Evidence map›Paper›PMID 38982502›Full record

ArticlePlant methods2024

Terrestrial laser scanning and low magnetic field digitization yield similar architectural coarse root traits for 32-year-old Pinus ponderosa trees.

Antonio Montagnoli, Andrew T Hudak, Pasi Raumonen, Bruno Lasserre, Mattia Terzaghi, Carlos A Silva, Benjamin C Bright, Lee A Vierling, Bruna N de Vasconcellos, Donato Chiatante and 1 more

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Article in Plant methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Antonio MontagnoliDepartment of Biotechnology and Life Science, University of Insubria, Varese, Italy. antonio.montagnoli@uninsubria.it.ORCID http://orcid.org/0000-0002-8921-0754
Andrew T HudakUSDA Forest Service, Rocky Mountain Research Station, Moscow, ID, USA.ORCID http://orcid.org/0000-0001-7480-1458
Pasi RaumonenComputing Sciences, Tampere University, Tampere, Finland.ORCID http://orcid.org/0000-0001-5471-0970
Bruno LasserreDepartment of Biosciences and Territory, University of Molise, Pesche, Italy.ORCID http://orcid.org/0000-0003-1150-8064
Mattia TerzaghiDepartment of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari, Italy.ORCID http://orcid.org/0000-0002-8803-7726
Carlos A SilvaSchool of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, USA.ORCID http://orcid.org/0000-0002-7844-3560
Benjamin C BrightUSDA Forest Service, Rocky Mountain Research Station, Moscow, ID, USA.ORCID http://orcid.org/0000-0002-8363-0803
Lee A VierlingDepartment of Natural Resources and Society, University of Idaho, University Federal of Parana, Moscow, ID, USA.ORCID http://orcid.org/0000-0001-5344-1983
Bruna N de VasconcellosUniversity Federal of Parana, Curitiba, Brazil.ORCID http://orcid.org/0000-0002-3868-4706
Donato ChiatanteDepartment of Biotechnology and Life Science, University of Insubria, Varese, Italy.ORCID http://orcid.org/0000-0003-4854-5408
R Kasten DumroeseUSDA Forest Service, Rocky Mountain Research Station, Moscow, ID, USA.ORCID http://orcid.org/0000-0002-2790-5286

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding how trees develop their root systems is crucial for the comprehension of how wildland and urban forest ecosystems plastically respond to disturbances such as harvest, fire, and climate change. The interplay between the endogenously determined root traits and the response to environmental stimuli results in tree adaptations to biotic and abiotic factors, influencing stability, carbon allocation, and nutrient uptake. Combining the three-dimensional structure of the root system, with root morphological trait information promotes a robust understanding of root function and adaptation plasticity. Low Magnetic Field Digitization coupled with AMAPmod (botAnique et Modelisation de l'Architecture des Plantes) software has been the best-performing method for describing root system architecture and providing reliable measurements of coarse root traits, but the pace and scale of data collection remain difficult. Instrumentation and applications related to Terrestrial Laser Scanning (TLS) have advanced appreciably, and when coupled with Quantitative Structure Models (QSM), have shown some potential toward robust measurements of tree root systems. Here we compare, we believe for the first time, these two methodologies by analyzing the root system of 32-year-old Pinus ponderosa trees.

resultsIn general, at the total root system level and by root-order class, both methods yielded comparable values for the root traits volume, length, and number. QSM for each root trait was highly sensitive to the root size (i.e., input parameter PatchDiam) and models were optimized when discrete PatchDiam ranges were specified for each trait. When examining roots in the four cardinal direction sectors, we observed differences between methodologies for length and number depending on root order but not volume.

conclusionsWe believe that TLS and QSM could facilitate rapid data collection, perhaps in situ, while providing quantitative accuracy, especially at the total root system level. If more detailed measures of root system architecture are desired, a TLS method would benefit from additional scans at differing perspectives, avoiding gravitational displacement to the extent possible, while subsampling roots by hand to calibrate and validate QSM models. Despite some unresolved logistical challenges, our results suggest that future use of TLS may hold promise for quantifying tree root system architecture in a rapid, replicable manner.

Indexed as

AMAPmodLiDARPonderosa pineQuantitative structure modelsRoot architectureTreeQSM

Identifiers

PMID38982502
PMCPMC11232291

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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.