The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
The role of multiple global change factors in driving soil functions and microbial biodiversity
Open accessAbstract
Many factors influence global change: Global environmental change is driven by multiple natural and anthropogenic factors. With a focus on global change as it affects soils, Rillig et al. point out that nearly all published studies consider just one or two factors at a time (see the Perspective by Manning). In a laboratory experiment, they tested 10 drivers of global change both individually and in combination, at levels ranging from 2 to 10 factors. They found that soil properties, processes, and microbial communities could not be predicted from single-effect responses and that multiple factors in combination produced unsuspected responses. They concluded that single-factor studies remain important for uncovering mechanisms but that global change biology needs to embrace more fully the multitude of drivers impinging on ecosystems. Science , this issue p. 886 ; see also p. 801
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
DADA2: High–resolution sample inference from Illumina amplicon data
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016) · Nature Methods · doi:10.1038/nmeth.3869 · Cited by 35,698
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828
Ecosystems and Human Well-being: Synthesis
Assessment, M. E. (2005) · Island Press · doi:10.5281/zenodo.18167309 · Cited by 10,665
Global Biodiversity Scenarios for the Year 2100
Sala, O. E., Stuart Chapin, F., III, Armesto, J. J., Berlow, E., Bloomfield, J., Dirzo, R., Huber-Sanwald, E., Huenneke, L. F., Jackson, R. B., et al. (2000) · Science · doi:10.1126/science.287.5459.1770 · Cited by 9,280
The ASA Statement on p -Values: Context, Process, and Purpose
Wasserstein, R. L., & Lazar, N. A. (2016) · The American Statistician · doi:10.1080/00031305.2016.1154108 · Cited by 6,306
Efron, B., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013815 · Cited by 6,033
Distance‐Based Tests for Homogeneity of Multivariate Dispersions
Anderson, M. J. (2006) · Biometrics · doi:10.1111/j.1541-0420.2005.00440.x · Cited by 3,304
The New Statistics: Why and How
Cumming, G. (2014) · Psychological Science · doi:10.1177/0956797613504966 · Cited by 3,200
Cited by
Zandalinas, S. I., Fritschi, F. B., & Mittler, R. (2021) · Trends in Plant Science · doi:10.1016/j.tplants.2021.02.011 · Cited by 1,122
Microbial Community Resilience across Ecosystems and Multiple Disturbances
Philippot, L., Griffiths, B. S., & Langenheder, S. (2021) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.00026-20 · Cited by 562
Soil plastispheres as hotspots of antibiotic resistance genes and potential pathogens
Zhu, D., Ma, J., Li, G., Rillig, M. C., & Zhu, Y.-G. (2022) · The ISME Journal · doi:10.1038/s41396-021-01103-9 · Cited by 459
Self-citationImpacts of hypoxic events surpass those of future ocean warming and acidification
Sampaio, E., Santos, C., Rosa, I. C., Ferreira, V., Pörtner, H.-O., Duarte, C. M., Levin, L. A., & Rosa, R. (2021) · Nature Ecology & Evolution · doi:10.1038/s41559-020-01370-3 · Cited by 295
Negative effects of multiple global change factors on soil microbial diversity
Yang, Y., Li, T., Wang, Y., Cheng, H., Chang, S. X., Liang, C., & An, S. (2021) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2021.108229 · Cited by 269
Metadata
- Authors
- Rillig, M. C., Ryo, M., Lehmann, A., Aguilar-Trigueros, C. A., Buchert, S., Wulf, A., Iwasaki, A., Roy, J., & Yang, G.
- Venue
- Science
- Published
- 2019-11-15
- Volume
- 366
- Issue
- 6467
- Pages
- 886-890
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2987820647
- Cited by
- 902
- References
- 16
- FWCI
- 53.16
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The role of multiple global change factors in driving soil functions and microbial biodiversity. https://app.cochat.ai/papers/10.1126/science.aay2832
- The paper
- Rillig, M. C., Ryo, M., Lehmann, A., Aguilar-Trigueros, C. A., Buchert, S., Wulf, A., Iwasaki, A., Roy, J., & Yang, G. (2019). The role of multiple global change factors in driving soil functions and microbial biodiversity. Science. https://doi.org/10.1126/science.aay2832
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.