Vegetation structural complexity and biodiversity in the Great Smoky Mountains
Abstract Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics...
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Online Access: | https://doi.org/10.1002/ecs2.3390 |
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doaj-70dc6f5165fb4db7a4633270b706ef8c2021-04-18T21:00:38ZengWileyEcosphere2150-89252021-03-01123n/an/a10.1002/ecs2.3390Vegetation structural complexity and biodiversity in the Great Smoky MountainsJonathan A. Walter0Atticus E. L. Stovall1Jeff W. Atkins2Department of Environmental Sciences University of Virginia Charlottesville Virginia22904USANASA Goddard Space Flight Center Biospheric Sciences Lab Greenbelt Maryland20771USADepartment of Biology Virginia Commonwealth University Richmond Virginia23284USAAbstract Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high‐biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height‐normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.https://doi.org/10.1002/ecs2.3390elevationforestLiDARspecies richnessstructural complexitytopography |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jonathan A. Walter Atticus E. L. Stovall Jeff W. Atkins |
spellingShingle |
Jonathan A. Walter Atticus E. L. Stovall Jeff W. Atkins Vegetation structural complexity and biodiversity in the Great Smoky Mountains Ecosphere elevation forest LiDAR species richness structural complexity topography |
author_facet |
Jonathan A. Walter Atticus E. L. Stovall Jeff W. Atkins |
author_sort |
Jonathan A. Walter |
title |
Vegetation structural complexity and biodiversity in the Great Smoky Mountains |
title_short |
Vegetation structural complexity and biodiversity in the Great Smoky Mountains |
title_full |
Vegetation structural complexity and biodiversity in the Great Smoky Mountains |
title_fullStr |
Vegetation structural complexity and biodiversity in the Great Smoky Mountains |
title_full_unstemmed |
Vegetation structural complexity and biodiversity in the Great Smoky Mountains |
title_sort |
vegetation structural complexity and biodiversity in the great smoky mountains |
publisher |
Wiley |
series |
Ecosphere |
issn |
2150-8925 |
publishDate |
2021-03-01 |
description |
Abstract Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high‐biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height‐normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms. |
topic |
elevation forest LiDAR species richness structural complexity topography |
url |
https://doi.org/10.1002/ecs2.3390 |
work_keys_str_mv |
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