Quantifying micro-environmental variation in tropical rainforest understory at landscape scale by combining airborne LiDAR scanning and a sensor network

Tymen, Blaise; Vincent, Grégoire; Courtois, Elodie A.; Heurtebize, Julien; Dauzat, Jean; Maréchaux, Isabelle; Chave, Jérôme

doi:10.1007/s13595-017-0628-z

Cited by 49 publications

(49 citation statements)

References 58 publications

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“…By coupling ALS data with on-ground networks of microclimate sensors, we are now in a position to robustly assess the relative importance of different topographic and canopy structural features in determining microclimate (Frey et al, 2016;Lenoir et al, 2017). Moreover, these same data can then be used to generate high-resolution microclimatic surfaces for entire landscapes using either empirical of physical-based modelling approaches (Hardwick, 2015;Tymen et al, 2017). This last step is critical if we are to generate realistic predictions of how ecological communities and the processes they underpin are likely to respond to rapid global change (Lenoir et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Canopy structure and topography jointly constrain the microclimate of human‐modified tropical landscapes

Jucker

Hardwick

Both

et al. 2018

Global Change Biology

183

203

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Local‐scale microclimatic conditions in forest understoreys play a key role in shaping the composition, diversity and function of these ecosystems. Consequently, understanding what drives variation in forest microclimate is critical to forecasting ecosystem responses to global change, particularly in the tropics where many species already operate close to their thermal limits and rapid land‐use transformation is profoundly altering local environments. Yet our ability to characterize forest microclimate at ecologically meaningful scales remains limited, as understorey conditions cannot be directly measured from outside the canopy. To address this challenge, we established a network of microclimate sensors across a land‐use intensity gradient spanning from old‐growth forests to oil‐palm plantations in Borneo. We then combined these observations with high‐resolution airborne laser scanning data to characterize how topography and canopy structure shape variation in microclimate both locally and across the landscape. In the processes, we generated high‐resolution microclimate surfaces spanning over 350 km2, which we used to explore the potential impacts of habitat degradation on forest regeneration under both current and future climate scenarios. We found that topography and vegetation structure were strong predictors of local microclimate, with elevation and terrain curvature primarily constraining daily mean temperatures and vapour pressure deficit (VPD), whereas canopy height had a clear dampening effect on microclimate extremes. This buffering effect was particularly pronounced on wind‐exposed slopes but tended to saturate once canopy height exceeded 20 m—suggesting that despite intensive logging, secondary forests remain largely thermally buffered. Nonetheless, at a landscape‐scale microclimate was highly heterogeneous, with maximum daily temperatures ranging between 24.2 and 37.2°C and VPD spanning two orders of magnitude. Based on this, we estimate that by the end of the century forest regeneration could be hampered in degraded secondary forests that characterize much of Borneo's lowlands if temperatures continue to rise following projected trends.

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Section: Introductionmentioning

confidence: 99%

Canopy structure and topography jointly constrain the microclimate of human‐modified tropical landscapes

Jucker

Hardwick

Both

et al. 2018

Global Change Biology

183

203

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“…While area‐based measurements, such as canopy cover, are frequently used (Morsdorf et al, ; Zellweger et al, ), point‐based measurements, such as canopy closure, are computationally more demanding and less often used, despite them being ecologically more relevant (Alexander et al, ). Similarly, voxel‐based ray tracing techniques have been successfully applied to estimate below‐canopy light conditions and associated microclimate conditions (Musselman, Pomeroy, & Link, ; Tymen et al, ).…”

Section: Introductionmentioning

confidence: 99%

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

Zellweger

Baltensweiler

Schleppi

et al. 2019

Ecology and Evolution

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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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“…LAD profiles have seen a gamut of applications in recent tropical forest studies: impact of fire and sensitivity to fire ; estimating tree diameter-class frequencies (Stark et al, 2015); forest type discrimination; and radiation transfer and absorption modeling Tymen et al, 2017;Wu et al, 2018;Atkins et al, 2018). ALS-derived estimations of LAD profiles and of LAI provide unprecedented opportunities for estimating canopy structure and function, including modeling the leaf environments and forest demographic structure, on a broad spatial scale to address problems in forest conservation and management.…”

Section: Conclusion and Implications For Future Researchmentioning

confidence: 99%

“…Some studies have used the lidar cloud to modelling structural parameters such as lead area density (LAD, m 2 m -3 ) and leaf area index (LAI, m 2 m -2 ) (Stark et al, , 2015. LAI is a widely used variable in ecology in aspects such as diversity, light environment, water interception, dynamics and seasonality (Bréda, 2003;Tymen et al, 2017). However, the modeling of LAD and LAI with lidar data is still quite recent and yet needs to be better understood and improved.…”

Section: Introductionmentioning

confidence: 99%

“…Measuring the density and distribution of leaves in forest canopies is key to understanding ecological and microclimate processes that drive forest function (Putz, 1983;Breda et al, 2008;Tymen et al, 2017;Stark et al, , 2015Atkins et al, 2018). The spatial structure of leaf area influences light transmittance and absorbance, biodiversity conservation, carbon fluxes, ecophysiology, leaf phenology, disturbances, and water and climate interactions (Breda et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Assessing tropical forest degradation and restoration through lidar remote sensing

Almeida¹

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Quantifying micro-environmental variation in tropical rainforest understory at landscape scale by combining airborne LiDAR scanning and a sensor network

Cited by 49 publications

References 58 publications

Canopy structure and topography jointly constrain the microclimate of human‐modified tropical landscapes

Canopy structure and topography jointly constrain the microclimate of human‐modified tropical landscapes

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

Assessing tropical forest degradation and restoration through lidar remote sensing

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