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R CMD Check lint codecov Project Status: Active – The project has reached a stable, usable state and is being actively developed. CRAN status


Mangal – a global ecological interactions database – serializes ecological interaction matrices into nodes (e.g. taxon, individuals or population) and interactions (i.e. edges). For each network, Mangal offers the opportunity to store study context such as the location, sampling environment, inventory date and informations pertaining to the original publication. For every nodes involved in the ecological networks, Mangal references unique taxonomic identifiers such as Encyclopedia of Life (EOL), Catalogue of Life (COL), Global Biodiversity Information Facility (GBIF) etc. and can extend nodes informations to individual traits.

rmangal is an R client to the Mangal database and provides various functions to explore his content through search functions. It offers methods to retrieve networks structured as mgNetwork or mgNetworksCollection S3 objects and methods to convert mgNetwork to other class objects in order to analyze and visualize networks properties: igraph, tidygraph, and ggraph.


So far, only the development version is available and can be installed via the remotes 📦

R> remotes::install_github("ropensci/rmangal")
R> library("rmangal")

How to use rmangal

There are seven search_*() functions to explore the content of Mangal, for instance search_datasets():

R> mgs <- search_datasets("lagoon")
Found 2 datasets

Once this first step achieved, networks found can be retrieved with the get_collection() function.

R> mgn <- get_collection(mgs)

get_collection() returns an object mgNetwork if there is one network returned, otherwise an object mgNetworkCollection, which is a list of mgNetwork objects.

R> class(mgn)
[1] "mgNetworksCollection"
R> mgn
A collection of 3 networks

* Network # from data set #
* Description: Dietary matrix of the Huizache–Caimanero lagoon
* Includes 189 edges and 26 nodes
* Current taxonomic IDs coverage for nodes of this network:
  --> ITIS: 81%, BOLD: 81%, EOL: 85%, COL: 81%, GBIF: 0%, NCBI: 85%
* Published in ref # DOI:10.1016/s0272-7714(02)00410-9

* Network # from data set #
* Description: Food web of the Brackish lagoon
* Includes 27 edges and 11 nodes
* Current taxonomic IDs coverage for nodes of this network:
  --> ITIS: 45%, BOLD: 45%, EOL: 45%, COL: 45%, GBIF: 18%, NCBI: 45%
* Published in ref # DOI:NA

* Network # from data set #
* Description: Food web of the Costal lagoon
* Includes 34 edges and 13 nodes
* Current taxonomic IDs coverage for nodes of this network:
  --> ITIS: 54%, BOLD: 54%, EOL: 54%, COL: 54%, GBIF: 15%, NCBI: 54%
* Published in ref # DOI:NA

igraph and tidygraph offer powerful features to analyze networks and rmangal provides functions to convert mgNetwork to igraph and tbl_graph so that the user can easily benefit from those packages.

R> ig <- as.igraph(mgn[[1]])
R> class(ig)
[1] "igraph"
R> library(tidygraph)
R> tg <- as_tbl_graph(mgn[[1]])
R> class(tg)
[1] "tbl_graph" "igraph"

📖 Note that the vignette “Get started with rmangal” will guide the reader through several examples and provide further details about rmangal features.

How to publish ecological networks

We are working on that part. The networks publication process will be facilitated with structured objects and tests suite to maintain data integrity and quality.Comments and suggestions are welcome, feel free to open issues.

rmangal vs rglobi

Those interested only in pairwise interactions among taxons may consider using rglobi, an R package that provides an interface to the GloBi infrastructure. GloBi provides open access to aggregated interactions from heterogeneous sources. In contrast, Mangal gives access to the original networks and open the gate to study ecological networks properties (i.e. connectance, degree etc.) along large environmental gradients, which wasn’t possible using the GloBi infrastructure.

Older versions


We are grateful to Noam Ross for acting as an editor during the review process. We also thank Anna Willoughby and Thomas Lin Petersen for reviewing the package. Their comments strongly contributed to improve the quality of rmangal.

Code of conduct

Please note that the rmangal project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.