Spatial populations
Many biological systems depend not only on how many individuals are present but also on where they are located. Spatial models therefore describe population density as a function of both space and time.
In one spatial dimension, a density may be written as
\[u(x,t),\]where \(x\) is position and \(t\) is time.
Why space matters
Movement, local crowding, environmental variation, habitat boundaries and local interactions can all make population behaviour depend on location.
Continuous and discrete space
Space may be represented continuously, using partial differential equations, or divided into patches, sites or network nodes.
Key idea. Spatial models extend ordinary population models by allowing the biological state to vary across location as well as time.