10.5061/DRYAD.61F2H
García-Callejas, David
Centre for Research on Ecology and Forestry Applications
Molowny-Horas, Roberto
Centre for Research on Ecology and Forestry Applications
Araújo, Miguel
Spanish National Research Council
Data from: Multiple interaction networks: towards more realistic
descriptions of the web of life
Dryad
dataset
2017
Interaction networks
Multiple interaction types
2017-07-25T15:55:16Z
2017-07-25T15:55:16Z
en
https://doi.org/10.1111/oik.04428
31326 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Ecological communities are defined by species interacting dynamically in a
given location at a given time, and can be conveniently represented as
networks of interactions. Pairwise interactions can be ascribed to one of
five main types, depending on their outcome for the species involved:
amensalism, antagonism (including predation, parasitism and disease),
commensalism, competition or mutualism. While most studies have dealt so
far with networks involving one single type of interaction at a time,
often focusing on a specific clade and/or guild, recent studies are being
developed that consider networks with more than one interaction type and
across several levels of biological organisation. We review these
developments and suggest that three main frameworks are in use to
investigate the properties of multiple interactions networks:
'expanded food-webs', 'multilayer networks' and
'equal footing networks'. They differ on how interactions are
classified and implemented in mathematical models, and on whether the
effect of different interaction types is expressed in the same units. We
analyse the mathematical and ecological assumptions of these three
approaches, and identify some of the questions that can be addressed with
each one of them. Since the overwhelming majority of multiple interaction
studies are theoretical and use artificially generated data, we also
provide recommendations for the incorporation of field data in such
studies.
R script for generating resultsThe file included is a self-contained R
script that was used to produce the results and images of the manuscript.
Figures obtained with this script will not exactly match the ones of the
paper due to the type of analyses performed, based on random
parameterizations (within given parameter intervals) of dynamic
models.0IK-04428.R