The Lotka-Volterra equations are a pair of first-order nonlinear differential equations used to model predator-prey interactions in biological systems.In the 1920s, American mathematician Alfred Lotka and Italian physicist Vito Volterra independently derived a system of two differential equations describing the dynamics of interacting populations. Lotka was interested in chemical reactions and extended the idea to ecology, while Volterra responded to a zoologist's request to explain strange fluctuations in fish catches in the Adriatic after World War I. The equations are simple: the growth rate of prey is proportional to their numbers but decreases proportionally to encounters with predators; the growth rate of predators is proportional to their numbers and the number of prey, but there is also natural mortality. The solution yields neutral cycles: the amplitude of oscillations depends on initial conditions, and the slightest perturbation changes the trajectory forever. This is an idealization: in reality, cycles often dampen or become chaotic due to external factors.
Alfred Lotka in 1920 published a paper on chemical oscillations, where he presented equations for autocatalytic reactions, and in 1925 in his book 'Elements of Physical Biology' applied them to ecology. Vito Volterra in 1926, inspired by fish catch data shown to him by his son-in-law, zoologist Umberto D'Ancona, derived the same equations and investigated their properties. Interestingly, Volterra initially considered the model as an argument against overfishing: he showed that a proportional increase in fishing of both species paradoxically increases the proportion of predators. Later, the model was extended to competition, mutualism, and systems with delays.
Applied for qualitative analysis of ecological systems: predicts cyclicity, estimates extinction thresholds, and helps design biocontrol strategies. For example, in fisheries, the model explains why intensive harvesting of predators can lead to outbreaks of low-value species. Limits of applicability: assumes a homogeneous environment and instantaneous population response, which is violated in real ecosystems with seasonality, migrations, and evolutionary adaptation.
Forecasting pest population outbreaks in agriculture and assessing the stability of rare species populations in nature reserves.
Volterra arrived at his model while pondering fishing: during the war, fishing ceased, and the proportion of predatory fish in catches increased. He realized that reduced harvesting of prey led to an increase in predators — pure mathematics.
| α | variable | Scaling exponent (same as in power law) |
| K | variable | Luttinger parameter — luttinger parameter |









