Models that estimate missing interactions change our understanding of
the structure and species roles in the largest seed-dispersal network
- André Martinez,
- Mathias Pires
André Martinez
Universidade Estadual de Campinas
Corresponding Author:andre.nmartinez6@gmail.com
Author ProfileMathias Pires
Universidade Estadual de Campinas Instituto de Biologia
Author ProfileAbstract
Interactions between species, such as seed-dispersal interactions, can
shape many aspects of those species' life, as well as ecological
patterns and evolutionary dynamics. Yet, sampling interactions in the
field is challenging. Even with extensive sampling efforts we can hardly
obtain a comprehensive picture of which species interact with each
other. Such missing interactions can produce important gaps that affect
how we perceive and interpret the network formed by species interactions
and the roles of individual species within those networks. In this study
we propose two methods that combine data on species interactions with
information on species traits and phylogenies to estimate potentially
missing interactions. We use one of the largest datasets on
plant-frugivore interactions, depicting thousands of interactions
between birds and plants in the Atlantic Forest hotspot, to test those
methods and analyze how adding newly estimated interactions change the
structure and the topological importance of the species within the seed
dispersal network. We show that estimated missing interactions more than
tripled the number of interactions in the network and impact the general
topological properties of the network increasing nestedness and reducing
modularity. Both models generated networks with a similar structure and
were effective in estimating new interactions, accurately predicting
known interactions without overestimating interactions in place of true
absences. More importantly, added interactions changed our perception on
the topological role of species, with several under-sampled species
earning several interactions and becoming more central to network
structure. This shows that estimating interactions can be helpful to get
a more complete idea of how a network may look like and may help inform
which interactions should be focused on in further sampling efforts.31 Oct 2023Submitted to Oikos 01 Nov 2023Submission Checks Completed
01 Nov 2023Assigned to Editor
01 Nov 2023Review(s) Completed, Editorial Evaluation Pending
28 Feb 2024Editorial Decision: Revise Major
20 Jun 2024Editorial Decision: Revise Minor
27 Jun 20242nd Revision Received
28 Jun 2024Review(s) Completed, Editorial Evaluation Pending
15 Jul 2024Editorial Decision: Accept