  Network inference is a major field of interest for the ecological community,
especially in light of the high cost and difficulty of manual observation, and
easy availability of remote, long term monitoring data. In addition, comparing
across similar network structures, especially with spatial, environmental, or
temporal variability and, simulating processes on networks to create toy models
and hypotheses - are topics of considerable interest to the researchers. A
large number of methods are being developed in the network science community to
achieve these objectives but either don't have their code available or an
implementation in R, the language preferred by ecologists and other biologists.
We provide a suite of three packages which will provide a central suite of
standardized network inference methods from time-series data (constructnet),
distance metrics (disgraph) and (process) simulation models (dynet) to the
growing R network analysis environment and would help ecologists and biologists
to perform and compare methods under one roof. These packages are implemented
in a coherent, consistent framework - making comparisons across methods and
metrics easier. We hope that these tools in R will help increase the
accessibility of network tools to ecologists and other biologists, who the
language for most of their analysis.
