Creates 'graphs' of species associations (interactions) and ordination biplots from 
    co-occurrence data by fitting discrete gaussian copula graphical models. Methods described in
    Popovic, GC., Hui, FKC., Warton, DI., (2018) <doi:10.1016/j.jmva.2017.12.002>.

A framework to simulate ecosystem dynamics through ordinary differential equations (ODEs). 
    You create an ODE model, tells 'ecode' to explore its behaviour, and perform numerical 
    simulations on the model. 'ecode' also allows you to fit model parameters by machine learning 
    algorithms. Potential users include researchers who are interested in the dynamics of ecological 
    community and biogeochemical cycles.

Biotracers and stomach content analyses are combined in a Bayesian hierarchical model
    to estimate a probabilistic topology matrix (all trophic link probabilities) and a diet matrix 
    (all diet proportions).
    The package relies on the JAGS software and the 'jagsUI' package to run a Markov chain Monte Carlo 
    approximation of the different variables.

Dissimilarity-based analysis functions including ordination and Mantel test functions, intended for use with spatial and community ecological data. The original package description is in Goslee and Urban (2007) <doi:10.18637/jss.v022.i07>, with further statistical detail in Goslee (2010) <doi:10.1007/s11258-009-9641-0>.

Computes alpha and beta diversity metrics using concurrent 'C' threads.
    Metrics include 'UniFrac', Faith's phylogenetic diversity, Bray-Curtis
    dissimilarity, Shannon diversity index, and many others.
    Also parses newick trees into 'phylo' objects and rarefies feature tables.

Fit and sample from the ensemble model described in Spence et al (2018): "A general framework for combining ecosystem models"<doi:10.1111/faf.12310>.

Simulates the soil water balance (soil moisture, evapotranspiration, leakage and runoff), rainfall series by using the marked Poisson process and the vegetation growth through the normalized difference vegetation index (NDVI). Please see Souza et al. (2016) <doi:10.1002/hyp.10953>.