Diversity from genes to ecosystems: a unifying framework to study variation across biological metrics and scales

Oscar E. Gaggiotti, Anne Chao, Pedro Peres-Neto, Chun-Huo Chiu, Christine Edwards, Marie-Josée Fortin, Lou Jost, Christopher Richards, Kimberly Selkoe

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organisation (genes, population, species, ecological communities and ecosystems), a diversity index that behaves consistently across these different levels has so far been lacking, hindering the development of truly integrative biodiversity studies. To fill this important knowledge gap we present a unifying framework for the measurement of biodiversity across hierarchical levels of organisation. Our weighted, information-based decomposition framework is based on a Hill number of order q = 1, which weights all elements in proportion to their frequency and leads to diversity measures based on Shannon’s entropy. We investigated the numerical behaviour of our approach with simulations and showed that it can accurately describe complex spatial hierarchical structures. To demonstrate the intuitive and straightforward interpretation of our diversity measures in terms of effective number of components (alleles, species, etc.) we applied the framework to a real dataset on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics, and eco-evolutionary dynamics.
Original languageEnglish
Pages (from-to)1176-1193
Number of pages18
JournalEvolutionary Applications
Volume11
Issue number7
Early online date20 Feb 2018
DOIs
Publication statusPublished - 17 Jul 2018

Keywords

  • Biodiversity indices
  • Hill numbers
  • Species diversity
  • Genetic diversity
  • Hierarchical spatial structure

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