The number of cells to divide each side of the arena into. Larger values
provide smoother looking surfaces, but values larger than 100 can require too much RAM
to run.
seeds
The number of "peaks" or trait "optima" that will be chosen in the
landscape. Default is 1.
exponent
The exponent to which the distances will be raised. Default is 1.
Values larger than 1 have the effect of making distance decay slowly at first, then
drop off more quickly at the end, while values smaller than 1 have the effect
of dropping off quickly and then decreasing slowly.
cutoff
Values below which distances from the focal cell will be converted to
zero. This operates after the exponent is applied to the distance matrix, and after the
distances specific to a given focal cell have been scaled to min 0 max 1. The default
cutoff is zero, meaning that all but the most distanct cells are still influenced by
the new optimum of the focal cell. Increasing this number towards 1 has the effect of
minimizing the distance over which the focal cell influences neighboring cells.
Value
A square matrix of dimensions cells x cells.
Details
This function forms the guts of a new habitat filtering spatial simulation.
The output from the function is a square matrix with values corresponding, in my mind,
to optimum trait values for a location in 2d space. Alternatively, this might be useful
for simulations of elevational gradients. A good sequence to show how landscapes can be
varied might be (all with cells = 100 and exponent = 1) to change seeds from 1 to 2 to
10 while holding cutoff at 0. Then change cutoff from 0.01 to 0.1 to 0.9 while holding
seeds at 10.
References
Miller, E. T. 2016. A new dispersal-informed null model for
community ecology shows strong performance. biorxiv.