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

Inferring, comparing and exploring ecological networks from time-series data through R packages constructnet, disgraph and dynet