
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 information pertaining to the original publication. For all 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 information to individual traits.
rmangal is an R client to the Mangal database and
provides various functions to explore its 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 :package:
R> remotes::install_github("ropensci/rmangal")
R> library("rmangal")rmangalThere 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 is 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
── Network Collection ──
6 networks in collection
── Network #86
• Dataset: #22
• Description: Dietary matrix of the Huizache–Caimanero lagoon
• Size: 189 edges, 26 nodes
• Taxonomic IDs coverage for nodes:
ITIS: 81%, BOLD: 81%, EOL: 85%, COL: 81%, GBIF: 0%, NCBI: 85%
• Published in reference # DOI: 10.1016/s0272-7714(02)00410-9
── Network #1104
• Dataset: #53
• Description: Food web of the shallow sublittoral at Cape Ann
• Size: 107 edges, 35 nodes
• Taxonomic IDs coverage for nodes:
ITIS: 77%, BOLD: 71%, EOL: 77%, COL: 74%, GBIF: 3%, NCBI: 71%
• Published in reference # DOI: 10.2307/1948658
── Network #1108
• Dataset: #53
• Description: Food web of the high salt marsh at Cape Ann
• Size: 44 edges, 19 nodes
• Taxonomic IDs coverage for nodes:
ITIS: 58%, BOLD: 53%, EOL: 58%, COL: 53%, GBIF: 11%, NCBI: 53%
• Published in reference # DOI: 10.2307/1948658
── Network #1105
• Dataset: #53
• Description: Food web of the rocky shore at Cape Ann
• Size: 124 edges, 29 nodes
• Taxonomic IDs coverage for nodes:
ITIS: 90%, BOLD: 86%, EOL: 90%, COL: 86%, GBIF: 10%, NCBI: 86%
• Published in reference # DOI: 10.2307/1948658
── Network #1107
• Dataset: #53
• Description: Food web of the low salt marsh at Cape Ann
• Size: 60 edges, 25 nodes
• Taxonomic IDs coverage for nodes:
ITIS: 80%, BOLD: 68%, EOL: 76%, COL: 68%, GBIF: 12%, NCBI: 72%
• Published in reference # DOI: 10.2307/1948658
── Network #1106
• Dataset: #53
• Description: Food web of the mudflat at Cape Ann
• Size: 175 edges, 37 nodes
• Taxonomic IDs coverage for nodes:
ITIS: 86%, BOLD: 84%, EOL: 86%, COL: 84%, GBIF: 3%, NCBI: 84%
• Published in reference # DOI: 10.2307/1948658igraph 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":book: Note that the vignette “Get started with rmangal” will guide the reader through several examples and provide further details about rmangal features.
Since rmangal version 2.2, the function verbosity is
controlled by the option rmangal.verbose. To quiet all
rmangal functions, use:
options(rmangal.verbose = "quiet")and to switch on the verbosity do:
options(rmangal.verbose = "verbose")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
rglobiThose interested only in pairwise interactions among taxa 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.
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 improving
the quality of rmangal.
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.
rmangal in R doing
citation(package = 'rmangal')