synchrony-package {synchrony}

Methods for Computing Spatial, Temporal, and Spatiotemporal Statistics

Description

Methods for computing spatial, temporal, and spatiotemporal statistics as described in Gouhier and Guichard (2014) <doi:10.1111/2041-210X.12188>. These methods include empirical univariate, bivariate and multivariate variograms; fitting variogram models; phase locking and synchrony analysis; generating autocorrelated and cross-correlated matrices.

Details

Package:	synchrony
Type:	Package
Version:	0.3.8
Date:	2019-12-05
License:	GPL (>=2)
URL:	https://github.com/tgouhier/synchrony
LazyLoad:	yes

Author(s)

Tarik C. Gouhier ([e-mail])

Maintainer: Tarik C. Gouhier ([e-mail])

References

Bjornstad, O. N., and W. Falck. 2001. Nonparametric spatial covariance functions: Estimation and testing. Environmental and Ecological Statistics 8:53-70.

Bjornstad, O. N., R. A. Ims, and X. Lambin. 1999. Spatial population dynamics: analyzing patterns and processes of population synchrony. Trends in Ecology & Evolution 14:427-432.

Buonaccorsi, J. P., J. S. Elkinton, S. R. Evans, and A. M. Liebhold. 2001. Measuring and testing for spatial synchrony. Ecology 82:1668-1679.

Cazelles, B., and L. Stone. 2003. Detection of imperfect population synchrony in an uncertain world. Journal of Animal Ecology 72:953-968.

Fortin, M. J., and M. R. T. Dale. 2005. Spatial Analysis: A Guide for Ecologists. Cambridge University Press.

Gouhier, T. C., and F. Guichard. 2007. Local disturbance cycles and the maintenance of spatial heterogeneity across scales in marine metapopulations. Ecology 88:647-657.

Gouhier, T. C., F. Guichard, and A. Gonzalez. 2010. Synchrony and stability of food webs in metacommunities. The American Naturalist 175:E16-E34.

Gouhier, T. C., F. Guichard, and B. A. Menge. 2010. Ecological processes can synchronize marine population dynamics over continental scales. Proceedings of the National Academy of Sciences 107:8281-8286.

Loreau, M., and C. de Mazancourt. 2008. Species synchrony and its drivers: Neutral and nonneutral community dynamics in fluctuating environments. The American Naturalist 172:E48-E66.

Purves, D. W., and R. Law. 2002. Fine-scale spatial structure in a grassland community: quantifying the plant's eye view. Journal of Ecology 90:121-129.

Vasseur, D. A. 2007. Environmental colour intensifies the Moran effect when population dynamics are spatially heterogeneous. Oikos 116:1726-1736.

Zar, J. H. 1999. Biostatistical Analysis, Fourth edition. Prentice-Hall, Inc., Upper Saddle River, NJ.

Examples

# Compute phase synchrony
t1=runif(100)
t2=runif(100)
sync=phase.sync(t1, t2)
# Distribution of phase difference
hist(sync$deltaphase$mod_phase_diff_2pi)

# Compute concordant peaks
p=peaks(t1, t2, nrands=100)
# Find proportion of time steps where both time series peak together
p$peaks
# Plot (null) distribution of proportion of time steps where both time
# series peak together
hist(p$rand)
# p-value of observed value
p$pval

# Compute Kendall's W 
data(bird.traits)
(w=kendall.w(bird.traits))

# Community matrix for 20 species undergoing random fluctuations 
comm.rand=matrix(runif(100), nrow=5, ncol=20)
community.sync(comm.rand, nrands=10)
# Community matrix for 20 species undergoing synchronized fluctuations 
comm.corr=matrix(rep(comm.rand[,1], 20), nrow=5, ncol=20)
community.sync(comm.corr, nrands=10)