tempVarH: Create Heterogeneity with Fractional Brownian Nnoise

In gabackus/rcomms: Simulate Randomized Metacommunities under Stochastic Climate Change

Description

This function adds some heterogeneity to the temperature gradient with fractional Brownian noise. See Keitt (2000), Spectral representation of neutral landscapes, Landscape Ecology 15.

Usage

tempVarH(L, H, cZero = T)

Arguments

L	Length of the temperature gradient.
H	Hurst exponent (should be between 0 and 1). It relates to the autocorrelation. When H is near 1, this function has positive long-term positive autocorrelation and will look relatively smooth. When H=0.5, this function is Brownian motion. When H is near 0, then autocorrelation is negative and positive values will more often be followed by negative values (and vice versa).
cZero	If TRUE, it will center the whole output so the mean is 0.

Value

A heterogeneous vector

gabackus/rcomms documentation built on Nov. 4, 2019, 1 p.m.