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Types of PP data, Things to consider in PP analysis - Coggle Diagram
Types of PP data
1) Number of species
1 = Univariate
E.g. Distribution of Kauri in the landscape
2 = Bivariate
E.g. Comparing the distribution of Kauri and Rimu in the landscape
3+ = Multivariate
E.g. Comparing the distribution of conifers in the landscape
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)
2) Mapped co-variate Y/N
Is there an environmental gradient in your map (e.g. Elevation?)
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.