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An equation of state unifies diversity, productivity, abundance and biomass
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Final Published Version
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School of Natural Resources & the Environment, University of ArizonaIssue Date
2022
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Nature ResearchCitation
Harte, J., Brush, M., Newman, E. A., & Umemura, K. (2022). An equation of state unifies diversity, productivity, abundance and biomass. Communications Biology, 5(1).Journal
Communications BiologyRights
Copyright © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
To advance understanding of biodiversity and ecosystem function, ecologists seek widely applicable relationships among species diversity and other ecosystem characteristics such as species productivity, biomass, and abundance. These metrics vary widely across ecosystems and no relationship among any combination of them that is valid across habitats, taxa, and spatial scales, has heretofore been found. Here we derive such a relationship, an equation of state, among species richness, energy flow, biomass, and abundance by combining results from the Maximum Entropy Theory of Ecology and the Metabolic Theory of Ecology. It accurately captures the relationship among these state variables in 42 data sets, including vegetation and arthropod communities, that span a wide variety of spatial scales and habitats. The success of our ecological equation of state opens opportunities for estimating difficult-to-measure state variables from measurements of others, adds support for two current theories in ecology, and is a step toward unification in ecology. © 2022, The Author(s).Note
Open access journalISSN
2399-3642PubMed ID
36008589Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1038/s42003-022-03817-8
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License.
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