Evidence map›Paper›PMID 39758151›Full record

ArticleEcosphere (Washington, D.C)2024

Characterizing localized nitrogen sensitivity of tree species and the associated influences of mediating factors.

Justin G Coughlin, Shih Ying Chang, Kenneth Craig, Charles Scarborough, Charles T Driscoll, Christopher M Clark, Nathan R Pavlovic

Abstract read
In one paragraph

Article in Ecosphere (Washington, D.C), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Justin G CoughlinSonoma Technology, Inc., Petaluma, California, USA.ORCID https://orcid.org/0000-0003-3882-3064
Shih Ying ChangSonoma Technology, Inc., Petaluma, California, USA.
Kenneth CraigSonoma Technology, Inc., Petaluma, California, USA.
Charles ScarboroughSonoma Technology, Inc., Petaluma, California, USA.
Charles T DriscollDepartment of Civil and Environmental Engineering, Syracuse University, Syracuse, New York, USA.
Christopher M ClarkU.S. Environmental Protection Agency, Office of Research and Development, Washington, DC, USA.
Nathan R PavlovicSonoma Technology, Inc., Petaluma, California, USA.ORCID https://orcid.org/0000-0003-2127-3940

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Critical loads (CLs) are frequently used to quantify terrestrial ecosystem impacts from nitrogen (N) deposition using ecological responses such as the growth and mortality of tree species. Typically, CLs are reported as a single value, with uncertainty, for an indicator across a species' entire range. Mediating factors such as climate and soil conditions can influence species' sensitivity to N, but the magnitudes of these effects are rarely calculated explicitly. Here, we quantify the spatial variability and estimation error in N CLs for the growth and survival of 10 different tree species while accounting for key environmental factors that mediate species sensitivity to N (e.g., soil characteristics). We used a bootstrapped machine learning approach to determine the level of N deposition at which a 1% decrease occurs in growth rate or survival probability at forest plot locations across the United States. We found minimal differences (<5 kg N ha

Indexed as

atmospheric depositioncritical loadsmachine learningmediating factorsnitrogenplant nutrient cyclingterrestrial ecosystemtree growthtree mortality

Identifiers

PMID39758151
PMCPMC11694898

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.