Research plans
Explaining the repeated evolution of complex social traits
My proposed laboratory program combines comparative biology, field and laboratory experiments, and evolutionary modeling to investigate how genetic kin recognition and related social traits originate, diversify, and persist.
Social amoebae provide a tractable empirical system in which predictions from association theory can be tested across species and under controlled ecological conditions. The program connects behavior, development, population genetics, and major transitions in biological organization.
Why genetic kin recognition?
Genetic kin recognition is one of the most complex and repeatedly evolved social traits in nature. Systems that allow organisms to preferentially associate with some conspecifics and avoid others have evolved independently in bacteria, fungi, slime molds, marine invertebrates, protochordates, and vertebrates. These systems often rely on highly polymorphic genetic cues and mediate decisions about fusion, aggregation, cooperation, and conflict. Yet we still lack a general explanation for how such recognition systems originate, diversify, and persist across lineages.
My research addresses this problem by combining evolutionary theory, comparative biology, and experimental work in social amoebae.
Why social amoebae?
Social amoebae vary in association behavior, migration strategy, and investment in sterile stalk structures within a well-resolved phylogenetic framework. Many species are common in nature and amenable to field collection, laboratory culture, and experimental study.
This variation makes it possible to examine the evolutionary relationships among the costs of chimerism, discriminatory conflict, and segregation. It also allows tests of why closely related species differ in the strength of kin discrimination. More than a century of work in cell and developmental biology also provides an unusually rich foundation for connecting genetic mechanisms to evolutionary outcomes.
A central puzzle
In Dictyostelium discoideum, the linked receptor–ligand genes tgrB1 and tgrC1 can mediate discriminatory segregation. Yet naturally co-occurring clones generally segregate weakly. What maintains recognition-cue variation when its apparent effect on segregation is modest? Comparative and experimental approaches can distinguish alternative explanations.
Four complementary research aims
01 · Identify the drivers of chimeric incompatibility and association preference
I will test the hypothesis that the strength of chimeric incompatibility selects for association preference through aggregation and segregation. Comparative analyses across the social amoeba phylogeny will quantify stalk investment, migration strategy, the costs of chimerism, and segregation behavior.
Key prediction: Species with greater allocation to stalk should exhibit stronger chimeric incompatibility, which in turn should favor stronger association preference.
02 · Develop comparative and high-throughput assays
Standardized assays will make it possible to measure segregation and the costs of chimerism across multiple species. Traditional fluorescent labeling and genetic markers can be combined with sensitive imaging and automated video analysis.
I have already explored approaches involving the measurement of spore and stalk masses and videography of segregation. Developing efficient assays will enable comparative tests at a scale that would be difficult with conventional methods.
03 · Experimentally test the origin and loss of kin recognition
Experimental evolution, serial passage, and mutation-accumulation approaches will examine how recognition systems arise, decay, or re-emerge under controlled ecological conditions.
A central question is whether loci other than tgrB1/tgrC1 contribute to the costs of chimerism. Such loci could provide a basis for testing whether variation in cues used for discriminatory conflict selects for greater polymorphism in a separate cue used for segregation.
04 · Develop models tied to microbial life histories
In parallel with the empirical work, I will develop population-genetic and game-theoretic models suited to haploid organisms with rare sexual stages, together with complementary diploid models relevant to marine invertebrates.
The models will represent association preference and differential treatment separately, generate quantitative predictions, and guide the design and interpretation of comparative and experimental tests. Agent-based simulations are a developing direction for exploring these models. An initial planned application is to compare my proposed historical process for the evolution of genetic kin recognition with that of Scott et al. (2022), under explicitly defined assumptions, and follow the evolution of association-preference cue polymorphism through time.
Additional experimental directions
Migration strategies
Species differ in whether they migrate without stalk, produce stalk briefly, or sustain stalked migration. Comparative work can identify hypotheses for this variation, while experiments in species with facultative behavior and experimental evolution can test the ecological conditions favoring different strategies.
Phenotype switching
I also plan to investigate phenotype switching in D. discoideum, in which apparent mutants can arise without genetic change. The work will ask whether switching occurs in wild clones and whether it can permit cheating. This connects microbial social evolution with broader questions about phenotypic variation and persistence.
Current theoretical foundations
My current work develops a genealogical bridge between population-genetic, inclusive-fitness, and regression models of social evolution. By explicitly defining association, social action, transmission, and reproductive success, I examine which biological effects each representation retains.
Social action and empirical measurement
I distinguish the benefits and costs of social action from the automatic effects of association. This guides the choice of empirical baselines and the interpretation of regression parameters.
Selection and the selective background effect
I distinguish the effect responsible for allele-frequency change from the selective background effect produced as the genetic and social environment changes. This connects Hamilton’s rule with adaptive landscapes and changes in mean reproductive success.
Historical causes and long-term consequences
My kin-recognition models examine how a complex trait can originate through a sequence of selective changes and later have incidental protective effects. This provides a bridge to my work on natural reward, ecological expansion, and macroevolutionary innovation.
An integrated laboratory program
Comparative observations will identify patterns requiring explanation; explicit models will generate predictions; and controlled experiments will test the mechanisms responsible. These approaches will inform one another as the program develops.
Projects can engage students at multiple levels, from field collection and behavioral assays to image analysis, comparative studies, and evolutionary modeling. The shared goal is to explain how complex social traits evolve repeatedly across lineages.