Ecosystem Species Diversity Simulator

Community Drivers

Disturbance rate 0.20

Immigration rate 0.15

Competitive dominance 0.30

Diversity Indices

Richness S

Individuals N

Shannon H′

0.00

Simpson 1−D

0.00

Evenness J′

0.00

Generation

Species Abundance

How it works

Each of the 96 plots in the meadow holds one individual belonging to one of up to 10 species. Every generation, a plot can be cleared by a disturbance event, refilled by an immigrant of a random species, or recolonised by a neighbour — weighted so that species with higher competitive dominance spread faster into open ground, exactly like a stochastic Lottery / neutral-competition community model.

Shannon:  H' = −∑ p_i · ln(p_i)
Simpson:  D  = ∑ p_i²      (index shown here: 1−D)
Evenness: J' = H' / ln(S)

where p_i is the fraction of individuals belonging to species i, and S is the number of species present (richness).

Disturbance rate — probability per generation a plot is cleared (fire, grazing, frost). Too high collapses richness; a moderate level can raise it (intermediate-disturbance effect) by preventing any one species from dominating.
Immigration rate — probability a cleared/open plot is filled by a fresh migrant of a random species rather than a local competitor, which is what keeps rare species from going locally extinct.
Competitive dominance — how strongly higher-ranked species out-compete lower-ranked ones when spreading into open plots. At 0 all species are neutral (pure ecological drift); high values drive competitive exclusion toward one or two species.

This is the same richness/evenness accounting real field ecologists use on quadrat survey data — only here the population dynamics generating the counts run live in front of you.

Meadow plot = 1 individual

Colour = species identityHeight = local crowding

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