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, 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.

Artifleck: The Study of Artifactual Responses to Light Flecks with Inappropriate Leaves

“…A heterogeneous shade treatment designed to match the percent light exclusion of the shade screen was created by constructing a slat house with 5 cm wood slats positioned at a homogeneous distance in order to provide gaps through which the solar beam could pass. Diffuse light [ 41 ] and penumbral effects [ 42 ] added photosynthetically active radiation within the shaded areas provided by the slats, so the quantification of the integrated 62% overall light exclusion was achieved by adjusting the diameter of the gaps during construction until the desired PPFD was achieved. On the days with clear sky conditions and no clouds, 62% light exclusion was 780 µmol·m −2 ·s −1 .…”

A Research Agenda for Microclimate Ecology in Human-Modified Tropical Forests

“…High spatial and spectral resolution remote sensing imagery would be one way to up-scale data from localized experiments. Using litter decomposition as an example, key components of this process could be estimated accurately using airborne LiDAR and hyperspectral imagery (Krishna and Mohan, 2017), including microclimate , litter quantity (Detto et al, 2015), litter quality , and solar radiation (Zellweger et al, 2019a).…”

Plant species richness increases with light availability, but not variability, in temperate forests understorey

“…Similarly, neither gap sizes nor Ellenberg light indicator values seem to be consistently good predictors of transmittance (e.g. [ 22 – 24 ], but see [ 25 ] for regional adjustment of indicators to lidar measurements). Hence, we regard the direct measurement of (photosynthetically active) light availability at the forest floor as the currently only uncontroversial way to assess light conditions.…”