Developmental systems theory

In developmental psychology, developmental systems theory (DST) is an overarching theoretical perspective on biological development, heredity, and evolution.[1] It emphasizes the shared contributions of genes, environment, and epigenetic factors on developmental processes. DST, unlike conventional scientific theories, is not directly used to help make predictions for testing experimental results; instead, it is seen as a collection of philosophical, psychological, and scientific models of development and evolution. As a whole, these models argue the inadequacy of modern evolutionary views on the roles of genes and natural selection as the principle explanation of living structures. Developmental systems theory embraces a large range of positions that expand biological explanations of organismal development and hold modern evolutionary theory as a misconception of the nature of living processes.

Overview

All versions of developmental systems theory espouse the view that:

In other words, although it does not claim that all structures are equal, development systems theory is fundamentally opposed to reductionism of all kinds. In short, developmental systems theory intends to formulate a perspective which does not presume the causal (or ontological) priority of any particular entity and thereby maintains an explanatory openness on all empirical fronts.[2] For example, there is vigorous resistance to the widespread assumptions that one can legitimately speak of genes ‘for’ specific phenotypic characters or that adaptation consists of evolution ‘shaping’ the more or less passive species, as opposed to adaptation consisting of organisms actively selecting, defining, shaping and often creating their niches.[3]

Developmental systems theory: Topics

Six Themes of DST [1]

1. Joint Determination by Multiple Causes

Development is a product of multiple interacting sources.

2. Context Sensitivity and Contingency

Development depends on the current state of the organism.

3. Extended Inheritance

An organism inherits resources from the environment in addition to genes.

4. Development as a process of construction

The organism helps shape its own environment, such as the way a beaver builds a dam to raise the water level to build a lodge.

5. Distributed Control

Idea that no single source of influence has central control over an organism's development.

6. Evolution As Construction

The evolution of an entire developmental system, including whole ecosystems of which given organisms are parts, not just the changes of a particular being or population.

A computing metaphor

To adopt a computing metaphor, the reductionists whom developmental systems theory opposes assume that causal factors can be divided into ‘processes’ and ‘data’. Data (inputs, resources, content, and so on) is required by all processes, and must often fall within certain limits if the process in question is to have its ‘normal’ outcome. However, the data alone is helpless to create this outcome, while the process may be ‘satisfied’ with a considerable range of alternative data. Developmental systems theory, by contrast, assumes that the process/data distinction is at best misleading and at worst completely false, and that while it may be helpful for very specific pragmatic or theoretical reasons to treat a structure now as a process and now as a datum, there is always a risk (to which reductionists routinely succumb) that this methodological convenience will be promoted into an ontological conclusion.[4] In fact, for the proponents of DST, either all structures are both process and data, depending on context, or even more radically, no structure is either.

Fundamental asymmetry

For reductionists there is a fundamental asymmetry between different causal factors, whereas for DST such asymmetries can only be justified by specific purposes, and argue that many of the (generally unspoken) purposes to which such (generally exaggerated) asymmetries have been put are scientifically illegitimate. Thus, for developmental systems theory, many of the most widely applied, asymmetric and entirely legitimate distinctions biologists draw (between, say, genetic factors that create potential and environmental factors that select outcomes or genetic factors of determination and environmental factors of realisation) obtain their legitimacy from the conceptual clarity and specificity with which they are applied, not from their having tapped a profound and irreducible ontological truth about biological causation.[5] One problem might be solved by reversing the direction of causation correctly identified in another. This parity of treatment is especially important when comparing the evolutionary and developmental explanations for one and the same character of an organism.

DST approach

One upshot of this approach is that developmental systems theory also argues that what is inherited from generation to generation is a good deal more than simply genes (or even the other items, such as the fertilised zygote, that are also sometimes conceded). As a result, much of the conceptual framework that justifies ‘selfish gene’ models is regarded by developmental systems theory as not merely weak but actually false. Not only are major elements of the environment built and inherited as materially as any gene but active modifications to the environment by the organism (for example, a termite mound or a beaver’s dam) demonstrably become major environmental factors to which future adaptation is addressed. Thus, once termites have begun to build their monumental nests, it is the demands of living in those very nests to which future generations of termite must adapt.

This inheritance may take many forms and operate on many scales, with a multiplicity of systems of inheritance complementing the genes. From position and maternal effects on gene expression to epigenetic inheritance [6] to the active construction and intergenerational transmission of enduring niches,[3] development systems theory argues that not only inheritance but evolution as a whole can be understood only by taking into account a far wider range of ‘reproducers’ or ‘inheritance systems’ – genetic, epigenetic, behavioural and symbolic [7] – than neo-Darwinism’s ‘atomic’ genes and gene-like ‘replicators’.[8] DST regards every level of biological structure as susceptible to influence from all the structures by which they are surrounded, be it from above, below, or any other direction – a proposition that throws into question some of (popular and professional) biology’s most central and celebrated claims, not least the ‘central dogma’ of Mendelian genetics, any direct determination of phenotype by genotype, and the very notion that any aspect of biological (or psychological, or any other higher form) activity or experience is capable of direct or exhaustive genetic or evolutionary ‘explanation’.[9]

Developmental systems theory is plainly radically incompatible with both neo-Darwinism and information processing theory. Whereas neo-Darwinism defines evolution in terms of changes in gene distribution, the possibility that an evolutionarily significant change may arise and be sustained without any directly corresponding change in gene frequencies is an elementary assumption of developmental systems theory, just as neo-Darwinism’s ‘explanation’ of phenomena in terms of reproductive fitness is regarded as fundamentally shallow. Even the widespread mechanistic equation of ‘gene’ with a specific DNA sequence has been thrown into question,[10] as have the analogous interpretations of evolution and adaptation.[11]

Likewise, the wholly generic, functional and anti-developmental models offered by information processing theory are comprehensively challenged by DST’s evidence that nothing is explained without an explicit structural and developmental analysis on the appropriate levels. As a result, what qualifies as ‘information’ depends wholly on the content and context out of which that information arises, within which it is translated and to which it is applied.[12]

Related theories

Developmental systems theory is by no means a narrowly defined collection of ideas, and the boundaries with neighbouring models are very porous. Notable related ideas (with key texts) include:

See also

References

  1. 1 2 Oyama, S., Griffiths, P.E., and Gray, R.D. (2001). Cycles of Contingency: Developmental Systems and Evolution. Cambridge, Mass.: MIT Press.
  2. Moss in Oyama et al. 2001: 90.
  3. 1 2 Lewontin 2000
  4. See, for example, Oyama’s discussion of the use and misuse of norms of reaction in Oyama et al. 2001: 179-184.
  5. Oyama in Oyama et al. 2001: 177-184.
  6. Jablonka and Lamb 1995.
  7. Jablonka in Oyama et al. 2001
  8. Dawkins 1976, 1982.
  9. Oyama 1985; Oyama et al. 2001; Lewontin 2000.
  10. Neumann-Held 1999; Moss in Oyama et al. 2001: 90-91
  11. 1 2 Levins and Lewontin 1985.
  12. See Oyama 2000 for a detailed critique of information processing theory from a developmental systems perspective)
  13. Baldwin 1895, 1896a, 1896b.
  14. Ludwig von Bertalanffy 1950, 1971.
  15. Edelman 1987; Edelman and Tononi 2001
  16. Gilbert Gottlieb, 1971, 2007.

Further reading

External links

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