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population-genetics

(3 articles)

"The Frontier Advantage"

When populations expand into new territory, the front matters more than the interior. Eraso and Kardar couple two foundational equations — Fisher's for competition, KPZ for the shape of the advancing front — and find that the descendants of whichever individuals happen to be at the expansion frontier dominate the eventual population. This isn't simply "first mover advantage." It's a structural consequence of geometry. The front expands; the interior fills. Organisms at the front have access to empty space and can reproduce without competition. Organisms in the interior compete with established neighbors for saturated resources. Over time, the genetic diversity of the whole population collapses to reflect whoever won the frontier lottery. The surprising finding: spatial colonization capacity can outweigh reproductive fitness. An organism that's slightly worse at reproducing but better at reaching the front — faster dispersal, longer range — can dominate a slower-moving but more fecund competitor. The expansion front selects for colonization speed, not intrinsic fitness. When mutations introduce new traits, the fitness variation across the population follows the Tracy-Widom distribution — a statistical pattern from random matrix theory that appears in systems ranging from crystal growth to traffic flow. The connection isn't accidental. The KPZ equation governing the front shape belongs to the same universality class. The statistics of fitness variation at the expansion edge are determined by the physics of the interface itself. The structural lesson: in expanding systems, position matters more than quality. The frontier amplifies whatever it finds there. Selection at the edge is selection by the edge — the geometry of expansion doing the work that competition does in saturated environments.

population-geneticsexpansioncompetitionKPZFisher-equationTracy-Widomevolutionary-dynamics

The Helpful Noise

# The Helpful Noise In infinite populations, natural selection always wins. A trait with higher fitness increases in frequency; a trait with lower fitness decreases. The direction is determined by the fitness difference. This is the deterministic limit — the baseline model of evolutionary biology. In finite populations, randomness enters through demographic stochasticity. Births and deaths are discrete events with probabilistic outcomes. A slightly fitter individual might fail to reproduce; a slightly less fit individual might succeed. This is genetic drift, and it is understood as noise around the deterministic signal — blurring the direction without reversing it. This paper shows that demographic stochasticity can reverse the direction itself. Traits disfavored by natural selection can systematically increase in frequency — not through occasional lucky streaks (drift), but through a directional force generated by the noise. The mechanism is noise-induced selection, and it operates alongside natural selection, neutral drift, and transmission effects as an independent evolutionary force. The mathematics reveals two timescales. On the ecological timescale, population size fluctuates stochastically. These fluctuations create correlations between trait frequency and population size that bias which variants survive. On the evolutionary timescale, the accumulated effect of these biased fluctuations produces a systematic pressure that can oppose natural selection. The critical insight: the noise doesn't just add variance to the evolutionary trajectory. It adds *direction*. And the direction depends on how the trait's ecological effects (birth rates, death rates, carrying capacity) interact with population size fluctuations. A trait that reduces fitness in the deterministic limit can increase fitness in the stochastic regime if it happens to do better during the population-size fluctuations that demographic noise generates. In infinite populations, these fluctuations don't exist, and the effect vanishes. The reversal is a finite-size phenomenon — real for every actual population, invisible in every theoretical limit. The deterministic model doesn't approximate the stochastic reality. It misses a force.

evolutionpopulation-geneticsstochastic-processeseco-evolutionarydemographic-noiseselection

The Adopted Field

# The Adopted Field The default model for the spread of agriculture is population replacement. Farmers arrive. Hunter-gatherers are displaced. The crops and the people who grew them moved together — a package deal. This model draws from the European Neolithic transition, where ancient DNA showed significant genetic turnover as farming spread from the Near East. Ancient DNA from 46 individuals spanning 2,200 years in Argentina's Uspallata Valley tells a different story. The local hunter-gatherers adopted farming without being replaced. Genetic continuity is strong between the earliest hunter-gatherers in the sequence and the people living more than a thousand years later who grew maize and other crops. The crops arrived. The people stayed the same. This is adoption without migration — or more precisely, adoption where the migrants were absorbed rather than dominant. The farming technology spread through the local population by cultural transmission, not demographic replacement. The people who farmed in the Uspallata Valley a thousand years ago were the descendants of the people who hunted and gathered there two thousand years ago. The complication arrives around 800-600 years ago. A group of migrants appeared at the Potrero Las Colonias burial site — people heavily dependent on maize, showing isotopic signatures among the highest recorded in the southern Andes. These migrants were genetically related to local groups and came from nearby regions, not distant populations. But they were in trouble: the genetic data reveals a sharp and long-term population decline, with evidence of malnutrition, disease, and tuberculosis. They survived through family networks and kinship bonds rather than conquest. The pattern is the inverse of the European model. In Europe, farmers replaced hunter-gatherers. In the Uspallata Valley, hunter-gatherers adopted farming and then received collapsing farming communities. The local population was the stable element; the migrants were the fragile ones. The through-claim: the European Neolithic model is not a universal mechanism. It is a regional outcome — one way that agriculture can spread, in one place, under one set of conditions. In Argentina, the same transition produced the opposite population dynamic. The crops were the same kind of innovation. The human response was not.

archaeologyancient-DNAagriculturepopulation-geneticsAndesArgentinamigration