Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysis

Abstract Light is a key driver of forest biodiversity and functioning. Light regimes beneath tree canopies are mainly driven by the solar angle, topography, and vegetation structure, whose three‐dimensional complexity creates heterogeneous light conditions that are challenging to quantify, especiall...

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Main Authors: Florian Zellweger, Andri Baltensweiler, Patrick Schleppi, Markus Huber, Meinrad Küchler, Christian Ginzler, Tobias Jonas
Format: Article
Language:English
Published: Wiley 2019-08-01
Series:Ecology and Evolution
Subjects:
Online Access:https://doi.org/10.1002/ece3.5462
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author Florian Zellweger
Andri Baltensweiler
Patrick Schleppi
Markus Huber
Meinrad Küchler
Christian Ginzler
Tobias Jonas
author_facet Florian Zellweger
Andri Baltensweiler
Patrick Schleppi
Markus Huber
Meinrad Küchler
Christian Ginzler
Tobias Jonas
author_sort Florian Zellweger
collection DOAJ
description Abstract Light is a key driver of forest biodiversity and functioning. Light regimes beneath tree canopies are mainly driven by the solar angle, topography, and vegetation structure, whose three‐dimensional complexity creates heterogeneous light conditions that are challenging to quantify, especially across large areas. Remotely sensed canopy structure data from airborne laser scanning (ALS) provide outstanding opportunities for advancement in this respect. We used ALS point clouds and a digital terrain model to produce hemispherical photographs from which we derived indices of nondirectional diffuse skylight and direct sunlight reaching the understory. We validated our approach by comparing the performance of these indices, as well as canopy closure (CCl) and canopy cover (CCo), for explaining the light conditions experienced by forest plant communities, as indicated by the Landolt indicator values for light (Llight) from 43 vegetation surveys along an elevational gradient. We applied variation partitioning to analyze how the independent and joint statistical effects of light, macroclimate, and soil on the spatial variation in plant species composition (i.e., turnover, Simpson dissimilarity, βSIM) depend on light approximation methodology. Diffuse light explained Llight best, followed by direct light, CCl and CCo (R2 = .31, .23, .22, and .22, respectively). The combination of diffuse and direct light improved the model performance for βSIM compared with CCl and CCo (R2 = .30, .27 and .24, respectively). The independent effect of macroclimate on βSIM dropped from an R2 of .15 to .10 when diffuse light and direct light were included. The ALS methods presented here outperform conventional approximations of below‐canopy light conditions, which can now efficiently be quantified along entire horizontal and vertical forest gradients, even in topographically complex environments such as mountains. The effect of macroclimate on forest plant communities is prone to be overestimated if local light regimes and associated microclimates are not accurately accounted for.
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spelling doaj.art-c601eddf7180407093d0df057af63b0c2022-12-21T20:20:02ZengWileyEcology and Evolution2045-77582019-08-019169149915910.1002/ece3.5462Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysisFlorian Zellweger0Andri Baltensweiler1Patrick Schleppi2Markus Huber3Meinrad Küchler4Christian Ginzler5Tobias Jonas6Swiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf SwitzerlandSwiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf SwitzerlandSwiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf SwitzerlandSwiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf SwitzerlandSwiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf SwitzerlandSwiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf SwitzerlandWSL Institute for Snow and Avalanche Research SLF Davos Dorf SwitzerlandAbstract Light is a key driver of forest biodiversity and functioning. Light regimes beneath tree canopies are mainly driven by the solar angle, topography, and vegetation structure, whose three‐dimensional complexity creates heterogeneous light conditions that are challenging to quantify, especially across large areas. Remotely sensed canopy structure data from airborne laser scanning (ALS) provide outstanding opportunities for advancement in this respect. We used ALS point clouds and a digital terrain model to produce hemispherical photographs from which we derived indices of nondirectional diffuse skylight and direct sunlight reaching the understory. We validated our approach by comparing the performance of these indices, as well as canopy closure (CCl) and canopy cover (CCo), for explaining the light conditions experienced by forest plant communities, as indicated by the Landolt indicator values for light (Llight) from 43 vegetation surveys along an elevational gradient. We applied variation partitioning to analyze how the independent and joint statistical effects of light, macroclimate, and soil on the spatial variation in plant species composition (i.e., turnover, Simpson dissimilarity, βSIM) depend on light approximation methodology. Diffuse light explained Llight best, followed by direct light, CCl and CCo (R2 = .31, .23, .22, and .22, respectively). The combination of diffuse and direct light improved the model performance for βSIM compared with CCl and CCo (R2 = .30, .27 and .24, respectively). The independent effect of macroclimate on βSIM dropped from an R2 of .15 to .10 when diffuse light and direct light were included. The ALS methods presented here outperform conventional approximations of below‐canopy light conditions, which can now efficiently be quantified along entire horizontal and vertical forest gradients, even in topographically complex environments such as mountains. The effect of macroclimate on forest plant communities is prone to be overestimated if local light regimes and associated microclimates are not accurately accounted for.https://doi.org/10.1002/ece3.5462airborne light detection and ranging LiDARbeta diversitybiodiversitycanopy structureEllenberg indicator valueforest biodiversity
spellingShingle Florian Zellweger
Andri Baltensweiler
Patrick Schleppi
Markus Huber
Meinrad Küchler
Christian Ginzler
Tobias Jonas
Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysis
Ecology and Evolution
airborne light detection and ranging LiDAR
beta diversity
biodiversity
canopy structure
Ellenberg indicator value
forest biodiversity
title Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysis
title_full Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysis
title_fullStr Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysis
title_full_unstemmed Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysis
title_short Estimating below‐canopy light regimes using airborne laser scanning: An application to plant community analysis
title_sort estimating below canopy light regimes using airborne laser scanning an application to plant community analysis
topic airborne light detection and ranging LiDAR
beta diversity
biodiversity
canopy structure
Ellenberg indicator value
forest biodiversity
url https://doi.org/10.1002/ece3.5462
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