Evidence map›Paper›PMID 32718434›Full record

ArticleeLife2020

Climate change and intensive land use reduce soil animal biomass via dissimilar pathways.

Rui Yin, Julia Siebert, Nico Eisenhauer, Martin Schädler

Abstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Does Intensive Land Use Contribute to Energy Efficiency?-Evidence Based on a Spatial Durbin Model.International journal of environmental research and public health · 2022
    Article
  6. Article
  7. 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

4 authors.

Rui YinDepartment of Community Ecology, Helmholtz-Centre for Environmental Research-UFZ, Halle, Germany.ORCID 0000-0002-4580-1317
Julia SiebertGerman Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Leipzig, Germany.
Nico Eisenhauer *German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Leipzig, Germany.ORCID 0000-0002-0371-6720
Martin Schädler *Department of Community Ecology, Helmholtz-Centre for Environmental Research-UFZ, Halle, Germany.

Funding

China Scholarship Council 201406910015Deutsche Forschungsgemeinschaft FZT 118European Research Council 677232H2020 European Research Council No. 677232
6 · The paper itself

Abstract

Global change drivers, such as climate change and land use, may profoundly influence body size, density, and biomass of soil organisms. However, it is still unclear how these concurrent drivers interact in affecting ecological communities. Here, we present the results of an experimental field study assessing the interactive effects of climate change and land-use intensification on body size, density, and biomass of soil microarthropods. We found that the projected climate change and intensive land use decreased their total biomass. Strikingly, this reduction was realized via two dissimilar pathways: climate change reduced mean body size and intensive land use decreased density. These findings highlight that two of the most pervasive global change drivers operate via different pathways when decreasing soil animal biomass. These shifts in soil communities may threaten essential ecosystem functions like organic matter turnover and nutrient cycling in future ecosystems.

Indexed as

ArthropodsBiodiversityBiotaClimate ChangeSoilAnimalsBiomassEcosystemGermanySoilbody sizeecologyfuture climateglobal changeland-use intensificationsoil fauna

Identifiers

PMID32718434
PMCPMC7386910

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.