Why fewer fishing boats in wartime meant more sharks in the nets
During the First World War, Adriatic fishing almost stopped, and when catches resumed a marine biologist noticed something odd: a larger share of predatory fish. He asked his girlfriend's father, the mathematician Vito Volterra, to explain it. The answer was a pair of equations that still anchors ecology.
The biologist was Umberto D'Ancona, who later married Volterra's daughter. Intuition said that with less fishing, the prized prey species should have boomed. Volterra's model, published in 1926, showed why predators benefited instead. Unknown to him, Alfred Lotka had already reached the same equations, first for chemical reactions in 1910 and later for plants and herbivores and for predators and prey. Volterra credited him, and the pairing of names stuck.
The logic is simple enough to say in words. Left alone, prey multiply exponentially. They are eaten at a rate proportional to how often predators and prey bump into each other. Predators grow in step with what they catch and die off steadily without food. Run those rules forward and the two populations chase each other in endless cycles, with predator numbers peaking a quarter-cycle behind prey. Real records show such swings: the Hudson's Bay Company's lynx and snowshoe hare pelts, and the wolves and moose of Isle Royale.
The model's counterintuitive twist is that the balancing level of prey depends only on the predators' traits, and vice versa. Improve conditions for the prey and, at equilibrium, you get more predators, not more prey. That is exactly D'Ancona's wartime puzzle. It also explains a disappointment in ocean iron fertilisation experiments: the added iron sparked brief blooms of plankton that grazers quickly ate, so most of the gain ended up as extra predators rather than captured carbon.
Its assumptions are plainly unrealistic, from unlimited food for prey to no ageing, no geography and no evolution, and later versions added limits on prey growth and more realistic feeding. Economists borrowed it too. Richard Goodwin used it in the 1960s to model wages and employment, drawing parallels with class conflict, and marketers use it for rival firms competing for share.
Source: Lotka–Volterra equations
