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Stem diameter variations as a versatile research tool in ecophysiology.

Tom De Swaef1, Veerle De Schepper2, Maurits W Vandegehuchte2

  • 1Plant Sciences Unit, Institute for Agricultural and Fisheries Research (ILVO), Caritasstraat 21, 9090 Melle, Belgium Laboratory of Plant Ecology, Department of Applied Ecology and Environmental Biology, Faculty of Bioscience Engineering, Ghent University, Coupure links 653, 9000 Gent, Belgium.

Tree Physiology
|September 18, 2015
PubMed
Summary
This summary is machine-generated.

Stem diameter variations (SDV) offer insights into plant water status and drought stress. Recent research uses SDV with modeling to explore plant physiology, hydraulics, and phenology for ecological and breeding applications.

Keywords:
carbon relationsdendrometerirrigation schedulinglinear variable displacement transducer (LVDT)nutrientsphloemplant water relationssap flowstem radius changesxylem

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Area of Science:

  • Plant Physiology and Biophysics
  • Dendrochronology
  • Ecological Research

Background:

  • High-resolution stem diameter variations (SDV) are established drought stress indicators used in irrigation scheduling.
  • SDV are increasingly integrated with other plant measurements and biophysical modeling for fundamental research on plant functioning and growth.

Purpose of the Study:

  • To review and scrutinize recent insights from advanced SDV applications.
  • To identify trends in ongoing fundamental research utilizing SDV.
  • To highlight the potential of SDV in understanding plant water relations, hydraulics, carbon dynamics, and phenology.

Main Methods:

  • Review of existing literature on stem diameter variations (SDV) applications.
  • Integration of SDV with other plant measurements (e.g., magnetic resonance imaging).
  • Application of mechanistic and biophysical modeling to interpret SDV data.
  • Analysis of short-term experiments and long-term SDV time series.

Main Results:

  • SDV primarily reflects stem water content variations due to tissue shrinkage/swelling and growth.
  • Mechanistic modeling is crucial for extracting physiological and biophysical information from SDV.
  • Two main research tracks identified: detailed short-term studies on physiological mechanisms and long-term phenotyping for ecological and breeding research.

Conclusions:

  • SDV is a versatile tool for examining diverse plant physiological and biophysical processes.
  • Long-term SDV data offers valuable phenotypic information for ecological studies and breeding under global change.
  • Coordinated initiatives are emerging to exploit SDV data pools through global analysis and data-mining.