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Terrestrial laser scanning and low magnetic field digitization yield similar architectural coarse root traits for 32-year-old Pinus ponderosa trees.
Montagnoli, Antonio; Hudak, Andrew T; Raumonen, Pasi; Lasserre, Bruno; Terzaghi, Mattia; Silva, Carlos A; Bright, Benjamin C; Vierling, Lee A; de Vasconcellos, Bruna N; Chiatante, Donato; Dumroese, R Kasten.
Affiliation
  • Montagnoli A; Department of Biotechnology and Life Science, University of Insubria, Varese, Italy. antonio.montagnoli@uninsubria.it.
  • Hudak AT; USDA Forest Service, Rocky Mountain Research Station, Moscow, ID, USA.
  • Raumonen P; Computing Sciences, Tampere University, Tampere, Finland.
  • Lasserre B; Department of Biosciences and Territory, University of Molise, Pesche, Italy.
  • Terzaghi M; Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari, Italy.
  • Silva CA; School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, USA.
  • Bright BC; USDA Forest Service, Rocky Mountain Research Station, Moscow, ID, USA.
  • Vierling LA; Department of Natural Resources and Society, University of Idaho, University Federal of Parana, Moscow, ID, USA.
  • de Vasconcellos BN; University Federal of Parana, Curitiba, Brazil.
  • Chiatante D; Department of Biotechnology and Life Science, University of Insubria, Varese, Italy.
  • Dumroese RK; USDA Forest Service, Rocky Mountain Research Station, Moscow, ID, USA.
Plant Methods ; 20(1): 102, 2024 Jul 09.
Article in En | MEDLINE | ID: mdl-38982502
ABSTRACT

BACKGROUND:

Understanding 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.

RESULTS:

In 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.

CONCLUSIONS:

We 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.
Key words

Full text: 1 Database: MEDLINE Language: En Journal: Plant Methods Year: 2024 Type: Article Affiliation country: Italy

Full text: 1 Database: MEDLINE Language: En Journal: Plant Methods Year: 2024 Type: Article Affiliation country: Italy