Abstract
Measuring commonness and rarity is pivotal to ecology and conservation. Zeta diversity, the average number of species shared by multiple sets of assemblages, and Dark diversity, the number of species that could occur in an assemblage but are missing, have been recently proposed to capture two aspects of the commonness-rarity spectrum. Despite a shared focus on commonness and rarity, thus far, Zeta and Dark diversities have been assessed separately. Here, we review these two frameworks and suggest their integration into a unified paradigm of the “rarity facets of biodiversity.” This can be achieved by partitioning Alpha and Beta diversities into five components (the Zeta, Eta, Theta, Iota, and Kappa rarity facets) defined based on the commonness and rarity of species. Each facet is assessed in traditional and multiassemblage fashions to bridge conceptual differences between Dark diversity and Zeta diversity. We discuss applications of the rarity facets including comparing the taxonomic, functional, and phylogenetic diversity of rare and common species, or measuring species' prevalence in different facets as a metric of species rarity. The rarity facets integrate two emergent paradigms in biodiversity science to better understand the ecology of commonness and rarity, an important endeavor in a time of widespread changes in biodiversity across the Earth.
Original language | English |
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Pages (from-to) | 13912-13919 |
Journal | Ecology and Evolution |
Volume | 11 |
Issue number | 20 |
DOIs | |
Publication status | Published - 1 Oct 2021 |
Externally published | Yes |
Funding
Thanks to Caio Graco Roza for useful discussions on Zeta diversity. SM acknowledges support from the European Commission (program H2020‐MSCA‐IF‐2019; grant award: 882221). Thanks to Caio Graco Roza for useful discussions on Zeta diversity. SM acknowledges support from the European Commission (program H2020-MSCA-IF-2019; grant award: 882221).
Funders | Funder number |
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Horizon 2020 Framework Programme | 882221 |
European Commission | H2020-MSCA-IF-2019 |