Interaction capacity as a potential driver of community diversity.

Masayuki Ushio

doi:10.1098/rspb.2021.2690

Abstract

How patterns in community diversity emerge is a long-standing question in ecology. Studies suggested that community diversity and interspecific interactions are interdependent. However, evidence from high-diversity ecological communities is lacking because of practical challenges in characterizing speciose communities and their interactions. Here, I analysed time-varying interaction networks that were reconstructed using 1197 species, DNA-based ecological time series taken from experimental rice plots and empirical dynamic modelling, and introduced ‘interaction capacity', namely, the sum of interaction strength that a single species gives and receives, as a potential driver of community diversity. As community diversity increases, the number of interactions increases exponentially but the mean interaction capacity of a community becomes saturated, weakening interspecific interactions. These patterns are modelled with simple mathematical equations, based on which I propose the ‘interaction capacity hypothesis': that interaction capacity and network connectance can be two fundamental properties that influence community diversity. Furthermore, I show that total DNA abundance and temperature influence interaction capacity and connectance nonlinearly, explaining a large proportion of diversity patterns observed in various systems. The interaction capacity hypothesis enables mechanistic explanations of community diversity. Therefore, analysing ecological community data from the viewpoint of interaction capacity would provide new insight into community diversity.

Highlights

How patterns in community diversity in nature emerge is one of the most challenging and long-standing questions in ecology [1]
This is largely due to two difficulties: (i) the number of species and interspecific interactions examined in previous theoretical and experimental studies have been limited compared with those of a real, highdiversity ecological community under field conditions, and (ii) detecting causal relationships between interspecific interactions and diversity is not straightforward because manipulative experiments, a most effective strategy to detect causality, are not feasible when a large number of species and interactions are targeted under field conditions
Causal relationships between the network properties and external forces were examined with convergent cross-mapping (CCM), and the results suggested that mean interaction capacity and connectance are causally influenced by mean air temperature and total DNA copy number

Summary

Introduction

How patterns in community diversity in nature emerge is one of the most challenging and long-standing questions in ecology [1]. DNA extraction and quantitative MiSeq sequencing with an internal standard DNA [16,17] overcame the first difficulty noted above: quantitative, highly diverse, multi-taxonomic, daily, 122-day-long ecological time series were obtained from five experimental rice plots under field conditions This extensive ecological time series was analysed using a framework of nonlinear time series analysis, empirical dynamic modelling (EDM) [18–20], to overcome the second difficulty: EDM quantified fluctuating interaction strengths, reconstructed the time-varying interaction network of the ecological communities, and detected potential causal relationships between network properties and community diversity. Dynamic stability [26], an index that quantifies how fast the community bounces back from small perturbations (i.e. the dominant eigenvalue of the interaction matrix), was almost always over 1, suggesting unstable community dynamics (electronic supplementary material, figure S5c–g) This pattern may not be surprising because the rice plots were open systems under field conditions.

Miseq sequencing

Verrucomicrobia

Conclusion

Method summary