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Diversity indices for ecological networks: a unifying framework using Hill numbers.

Marc Ohlmann¹, Vincent Miele^2,3,4, Stéphane Dray^2,3,4

¹Univ. Grenoble Alpes, CNRS, Univ. Savoie Mont Blanc, CNRS, LECA, Laboratoire d'Écologie Alpine, F-38000, Grenoble, France.

Ecology Letters

|January 25, 2019

Summary

Understanding ecological networks requires measuring diversity across space and time. This study introduces a new framework using Hill numbers to quantify ecological network diversity (alpha, gamma, beta) and analyze species interactions.

Keywords:

Hill numbers Metanetwork interaction network diversity species aggregation level

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Area of Science:

Ecology
Network Analysis
Biodiversity Science

Background:

Understanding ecosystem trajectories necessitates describing ecological interactions across space and time.
Measuring local (alpha), regional (gamma), and between-sample (beta) network diversity requires appropriate frameworks.
Existing methods may not fully capture the probabilistic nature of biotic interactions or species abundances.

Purpose of the Study:

To propose a unifying framework for measuring ecological network diversity.
To incorporate Hill numbers to account for interaction probabilities and species abundances.
To enable analysis of network diversity at various species aggregation levels.

Main Methods:

Developed a framework based on Hill numbers for network diversity measurement.
Accounted for the probabilistic nature of biotic interactions and species/group abundances.
Applied the framework to a simulation experiment and a global food-web database.

Main Results:

The proposed framework successfully quantifies alpha, gamma, and beta diversity in ecological networks.
Analysis across different species aggregation levels provides deeper insights into network structure.
The framework demonstrates utility in comparing ecological networks and analyzing variations across environmental gradients and time.

Conclusions:

The unifying framework offers a robust method for assessing ecological network diversity.
It facilitates a more comprehensive understanding of how environmental conditions shape ecosystem dynamics.
This approach addresses current needs for comparing and analyzing ecological networks over space and time.