AHMbook (version 0.2.10)

sim.fn: Simulate a Poisson point process

Description

Simulates animal or plant locations in space according to a homogenous Poisson process. This process is characterized by the intensity, which is the average number of points per (very small)unit area. The resulting point pattern is then discretized to obtain abundance data and presence/absence (or occurrence) data. The discretization of space is achieved by choosing the cell size. It is used in AHM1 Section 1.1 to help to understand the relationship between point patterns, abundance data and occurrence data (also called presence/absence or distribution data). For a similar and somewhat more sexy version of this function, see simPPe.

Usage

sim.fn(quad.size = 10, cell.size = 1, intensity = 1, show.plot = TRUE)

Value

A list with the values of the arguments and the following additional elements:

exp.N

Expected population size in quadrat

breaks

boundaries of grid cells

n.cell

Number of cells in the quadrat

mid.pt

Cell mid-points

M

Realized population size in quadrat

u1

x coordinate of each individual

u2

y coordinate of each individual

N

The number of individuals in each cell (a vector of length n.cell)

z

Presence/absence (1/0) in each cell (a vector of length n.cell)

psi

Proportion of cells occupied, ie, the species is present.

Arguments

quad.size

The length of each side of the quadrat (in arbitrary units)

cell.size

The length of each side of the cells into which the quadrat is divided. The ratio of quad.size to cell.size must be an integer.

intensity

The average number of points (animals or plants) per unit area.

show.plot

If TRUE, the results are plotted. Set to FALSE when running simulations.

Author

Marc Kéry and Andy Royle

References

Kéry, M. & Royle, J.A. (2016) Applied Hierarchical Modeling in Ecology AHM1 - 1.1.

Examples

# Generate a simulated data set with default arguments and look at the structure:
tmp <- sim.fn()
str(tmp)

# Effect of grain size of study on abundance and occupancy (intensity constant)
tmp <- sim.fn(quad.size = 10, cell.size = 1, intensity = 0.5)
tmp <- sim.fn(quad.size = 10, cell.size = 2, intensity = 0.5)
tmp <- sim.fn(quad.size = 10, cell.size = 5, intensity = 0.5)
tmp <- sim.fn(quad.size = 10, cell.size = 10, intensity = 0.5)

# Effect of intensity of point pattern (intensity) on abundance and occupancy
tmp <- sim.fn(intensity = 0.1) # choose default quad.size = 10, cell.size = 1
tmp <- sim.fn(intensity = 1)
tmp <- sim.fn(intensity = 5)
tmp <- sim.fn(intensity = 10)