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.