Integrating forest structural diversity measurement into ecological research

Jeff W. Atkins, Parth Bhatt, Luis Carrasco, Emily Francis, James E. Garabedian, Christopher R. Hakkenberg, Brady S. Hardiman, Jinha Jung, Anil Koirala, Elizabeth A. LaRue, Sungchan Oh, Gang Shao, Guofan Shao, H. H. Shugart, Anna Spiers, Atticus E.L. Stovall, Thilina D. Surasinghe, Xiaonan Tai, Lu Zhai, Tao ZhangKeith Krause

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


The measurement of forest structure has evolved steadily due to advances in technology, methodology, and theory. Such advances have greatly increased our capacity to describe key forest structural elements and resulted in a range of measurement approaches from traditional analog tools such as measurement tapes to highly derived and computationally intensive methods such as advanced remote sensing tools (e.g., lidar, radar). This assortment of measurement approaches results in structural metrics unique to each method, with the caveat that metrics may be biased or constrained by the measurement approach taken. While forest structural diversity (FSD) metrics foster novel research opportunities, understanding how they are measured or derived, limitations of the measurement approach taken, as well as their biological interpretation is crucial for proper application. We review the measurement of forest structure and structural diversity—an umbrella term that includes quantification of the distribution of functional and biotic components of forests. We consider how and where these approaches can be used, the role of technology in measuring structure, how measurement impacts extend beyond research, and current limitations and potential opportunities for future research.

Original languageEnglish (US)
Article numbere4633
Issue number9
StatePublished - Sep 2023

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecology


  • forest ecology
  • forest structure
  • forestry
  • landscape ecology
  • lidar
  • measurement
  • remote sensing
  • spatial sampling
  • structural diversity


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