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Ecosystemforest, meadow and stream — who eats whom

Grass, shrubs and trees, mice, hares and roe deer, and above them foxes, wolves and buzzards. In spring the young are born, in winter food runs short, and fungi and bacteria turn remains into fertile soil. Watch the population cycles and trophic cascades, compare them with the Lotka–Volterra equations, and don't let any species die out.

Year0.0
Grass0%
Saplings0%
Soil fertility0%

Click the world to release 12 hares

Speed (years/s)
Hunting target:

Species abundance

How does it work?

Ecosystem: every animal on its own

In Ecosystem mode each animal is a separate “agent” with a position and an energy reserve. The terrain is a grid of cells: on each one grow grass, shrubs, young trees (saplings) and trees, and a stream with a pond flows through the meadow. The rules are simple:

  • herbivores (mice, hares, roe deer) graze the plants on the cell they stand on and look for better spots; they flee from predators; well-fed animals give birth in the breeding season; hungry ones die; when the area is crowded, fewer young are born;
  • predators (foxes, wolves, buzzards, and after an intervention minks) sniff out prey, chase it and attack; in dense bushes and in the forest prey can hide more easily, and when prey is very scarce it becomes more wary; wolves share their kill with the pack; predators guard territories, so they don't multiply without limit;
  • seasons: in spring plants grow fastest and the young are born, in autumn leaves fall, and in winter plants stop growing, snow makes foraging harder and animals need more energy — it's the hungry season.

The cycling of matter

Dead animals, fallen leaves and dead grass go into the soil as dead organic matter. Fungi and bacteria — the decomposers — break it down (fastest in summer, hardly at all in winter) and release mineral nutrients that make the soil more fertile. On fertile soil plants grow faster. Turn on the “Soil layer” to see where the soil is rich and where the decomposers are at work (glowing dots). After a fire, ash and burnt wood briefly enrich the ground, and then comes succession: first grass, then shrubs, finally trees.

Food web and cascades

In Food web mode the same ecosystem is described by equations — for whole populations, without randomness. The biomass of each consumer Bi changes like this (the Yodzis–Innes bioenergetic model):

dBidt = −xiBi + Σj xiyiBiFij − Σk xkykBkFkieki

The first term is respiration (energy used to stay alive), the second — food turned into the consumer's own body, the third — losses to predators. Fij is the functional response: the more prey, the more a predator eats, but not without limit — eventually it is full. Plants grow logistically, and their growth depends on mineral nutrients from the soil. Remove a species and you'll see a trophic cascade: without wolves roe deer increase, and shrubs and saplings decline. Wolves are only a fraction of a percent of animal biomass, yet they change the whole forest — they are a keystone species.

The 10% rule

Plants capture the Sun's energy, but herbivores assimilate only a small part of it, and predators only a small part of the herbivores' energy. The rest dissipates as heat. In nature, usually 5–20% of the energy passes to the next level (about 10% on average — Raymond Lindeman, 1942). That's why energy pyramids, and usually biomass pyramids too, narrow toward the top.

The Lotka–Volterra equations

Alfred Lotka (1925) and Vito Volterra (1926) independently described predator and prey with two equations. Let x be the number of hares and y the number of foxes (here in hundreds of animals):

dxdt = αx − βxyhares are born and get eaten
dydt = δxy − γyfoxes are born thanks to prey, and die

The product xy says how often a fox meets a hare. The populations stop changing at the equilibrium point:

x* = γδ,    y* = αβ

The equilibrium number of hares depends only on the foxes' parameters, and vice versa. When the start is away from equilibrium, the populations circle along a closed orbit, because the quantity

V = δx − γ ln x + βy − α ln y = const

does not change over time. For small oscillations the period is T ≈ 2π/√(αγ), and the fox peak lags by a quarter of a period. If we add a limited amount of grass (capacity K: dx/dt = αx(1 − x/K) − βxy), the orbit turns into a spiral winding in to equilibrium — the system becomes stable.

The satiated predator and the paradox of enrichment

A real fox can't eat infinitely many hares — it needs a time h to chase and eat each one. This is the type II functional response (Crawford Holling, 1959). The Rosenzweig–MacArthur model:

dxdt = rx(1 − xK) − axy1 + ahx
dydt = eaxy1 + ahx − my

With a small K the populations settle down at equilibrium. But when we “enrich” the environment — raise K above the threshold KH = 2x* + 1/(ah) — the equilibrium loses stability (a so-called Hopf bifurcation) and a limit cycle appears, with ever larger swings. More food for the prey can thus endanger both species. This is the paradox of enrichment (Michael Rosenzweig, 1971).

Competition and Gause's principle

Two species that eat the same thing get in each other's way. The Lotka–Volterra competition model:

dxdt = r1x(1 − x + α12yK1),   dydt = r2y(1 − y + α21xK2)

The coefficient α12 says how strongly one individual of species 2 “takes up room” from species 1. Both species survive when each limits itself more than its rival (α12 < K1/K2 and α21 < K2/K1). Otherwise one displaces the other — this is the competitive exclusion principle. Georgy Gause demonstrated it in 1934 with paramecia grown in test tubes.

How does a computer solve the equations? The RK4 method

The computer moves in small steps h. The 4th-order Runge–Kutta method checks the slope four times within each step and takes a weighted average:

sn+1 = sn + h6(k1 + 2k2 + 2k3 + k4)

As a result, with the default parameters V changes by less than one billionth of its value after a hundred years. Euler's method with the same step would change it by tens of percent.

Simplifications: all the models are sketches, not forecasts. Time is nominal (in the ecosystem 1 year = 120 steps), animals have no sex or families (apart from wolves sharing their kill), buzzards stand in for all birds of prey, and the fish and amphibians that minks eat are not modeled separately. Biomasses in the food web are nominal kg per hectare. The parameters were chosen so that the models behave sensibly, not to reproduce a particular forest. Real hare and lynx cycles also depend on food, disease and stress — not just on predators.

Did you know…?

  • Volterra took up predators at the request of his son-in-law, the biologist Umberto D’Ancona. He had noticed that during World War I, when there was less fishing in the Adriatic, the share of predatory fish in the catch grew. The equations explained why: fishing harms predators more than their prey.
  • The concept of a keystone species was introduced in 1969 by the ecologist Robert Paine. For years before that he had been prying starfish off the rocks on the coast of Washington State. Without them, mussels took over the rocks, and the number of species on the study plot fell by roughly half (from 15 to 8).
  • In some of the Hudson's Bay Company records the cycle looks “backwards”, as if the hares were chasing the lynx. Ecologist Michael Gilpin playfully titled his 1973 paper about it: “Do hares eat lynx?”.

Challenges

  1. Keep hares and foxes alive for 100 yearsIn Ecosystem mode (any scenario), without hares or foxes dying out, and along the way use at least two different interventions (the buttons, or releasing hares with a click).not completed
  2. Drive the hares to extinction and see what happens to the foxesHint: hunting hares, a drought, or the parameters in the simple version. In the full ecosystem, keep watching the foxes for another 5 years.not completed
  3. Bring back the wolves and see a trophic cascadeIn the food web, remove the wolves, wait about 20 years, then restore them — or in the “Forest without wolves” scenario use “Bring back wolves”. Roe deer should drop by ¼, and shrubs and saplings should increase.not completed
  4. Find the equilibrium point of the Lotka–Volterra modelIn Equations mode, choose a start at which the populations don't change at all (to within 3%).not completed
  5. Show the paradox of enrichmentIn the Holling II model, raise the capacity K above the Hopf threshold and wait for lasting oscillations to settle in.not completed
  6. Bring about competitive exclusionIn the Competition model, set the parameters so that one species displaces the other (falling below 1% of its capacity).not completed
  7. Measure the period of the hare cycleIn In nature mode, mark two neighboring peaks in the hare fur counts.not completed