A great opportunity
A historical perspective
When I first sought to study social amoebae, it was because experiments on one species, Dictyostelium discoideum, could test a key theoretical assumption. This assumption was that kin recognition evolves in response to cheaters. My experiments called this assumption into question, and so I developed an alternative model of kin recognition. My model suggested that kin recognition is a more complex trait than usually assumed. Would social amoebae, however, be a good model system for studying the evolution of a complex trait? An ideal model system would be composed of many species that vary in a key subtrait. Fortunately, social amoebae are an ideal model system because they vary in stalk production, which determines the potential for conflict and thus selection for kin recognition (according to my model).
Among all microbes subjected to social-evolutionary study, social amoebae have the best-characterized phylogenetic, taxonomic, and biogeographical distribution. This owes in large part to a community of naturalists who have been interested in these organisms in their own right. Yet, the data collected affords the perfect opportunity to study the evolution of a complex trait. There are a number of common species that exhibit variation in the key trait of stalk production that determines the potential for conflict and selection for kin recognition. Many of these species are common in nature and amenable to field and laboratory study (see figure). Therefore, the history of research on social amoebae makes them an ideal model system for studying the evolution of a complex trait.
A note on model systems
Usually, when a model organism is such a useful tool for research, one initial laboratory gives rise to others. For example, T. H. Morgan’s lab quickly gave rise to numerous other labs studying Drosophila. This meant that students graduating from one lab could join others, and continue their research on Drosophila. In contrast, when I graduated from the Strassmann-Queller laboratory, there were no other laboratories studying social amoebae from a social-evolutionary approach. I had an opportunity to study yeasts as a postdoc, but the system was not yet developed in the same way. This seemed highly unfortunate, because if there had been another laboratory studying social amoebae, I could have continued my research. To amend this situation, I would like to found a new lab studying social amoebae from a social-evolutionary approach.
Motivation
In what follows, I will give background on standard approaches to studying macroevolution, including the origin of complex traits and the major trends of evolution. I will then explain my own approach and how it relates to my proposed studies of social amoebae. My goal here is to give background to my research, not to explain the proposed lines of research (included in my research proposal).
NeoDarwinian approaches to macroevolution
NeoDarwinists have bridged microevolution and macroevolution by focusing on simple quantitative traits like body size. If all traits evolve as if they were simple, then complex traits would be explained as natural selection pushing populations up “peaks” on adaptive landscapes. In turn, the course of evolution would be dominated by known microevolutionary factors like mutation, genetic drift, migration, and natural selection. Among these factors, natural selection is the only non-random evolutionary force.
This view of macroevolution differs from Darwin’s because it considers mutation, drift, and migration—a larger focus on processes that are relatively random with respect to adaptation and the origin of diversity. For the most part, however, evolutionists see the major trends of macroevolution, for example increasing diversity and complexity, as resulting from natural selection continued into vast expanses of time. The NeoDarwinian view states that natural selection has created the patterns, which over time record the history of life and constrain what natural selection can later accomplish. If some macroevolutionary phenomena seem anomalous, for example apparently progressive trends, punctuated equilibrium, or the ubiquity of sexual reproduction in higher plants and animals, the paradigm states that the best recourse is to return to natural selection for an explanation.
This NeoDarwinian theory of macroevolution stems mainly from the field of quantitative genetics, but it meshes with social theory. In social theory, evolutionists have typically treated complex traits as if they were simple. This has yielded a picture of evolution that agrees with adaptive landscapes. The idea that organisms “maximize inclusive fitness” is a derivative of the idea behind adaptive landscapes—that “fitness maximization” pushes populations up peaks.
Some evolutionists are critical of adaptive landscapes and of maximization principles, in part because fitness has not been shown to maximize in general when it depends on more than one gene (including “inclusive fitness” and “regular fitness”). Such critics often say that complex genetics “constrain” natural selection, and therefore that it is important to identify the “genotype-phenotype map.” Such critics, however, unwittingly adhere to the NeoDarwinian paradigm because they assume that natural selection is the only non-random force of evolution. Therefore, their criticisms usually fall on deaf ears—with the response being that natural selection is the only force capable of explaining adaptation, complexity, diversity, and other evolutionary phenomena.
My perspective
A growing number of studies have revealed that complex traits are sometimes composed of interacting sub-traits, where the subtraits evolve for reasons that have nothing to do with their ultimate impacts as part of complex wholes. This phenomenon might be called “multicomponent emergence.” Multicomponent emergence differs from “exaptation” because it involves the emergent function of multiple traits, rather than the cooption of a single trait for a new purpose.
In 2020, I explained the importance of this type of emergence for macroevolution. If the subparts of complex traits originate without foresight for the emergent functions as parts of complex wholes, then it follows that complex traits originate for reasons that may have little to do with their ultimate causes for success. For example, in the Lenski Long Term Evolutionary Experiment, most of the components of a metabolic system that allowed exploitation of a novel resource zone originated for reasons that had nothing to do with metabolizing the resource. Only some of the final steps involved fine tuning for this purpose, and only once an adaptive threshold was reached did the population expand. Therefore, the ultimate impact on population expansion was decoupled from the cause(s) for origin.
These findings, and others, suggest that there is a “randomness of invention” in evolution, in which only some inventions result in major population expansions. Population expansion results in diversification and specialization to a resource base. If diversification and specialization protect incumbents from invasion by future competitors, then those who expand first gain an incumbent advantage. In agreement with this, paleontological studies found that for incumbents to be replaced, they must usually dwindle or go extinct first. Similar results have been found in laboratory studies of microbes.
If the first organisms to expand in population are “naturally rewarded” with an incumbent advantage, then what is the unit being rewarded? It is the genetic system shared by the higher taxonomic category that receives the incumbent advantage. I therefore argued that “natural reward” is a second non-random evolutionary force, which acts upon higher levels of the genetic hierarchy. I used the term “reward” as Darwin used the term “selection” to make an analogy between something that humans do and something that happens in nature. Just as humans reward innovation with intellectual property and contract laws in capitalistic economies, which endow an incumbent advantage to companies whose “DNA” caused them to create and disseminate inventions first, so nature rewards genetic systems that cause them to expand and diversity first with an incumbent advantage.
I will not here explain all of the implications of this new macroevolutionary theory. Rather, I note that many evolutionists have assigned foresight to natural selection, and formulated models of saltational evolution to explain traits for their future effects. I believe this is because there has always been a self-contradiction in Darwin’s theory, about whether natural selection acts only through small modifications and through gradual, stepwise processes, producing relative progress; or whether it acts through major leaps and for ultimate goals, producing absolute progress. Even Darwin himself created confusion on this subject, often referring to natural selection as acting only for immediate benefits and through minor, gradual changes, while elsewhere arguing that traits, like sex ratios, evolve for species-level benefits, or that natural selection produces overall progress as newer forms of life directly supplant their “less-improved” ancestors. While some evolutionists have been content to apply natural selection narrowly, as Darwin usually did, others have assigned foresight and the ability to take major leaps to natural selection. This ultimately stems from an inherent contradiction in Darwin’s theory and a yearning to explain macroevolution.
In the field of social evolution, motivated by “inclusive fitness” and the idea that traits originate for their ultimate benefits to immortal genes, many evolutionists have assigned foresight to natural selection. They have thus surmised that if a trait might promote the evolution of cooperation, then it could evolve for this purpose. Explicit models therefore assume that two traits evolve simultaneously through linkage disequilibrium of the genes coding for them. This approach was used to explain kin recognition and other traits that might promote the evolution of cooperation, like breeding systems and bottlenecked life cycles. The paradigm suggests a simplistic view of macroevolution, in which natural selection for cooperation drives the origin of population-structuring traits that facilitate the origin of organisms and the diversification of life. Yet, this approach has produced minimal explanatory power for the traits thought to evolve through saltation, and most empirical evidence contradicts it.
Approach to studying social amoebae
The utility of my broader macroevolutionary perspective for everyday research is that it allows me to winnow the principle of natural selection to its most effective use—as a short-sighted force that acts through minor modifications, and which gradually builds complex traits through stepwise processes. After all, there is no need to make natural selection do what natural reward can accomplish, i.e., as a force that acts through transient population increases and produces progress on an absolute scale (greater numbers, diversity, command over resources, etc.). For some people, this might seem like a roundabout way of saying that I will just approach the study of evolution correctly, in the way that many evolutionists already know to be the best. Indeed, Darwin himself most often broke complex traits into simpler components and inferred how they historically evolved. Darwin also often took a lack of fitness as evidence of natural selection over teleological design. Many evolutionists today utilize natural selection in this way, so to them my approach is well accepted as a “gold standard.”
Therefore, it is worth emphasizing that in the field of social evolution, employing a standard Darwinian approach to biology leads to much resistance, because it questions the dogma of whole-organism maximization principles. Indeed, social evolutionists have reinterpreted the entire history of biology to agree with their perspective, in my view, misrepresenting the works of Darwin and Fisher. My approach to explaining kin recognition with historical models has thus encountered much resistance, often based on a priori arguments that my “historical approach” does not conform to the dogma of general “fundamental theorems.” The simple fact, however, is that my models have yielded useful predictions for empirical research, and many of them have been supported by empirical evidence. This alone should be sufficient reason to employ my perspective as a guide for empirical research. However, I have also given a bigger picture that justifies why I depart from a paradigm that make natural selection into a force that acts for future benefits or through major leaps, which in my view, erases the power of natural selection as an explanatory tool. This is why I started my original 2015 paper on kin recognition with the following quote from Darwin, “He who believes that some ancient form was transformed suddenly… will further be compelled to believe that many structures beautifully adapted to all the other parts of the same creature and to the surrounding conditions, have been suddenly produced; and of such complex and wonderful coadaptations, he will not be able to assign a shadow of an explanation.”