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Updated: Aug 5, 2025

07:41
Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems
Published on: July 30, 2019
7.5K
The sizes of life.
Eden W Tekwa1,2, Katrina A Catalano2, Anna L Bazzicalupo1
1Department of Zoology, University of British Columbia, Vancouver, BC, Canada.
Plos One
|March 29, 2023
Summary
Global body size-biomass spectra reveal that while abundance decreases exponentially with size, biomass is best described by a bimodal distribution, with small and large organisms dominating. This suggests a complex global pattern, not a single universal constraint.
Area of Science:
- Ecology
- Biodiversity Science
- Biogeography
Background:
- Ecosystems host diverse life, but global body size-biomass distribution remains poorly understood.
- Previous research focused on specific realms or groups, lacking comprehensive global scope.
Purpose of the Study:
- To compile and analyze global body size-biomass spectra across terrestrial, marine, and subterranean realms.
- To statistically describe the distribution of biomass across organismal body sizes worldwide.
Main Methods:
- Integrated existing biomass estimates with uncatalogued body size ranges for free-living organisms.
- Propagated uncertainties in biomass and size data.
- Applied power law and bimodal Gaussian mixture models for statistical analysis.
Main Results:
- Global body size-biomass spectra show exponentially decreasing abundance (exponent -0.9) and nearly equal biomass across log size bins when analyzed with power laws.
- A bimodal Gaussian mixture model better describes biomass patterns (R2 = 0.86), indicating peaks in biomass for small (~10-15 g) and large (~107 g) organisms.
- Neither small nor large organisms exclusively dominate biomass; multiple groups share size ranges where biomass is highest.
Conclusions:
- The global body size-biomass relationship appears bimodal, with significant biomass concentrated in both small and large organisms.
- Substantial uncertainties necessitate further data to determine if universal constraints or local factors shape these global patterns.
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