Description Usage Arguments Details Value References Examples
This function will simulate 3-dimensional landscapes of varying complexity.
1 | varLandscape(cells, seeds = 1, exponent = 1, cutoff = 0)
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cells |
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 distinct 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. |
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.
A square matrix of dimensions cells x cells.
Miller, E. T. 2016. A new dispersal-informed null model for community ecology shows strong performance. biorxiv.
1 2 | plotrix::color2D.matplot(varLandscape(10, seeds=1, exponent=1, cutoff=0),
cs1=c(0.2,0.4,0.8), cs2=c(0,0.5,0.8), cs3=c(1,0.5,0), border=NA)
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