Vegetation structure derived from airborne laser scanning to assess species distribution and habitat suitability: The way forward

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Vítězslav Moudrý - , Czech University of Life Sciences Prague, Charles University Prague, Czech Academy of Sciences (Author)
  • Anna F. Cord - , Chair of Computational Landscape Ecology, Technische Universität Dresden (Author)
  • Lukáš Gábor - , Czech University of Life Sciences Prague, Yale University (Author)
  • Gaia Vaglio Laurin - , Tuscia University (Author)
  • Vojtěch Barták - , Czech University of Life Sciences Prague (Author)
  • Kateřina Gdulová - , Czech University of Life Sciences Prague (Author)
  • Marco Malavasi - , Czech University of Life Sciences Prague, University of Sassari (Author)
  • Duccio Rocchini - , Czech University of Life Sciences Prague, University of Bologna (Author)
  • Krzysztof Stereńczak - , Forest Research Institute (Author)
  • Jiří Prošek - , Czech University of Life Sciences Prague, Czech Academy of Sciences (Author)
  • Petr Klápště - , Czech University of Life Sciences Prague (Author)
  • Jan Wild - , Czech University of Life Sciences Prague, Czech Academy of Sciences (Author)

Abstract

Ecosystem structure, especially vertical vegetation structure, is one of the six essential biodiversity variable classes and is an important aspect of habitat heterogeneity, affecting species distributions and diversity by providing shelter, foraging, and nesting sites. Point clouds from airborne laser scanning (ALS) can be used to derive such detailed information on vegetation structure. However, public agencies usually only provide digital elevation models, which do not provide information on vertical vegetation structure. Calculating vertical structure variables from ALS point clouds requires extensive data processing and remote sensing skills that most ecologists do not have. However, such information on vegetation structure is extremely valuable for many analyses of habitat use and species distribution. We here propose 10 variables that should be easily accessible to researchers and stakeholders through national data portals. In addition, we argue for a consistent selection of variables and their systematic testing, which would allow for continuous improvement of such a list to keep it up-to-date with the latest evidence. This initiative is particularly needed not only to advance ecological and biodiversity research by providing valuable open datasets but also to guide potential users in the face of increasing availability of global vegetation structure products.

Details

Original languageEnglish
Pages (from-to)39-50
Number of pages12
JournalDiversity and Distributions
Volume29
Issue number1
Publication statusPublished - Jan 2023
Peer-reviewedYes

Keywords

Keywords

  • habitat heterogeneity, LiDAR, niche, point cloud, predictors, SDM