of the three 'R's: reduce, reuse, and recycle, nature thus shows us a way forward towards better solutions. However, our current approach, dominated by short-term economic thinking, inhibits full utilization of the three 'R's and other successful approaches from nature. Building on ecological principles, the authors present a global model and futures scenario analyses which show that implementation of the proposed changes will lead to a win-win situation. In other words, we can learn from nature how to develop a society that can flourish within the limits to growth with better conditions for prosperity and well-being. © 2015 Sven Erik Jørgensen, Brian D. Fath, Søren Nors Nielsen, Federico Pulselli, Daniel A. Fiscus and Simone Bastianoni. All rights reserved.
Ecosystem services are usually interpreted as a free of charge “favour” provided to us and our society by nature. In other words, nature supplies us with a functionality that we would otherwise have to pay for. Our cost would be to provide resources either (1) to ensure the necessary inputs to drive our society, or (2) to assist in counteracting, absorbing or remediating unwanted effects that are results of our societal activities. Through ecosystem studies it has been found that a substantial part of the functionality of nature is laid out in all types of components—the compartments of the ecosystems together with the transactional interrelations (flows) and controls between them. Eventually, many so-called indicators have been proposed during the last decades. Such measures are dedicated to tell us about the quality side of ecosystem functionality, e.g. to tell us how well the system performs relatively to a theoretical maximum efficiency possible. As an additional hypothesis, such functions are thought to orient the systems and thus increase through time development, i.e. to be optimised under the given the constraints, through the evolution of the system. Recently is has been pointed out that natural and societal systems share the feature of being complex in their organisation. Meanwhile, it was remarked that societal systems in many ways evolved in opposite direction of how natural evolution would drive an ecosystem. Many philosophers of biology have stated that biological systems posses information and memory functions which improve their long-term capability to survive. This information is believed to be contained in the organisational structures of the system as much as in its gene pool. If we accept such arguments it means that studies of organisation and function of natural systems will provide us with another type of ecosystem services. This would namely give us information about in what direction to drive society in order to achieve a more sustainable system.This paper discusses what measures derived from modern ecosystem theory can possibly be used to study and compare the functionality of the two types of systems. The discussion takes an entrance point in two graphs—one that represents a natural system and one of a socio-economic system. The systems possess similar levels of complexity in terms of number of compartments whereas their connectivities do differ in quantity and quality. The differences between the systems are compared from both a network and a thermodynamic perspective. Indications of the best available options that we have at present, will help to increase our knowledge about and understanding of the systems given. As a main conclusion it is possible to view and treat our society as an ecosystem. This means that it is possible to apply the same measures (indicators) that we use in ecological theory. The idea to use these features is so clear, obvious and at the same time cheap that this option necessarily has to be tried out. It seems a bit surprising that we – from a “natural science point-of-view” – to a certain extent understand natural systems better than socio-economic ones. One major reason is that the latter type includes a large set of regulatory mechanisms that are exerted on a subjective basis as opposed to natural systems. As a consequence societal systems become much more difficult to evaluate, forecast and regulate than ecosystems.
