Emergence (biology)

Systems biologists and theoretical biologists study, among other things, the phenomenon of emergence, whereby properties, functions and behaviors manifest themselves in living systems though not exhibited by any individual component of the system, and not explainable or predictable from complete understanding the components' properties/behaviors considered in isolation from the system that embeds them. Every cellular system exhibits emergent behaviors. Emergent behaviors of living systems include such things as locomotion, sexual display, flocking, and conscious experiencing. Even the biological components of living cells, such as mitochondria and other organelles, exhibit emergent properties.

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

Emergence vs. vitalism

Some biologists might find it tempting to see a type of 'vitalism', or 'life force', in living systems, given that some whole-system properties/behaviors of organisms, including even the activity of living itself, exemplify emergent phenomena as defined in the introduction. One could not explain, for example, the behavior of an organism fleeing from a predator from a study of the properties of an organism's component subsystems. The properties of the component parts in a living system depend on the organization of those parts in the system, which differ from those found when their properties are studied isolated from the system. 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 such ‘vitalism’ properly qualifies only as a ‘materialistic vitalism’.

Examples of emergence

One example of emergence: When the components of signaling pathway that enable between-cell communication interact to form a signaling network system, novel properties/behaviors can emerge — such as a self-sustaining feedback loop and generation of the signals themselves; signal integration across nultiple time scales; and, generation of distinct outputs depending on input strength and duration. One cannot explain or predict those novelties from combined knowledge of the individuated properties of the separate components of the network system. Networks represent emergent phenomena.

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 with increasing knowledge of those properties one approaches no closer to explaining any of the properties it has only in the context of the system that embeds it, such as the operation of catalyzing a biochemical reaction, or of binding to other proteins to form a protein complex that generates novel behavior. Those properties of the protein emerge in the context of the protein’s environment — how it interacts in the context of the system as a whole. 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 recognised 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

Why do not all of the properties/behaviors of a system predictably result from the properties of its components? After all, the reductionist paradigm that dominated the Scientific method in the 20th century operated on the exactly opposite assumption. For one thing, the intrinsic properties of a system’s components themselves do not determine those of the whole system; rather, their 'organizational dynamics' does — how the components interact coordinately in time and space. Those organizational dynamics include not only the interrelations among the components themselves, but also interactions among the many different organizational units in the system. Secondly, the living system always operates in a certain 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 — a 'downward causation'. For another example, environmental signals can activate or suppress a metabolic pathway, reorganizing cellular activity One cannot simply take a living system apart and predict how it will behave in its natural environment.

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.”

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'.

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. Complex systems appear to require more bits of information (words, sentences, lines of computer code, etc.) to describe than the bits of information in the system itself.  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.