Evidence map›Paper›PMID 32811317›Full record

ArticleProceedings. Biological sciences2020

How to estimate community energy flux? A comparison of approaches reveals that size-abundance trade-offs alter the scaling of community energy flux.

Giulia Ghedini, Martino E Malerba, Dustin J Marshall

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Giulia GhediniCentre for Geometric Biology, School of Biological Sciences, Monash University, Melbourne VIC 3800, Australia.
Martino E MalerbaCentre for Geometric Biology, School of Biological Sciences, Monash University, Melbourne VIC 3800, Australia.
Dustin J MarshallCentre for Geometric Biology, School of Biological Sciences, Monash University, Melbourne VIC 3800, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Size and metabolism are highly correlated, so that community energy flux might be predicted from size distributions alone. However, the accuracy of predictions based on interspecific energy-size relationships relative to approaches not based on size distributions is unknown. We compare six approaches to predict energy flux in phytoplankton communities across succession: assuming a constant energy use among species (per cell or unit biomass), using energy-size interspecific scaling relationships and species-specific rates (both with or without accounting for density effects). Except for the per cell approach, all others explained some variation in energy flux but their accuracy varied considerably. Surprisingly, the best approach overall was based on mean biomass-specific rates, followed by the most complex (species-specific rates with density). We show that biomass-specific rates alone predict community energy flux because the allometric scaling of energy use with size measured for species in isolation does not reflect the isometric scaling of these species in communities. We also find energy equivalence throughout succession, even when communities are not at carrying capacity. Finally, we discuss that species assembly can alter energy-size relationships, and that metabolic suppression in response to density might drive the allometry of community energy flux as biomass accumulates.

Indexed as

EcosystemPhytoplanktonBiomassBody SizeEnergy MetabolismModels, BiologicalPopulation Densitycompetitionhomeostasismetabolismphenotypespecies interactionsstability

Identifiers

PMID32811317
PMCPMC7482288

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.