Convergent evolution

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[Note: This is the EDU Community version of the Wikipedia page, Convergent evolution].


Convergent evolution (CE) is evidence or argument for physical attractors in the phase space of dynamical possibility which guide and constrain contingently adaptive evolutionary processes into statistically predictable future-specific structure or function, in a variety of physical and informational environments. When we look at evolutionary history, the dynamics of several species morphology or function is seen to converge to particular "archetypal forms and functions" in a variety of environments.

Such attractors have been called deep structure, guiding evolutionary process in predictable ways, regardless of local environmental differences. Organismic development depends on specific initial conditions (developmental genes in the "seed"), the emergence of hierarchies of modular structure and function in the unfolding organism, and persistent constancies (physical and chemical laws, stable biomes) in the environment. Likewise, some examples of convergent evolution may be best characterized as ecological, biogeographical, stellar-planetary, or universal evolutionary development (ED) if their emergence can modeled, after adjusting for observer selection, to depend on specific universal initial conditions, emergent hierarchies, and environmental constancies.

A famous example of convergence is found in eyes, which appear to have evolved on Earth from different genetic lineages to work similarly (function) in all species, and in the case of camera eyes, to also look very similar (form) in both vertebrate and invertebrate species, like humans and octopi. One can easily advance the argument that, in universes of our type, eyes, though first created by a process of evolutionary contingency, become an archetype, a kind of general optimization for almost all eye-possessing multicelluar species in Earth-like environments, once they exist. Presumably, the previously rapidly-changing "evolutionary" gene groups that led to eye creation become part of the "developmental" genetic toolkit for eye-possessing species. Such developmental features should become increasingly strongly conserved and eventually, due to path dependency and emergent hierarchies, incapable of being changed without preventing development itself. Proving such genetic convergence arguments with evidence and theory is of course more difficult, yet it is a fertile area of investigation today.

Some proposed convergences are also major evolutionary transitions, such as cellularization (prebiotic evolution) and nervous systems (synapses emerged in comb jellies, cnidarians and bilaterians). Others are convergences in generically useful function, like echolocation (bats and cetaceans), bioluminescence (many species), and thumbs (primates and pandas). There are also many convergence examples at the gene-protein level, like protocadherins (cephalopods and humans), caffeine (coffee, tea, and cacao plants), and in virus form and function, like viral capsids, and retroviruses.

For a longer list, see our page list of examples of convergent evolution.

For a leading website chronicling convergence, see Simon Conway-Morris's team's excellent Map of Life: Convergent Evolution Online.

Less-optimizing convergence (LOC) vs. optimizing convergence (OC)


In our mostly chaotic, contingent, and deeply nonlinear universe, we can predict that many, perhaps even the vast majority, of examples of CE will not be driven by the evolving system's discovery of some hidden general optimization function, like the discovery of the eye archetype. To understand convergence, we will need some kind of general optimization theory. Let's consider two necessary features of that theory now.

  1. We can predict that any optimization that occurs must be on a continuum, from highly-optimizing convergence, which we will refer to simply as optimizing convergence (OC), conferring advantage in all the most competitive and complex environments, to a wide variety of other cases, which we can refer to collectively as less-optimizing convergence (LOC). LOC cases would include convergence that offers only some temporary or local adaptive advantage, to just a few specific species, or in some subset of specialized or less-complex environments, convergence that offers no advantage, or convergence that is deleterious but not fatal. Names for a few general classes of LOC cases have been offered by scholars, including passive convergence, parallel evolution, etc.
  2. Optimizing convergence can occur via both physical and informational processes. Physically, we might see greater efficiency of employment of physical resources, as in Bejan's constructal law, or greater density of employment of physical resources for offense or defense, the escalation hypothesis (Vermeij 1987). Informationally, we might see efficiency or density gains via informational substitution for physical processes, what Fuller called ephemeralization, or greater general intelligence (modeling ability), greater immunity, or a more useful collective morality, offering more general and persistent adaptation to a wider range of environments than previous strategies. Intelligence also offers the ability to modify environments to suit the organism, what biologists call niche-construction, as humans extensively do today. To understand OC, we will need a theory of optimization that tells us when a physical or informational advantage is likely to be more generally adaptive, particularly in the most complex, competitive and rapidly-changing environments. We also need to know whether there are any other paths that can lead, in a competitive timeframe, toward a competitively superior new form of adaptiveness. If not, then we may have discovered a developmental portal, a global optimum that represents a bottleneck, a singular pathway toward greater adaptation at the leading edge of local complexity. Organic chemistry, RNA, photosynthesis, and oxidative phosphorylation are all potential examples of portals that all universal life must pass through first, on the way toward greater adaptive complexity. They may be the only global optima on their landscapes, at the relevant timeframes, that will allow the creation of vastly greater adaptive complexity. For more on developmental portals, see our page on evolutionary development.

Consider eyes again. For their time, eyes were "the leading edge" of general optimization, for animals, in the most morphologically complex (multicellular) environments on Earth. Andrew Parker's light switch theory (In the Blink of an Eye, 2003) proposes that the development of vision in Precambrian animals directly caused the Cambrian explosion. This is a fascinating theory, implying an intelligence-driven optimization and acceleration of morphological and functional complexity. It proposes that eyes created a vastly more competitive, discriminatory, and intelligent evolutionary environment (set of selection pressures) in multicellular evolutionary space. OOnce they emerged, it is easy to argue that all visible animals in that intelligence-leading environment needed eyes, or other highly effective defensive strategies, to survive. Intelligence, in this case, and perhaps generally, appears to be part of a physical and informational optimization function, in the most morphologically and functionally complex environments.

Many other examples of OC can be proposed, in the most physically and informationally complex, and rapidly changing, environments on Earth, including the necessary emergence of eukaryotes, oxidative phosphorylation, multicellularity, nervous systems, bilateral symmetry, jointed limbs, opposable thumbs, tool and language use on land (much faster-improving than aqueous environments), culture, and technology, including machine intelligence. Future science will need better theories of complexity, complexification, and optimization, to deeply understand convergence, and to distinguish the much greater variety of examples of less-optimized convergence from the most highly optimized forms.

Optimizing convergence as evolutionary development (ED)

Embryogenesis is an evo devo process.

When convergence is viewed from the perspective not of the evolving species, but from some larger systems level (the biogeography, the planet, the universe) we can view optimizing convergent evolution as a process of not simply evolution, but of evolutionary development (ED).

Evo-devo biology offers us the canonical example of evolutionary development, at the organismic system level. In organisms, most molecular and cellular processes operate chaotically, contingently, and locally adaptively, a process with many dynamical similarities to species evolution. Yet a special few of these molecular and cellular processes, driven by developmental genes and environmental constancies, are chaos-reducing, convergent, constraining, and statistically predictable, or developmental. We can generalize from organismic evo-devo to construct a general theory of ED for any replicating system.

When we claim a convergence process is an example of ED, we are not only claiming that some kind of general optimization is occurring. We are also claiming that some kind of evolutionary developmental process, with both "random" and creative evolutionary search, and predictable convergence, directionality, hierarchy, modularity, life cycle, and perhaps other features found in biological development, is being followed, at some larger systems level. We see both mostly stochastic and contingent processes, along with a few convergent and hierarchical processes, in such evolutionary as developmental phenomena as embryogenesis. Evo devo models assume such a process is going on even at the universal scale, and thus that some examples of convergence can be better understood in complex systems theory as not simply evolution, but evolutionary development.

  • Ecology offers several examples of not only evolutionary but apparent developmental change. When we look above the level of species change to ecologies, we can identify predictable patterns of ecological change, including ecological succession.
  • Biogeography offers more examples. When we look above ecologies to biogeography, we find scaling laws, like Copes rule, and biogeographic laws like Foster’s rule and Bergmann’s rule, with their predictable processes of convergent and optimizing CE, or evolutionary development. The famous convergence of form seen in placental and marsupial mammals, on separate continents, offers another example of not just evolution, but biogeographic ED. For many more examples, including convergence in intelligence traits, see Conway-Morris (2004,2015) and McGhee (2011) and our list of examples of convergent evolution in species morphology and function.
  • Culture change offers more examples. When we look above individual cultures and do cross-cultural comparisons, we find many examples of developmental features at the leading edge of competitiveness, including inventions like fire, language, stone tools, clubs, sticks, levers, written language, hydraulic empires for our first great cities, wheels, electricity, computers. etc. In each of these cases, a high-order convergence has occurred. These and other specific examples of cultural change look not only evolutionary, but evolutionary developmental (ED). Once they exist, there's no going back, for any culture seeking to stay on the leading edge of physical and informational complexification, and general adaptiveness. We also find many examples of constraint laws that operate in social and economic systems, like physicist and EDU scholar Adrian Bejan’s constructal law, and more generally, the least action principle (Georgiev etal. 2015).
  • Stellar-Planetary change offers more examples. When we look above human culture to our planet and its star, astrophysical theory tells us that the way stars have replicated, and chemically complexified, through three different populations over billions of years, has been not only evolutionary (a variety of randomly arrived at star and planet types and distributions) but evolutionary developmental, involving a progressive drive to complexification in a predictable subset of types. Many astrobiologists and planetologists argue that a subset of chaotic and nonlinear (“evolutionary”) stellar-planetary change has reliably led, with high probability and massive parallelism, to M-class stars and Earth-like planets that are biochemically and geohomeostatically ideal for the development of archaebacterial (geothermal vent) life, and from there to prokaryotes and eukaryotes. See Nick Lane's The Vital Question (2016) for one such story.
  • Universal change offers more examples. When we look beyond stars to galaxies (which do not replicate within this universe) and to the universe as a system, several cosmologists propose that it has not only much change that is evolutionary (random, contingent, experimental), but a large subset that appears developmental. If the universe and its galaxies are a replicative system in the multiverse, as some cosmologists have proposed, such special initial conditions and constancies may have themselves self-organized in an iterative and selective process, just as biological developmental parameters have self-organized, in biological systems over multiple replications. For more on the latter idea, see our wiki page cosmological natural selection (fecund universes). The fine-tuned universe hypothesis also offers one of several examples that the initial conditions of our universe seem self-organized for the emergence of internal complexity and its persistence over billions of years. As in biological genes, only a handful of which are developmental, highly conserved, and finely-tuned, only a handful of these universal parameters seem improbably finely tuned, to a degree far beyond that we would expect through obvious observer-selection effects. See Martin Rees, Just Six Numbers, 1999 for one such account.

If universal evolutionary development is occurring, future science must show that each successive environment in the developmental hierarchy inherits certain initial conditions and physical constancies from the environment that preceded it, back to the birth of the universe, and that some of these initial conditions and constancies act to predictably constrain the future dynamics of each successive environment, to some degree. These constraints have been called developmental portals by some scholars. M-class stars and organic chemistry may be necessary portals to planets capable of generating life. Fats, proteins, and nucleic acids may be necessary portals to cells. Eyes may be necessary portals to higher nervous systems, etc. These portals must also work together to periodically produce a metasystem transition (a higher level of order or control), a new level of ED hierarchy.

Another example of predictable developmental signal, across all of these environments, may be the ever-faster complexification we see in the historical record of the most physically and informationally complex locations in our universe, since the emergence of M-class stars, Earth-like planets, and almost simultaneously, on our planet, life. This acceleration was famously summarized in Carl Sagan's metaphor of the Cosmic Calendar. Ever since August, on this calendar metaphor, leading-edge complexity environments have become exponentially faster, more complex, and more intelligent, on average, on Earth. Sagan said this phenomenon, which we can call acceleration studies, was an understudied area of science, in need of better understanding. See Sagan's The Dragons of Eden (1977) for his original account. It our hope that better models of early universe, astrophysical, chemical, biological, psychological, social, economic, technological, and other evolutionary development will help us understand our universe's emergence record of ever faster and more physically- and informationally-complex local environments.

For a deeper introduction to this topic, see our wiki page, evolutionary development.

Research questions

  • How can we better develop a general theory of both optimizing convergence (OC) and less-optimizing convergence (LOC) so we can reliably differentiate between the two?
  • How much more common is LOC than OC, in various complex systems?
  • When are physical and when are informational forms of optimization more important, in various complex systems?
  • Can a general theory of optimizing convergence (OC) be created without the metaphor of evolutionary development (ED)?
  • How can we better test and develop theories of evolutionary development (ED) at all scales, from organisms to universes?
  • In the theory of evolutionary development (ED), when comparing successively emergent environments (early universe, astrophysics, chemistry, biology, psychology, and societal systems, technological systems), what are the similarities and differences between contingently adaptive ("evolutionary") processes?
  • In the theory of evolutionary development (ED), when comparing successively emergent environments , what are the similarities and differences in processes of apparent high optimization ("developmental") processes?