Density dependence is about crowding
- The idea
- Predict
- See it
- Why
- Check
The idea
“A yearly factor is density dependent, and a random one, like a fire, is density independent.”
The usual density-independent examples are sudden events like fires and floods, so timing seems like the test. They count because they take about the same share at any density.
The short version
The mistake: A yearly factor is density dependent, and a random one, like a fire, is density independent.
What's actually true: A factor is density dependent when the share it removes changes with density, however often, regularly or long it acts.
- A factor is density dependent when its share changes with density. A virus spreads faster among crowded hosts, so it kills a bigger share.
- A hard frost is density independent. It takes about the same share of few caterpillars or many.
- Timing is separate. A factor can strike yearly or once a decade, for a day or for months, and be either kind.
- Density-dependent factors can slow a crowded population's growth, acting as negative feedback.
On the exam: Ignore when, how often or how long it strikes. Ask whether the share it kills rises with crowding.