Evidence map›Paper›PMID 39848987›Full record

ArticleNature communications2025

Deep soil contributions to global nitrogen budgets.

Maya Almaraz, Chao Wang, Michelle Y Wong

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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.

Maya AlmarazYale Center for Natural Carbon Capture, Yale University, New Haven, CT, USA. maya.almaraz@yale.edu.ORCID http://orcid.org/0000-0003-0556-633X
Chao WangCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China.ORCID http://orcid.org/0000-0002-5756-7505
Michelle Y WongCary Institute of Ecosystem Studies, Millbrook, NY, USA.ORCID http://orcid.org/0000-0002-7830-8035

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous estimates of deep soil inorganic nitrogen (N) reservoirs have been mainly limited to desert soils, however, recent evidence suggests that deep soil pools are far more ubiquitous across biomes and therefore may be important for global N budgets. Here, we used observations from 280 deep soil profiles (2-205 m) across a wide array of ecosystem and land cover types to seek insight into the full geospatial variation of deep soil nitrate. Using a random forest machine learning approach we estimate a total deep soil nitrate pool of 15.2 ( ± 1.1 SD) Pg of N. When included in the global soil N pool, our estimates of deep soil N increase the global N storage budget by 16%. Estimating these deep soil N pools continues to add to our understanding of soils as a fate for anthropogenically fixed N, and the critical role that deep soils play in our biosphere.

Indexed as

NitrogenSoilEcosystemMachine LearningNitratesNitratesNitrogenSoil

Identifiers

PMID39848987
PMCPMC11758002

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.