Systems develop structure i. The example of neural networks offers a good explanation of this principle: neural networks are chemically-connected or functionally-associated neurons. The interconnections between these neurons are called synapses. Over time, certain pathways are established in the brain, meaning that some of the synapses are reinforced through impulses, whereas others die off. This implies that a fairly undifferentiated brain develops structure or consciousness over time Cilliers, It therefore seems that, whilst self-organisation is a necessary condition for emergence, it is not sufficient.
As such, anyone working with complex systems must take note of and try to formulate answers to the following questions pertaining to the nature of emergence4: Does our notion of emergence depend on the nature of the system under study? How should emergence be defined and are ideas such as irreducibility, unpredictability, conceptual novelty, ontological novelty, and supervenience necessary for understanding emergence? What categories of entities can be emergent: properties, substances, processes, phenomena, patterns, laws, or something else?
Is emergence an objective feature of the world, or is it merely in the eye of the beholder? What is the scope of actual emergent phenomena? Does the emergence imply or require the existence of new levels of phenomena? Compounding the issue further is the fact that complex systems are open systems. Unlike isolated systems, the intelligibility of open systems can only be understood in terms of their relation with the environment. This is because our identities develop over time within a network of relationships with other identities.
As such, who I become i. Regardless of the system under study, we can say that, methodologically-speaking, it is very difficult to study open systems. This is because the environment is simultaneously intimate and foreign: it is both part of the system in that we reproduce the system-environment distinction when we model and remains exterior to the system Morin, In other words, the environment cannot be appropriated by the system. This means that the boundary between a system and its environment should be treated both as a real, physical category, and a mental category or ideal model Morin, It is not the case that simple systems suddenly start showing emergent behaviour.
As soon as dynamic and complex interactions between systemic components exist, systems start developing structures. However, complexity is also not an additive process, since the interactions between components are non-linear and allow for surprising reconfigurations of systemic structures.
In this regard, an engine serves as an example of a complicated system Cilliers, Restricted complexity is premised on the belief that complex systems are merely complicated systems; and that, with enough hard work, we can get to the underlying principles that govern these systems. Admittedly, the distinction between complicated and complex systems is often undermined in practice by powerful new technologies, where complex phenomena turn out on further inspection to be merely complicated. However, despite the fact that this distinction cannot be drawn in an unproblematic fashion, it nevertheless remains a useful analytical tool, as it determines whether the study of complexity constitutes a search for rules, or whether it constitutes an engagement with both complexity and the implications that arise from complexity.
Modelling complexity is partly a normative exercise We cannot understand phenomena in their full complexity, and therefore modelling is a necessary condition for creating meaning. In terms of restricted complexity, modelling complexity remains a purely descriptive task, in that the goal is to describe preferably in mathematical terms the principles and rules that underlie complex systems.
In terms of general complexity, modelling necessarily involves a normative component, as we must make choices, judgements, and assumptions when deciding on the factors that are relevant in modelling complex systems. It is precisely because we cannot escape the realm of choice that complexity involves ethics and often also politics! The point is that we must apply our complexity reduction assumptions honestly. However, a problem arises when weak reductionism i. We must take responsibility for the consequences that arise from our models If our models do not correspond with reality, and if they are the outcomes of certain choices, then we must also take responsibility for both the intended and unintended consequences that arise from our modelling strategies.
As scientists, the critical attitude therefore also lies in acknowledging that: There is no science of science, and even the science of science would be insufficient if it did not include epistemological problems. Science is a tumultuous building site, science is a process that could not be programmed in advance, because one can never program what one will find, since the characteristic of a discovery is in its unexpectedness. This uncontrolled process has led today to the development of potentialities of destruction and manipulation, which must bring the introduction into science of a double conscience: a conscience of itself and an ethical conscience Morin, 21; my italics.
Science cannot be practiced in a vacuum, since our scientific practices are intricately connected with other aspects of our lives. Given the myriad crises that we face today, it is no longer viable to separate disciplines, cognitive difficulties, and challenges from one another.
We have a moral obligation to account for the consequences that arise from our practices; and, if need be, to take corrective action. Although this article does not provide practical guidance on how to model complex systems within a systems engineering environment, it does seek to focus attention on the general features of complex systems that should be considered when modelling, as well as on the ethical implications that arise when we model complex phenomena. Above all, a serious engagement with complexity implies that we should be critical of the reach of our claims, practice science modestly and vigilantly, and avoid falling in love with our models!
Bedau, M. Bak, P. New York: Oxford University Press. Chu, D. Cilliers, P. London: Routledge. Langton, C. Mahwah: Erlbaum, — Damon, William, and Daniel Hart. Self-Understanding in Childhood and Adolescence. Davey, Brian A. Introduction to Lattice and Order. De Beer, Carel S. Amsterdam: Chandos Publishing. Deacon, Terrence. London: Penguin Press. Dilthey, Wilhelm. Oxford: Princeton University Press. Donald, Merlin. New York: Norton. Dousa, Thomas M. Cutter and E. Richardson: Its Nature and Limits. Bielefeld: Transcript. Egan, Kieran. Chicago: University of Chicago Press. Elias, Norbert. Oxford: Blackwell.
Boston: Integral Books. Farradane, Jason. Feibleman, James K. Feinberg, Todd E. Fenzl, Norbert et al. Berlin: VCH, — Fischer, Kurt W. Forsche, Joachim B. Meisenheim am Glan: Hain. Foskett, Douglas J. Foskett and Bernard I. Palmer, — Fowler, James W. Gnoli, Claudio. Part 2: Types and Levels. Gnoli, Claudio, and Roberto Poli. Gnoli, Claudio, and Riccardo Ridi. Graves, Clare W. Greenberg, Gary.
Greenberg, Gary, and G. Greenberg, Gary, et al. Guizzardi, Giancarlo. Berlin, Heidelberg: Springer, 94— Moral Consciousness and Communicative Action. Cambridge: MIT Press. Hallpike, Christopher R. Milton Keynes: AuthorHouse. Hartmann, Nicolai. Berlin: De Gruyter. Hegel, Georg W. Encyclopaedia of the Philosophical Sciences.
Herre, Heinrich. Greenwood Village: Libraries Unlimited, — Huckaby, Sarah A. Jacob, Elin K. Howarth, and Nancy J. Jantsch, Erich. Oxford, New York: Pergamon Press. Jolley, John L. London: Duckworth. Kegan, Robert. Cambridge, London: Harvard University Press. King, Patricia M. San Francisco: Jossey-Bass. Kleineberg, Michael. Berlin, Boston: De Gruyter, 81— Kohlberg, Lawrence, and Richard H. Kramer, Deidre A. Sinnott, Fracis A. Richards, and Cheryl Armon. Westport, London: Praeger, — Kuhn, Thomas S. Chicago, London: University of Chicago Press.
Kummer, Christian. Kyle, Barbara R. London: The Library Association, 11— Lamarck, Jean-Baptiste. London: Macmillan. Langridge, Derek W. Classification and Indexing in the Humanities. London: Butterworths. Leibniz, Gottfried W. Edinburgh: Edinburgh University Press. Leontiev, Alexei N. Pacifica: Marxist Internet Archive, 27— LePan, Don. Houndsmill, London: Macmillan. Linnaeus, Carl. Stockholm: Laurentii Salvi. Lobo, Ingrid. Loevinger, Jane.
Mahwah: Erlbaum, 33— Lorenz, Konrad. New York, London: Harvest. Lovejoy, Arthur O. Luria, Alexander R. Mai, Jens-Erik.
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Mannheim, Karl. Structures of Thinking. Collected Works of Karl Mannheim , Vol. London: Routledge.
Maslow, Abraham H. Mithen, Steven. London: Phoenix. Morgan, C. Emergent Evolution. The Gifford Lectures. London: Williams and Norgate. Mortimer, Eduardo F. Mortimer and Charbel N. Dordrecht: Springer, 3— Needham, Joseph. Oxford: Clarendon Press. Neumann, Erich. The Origins and History of Consciousness. Princeton: Princeton University Press. Nicolescu, Basarab. Nolan, Patrick, and Gerhard Lenski. Human Societies. An Introduction to Macrosociology. Novikoff, Alex B. Oesterdiekhoff, Georg W. Olson, Hope A. Oppenheimer, Paul, and Hilary Putnam. Minneapolis: University of Minnesota Press, 3— Overton, Willis F.
Lerner and William Damon. Hoboken: Wiley, 18— Parker, Sue T. Russon, Kim A. Bard, and Sue T. Cambridge: Cambridge University Press, — Parsons, Michael J. Perry, William G. Piaget, Jean. Edited by Howard E. Gruber and J. New York: Basic Books. Pisula, Wojciech. Boca Raton: Brown Walker Press. Epistles , 1— Poli, Roberto. Priss, Uta. Washington, D. Medford: Information Today, 53— Pseudo-Dionysius the Aeropagite. Mahwah: Paulist, — Quilley, Stephen. Rajasurya et al. Ranganathan, Shiyali R.
Prolegomena to Library Classification. London: Asia Publihsing House. Reiser, Oliver L. Boston: Porter Sargent. Richardson, Ernest C. Classification: Theoretical and Practical. New York: Scribner. Richmond, Phyllis A. Copenhagen: Munksgaard, 39— Robinson, Lyn, and Mike Maguire. Roetz, Heiner. Rowe, J. Sahlins, Marshall D.
Evolution and Culture. Salthe, Stanley N. Geschichte der bibliothekarisch-bibliographischen Klassifikation. Munich: Verlag Dokumentation. Santis, Rodrigo De, and Claudio Gnoli. Schelling, Friedrich W. System of Transcendental Idealism. Charlottesville: University Press of Virgina. Schluchter, Wolfgang. Scrivner, Buford. Selman, Robert L. Smith, Huston. New York: Harper One.
Spencer, Herbert. A System of Synthetic Philosophy, Vol. New York: Appleton. Spiteri, Louise F. Stern, Daniel N. London, New York: Karnac. Steward, Julian H. Urbana, Chicago: University of Illinois Press. Stock, Wolfgang, and Mechthild Stock. Handbook of Information Science. Svenonius, Elaine. The Intellectual Foundation of Information Organization. Szostak, Rick. Interdisciplinary Knowledge Organization. Cham: Springer. Thompson, William I. New York: St. Martins Press. Tobach, Ethel. The T. Schneirla Conference Series, Vol.
Hillsdale, London: Erlbaum, — Tolman, Charles W. Tomasello, Michael. A Natural History of Human Thinking. Tomlinson, Helen. London: The Library Association, 73— London: The Library Association, 29— Torbert, Bill et al. San Francisco: Berrett-Koehler. Trigger, Bruce G. Turiel, Elliot. Vickery, Brian C. Vroman, Leo. Hood, Gary Greenberg, and Ethel Tobach. New York, London: Garland, — Wear, Sarah K.
Adlershot: Ashgate. Werner, Heinz, and Bernhard Kaplan. Wheeler, William M. Emergent Evolution and the Development of Societies. Whitehead, Alfred N. Process and Reality: An Essay in Cosmology. New York: The Free Press. Wilber, Ken. Boston, London: Shambhala, 1— Boston, London: Shambhala, — Wilson, Thomas D.
Wundt, Wilhelm. Wynn, Thomas. Yao, Yiyu. Berlin, Heidelberg: Springer, 31— Comte, Auguste  , 55 : Phenomena 1. Physical 2. Chemical 3. Physiological 4. Social Comte, Auguste  , 20 : Human mind 1. Theological or fictitious 2. Metaphysical or abstract 3. Scientific or positive Spencer, Herbert , 3 : Phenomena 1. Inorganic 2. Organic 3. Super-organic Hobhouse, Leonard T. Pre-intelligence 2. Unconscious readjustment 3. Concrete experience and the practical judgment 4. Conceptual thinking and will 5.
Rational system Richardson, Ernest C. Lifeless 2. Living 3. Human 4. Superhuman Baldwin, James M. Pre-logical 2. Quasi-logical 3. Logical 4. Hyper-logical 5. Extra-logical Alexander, Samuel  , Vol. II: 52, : Entities 1. Space-time 2. Matter 3. Life 4. Mind 5. Deity Morgan, Conwy Lloyd , 27 : Events 1. Matter with psychical correlates 2. Life with psychical correlates 3. Mind with physical correlates Conger, George P. Energies 2. Electrons 3. Atoms 4. Molecules 5.
Astronomical masses, or bodies 6. Solar systems 7. Star clusters 8. Galaxies 9. Universes Conger, George P. Organic compounds 2. Infra-cellular organisms 3. Unicellular organisms 4. Multicellular organisms 5. Plant-and-animal groups 6. Families or tribes 7. Nations 8. Specialized cells 2. Nervous areas 3. Reflex arcs 4. Complex reflexes 5. Instinctive emotional complexes 6. Sentiments 7. Values 8. Personalities Wheeler, William M. Psychological 4.
Social Vygotsky, Lev S. Syncretic 2. Complex pseudoconcept 3. Potential concept 4. True concept Needham, Joseph , 6 : Phenomena 1. Biological 3. Social Bachelard, Gaston  , 15 : Philosophical explanation 1. Animism 2. Realism 3. Positivism 4. Rationalism 5. Complex rationalism 6. Dialectical rationalism Hartmann, Nicolai , : Nature 1.
Matter 2. Life Hartmann, Nicolai  , 46 : Consciousness 1. Spiritless psyche 2. Spiritual personal spirit Novikoff, Alex B. Biological 4. Sociological Novikoff, Alex B. Cells 2. Tissues 3. Organs 4. Organ-systems 5. Organisms 6. Populations Gebser, Jean  , 42 : Consciousness 1.
Archaic 2. Magical 3. Mythical 4. Mental 5. Integral Neumann, Erich  , : Collective consciousness mythology 1. Uroboros 2. Great Mother 3. Dragon fight Piaget, Jean  , —61 : Cognition 1. Sensorimotor 2. Preoperational 3. Concrete operational 4. Formal operational Feibleman, James K. Electrons, protons, neutrons 2. Atoms 3. Molecules 4. Cells 5. Human cultures Feibleman, James K. Physical cause-and-effect 2.
Chemical combination-rearrangement 3. Biological sensitivity-reactivity 4. The first autotrophs in evolutionary history, as cyanobacteria, were unicellular organisms that performed all their specialized functions in a single cell and reproduced through cell division. Three billion years later, modern multicellular plants have evolved specialized organs for all different aspects of their functioning: roots for the uptake of nutrients and water, leaves for photosynthesis, seeds for reproduction, stems for structure, etc. Each of these specialized organs requires resource investment and the allocation of resources among different organs.
Their structure differs greatly between species, representing a set of distinct plant strategies Grime , Westoby Such different resources produced by plants can subsequently be consumed by different groups of consumers which is frequently intended by the plant , forming a starting point for alternative loops Fig. Often, the consumers benefit from the resources and provide specialized services to the plant e.
Therefore, the higher the diversity in the number of resources produced by the plant, the more possible loops exist. Feedback by consumers on the production of these resources is evident and suggests ecological autocatalysis. For example, granivorous harvester ants have been shown to increase both the number and size of the plant species involved Rissing Furthermore, the large diversity in plant reproductive organs flowers, fruits, seeds suggests evolutionary feedbacks between consumer diversity and plant functional differentiation Fig.
The two hypotheses outlined above for the emergence of multiple autocatalytic loops in ecosystems are intricately linked. Which loop prevails or dominates in a specific situation or whether multiple loops are able to coexist depends on the interactions between loops, mediated by environmental conditions.
In contrast, when plants are not eaten, they release litter fragmented by macrodetritivores e. Besides these consumer—resource interactions that form the backbone of both loops, they exhibit important additional feedback mechanisms. The outcome of such competition between sets of species is likely conditional on environmental conditions.
A key finding in the study of autocatalytic processes is that a significant fraction of nutrient cycling takes place at much smaller spatial and temporal scales than previously believed. This is to their own benefit, as nitrate is easier to metabolize for plants than ammonia.
In this case, a relatively tight association between individual plants and microbial populations should be expected.
A New Physics Theory of Life
Further evaluation of the importance of such mechanisms is needed. Assume that sites become vacant when previous occupant pairs are extirpated by natural death or disturbance, and establishment of both plants and decomposers at vacant sites obeys a competitive lottery. Finally, assume that the probability of a genotype's successful establishment at a site is proportional to its total production in all other sites, because higher production means production of more propagules of a higher quality.
The aggregated parameter r Pi , which is plant genotype i 's average productivity times its reproductive efficiency, represents a potential reproduction rate, reproduction here being considered completed after the establishment of offspring at new sites. Last, V P is the proportion of vacant sites; only dispersal to vacant sites leads to successful reproduction. At equilibrium, the fraction of vacant sites, , in Eqs. This relation can be satisfied only by a single species or genotype. In the simplest case, where plants and decomposers disperse independently and their effects on their local environment are additive, the outcome of this dual selective process is the selection of the material cycle that combines the plant and decomposer genotypes with the highest basic reproductive capacities.
Since the basic reproductive capacity of a genotype is proportional to its average productivity at a site Eq. This assumes that dynamics of site occupancy dispersal, establishment is slow compared with the dynamics of material cycles nutrient uptake, growth within sites. In particular, selection for increased nutrient conservation is possible, leading to enhanced ecosystem properties, in particular increased ecosystem cycling efficiency and primary and secondary productivities.
Selection of traits advantageous to the whole cycle set of interacting species is then just as natural as selection of traits advantageous to the individual organism in classical individual selection theory. Unlike organisms, however, the biotic components of the material cycle reproduce separately, but this does not affect the overall direction of the outcome.
Consider, for example, the widespread case of plant—herbivore interactions. Both plants and herbivores recycle limiting nutrients, leading to two alterative recycling pathways. But herbivores eat plants, hence there is a direct antagonism between the two partners. The ecological and evolutionary dynamics of this interaction are much more complex than in the indirect positive interaction between plants and decomposers. This occurs when herbivores recycle limiting nutrients more effectively than do plants, i. Thus, the more efficient alternative autocatalytic loop provided by herbivores benefits plants indirectly.
This is despite the direct cost plants incur from being eaten and generates an indirect mutualism between the two partners. Such indirect effects of predation benefiting prey are surprisingly widespread in ecosystem networks and play a much more important role than is generally assumed Bondavalli and Ulanowicz Over evolutionary time scales, however, this ecological benefit is not necessarily selected for. Indeed, it is not absolute, but relative fitness that counts. As a result, the fitness of the resistant type is higher than that of the tolerant type and tolerance does not evolve, even though it is indirectly beneficial to both types.
Two factors can counteract the advantage of antiherbivore defense: spatial heterogeneity and the cost of defense. Similar to the plant—herbivore example, Harte and Kinzig modeled the dynamics of microbial decomposers that compete with plants for inorganic nutrients and also benefit from plants through their carbon input via dead organic matter. Therefore, there is a direct negative effect of plants on microbes but, at the same time, an indirect positive effect. In contrast, in a homogeneous environment mutualistic microbes were not selected for.
Throughout this paper, we have reviewed the importance of ecological autocatalysis as a key internal driver of ecosystem organization. These nested autocatalytic sets now require further quantification and theoretical study, especially with regard to the interplay of ecological and evolutionary dynamics. As many chemical elements are essential for life and often limiting, the reuse of such elements results in the closure of such interaction chains formation of loops , where material circulates and autotrophs fuel these interaction structures with an input of energy.
Autocatalysis emerges in such circular interaction structures through basic principles from community ecology resource competition and natural selection and evolutionary biology with indirect mutualism as an extended form of coevolution.
In addition, development of the concept yields key patterns observed at the ecosystem scale, such as alternative stable states, landscape heterogeneity, and ecosystem resilience. These arise as a consequence of autocatalytic loops instead of having to be seen as independent processes Fig. More importantly, the resulting macroscopic properties may feed back as a selective force to lower levels of organization diffuse feedback , and affect the future development of its components.
The historic focus of ecology on pairwise interactions and on responses of species to ecological factors has obscured the importance of higher level ecosystem organization and species—environment feedback. The framework of ecological autocatalysis proposed here aims to include all these interactions and at the same time reduce overall complexity.
We suggest that it provides a rich set of opportunities in further developing, formalizing, modeling, and experimentally testing the fundamental principles of ecosystem organization. Veldhuis, M. Berg, and H. Olff together developed the concept. Veldhuis wrote the first draft of the manuscript.
Loreau contributed the modeling sections and all authors contributed substantially to the revisions. We thank Eric S. Higgs and two anonymous reviewers for their valuable comments on earlier versions of the manuscript. The last funding statement was mistakenly omitted from the original manuscript. Volume 88 , Issue 3. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account.
If the address matches an existing account you will receive an email with instructions to retrieve your username. Become a Member ESA. Ecological Monographs Volume 88, Issue 3. Reviews Open Access. Michiel P. Veldhuis Corresponding Author E-mail address: m. Matty P. Corresponding Editor: Brian D.
Tools Request permission Export citation Add to favorites Track citation. Share Give access Share full text access. Share full text access. Please review our Terms and Conditions of Use and check box below to share full-text version of article. Abstract Ecosystems comprise flows of energy and materials, structured by organisms and their interactions. Research field Observation References Biochemistry The citric acid cycle. Zooplankton provides nourishment to the Utricularia via mineralization of periphyton Ulanowicz Ecology Phytoplankton produces dissolved organic matter that is rapidly mineralized by bacteria and Protozoa and returned as nutrients for plankton uptake.
A long history in ecosystem ecology Building on the pioneering work of R. The universality of circular interaction structures loops in ecology Nutrient cycling is one of the fundamental aspects of the organization and dynamics of ecosystems. Figure 1 Open in figure viewer PowerPoint. A The most basic autocatalytic loop present in all ecosystems where autotrophs and decomposing microbes form a circular configuration.