Evidence map›Paper›PMID 41854252›Full record

ReviewThe New phytologist2026

Scaling plant hydraulic traits to predict ecosystem fluxes under drought.

Yanlan Liu

Abstract readReview
In one paragraph

Review in The New phytologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Yanlan LiuDepartment of Geography, University of California, Los Angeles, CA, 90095, USA.ORCID https://orcid.org/0000-0001-5129-6284

Funding

Earth Sciences Division 80NSSC21K1523Earth Sciences Division 80NSSC22K1249
6 · The paper itself

Abstract

Expanding plant hydraulic trait measurements and advances in hydraulic modeling have improved mechanistic predictions of water-carbon fluxes under drought. However, mismatches between individual-scale traits and ecosystem-scale model representations introduce prediction uncertainties and obscure how drought impacts propagate across scales. This synthesis identifies four key sources of scale-induced uncertainty: trait variability, Jensen's inequality, within-community processes, and compensation errors. I review current efforts to bridge these gaps using both forward modeling and inversion approaches and highlight emerging opportunities from improved characterization of trait variability, mechanistic models that represent community diversity and interactions, and multi-scale observational networks. Leveraging these opportunities will elucidate the mechanistic propagation of drought impacts across scales and improve predictions of ecosystem flux responses to future droughts.

Indexed as

DroughtsEcosystemPlant Physiological PhenomenaPlantsQuantitative Trait, HeritableWaterModels, BiologicalWaterdroughtecosystem diversityland surface modelingmodel‐data integrationplant hydraulicsscalingtraits

Identifiers

PMID41854252
PMCPMC13103435

What OpenQuestion holds

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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.