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Use and categorization of Light Detection and Ranging vegetation metrics in avian diversity and species distribution research

Bakx, Tristan LU ; Koma, Zsófia ; Seijmonsbergen, Arie C. and Kissling, W. Daniel (2019) In Diversity and Distributions 25(7). p.1045-1059
Abstract
Aim: Vegetation structure is a key determinant of animal diversity and species distributions. The introduction of Light Detection and Ranging (LiDAR) has enabled the collection of massive amounts of point cloud data for quantifying habitat structure at fine resolution. Here, we review the current use of LiDAR‐derived vegetation metrics in diversity and distribution research of birds, a key group for understanding animal–habitat relationships.Location: Global.Methods: We review 50 relevant papers and quantify where, in which habitats, at which spatial scales and with what kind of LiDAR data current studies make use of LiDAR metrics. We also harmonize and categorize LiDAR metrics and quantify their current use and effectiveness.Results: Most... (More)
Aim: Vegetation structure is a key determinant of animal diversity and species distributions. The introduction of Light Detection and Ranging (LiDAR) has enabled the collection of massive amounts of point cloud data for quantifying habitat structure at fine resolution. Here, we review the current use of LiDAR‐derived vegetation metrics in diversity and distribution research of birds, a key group for understanding animal–habitat relationships.Location: Global.Methods: We review 50 relevant papers and quantify where, in which habitats, at which spatial scales and with what kind of LiDAR data current studies make use of LiDAR metrics. We also harmonize and categorize LiDAR metrics and quantify their current use and effectiveness.Results: Most studies have been conducted at local extents in temperate forests of North America and Europe. Rasterization is currently the main method to derive LiDAR metrics, usually from airborne laser scanning data with low point densities (<10 points/m2) and small footprints (<1 m diameter). Our metric harmonization suggests that 40% of the currently used metric names are redundant. A categorization scheme allowed to group all metric names into 18 out of 24 theoretically possible classes, defined by vegetation part (total vegetation, single trees, canopy, understorey, and other single layers as well as multi‐layer) and structural type (cover, height, horizontal variability and vertical variability). Metrics related to canopy cover, canopy height and canopy vertical variability are currently most often used, but not always effective.Main conclusions: Light Detection and Ranging metrics play an important role in understanding animal space use. Our review and the developed categorization scheme may facilitate future studies in the selection, prioritization and ecological interpretation of LiDAR metrics. The increasing availability of airborne and spaceborne LiDAR data and the development of voxel‐based and object‐based approaches will further allow novel ecological applications, also for open habitats and other vertebrate and invertebrate taxa. (Less)
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author
; ; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Airborne laser scanning, animal diversity, habitat use, LiDAR, literature review, species distribution modelling, structural heterogeneity, vertical vegetation structure
in
Diversity and Distributions
volume
25
issue
7
pages
15 pages
publisher
Wiley-Blackwell
ISSN
1366-9516
DOI
10.1111/ddi.12915
language
English
LU publication?
no
id
c8201f3f-c63a-49dd-9231-b65242c112ac
date added to LUP
2019-10-25 15:12:54
date last changed
2021-02-01 14:22:58
@article{c8201f3f-c63a-49dd-9231-b65242c112ac,
  abstract     = {Aim: Vegetation structure is a key determinant of animal diversity and species distributions. The introduction of Light Detection and Ranging (LiDAR) has enabled the collection of massive amounts of point cloud data for quantifying habitat structure at fine resolution. Here, we review the current use of LiDAR‐derived vegetation metrics in diversity and distribution research of birds, a key group for understanding animal–habitat relationships.Location: Global.Methods: We review 50 relevant papers and quantify where, in which habitats, at which spatial scales and with what kind of LiDAR data current studies make use of LiDAR metrics. We also harmonize and categorize LiDAR metrics and quantify their current use and effectiveness.Results: Most studies have been conducted at local extents in temperate forests of North America and Europe. Rasterization is currently the main method to derive LiDAR metrics, usually from airborne laser scanning data with low point densities (&lt;10 points/m2) and small footprints (&lt;1 m diameter). Our metric harmonization suggests that 40% of the currently used metric names are redundant. A categorization scheme allowed to group all metric names into 18 out of 24 theoretically possible classes, defined by vegetation part (total vegetation, single trees, canopy, understorey, and other single layers as well as multi‐layer) and structural type (cover, height, horizontal variability and vertical variability). Metrics related to canopy cover, canopy height and canopy vertical variability are currently most often used, but not always effective.Main conclusions: Light Detection and Ranging metrics play an important role in understanding animal space use. Our review and the developed categorization scheme may facilitate future studies in the selection, prioritization and ecological interpretation of LiDAR metrics. The increasing availability of airborne and spaceborne LiDAR data and the development of voxel‐based and object‐based approaches will further allow novel ecological applications, also for open habitats and other vertebrate and invertebrate taxa.},
  author       = {Bakx, Tristan and Koma, Zsófia and Seijmonsbergen, Arie C. and Kissling, W. Daniel},
  issn         = {1366-9516},
  language     = {eng},
  month        = {06},
  number       = {7},
  pages        = {1045--1059},
  publisher    = {Wiley-Blackwell},
  series       = {Diversity and Distributions},
  title        = {Use and categorization of Light Detection and Ranging vegetation metrics in avian diversity and species distribution research},
  url          = {http://dx.doi.org/10.1111/ddi.12915},
  doi          = {10.1111/ddi.12915},
  volume       = {25},
  year         = {2019},
}