Evidence map›Paper›PMID 24756001›Full record

ArticlePLoS biology2014

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model.

Michael B J Harfoot, Tim Newbold, Derek P Tittensor, Stephen Emmott, Jon Hutton, Vassily Lyutsarev, Matthew J Smith, Jörn P W Scharlemann, Drew W Purves

Open access · goldAbstract read
In one paragraph

Article in PLoS biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
15.8field-weighted citation impact, top 1% of its field
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

39 citing papers in PubMed, 222 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Towards an ecosystem model of infectious disease.Nature ecology & evolution · 2021
    Review
  14. Article
  15. Linking dimensions of data on global marine animal diversity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Article
  16. Article
  17. Climate drives the geography of marine consumption by changing predator communities.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  18. Article
  19. Relationship between conservation biology and ecology shown through machine reading of 32,000 articles.Conservation biology : the journal of the Society for Conservation Biology · 2020
    Article
  20. Review
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

9 authors at 3 institutions in 2 countries.

Michael B J HarfootUnited Nations Environment Programme World Conservation Monitoring Centre, Cambridge, United Kingdom; Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.
Tim NewboldUnited Nations Environment Programme World Conservation Monitoring Centre, Cambridge, United Kingdom; Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.
Derek P TittensorUnited Nations Environment Programme World Conservation Monitoring Centre, Cambridge, United Kingdom; Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom; Dalhousie University, Halifax, Nova Scotia, Canada.
Stephen EmmottComputational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.
Jon HuttonUnited Nations Environment Programme World Conservation Monitoring Centre, Cambridge, United Kingdom.
Vassily LyutsarevComputational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.
Matthew J SmithComputational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.
Jörn P W ScharlemannUnited Nations Environment Programme World Conservation Monitoring Centre, Cambridge, United Kingdom; School of Life Sciences, University of Sussex, Falmer, Brighton, United Kingdom.
Drew W PurvesComputational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.
Microsoft Research (United Kingdom) · GBWorld Conservation Monitoring Centre · GBUniversity of Sussex · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures.

Indexed as

Computer SimulationEcologyEcosystemGlobal WarmingModels, TheoreticalClimateEcological and Environmental PhenomenaEnvironmentHumansModels, Biological

Identifiers

PMID24756001
PMCPMC3995663
OpenAlexW2003251517

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.