Evidence map›Paper›PMID 35300262›Full record

ArticleNature geoscience2022

Confronting the water potential information gap.

Kimberly A Novick, Darren L Ficklin, Dennis Baldocchi, Kenneth J Davis, Teamrat A Ghezzehei, Alexandra G Konings, Natasha MacBean, Nina Raoult, Russell L Scott, Yuning Shi and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Nature geoscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
15.5field-weighted citation impact, top 1% of its field
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

28 citing papers in PubMed, 146 citations in OpenAlex.

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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

12 authors at 9 institutions in 2 countries.

Kimberly A NovickO'Neill School of Public and Environmental Affairs, Indiana University - Bloomington. Bloomington, IN USA.
Darren L FicklinDepartment of Geography, Indiana University - Bloomington. Bloomington, IN USA.
Dennis BaldocchiDepartment of Environmental Science, Policy, and Management. University of California, Berkeley. Berkeley, CA, USA.
Kenneth J DavisDepartment of Meteorology and Atmospheric Science and Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, USA.
Teamrat A GhezzeheiLife and Environmental Sciences Department, University of California - Merced. Merced, CA, USA.
Alexandra G KoningsDepartment of Earth System Science, Stanford University. Stanford, CA, USA.
Natasha MacBeanDepartment of Geography, Indiana University - Bloomington. Bloomington, IN USA.
Nina RaoultLaboratoire des Sciences du Climat et de l'Environnement. Paris, France.
Russell L ScottSouthwest Watershed Research Center, USDA - Agricultural Research Service. Tucson, AZ, USA.
Yuning ShiDepartment of Plant Science. The Pennsylvania State University, University Park, PA, USA.
Benjamin N SulmanEnvironmental Sciences Division, Oak Ridge National Laboratory. Oak Ridge, TN, USA.
Jeffrey D WoodSchool of Natural Resources, University of Missouri, Columbia, MO, USA.
Indiana University Bloomington · USPennsylvania State University · USAgricultural Research Service · USLaboratoire des Sciences du Climat et de l'Environnement · FROak Ridge National Laboratory · USStanford University · USUniversity of California, Berkeley · USUniversity of California, Merced · USUniversity of Missouri · US

Funding

Shared Services Center NASA 80NSSC18K0715
6 · The paper itself

Abstract

Water potential directly controls the function of leaves, roots, and microbes, and gradients in water potential drive water flows throughout the soil-plant-atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in-situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely-sensed proxies. Together, these considerations offer a roadmap for clearer links between ecohydrological processes and the water potential gradients that have the 'potential' to substantially reduce conceptual and modeling uncertainties.

Identifiers

PMID35300262
PMCPMC8923290
OpenAlexW4220672152

What OpenQuestion holds

Textmetadata
LicenceTDM
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.