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Scaling laws predict global microbial diversity - PubMed

  • ️Fri Jan 01 2016

Scaling laws predict global microbial diversity

Kenneth J Locey et al. Proc Natl Acad Sci U S A. 2016.

Abstract

Scaling laws underpin unifying theories of biodiversity and are among the most predictively powerful relationships in biology. However, scaling laws developed for plants and animals often go untested or fail to hold for microorganisms. As a result, it is unclear whether scaling laws of biodiversity will span evolutionarily distant domains of life that encompass all modes of metabolism and scales of abundance. Using a global-scale compilation of ∼35,000 sites and ∼5.6⋅10(6) species, including the largest ever inventory of high-throughput molecular data and one of the largest compilations of plant and animal community data, we show similar rates of scaling in commonness and rarity across microorganisms and macroscopic plants and animals. We document a universal dominance scaling law that holds across 30 orders of magnitude, an unprecedented expanse that predicts the abundance of dominant ocean bacteria. In combining this scaling law with the lognormal model of biodiversity, we predict that Earth is home to upward of 1 trillion (10(12)) microbial species. Microbial biodiversity seems greater than ever anticipated yet predictable from the smallest to the largest microbiome.

Keywords: biodiversity; macroecology; microbiology; microbiome; rare biosphere.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.

Microbial communities (blue dots) and communities of macroscopic plants and animals (red dots) are similar in the rates at which rarity, absolute dominance, and species evenness scale with the number of individuals or genes reads (N). However, for a given N, microbial communities have greater rarity, less evenness, and greater richness than those of macroorganisms. Coefficients and exponents of scaling equations are mean values from 10,000 bootstrapped multiple regressions, with each regression based on 500 microbial and 500 macrobial communities chosen by stratified random sampling. Each scatterplot represents a single random sample; hulls are 95% confidence intervals.

Fig. 2.
Fig. 2.

The dominance-abundance scaling law (dashed red line) predicts the abundance of the most abundant microbial taxa (Nmax) up to global scales. The pink hull is the 95% prediction interval for the regression based on 3,000 sites chosen by stratified random sampling (red heat map) from our microbial data compilation. Gray cross-hairs are ranges of published estimates of N and Nmax for large microbiomes, including Earth (6, 7, 31, 32) (Materials and Methods, Approximating Ranges of Nmax for Large Microbiomes). The light-gray dashed line is the 1:1 relationship. The scaling equation and r2 only pertain to the scatterplot data.

Fig. 3.
Fig. 3.

The microbial richness-abundance scaling relationship (dashed red line) supports values of S predicted from the lognormal model using the published ranges of N and Nmax (gray dots) as well as ranges of Nmax predicted from the dominance scaling law (blue dots). The pink hull is the 95% prediction interval for the regression based on 3,000 sites chosen by stratified random sampling (red scatterplot). The scaling equation and r2 value are based solely on the red scatterplot data. SEs around predicted S are too small to illustrate.

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