Abstract
Biotic interactions are part of all ecosystem attributes and play an important role in the structure and stability of biological communities. In this study, we give a brief account of how the threads of biotic interactions are linked and how we can measure such complexity by focusing on mutualistic interactions. We start by explaining that although biotic interactions are fundamental ecological processes, they are also a component of biodiversity with a clear α, β and γ diversity structure which can be measured and used to explain how biotic interactions vary over time and space. Specifically, we explain how to estimate the α-diversity by measuring the properties of species interaction networks. We also untangle the components of the β-diversity and how it can be used to make pairwise comparisons between networks. Moreover, we move forward to explain how local ecological networks are a subset of a regional pool of species and potential interactions, γ-diversity, and how this approach allows assessing the spatial and temporal dynamics of ecological networks. Finally, we propose a new framework for studying interactions and the biodiversity–ecosystem function relationship by identifying the unique and common interactions of local networks over space, time or both together.
Highlights
Since the first observations and studies by modern naturalists, biologists have recognized that interactions between individuals of different species are the building blocks of ecosystems and ecological communities [1,2]
With ant–plant mutualisms, it was revealed that the main driver of interaction turnover between two neighboring communities sharing great numbers of species is interaction rewiring [58]. Another example found that the temporal turnover of pollination networks was mainly driven by interaction rewiring [63]. As these measures are computed to compare ecological networks, we have to acknowledge that the two groups or trophic levels that form the network may contribute in different ways to the turnover of interactions driven by species turnover
We propose two new ways to measure the uniqueness and commonness of interactions: (i) Local Network Uniqueness (LNU), which measures the proportion of unique interactions of a focal network in relation to its metaweb and (ii) Shared Interactions Frequency (SIF), which measures the proportion of common interactions of a focal network in relation to its metaweb
Summary
Since the first observations and studies by modern naturalists, biologists have recognized that interactions between individuals of different species are the building blocks of ecosystems and ecological communities [1,2]. Another example found that the temporal turnover of pollination networks was mainly driven by interaction rewiring [63] As these measures are computed to compare ecological networks, we have to acknowledge that the two groups or trophic levels that form the network may contribute in different ways to the turnover of interactions driven by species turnover. It has been observed in pollination networks that the interaction turnover driven by species turnover can be generated by plants [65], and in other cases by pollinators [64] This indicates that the trophic level explaining the turnover of interactions over space is particular to the study area. By identifying unique interactions we might be able to conserve species, and conserve ecological functions and ecosystem stability [30]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
