Types of PP data

1) Number of species

1 = Univariate

2 = Bivariate

3+ = Multivariate

E.g. Distribution of Kauri in the landscape

E.g. Comparing the distribution of Kauri and Rimu in the landscape

E.g. Comparing the distribution of conifers in the landscape

2) Mapped co-variate Y/N

Is there an environmental gradient in your map (e.g. Elevation?)

3) Do my data have marks?

None - all trees are the same (they only differ by species)

Qualitative - They can be classed as various categories (Alive, Dead)

Quantative - They can be classed by another metric (e.g. Size, Canopy Health)

Things to consider in PP analysis

Requirements

Good size - needs to be larger than potential clusters to get an accurate representation of the data

Good shape = rectangle, long and narrow plots increase the amount of 'Exterior' habitat that is not as useful

High number of points = at least 100

Homogeneity - processes that govern the formation of a point the same across map

Isotropic = same even if you rotate plot

Allows the creation of 'Typical points'

can calculate mean number of points within certain distance of typical point

Can also create probabilites of a nearest neighbour being within a certian dist from a point

Non homogeneity

Caused by features in environment e.g. Rock formations, changes in soil

Some = hard to find

Can be created based on individuals

Dispersal limited spp can leave spaces unoccupied

Invasive spp = spreading throughout plot - start in one corner and haven't dispersed through plot yet

Threatened spp = retracting from plot = not found in suitable habitat anymore.

Dimensionality

Assumes that invididuals do not have dimensions themselves - not much of a problem in forest ecology.