Characterising and Locating Ecotones and Communities
Clustergram base function
Vegclust clustering with fuzzy indices computation for clustergram
Vegclust function for clustergram
Clustergram with fuzzy indices plot
Tool to assign color to species distribution plots given fuzzy cluster...
Re-ordering columns in dataframes:
qpcR cbind.na method.
cmeans clustering with fuzzy indices computation for clustergram
cmeans function for clustergram
Type function that clustergram takes for clustering.
Plot function for clustergram
Adaptation of the curve function (without plot).
Tools for internal data structure exploration
Wraper function to perform ecological gradient analysis
Extension of EcotoneFinder for space/time series
Visualisation of fuzzy centroids:
Plot function for fuzzy indices with clustergram.
GGplot method for EcotoneFinder
Perform Spinglass algorythm and find networks communities
Networks for ecotones and communities
Networkeco for data series
Plotting component for EcotoneFinder
Plot method for EcotoneFinder
Plotting component for EcotoneFinder when run on environmental data
Plotting component for Slope
qpcR rbind.na method.
Method to calculate the derivative of irregular functions:
Create synthetic gaussian-shaped species abundance data
Synthetic data for Space/Time series
Analytical methods to locate and characterise ecotones, ecosystems and environmental patchiness along ecological gradients. Methods are implemented for isolated sampling or for space/time series. It includes Detrended Correspondence Analysis (Hill & Gauch (1980) <doi:10.1007/BF00048870>), fuzzy clustering (De Cáceres et al. (2010) <doi:10.1080/01621459.1963.10500845>), biodiversity indices (Jost (2006) <doi:10.1111/j.2006.0030-1299.14714.x>), and network analyses (Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>) - as well as tools to explore the number of clusters in the data. Functions to produce synthetic ecological datasets are also provided.