Emergence (biology)

The term emergence refers to the exhibition of novel collective phenomena in some large systems stemming from a complex organization of their many constituent parts. In systems biology and theoretical biology, one topic is emergence in living systems. Often-used examples are termite and bees' nests, made by the cooperative action of multitudes of individuals.

In biology emergent behavior includes such things as locomotion, sexual display, flocking, and conscious experiencing. Emergence is found even in biological subsystems, such as mitochondria and other organelles of living cells.

Emergent properties are viewed by some as novel properties, functions and behaviors, ones not observed in the system's subsystems and their components, and neither explicable nor predictable from even a complete understanding of the components' properties/functions/behaviors considered in isolation. Others take the view that these novel properties are the outcome of interactions between the constituents understandable from microscopic behavior, but more readily envisioned by introduction of novel organizational concepts.

This article will explore emergence as a concept with a long history, differing interpretations, and much controversy.

Is water an example?

Do the properties we associate with liquid water, its transparency, its wetness, its ability to flow, etc., 'emerge' from the properties of oxygen and hydrogen and their organizational dynamics? Consider these questions:

• Would we expect that oxygen and hydrogen interacting in accord with their known properties, enabling them to self-assemble into a self-organized dynamic, to result in a fluid with the characteristics of a bowlful of water as we observe them with our native senses?

• Would we need to know thoroughly the characteristics/dynamics of the environment — to see how they might co-determine the behavior of hydrogen and oxygen, known to behave differently under different environmental conditions — in order to approach the task of visualizing water from its particulate/energetic components, hydrogen and oxygen?

• Would constructing a computer requiring the resources of the entire universe provide sufficient information processing capability to explain the look and feel, and the chemistry, of water as medium for living systems and their systems?

• Wouldn't the computer need the ability to compute water molecule interactions with every other compound/ion in the system?

These questions suggest that classification of certain properties of water as "'emergent' is to a degree a question of our capacity to predict these behaviors. However, our state of knowledge and computer technology are not really part of the identification of a property as emergent. A different perspective is that the descriptions of water at a microscopic level and at a macroscopic level are couched in a different vocabulary, and the terms used in one description may not appear in another, although (perhaps only in principle) they might be related to one another by some intermediary theory. An example might be the dielectric properties of water, such as its transparency in visible light, which is related by condensed matter physics to the underlying microscopic quantum mechanical description of water's constituent electrons and nucleii.

For some emergent properties of some systems, the theory intermediating between the system properties and the properties of its subsystems might not yet exist, and some scholars believe such an intermediary theory in some cases might be impossible to obtain, even in principle. A view that approximates the present state of science is model-dependent realism, which takes the view that explanations are a patchwork of overlapping descriptions that use different terminologies, that agree with one anther in areas where they both apply, and with vocabularies that can be related to each other where they overlap, but which cover different areas of experience and are not reducible one to another outside their region of overlap. It may be noted that the regions of overlap may change as knowledge and calculation advance, and new theories may evolve that encompass and extend older theories, as special relativity extends Newtonian mechanics.

Nominal, strong, and weak emergence

Above the distinctive property of emergence has been taken to be a collective behavior of subsystems imbedded in a complex system. There are several identifiable forms of emergence, whether or not all of them exist in nature:

1. Emergence is nominal when it depends upon micro-level phenomena in the sense that wholes are dependent upon their constituents and their autonomous interactions, and the emergent properties do not apply to the underlying entities themselves.
2. Emergence is strong when the emergent properties have power over the underlying entities that is not reducible to the properties of these entities. These "macro causal powers" have effects on both the macro and micro-levels, and macro-to-micro effects are termed downward causation.
3. Emergence is weak when it is explained by nominal emergence, but only by a very nontrivial inference that involves extensive computation.

The strong emergence school of thought invokes an influence of the whole upon its parts, not simply by connections between the parts, but by communication of the whole to its parts. Another name for this approach is organicism:

Emergence relates to phenomena that arise from and depend on some more basic phenomena yet are simultaneously autonomous from that base.

"...complex wholes are inherently greater than the sum of their parts in the sense that the properties of each part are dependent upon the context of the part within the whole in which they operate. Thus, when we try to explain how the whole system behaves, we have to talk about the context of the whole and cannot get away talking only about the parts. This philosophical stance is variously called wholism, holism, or organicism. ...top-down and bottom-up approaches must both be used to explain phenomena." Gilbert & Sarkar, Embracing Complexity

What explains the behavior of an organism fleeing from a predator if studying all the subsystems does not visualize the predator-prey phenomenon? One answer: to see the emergent phenomenon one must study the organized behavior of those subsystems and the dynamics of that organized behavior and consider the novelty of the system's behaviors that organized interacting subsystems would engender, and that natural selection would operate on its variations.

Given emergence, some biologists might find it tempting to see a type of 'vitalism', or 'life force', in living systems. However, because biologists and their co-scientists can explain emergent properties/phenomena, if only sometimes in principle, by mechanisms that do not transcend interactions of matter and energy, any ‘vitalism’ position properly can credit only a new sort of 'vitalism': ‘materialistic vitalism’ that incorporates the realization that organisms organize themselves, having developed their pattern of behavior by trial and error and natural selection. bent, and philosophers of science, like to consider those kinds of interesting meta-science questions.

The concept of strong emergence has some difficulties. One may observe: |}

" Although strong emergence is logically possible, it is uncomfortably like magic. How does an irreducible but supervenient downward causal power arise, since by definition it cannot be due to the aggregation of the micro-level potentialities....Their mysteriousness will only heighten the traditional worry that emergence entails illegitimately getting something from nothing." Mark Bedau, Weak emergence

A moderate view is that strong emergence is a classification that may have to be removed if a more complete theory emerges rendering the emergent phenomena in the weak or nominal category, but even if such a reductionist approach is possible, the language and models based upon strong emergence might prove useful in describing the collective behavior.

Supervenience

A concept often used in discussing emergence is supervenience, often mistakenly taken to indicate what controls what, and confused with downward causation. State A is supervenient of state B if and only if every change in A requires a change in B.

Supervenience is a deceptive descriptor. For example, consider the relations between a microscopic theory like kinetic theory based upon specific interactions, a mesoscopic theory like statistical mechanics largely independent of the specifics of interactions, and a macroscopic theory like thermodynamics where microscopic considerations about interactions are not considered. According to the definition above, microscopic theory is not supervenient of thermodynamics, because many different systems have the same thermodynamic description. On the other hand, a change in temperature is a key element in thermodynamics, related to microscopic theory by statistical mechanics, and changes in temperature always imply correlated changes in the microscopic description. So it appears that a macroscopic theory is supervenient of a more microscopic theory that explains the macroscopic theory on a more fundamental level. Although strictly within a thermodynamic description it may be correct to say that a change in temperature causes a phase change, say from ice to water, the microscopic theory provides a deeper understanding of phase changes entirely in terms of the fundamental atomic interactions.

In a similar vein, the notions of chemical bonding, valence, and so forth are used directly in molecular physics and chemistry to explain how atoms engage with one another, and one might say a particular molecule is the result of such factors, which supervene atomic behavior. But the explanation of these factors lies within quantum mechanics, which does not use the term "bond" at all, and describes all chemistry in terms of electron behavior and electromagnetic interactions.

One may well assert the "poverty of the supervenience relation".

Examples of emergence

One example of emergence: When the components of signaling pathway, one that enable between-cell communication, interact to form a functional network of signaling systems, novel properties/behaviors can arise — such as a self-sustaining feedback loop and generation of the signals themselves; signal integration across multiple time scales; and, generation of distinct outputs depending on input strength and duration. Such a network is an emergent phenomenon.

For another example, in studying a protein separated from the cellular system that embeds it in a cell, one can observe many of its chemical and physical properties. But the operation of catalyzing a biochemical reaction, or of binding to other proteins to form a protein complex that generates novel behavior, emerge in the context of the protein’s environment — how it interacts in the context of the system as a whole, they are emergent properties. Moreover, those emergent properties may result in effects within the system that, in a feedback way, further alters the emergent behavior of the protein in the system, as when a reaction product alters the catalytic ability of the protein.

Emergent processes have been recognized as, for example, contributing to understanding:

• subcellular morphology,
• developmental biology,
• metabolic networks,
• proteomics 
• evolution of complexity in living things

Emergent phenomena appear even in non-biological physical systems. Emergent phenomena attract the attention of cellular neuroscientists;  and cognitive scientists. Emergent properties manifest in the behaviour of ant colonies and in swarm intelligence. Systems scientists have simulated emergent phenomena.  Emergent phenomena in human societies has also received attention. . Biologists even explain the biosphere itself as emergent.

Why emergence?

Do some of the properties/behaviors of a living system result from something other that the properties of its components? After all, the reductionist paradigm that dominated the scientific method in the 20th century operated on the assumption that they could.

According to organicism, it may be that the intrinsic properties of a system’s components cannot themselves determine those of the whole system; rather, their 'organizational dynamics' does — how the components interact coordinately in time and space. Those organizational dynamics might include not only the interrelations among the components themselves, but also interactions originating in the many different organizational units in the system.

It is obvious from any standpoint that context is important to system behavior, whether that is as simple as a violin player's finger on a string or as complicated as psychotherapy. A real system always operates in a context (its external environment, or surroundings), and those surroundings, in turn, always affect the properties of the system-as-a-whole. For example, nutrient gradients in its environment influence the direction a bacterium’s locomotion. The impact of environmental context affects the dynamic organization of the components within the system. Environmental signals can activate or suppress a metabolic pathway, reorganizing cellular activity. As Gilbert and Sarkar puts it: “Thus, when we try to explain how the whole system behaves, we have to talk about its parts the context of the whole and cannot get away talking only about the parts.”

These effects of context sometimes are interpreted as "downward causation", perhaps an overly dramatic description of the effects of context, which is primarily a filter or selection mechanism for subsystem behavior. These effects can be profound, however. For example, the environment’s effect can sometimes reach down to the genetic database with molecular signals, altering its expression and consequently the characteristics of the cells without altering the database itself — so-called 'epigenetic' effects. When epigenetic alterations of gene expression occur in the reproductive organs, the system changes can be transmitted to the next generation. Particularly where environment and subsystem interact, one cannot simply take a living system apart and predict without these interactions how it will behave in its natural environment.

Philosopher of science D.M. Walsh puts it this way: "The constituent parts and processes of a living thing are related to the organism as a whole by a kind of 'reciprocal causation'." In other words, the organization of the components determine the behavior of the system, but that organization arises from more than the set of its internal components. How the whole system behaves as it interacts with its environment determines how those components organize themselves, and so novel properties of the system 'emerge' that characterize neither the environment nor that set of internal components.

For example, the behavior of a human kidney cell depends not only on its cellular physiology, but also on all the properties of the organ (kidney) which constitutes its environment. The kidney's overall structure and function influence the cell’s structure and behavior (e.g., by physical confinement and by cell-to-cell signaling), which in turn influence the organization of its intracellular components. The kidney in turn responds to its environment, namely the individual body that it lives in, and that body responds to its environment, which includes such factors as the availability of particular food items, fresh water, and ambient temperature and humidity. Systems biologists regard emergent properties as arising from a combination of bottom-up and top-down effects — Walsh's 'reciprocal causation'. The "top" consists in the effects of the system's interactions with its environments. The "bottom", the effects of the interactions of the system's components.

A term prevalent today is swarm intelligence, applied to computer and robotic systems as well as biology. Using the example of termites out of whose combined individual behaviors without outside management emerge complex colony mounds, a recent National Research Council report on the role of theory in advancing 21st century biology commented on emergent behavior as follows:

A reasonable way of thinking about emergent behavior might be to focus on the level or scale at which the rules reside. If the rules are specified at a low level, for example, the individual termites, and the patterns and structures, like termite mounds, emerge at a scale where there are no rules specified, we may call this emergent behavior.

Other examples of rule-free emergent behavior for which the 'rules' appear specified at a lower level than the emergent behavior itself include the flocking behavior of birds, and the folding of amino acid polymers into catalytic proteins.

Emergence and complexity

Emergent systems always display what we recognize as ‘complexity’, a feature we have a difficult time precisely defining. The operation of the system itself supplies its own most economical model.

According the paleontologist and origin of life researcher, Robert Hazen, four basic complexity elements underpin emergence in a system:

• a sufficiently large ‘density’ of components, with increasing complexity as the concentration increases, up to a point;

• sufficient interconnectivity of the components, with increasing complexity with greater and more varied types of interconnectivity, up to a point;

• a sufficient energy flow through the system to enable the system’s components to perform the work of interacting in the self-organized way characteristic of the energized system;

• flow of energy through the system in a cyclic manner, presumably facilitating the spatiotemporal patterning characteristic of organized systems.

Coherent entities and coherence detectors

We can think of emergence as the appearance of a novel 'coherent entity', coherent in the sense of the entity behaving in a functionally consistent manner, and an entity in virtue of that functionally consistent behavior. Perhaps the human circulatory system exemplifies functionally consistent behavior, and qualifies as a coherent entity. But to see it, we need a way to detect the existence, properties, and behaviors of the circulatory system — a coherence detector. Physiology and systems biology predominately study emergent phenomena, coherent entities exhibiting unexpected behavior produced by dynamic physico-chemical processes of great complexity. The emergent behaviors they study depend on their resources of coherence detectors, making observer-dependence a property of emergence. In biology, emergent systems abound, suggesting greater abundance as coherence detection advances in sensitivity and power.