Week 3: questions to ask; Extended Evolutionary Synthesis

• Dobzhansky, T. (1973). Nothing in biology makes sense except in the light of evolution. The American Biology Teacher, 35, 125–129.
• Tinbergen, N. (1963). On aims and methods in ethology. Zeitschrift für Tierpsychologie, 20, 410–433.
• Mayr, E. (1961). Cause and effect in biology. Science, 134, 1501–1506.
• Marr, D. and Poggio, T. (1977). From understanding computation to understanding neural circuitry. Neurosciences Res. Prog. Bull., 15, 470–488.
• Laland, K. N., Uller, T., Feldman, M. W., Sterelny, K., Müller, G. B., Moczek, A., Jablonka, E., and Odling-Smee, J. (2015). The extended evolutionary synthesis: its structure, assumptions and predictions. Proc. R. Soc. B, 282, 20151019.

On aims and methods in ethology [Tinbergen, 1963]

Tinbergen's famous "four questions" that need to be answered so that a particular behavior can be fully understood (the first three are Huxley's "three major problems of biology"):

• Causation: what traits and events caused the behavior?
• Survival value: how does the behavior affect the species survival?
• Evolution: how did it evolve in the species in question?
• Ontogeny: how does its development in the individual animal proceed?

On aims and methods in ethology [Tinbergen, 1963]

Tinbergen's famous "four questions" that need to be answered so that a particular behavior can be fully understood (the first three are Huxley's "three major problems of biology"):

• Causation: what traits and events caused the behavior?
• Survival value: how does the behavior affect the species survival?
• Evolution: how did it evolve in the species in question?
• Ontogeny: how does its development in the individual animal proceed?

Bateson & Laland, 2013 — a retrospective on Tinbergen, 1963

"Despite Tinbergen's emphasis on the need for an integrated understanding, in few study systems have all four of Tinbergen's questions been addressed. One such system is bird song."

• Causation: what traits and events caused the behavior?
• Survival value: how does the behavior affect the species survival?
• Evolution: how did it evolve in the species in question?
• Ontogeny: how does its development in the individual animal proceed?

Cause and effect in biology [Mayr, 1961]

Functional biology. The functional biologist is vitally concerned with the operation and interaction of structural elements, from molecules up to organs and whole individuals. His ever-repeated question is "How?" How does something operate, how does it function?

Evolutionary biology. The evolutionary biologist differs in his method and in the problems in which he is interested. His basic question is "Why?" When we say "why" we must always be aware of the ambiguity of this term. It may mean "how come?," but it may also mean the finalistic "what for?" It is obvious that the evolutionist has in mind the historical "how come?" when he asks "why?"

Cause and effect in biology [Mayr, 1961]

What is the cause of bird migration? Or more specifically: Why did the warbler in my summer place in New Hampshire start his southward migration on the night of the 25th of August?

1. An ecological cause. The warbler, being an insect eater, must migrate, because it would starve to death if it should try to winter in New Hampshire.
2. A genetic cause. The warbler has acquired a genetic constitution in the course of the evolutionary history of its species which induces it to respond appropriately to the proper stimuli from the environment. On the other hand, the screech owl, nesting right next to it, lacks this constitution and does not respond to these stimuli. As a result, it is sedentary.
3. An intrinsic physiological cause. The warbler flew south because its migration is tied in with photoperiodicity. It responds to the decrease in day length and is ready to migrate as soon as the number of hours of daylight have dropped below a certain level.
4. An extrinsic physiological cause. Finally, the warbler migrated on the 25th of August because a cold air mass, with northerly winds, passed over our area on that day. The sudden drop in temperature and the associated weather conditions affected the bird, already in a general physiological readiness for migration, so that it actually took off on that particular day.

Cause and effect in biology [Mayr, 1961]

• Proximate vs. ultimate causes. If we look over the four causations of the migration of this bird once more we can readily see that there is an immediate set of causes of the migration, which we might call PROXIMATE.
  • the physiological condition of the bird
  • photoperiodicity and drop in temperature
  The other two are the ULTIMATE causes.
  • the lack of food during winter
  • the genetic disposition of the bird
  These are causes that have a history and that have been incorporated into the system through many thousands of generations of natural selection. [...] The functional biologist would be concerned with analysis of the proximate causes, while the evolutionary biologist — with analysis of the ultimate causes.
• Prediction and indeterminacy in biology. In the classical theory of causality the touchstone of the goodness of a causal explanation was its predictive value.
  • Bunge's modern classic: "A theory can predict to the extent to which it can describe and explain."
  • It is evident that Bunge is a physicist; no biologist would have made such a statement. The theory of natural selection can describe and explain phenomena with considerable precision, but it cannot make reliable predictions, except through such trivial and meaningless circular statements as, for instance: "the fitter individuals will on the average leave more offspring."
  • Probably nothing in biology is less predictable than the future course of evolution. Looking at the Permian reptiles, who would have predicted that most of the more flourishing groups would become extinct (many rather rapidly), and that one of the most undistinguished branches would give rise to the mammals?
• Reasons for indeterminacy in biology.
  • Randomness of an event with respect to the significance of the event.
  • Uniqueness of all entities at the higher levels of biological integration.
  • Extreme complexity.
  • Emergence of new qualities at higher levels of integration.

Cause and Effect in Biology Revisited [Laland et al., 2011]

Graphs depicting the causal pathways involved in the evolution and development of traits.

Arrows represent possible causal influences; dashed lines represent features that persist over time.

(A) Ernst Mayr's (1961) perspective.

Cause and Effect in Biology Revisited [Laland et al., 2011]

(B) A modern developmental perspective.

Red arrows denote additional causal influences relative to (A) recognized by fields such as evo-devo and niche construction theory.

During development, features of the trait cause changes in both gene expression and environment, which feed back to the developmental process, resulting in a different trait in the adult and modifications of both developmental and selective environments. Development cannot be considered purely proximately causal because it results in additional causal pathways from the trait in one generation to the trait in future generations.

Cause and Effect in Biology Revisited [Laland et al., 2011]

Alternative [= parallel] evolutionary processes.

1. Biological evolution: The ultimate explanation for the behavior is its effect on biological fitness.
2. Cultural evolution: The behavior can be inherited from the previous generation through intergenerational cultural transmission and differential cultural selection. Here, the ultimate explanation for the behavior is its effect on cultural fitness.
3. Gene-culture coevolution: Genetically and culturally inherited traits coevolve, with each trait affecting the fitness of the other. [For illustration, trait 1 might be lactose absorption and trait 2 dairy farming or milk use.] Inheritance pathways are shown in red. For any given data set, causal modeling can be used to establish whether a particular causal influence is operating.

From understanding computation to understanding neural circuitry [Marr and Poggio, 1977]

"Complex systems cannot be understood as simple extrapolations of the properties of their elementary components. [...] The core of the problem is that a system as complex as a nervous system or a developing embryo must be analyzed and understood at several different levels."

From understanding computation to understanding neural circuitry [Marr and Poggio, 1977]

"Complex systems cannot be understood as simple extrapolations of the properties of their elementary components. [...] The core of the problem is that a system as complex as a nervous system or a developing embryo must be analyzed and understood at several different levels." For a system that solves an information processing problem, we may distinguish these levels:

[HARDWARE]
At the lowest, there is basic component and circuit analysis — how do transistors, neurons, diodes, and synapses work?

[MECHANISMS]
The second level is that of particular mechanisms: adders, multipliers, and memories accessed by address or by content.

[ALGORITHM]
The third level is that of the algorithm, and ...

[COMPUTATION]
... the top level contains the theory of the overall computation.

"In general, mechanisms are strongly determined by hardware, the nature of the computation is determined by the problem, and the algorithms are determined by the computation and the available mechanisms."

the (Mayr & Tinbergen &) Marr & Poggio levels of analysis/understanding

• Understanding the behavioral and evolutionary context and needs, shedding light on computational problems that may need to be solved. What does the animal do in general (to survive and procreate)? In the present context? What are the effects of evolutionary pressures on its behavior? What are its evolutionary roots?
• Understanding the computational problem, leading to a theory. What could be the goal of the computation? What is the goal of the computation, why is it appropriate, and what is the logic behind the strategy by which it can be carried out?
• Understanding/developing representations and algorithms that solve the problem. What could be the input and output representations and the algorithm for mapping inputs to outputs? What are the representations and algorithms in the given system?
• Understanding/developing the mechanism and the hardware that implements the algorithm. How could a given representation and algorithm be realized physically? How are they realized in a given system?

the Extended Evolutionary Synthesis [Laland et al., 2015]

"Extended Evolutionary Synthesis (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation.

In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism-environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology."

Modern Synthesis vs. Extended Evolutionary Synthesis

[EXTRA] alternative interpretations of developmental bias, developmental plasticity, inclusive inheritance and niche construction

contrasting views of development

(a) Programed development. Traditionally, development has been conceptualized as programed, unfolding according to rules and instructions specified within the genome. DNA is ascribed a special causal significance, and all other parts of the developing organism serve as ‘substrate’, or ‘interpretative machinery’ for the expression of genetic information.

(b) Constructive development. By contrast, in the EES, genes and genomes represent one of many resources that contribute to the developing phenotype. Causation flows both upwards from lower levels of biological organization, such as DNA, and from higher levels downwards, such as through tissue- and environment-specific gene regulation. Exploratory and selective processes are important sources of novel and evolutionarily significant phenotypic variation. Rather than containing a ‘program’, the genome represents a component of the developmental system, shaped by evolution to sense and respond to relevant signals and to provide materials upon which cells can draw.

the structure of the EES

¶ Mutation pressure refers to the population-level consequences of repeated mutation, here depicted as dashed because mutation is also represented in ‘processes that generate novel variation’.

‡ In the EES, this category of processes will often need to be broadened to encompass processes that modify the frequencies of other heritable resources.

§ Developmental bias and niche construction can also affect other evolutionary processes, such as mutation, drift and gene flow.

[EXTRA] predictions made by a traditional interpretation vs. the EES

some conclusions

"A further benefit [of EES] comes from strengthening ties to adjacent disciplines, such as ecology [76,143,144], or the human sciences, including archaeology, biological anthropology, developmental psychology, epidemiology, and economics [145–150], where some of these ideas are already starting to have an impact.

Moreover, other advances in biology potentially take on new significance within the EES. For instance, the emphasis on inclusive inheritance potentially gives multi-level selection even greater significance, as selection can operate on all forms of heritable variation.

Another case is genome evolution, where horizontal gene transfer in prokaryotes, and genetic transfer from endosymbionts in eukaryotes [151], can be understood as part of a broader suite of phenomena with the propensity to propagate horizontally (e.g. social transmission, ecological inheritance). The recognition that genome change is an active cell-mediated physiological process that responds to challenging life-history events [152] fits neatly with the EES’s treatment of plasticity.

The EES perspective may also facilitate implementation of approaches from computer science that enable mathematical representation of complex dynamic systems, such as connectionist models of memory and learning applied to model genotype to phenotype relations [153]."

Mutual Aid: A Factor of Evolution [Pëtr Kropotkin, 1902]

Mutual Aid: A Factor of Evolution [Pëtr Kropotkin, 1902]

"Two aspects of animal life impressed me most during the journeys which I made in my youth in Eastern Siberia and Northern Manchuria. One of them was the extreme severity of the struggle for existence which most species of animals have to carry on against an inclement Nature; the enormous destruction of life which periodically results from natural agencies; and the consequent paucity of life over the vast territory which fell under my observation. And the other was, that even in those few spots where animal life teemed in abundance, I failed to find — although I was eagerly looking for it — that bitter struggle for the means of existence, among animals belonging to the same species, which was considered by most Darwinists (though not always by Darwin himself) as the dominant characteristic of struggle for life, and the main factor of evolution."

[Read all of it here.]

Questions?