Distribution Of Leaf Area Density Research Articles

MAPPING 3D STRUCTURE OF URBAN TREES USING AIRBORNE LIDAR DATA FOR TOPOGRAPHIC SURVEY

Abstract. The designing of urban spaces utilizing trees is a promising approach to alleviate the severe thermal environment. Three-dimensional (3D) information on individual trees is important for their maintenance and for evaluating their microclimatic effects. Methods have been developed for estimating the 3D distribution of leaf area density (LAD) using high-density airborne light detection and ranging (LiDAR) point cloud. However, the coverage of high-density data is limited. This study sought to develop a method for estimating LAD distribution using existing low-density LiDAR data that was obtained for the nationwide topographic survey. A point cloud with the same density as the existing data was generated from the high-density data. LAD was estimated using the generated point cloud and was compared with LAD derived from the high-density data and terrestrial LiDAR to clarify the spatial scale of information obtained from the existing data. A method to improve the spatial scale was also examined. These methods were applied to the actual existing LiDAR data to generate a 3D information map at an urban scale.

Direct measurement of the three-dimensional distribution of leaf area density and light conditions in a mature oak stand by the cube method

Direct measurement of the three-dimensional distribution of leaf area density and light conditions in a mature oak stand by the cube method

Estimating Three-Dimensional Distribution of Leaf Area Using Airborne LiDAR in Deciduous Broad-Leaved Forest

We examined the performance of airborne light detection and ranging (LiDAR) data obtained in 2011 for leaf area estimation in deciduous broad-leaved forest using the Beer–Lambert law in Takayama, Gifu, Japan. We estimated leaf area index (LAI, allometry-LAI) and vertical leaf area density (LAD) using field survey data by applying allometric equations to estimate leaf-area of trees and a Weibull distribution equation to estimate vertical leaf distribution. We then estimated extinction coefficients (Ke) of LiDAR data for three height layers from the ground to the canopy top using the vertical LAD and vertical laser pulse distribution. The estimated PAI (LiDAR-PAI) using the Beer–Lambert law and Ke, when treating the canopies as three height layers, showed a significant linear relationship with allometry-LAI (p < 0.001). However, LiDAR-PAI when treating the canopies as single layer saturated at a PAI of six. It was similar to the lesser PAI estimation by hemispherical photography or relative photosynthetic photon flux density which treated the canopy as a single layer, compared to LAI measurements by litter traps. It is therefore important to allocate distinct Ke values to each of the multiple height layers for an accurate estimation of PAI and vertical PAD when applying the Beer–Lambert law to airborne LiDAR data.

Large-Eddy Simulation of Wind Turbine Wakes in Forest Terrain

In this study, large-eddy simulation was employed to investigate the influence of the forest canopy on wind turbine wakes. Nine forest case studies were carried out with different vertical distributions of leaf area density (LAD) and values of leaf area index (LAI). It was found that the wake in forest canopies recovers at a faster rate when compared with the flat terrain. An interesting observation was the significant reduction in turbulence kinetic energy (TKE) in the lower part of the wake above the forest in comparison with the inflow TKE, which occurred for a wide range of turbine downstream positions. The increase of TKE, on the other hand, was mainly located in the region around the top tip. Analyses of the power spectral density showed that the increase in TKE happened at a certain range of frequencies for the forest canopy cases and at all the examined frequencies for the flat case. Wake meandering was also examined and was found to be of a higher amplitude and a lower dominant frequency for the forest cases compared with the flat case. In terms of the influence of forest canopy parameters, the LAI was found to have an impact greater than the vertical distribution of LAD. Specifically, the wake-added TKE and wake-added Reynolds shear stress were found to be approximately the same for cases with the same LAI, regardless of the vertical distribution of LAD.

Isoprene and monoterpene simulations using the chemistry–climate model EMAC (v2.55) with interactive vegetation from LPJ-GUESS (v4.0)

Abstract. Earth system models (ESMs) integrate previously separate models of the ocean, atmosphere and vegetation into one comprehensive modelling system enabling the investigation of interactions between different components of the Earth system. Global isoprene and monoterpene emissions from terrestrial vegetation, which represent the most important source of volatile organic compounds (VOCs) in the Earth system, need to be included in global and regional chemical transport models given their major chemical impacts on the atmosphere. Due to the feedback of vegetation activity involving interactions with weather and climate, a coupled modelling system between vegetation and atmospheric chemistry is recommended to address the fate of biogenic volatile organic compounds (BVOCs). In this work, further development in linking LPJ-GUESS, a global dynamic vegetation model, to the atmospheric-chemistry-enabled atmosphere–ocean general circulation model EMAC is presented. New parameterisations are included to calculate the foliar density and leaf area density (LAD) distribution from LPJ-GUESS information. The new vegetation parameters are combined with existing LPJ-GUESS output (i.e. leaf area index and cover fractions) and used in empirically based BVOC modules in EMAC. Estimates of terrestrial BVOC emissions from EMAC's submodels ONEMIS and MEGAN are evaluated using (1) prescribed climatological vegetation boundary conditions at the land–atmosphere interface and (2) dynamic vegetation states calculated in LPJ-GUESS (replacing the “offline” vegetation inputs). LPJ-GUESS-driven global emission estimates for isoprene and monoterpenes from the submodel ONEMIS were 546 and 102 Tg yr−1, respectively. MEGAN determines 657 and 55 Tg of isoprene and monoterpene emissions annually. The new vegetation-sensitive BVOC fluxes in EMAC are in good agreement with emissions from the semi-process-based module in LPJ-GUESS. The new coupled system is used to evaluate the temperature and vegetation sensitivity of BVOC fluxes in doubling CO2 scenarios. This work provides evidence that the new coupled model yields suitable estimates for global BVOC emissions that are responsive to vegetation dynamics. It is concluded that the proposed model set-up is useful for studying land–biosphere–atmosphere interactions in the Earth system.

CFD simulations of the tree effect on the outdoor microclimate by coupling the canopy energy balance model

Trees can effectively regulate the urban microclimate, while the change of microclimate conditions in turn affect the physiological state of trees. In this paper, CFD simulations are performed by coupling canopy energy balance (CEB) model to study the effects of trees on outdoor microclimate. The results show that the tree has different effects on outdoor microclimate under different wind speeds, air conditions, solar radiation and stomatal resistance. Increasing the wind speed will weaken the cooling effect of the tree. This weakening effect can extend to a distance of about 3.2 times of the tree canopy width behind the tree when the inflow air temperature is 30 °C. However, the influence range at high wind speeds is greater than that at low wind speeds. Air temperature and relative humidity have opposite effects on the sensible and latent heat fluxes of the tree, while they both have negligible effects on the net radiation flux. The humidification effect of the tree will be weakened as the relative humidity increases. Solar radiation has a greater effect on leaf surface temperature (LST) than on air temperature. The net radiation flux is high at the top and bottom of the tree and comparatively low at the central section, which is related to the vertical distribution of leaf area density (LAD). Trees can mitigate the effects of environmental changes on the LST by regulating stomatal resistance, and the reduction of stomatal resistance leads to a greater cooling effect.

Three-dimensional estimation of deciduous forest canopy structure and leaf area using multi-directional, leaf-on and leaf-off airborne lidar data

Airborne laser scanning (ALS) has been widely used to map gap probability and leaf area index (LAI) distribution at plot and landscape scales. As an indirect measurement, most ALS methods to estimate LAI combine waveform or point density information with supporting field measurements such as the leaf angle distribution, gap probability, or direct LAI measures. The development of a more independent estimation approach would facilitate more widespread use of existing ALS data to investigate patterns of forest structure and build realistic 3-D vegetation scenes to simulate remote sensing imagery and energy balance. Here, we develop a data processing workflow (named PVlad) using ALS point cloud apparent reflectance to estimate LAI and voxel-based leaf area density (LAD), aiming to reduce the need for associated field measurements such as the gap probability. The adaptation of the path volume (PV) concept derived from apparent reflectance integrates information from multi-directional ALS pulses, and quantifies the percentage exploration of each voxel for classification and occlusion correction, such that rigorous volumetric sampling approaches can be developed to derive LAI and LAD. The PVlad workflow was applied to discrete-return lidar data (Riegl VQ480i) acquired by NASA Goddard's LiDAR, Hyperspectral and Thermal Imager (G-LiHT) Airborne Imager during leaf-on (summer) and leaf-off (spring) conditions at the Smithsonian Environmental Research Center (SERC). The estimates of LAI and LAD captured structural differences between mature, logged, and intermediate-aged stands over eight deciduous forest plots. The derived LAI values were compared to field litter collection measurements, and the derived LAD vertical distribution was compared to the output of the VoxLAD model using terrestrial laser scan (TLS) field survey data. Using voxel sizes ranging from 0.5 m to 5 m, overall LAI estimation showed linear fitting coefficient bias <0.035 and RMSE<0.5m2/m2 for 1 and 2 m voxel sizes, and vertical LAD distribution showed strong correlation with R≈0.9 and RMSE≈0.028m2/m3 for 0.5 and 1m voxel sizes. For every forest stand, upper-canopy LAD had a low variance for voxel sizes of ≤ 2m. Application of PVlad to the G-LiHT and other similar ALS data archives enables the development of fine-resolution LAI map products, including voxelization of LAD for ecosystem science and radiative transfer simulations of remote sensing imagery or surface energy balance.

A study on diurnal microclimate hysteresis and plant morphology of a Buxus sempervirens using PIV, infrared thermography, and X-ray imaging

Plants modify the climate and provide natural cooling through transpiration. However, plant response is not only dependent on the atmospheric evaporative demand due to the combined effects of wind speed, air temperature, humidity, and solar radiation, but is also dependent on the water transport within the plant leaf-xylem-root system. These interactions result in a dynamic response of the plant where transpiration hysteresis can influence the cooling provided by the plant. Therefore, a detailed understanding of such dynamics is key to the development of appropriate mitigation strategies and numerical models. In this study, we unveil the diurnal dynamics of the microclimate of a Buxus sempervirens plant using multiple high-resolution non-intrusive imaging techniques. The wake flow field is measured using stereoscopic particle image velocimetry, the spatiotemporal leaf temperature history is obtained using infrared thermography, and additionally, the plant porosity is obtained using X-ray tomography. We find that the wake velocity statistics are not directly linked with the distribution of the porosity but depends mainly on the geometry of the plant foliage which generates the shear flow. The interaction between the shear regions and the upstream boundary layer profile is seen to have a dominant effect on the wake turbulent kinetic energy distribution. Furthermore, the leaf area density distribution has a direct impact on the short-wave radiative heat flux absorption inside the foliage where 50% of the radiation is absorbed in the top 20% of the foliage. This localized radiation absorption results in a high local leaf and air temperature. Furthermore, a comparison of the diurnal variation of leaf temperature and the net plant transpiration rate enabled us to quantify the diurnal hysteresis resulting from the stomatal response lag. The day of this plant is seen to comprise of four stages of climatic conditions: no-cooling, high-cooling, equilibrium, and decaying-cooling stages.

Trait‐based projections of climate change effects on global biome distributions

AbstractAimClimate change will likely modify the global distribution of biomes, but the magnitude of change is debated. Here, we followed a trait‐based, statistical approach to model the influence of climate change on the global distribution of biomes.LocationGlobal.MethodsWe predicted the global distribution of plant community mean specific leaf area (SLA), height and wood density as a function of climate and soil characteristics using an ensemble of statistical models. Then, we predicted the probability of occurrence of biomes as a function of the three traits with a classification model. Finally, we projected changes in plant community mean traits and corresponding changes in biome distributions to 2070 for low (RCP 2.6; +1.2°C) and extreme (RCP 8.5; +3.5°C) future climate change scenarios.ResultsWe estimated that under the low climate change scenario (sub)tropical biomes will expand (forest by 18%–22%, grassland by 9%–14% and xeric shrubland by 5%–8%), whereas tundra and temperate broadleaved and mixed forests contract by 30%–34% and 16%–21%, respectively. Our results also indicate that over 70%–75% of the current distribution of temperate broadleaved and mixed forests and temperate grasslands is projected to shift northwards. These changes become amplified under the extreme climate change scenario in which tundra is projected to lose more than half of its current extent.Main conclusionsOur results indicate considerable imminent alterations in the global distribution of biomes, with possibly major consequences for life on Earth. The level of accuracy of our model given the limited input data and the insights on how trait–environment relationships can influence biome distributions suggest that trait‐based correlative approaches are a promising tool to forecast vegetation change and to provide an independent, complementary line of evidence next to process‐based vegetation models.

Numerical simulation of the nocturnal cooling effect of urban trees considering the leaf area density distribution

The design of urban areas and building that utilizes the microclimatic effects of trees is a promising approach for reducing the severe heat stress caused by urban heat islands and global warming. Although trees can reduce heat stress through solar shading during the daytime, their influence on the air temperature under and around them during the nighttime, which is important for nighttime thermal comfort, has not yet been fully elucidated. In this study, we investigated the nocturnal cooling effect of trees in a physical urban space by the coupled numerical simulation of longwave radiative transfer and computational fluid dynamics. To represent the spatial structure of an actual urban space, airborne LiDAR-derived three-dimensional data of leaf area density distribution and building shape were used. The species-specific convective heat transfer coefficient was also considered. An analysis of the calculated sensible heat flux shows that both leaf area density and sky view factor are important factors in the production of cool air. According to the calculated distributions of air temperature and velocity, even under the condition of a certain degree of incident flow, the cooled air can flow down to the space under the crown, accumulate, and then diverge when the wind speed is sufficiently low in the crown owing to the crown drag. Buildings contribute to both the accumulation and dissipation of cool air. The findings of the present study suggest that cool spots can be produced during nighttime by trees planted near streets by devising a suitable arrangement and morphology of trees and buildings.

Dry deposition of dust particles during medium- and high-level dust storms to a forest canopy in a semi-arid region

In the present study the impact of forest canopy on the spatial distribution of PM10 concentration during dust events in a region, which is subjected to frequent occurrences such as dust storms is investigated. The developed two-dimensional model is based on the application of theory of turbulent diffusion in the forest canopy in conjunction with model of dust particles deposition to vegetation elements. The leaf area density (LAD) distribution with height as well as dust particle size distribution are taken into account. The initial wind velocity profiles on the windward side of the forest were fitted from data obtained in field measurements in the studied region. The resulted dust transport in the forest canopy was validated by comparison of theoretical results with the empirical data in the studied region. Using the suggested model, we analyzed the evolution of wind velocity profiles in and above the forest canopy as well as the process of dry deposition of PM to vegetation elements. Numerical calculations performed using the developed model showed that in dust storms, PM10 concentrations at the leeward side of the forest are reduced by ≈ 16–18% depending on dust storm level. We also found that inside the canopy the ratio of PM10 concentrations between the points along the studied transect and windward side (not affected by the forest) is higher, the higher the level of the dust storm. Our model results of the atmospheric PM distribution show fairly good agreement with the data of the field measurements.

Mapping forest leaf area density from multiview terrestrial lidar

Abstract Terrestrial lidar data are known to be useful for estimating the three‐dimensional (3D) distribution of leaf area in forests. This type of product holds great potential for modelling canopy reflectance and light interception to study the links between structure and function. However, little is currently known about its potential and limits in dense forests. Higher leaf area density implies that more laser pulses emitted by the ground‐based instrument are intercepted in lower canopy levels, and the implications of such occlusion effects on radiative transfer simulations are unknown. Occlusion effects can be minimized by increasing the number of locations lidar data is acquired from; how many locations are required for a forest with a given structure? This paper aims to address these knowledge gaps. We acquired terrestrial lidar data using a very high density of scanning positions (5 m between positions) over four dense forest 60 m × 60 m plots along a structural gradient. Occlusion effects were quantified, and the 3D distribution of leaf area density was mapped using voxels (cubic volumes) for four different scan densities (one original and three downsampled). The voxel arrays were then input into a radiative transfer model to simulate bidirectional reflectance factors and vertical fraction of absorbed radiation. We found that the summation of leaf area estimates for all voxels within the plot provided leaf area index (LAI) values close to LAI values estimated using traditional methods at each site. Occluded areas occurred mostly at the top of bottom heavy canopies. Radiative transfer simulations suggest that modelling small scale (&lt;1 m) bidirectional reflectance factors (BRF) and light interception requires the highest scan position density used (5 m between scan positions), particularly at bottom heavy sites, and that 10 m between scan positions can be used for plot scale BRF simulations in forests with foliage density and vertical profiles similar to those tested here. This work establishes some initial guidelines for establishing terrestrial lidar survey protocols for mapping leaf area density in forests. The leaf area density voxel arrays derived are among the most accurate plot‐level 3D characterizations of foliage arrangement produced to date.

A Multi-Layer Model for Transpiration of Urban Trees Considering Vertical Structure

As the intensity of the urban heat island effect increases, the cooling effect of urban trees has become important. Urban trees cool surfaces during the day via shading, increasing albedo and transpiration. Many studies are being conducted to calculate the transpiration rate; however, most approaches are not suitable for urban trees and oversimplify plant physiological processes. We propose a multi-layer model for the transpiration of urban trees, accounting for plant physiological processes and considering the vertical structure of trees and buildings. It has been expanded from an urban canopy model to accurately simulate the photosynthetically active radiation and leaf surface temperature. To evaluate how tree and surrounding building conditions affect transpiration, we simulated the transpiration of trees in different scenarios such as building height (i.e., 1H, 2H and 3H, H = 12 m), tree location (i.e., south tree and north tree in a E-W street), and vertical leaf area density (LAD) (i.e., constant density, high density with few layers, high density in middle layers, and high density in lower layers). The transpiration rate was estimated to be more sensitive to the building height and tree location than the LAD distribution. Transpiration-efficient trees differed depending on the surrounding condition and plant location. This model is a useful tool that provides guidelines on the planting of thermo-efficient trees depending on the structure or environment of the city.

Aboveground Biomass Estimation in Amazonian Tropical Forests: a Comparison of Aircraft- and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil

Tropical forests are often located in difficult-to-access areas, which make high-quality forest structure information difficult and expensive to obtain by traditional field-based approaches. LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-efficient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon. The LiDAR products were similar and comparable among the two platforms and sensors. Principal differences between derived products resulted from the GatorEye system flying lower and slower and having increased returns per second than the aircraft, resulting in a much higher point density overall (11.3 ± 1.8 vs. 381.2 ± 58 pts/m2). Differences in ground point density, however, were much smaller among the systems, due to the larger pulse area and increased number of returns per pulse of the aircraft system, with the GatorEye showing an approximately 50% higher ground point density (0.27 ± 0.09 vs. 0.42 ± 0.09). The LiDAR models produced by both sensors presented similar results for digital elevation models and estimated AGB. Our results validate the ability for UAV-borne LiDAR sensors to accurately quantify AGB in dense high-leaf-area tropical forests in the Amazon. We also highlight new possibilities using the dense point clouds of UAV-borne systems for analyses of detailed crown structure and leaf area density distribution of the forest interior.

Verifying the Accuracy of the Leaf Area Density Distribution of an Individual Tree Derived from Terrestrial Laser Scanning While Considering the Penetration of Beams into the Crown and the Influence of Wind

Verifying the Accuracy of the Leaf Area Density Distribution of an Individual Tree Derived from Terrestrial Laser Scanning While Considering the Penetration of Beams into the Crown and the Influence of Wind

Accounting for Wood, Foliage Properties, and Laser Effective Footprint in Estimations of Leaf Area Density from Multiview-LiDAR Data

The spatial distribution of Leaf Area Density (LAD) in a tree canopy has fundamental functions in ecosystems. It can be measured through a variety of methods, including voxel-based methods applied to LiDAR point clouds. A theoretical study recently compared the numerical errors of these methods and showed that the bias-corrected Maximum Likelihood Estimator was the most efficient. However, it ignored (i) wood volumes, (ii) vegetation sub-grid clumping, (iii) the instrument effective footprint, and (iv) was limited to a single viewpoint. In practice, retrieving LAD is not straightforward, because vegetation is not randomly distributed in sub-grids, beams are divergent, and forestry plots are sampled from more than one viewpoint to mitigate occlusion. In the present article, we extend the previous formulation to (i) account for both wood volumes and hits, (ii) rigorously include correction terms for vegetation and instrument characteristics, and (iii) integrate multiview data. Two numerical experiments showed that the new approach entailed reduction of bias and errors, especially in the presence of wood volumes or when multiview data are available for poorly-explored volumes. In addition to its conciseness, completeness, and efficiency, this new formulation can be applied to multiview TLS—and also potentially to UAV LiDAR scanning—to reduce errors in LAD estimation.

A Simulation Study Using Terrestrial LiDAR Point Cloud Data to Quantify Spectral Variability of a Broad-Leaved Forest Canopy.

In this analysis, a method for construction of forest canopy three-dimensional (3D) models from terrestrial LiDAR was used for assessing the influence of structural changes on reflectance for an even-aged forest in Belgium. The necessary data were extracted by the developed method, as well as it was registered the adjacent point-clouds, and the canopy elements were classified. Based on a voxelized approach, leaf area index (LAI) and the vertical distribution of leaf area density (LAD) of the forest canopy were derived. Canopy–radiation interactions were simulated in a ray tracing environment, giving suitable illumination properties and optical attributes of the different canopy elements. Canopy structure was modified in terms of LAI and LAD for hyperspectral measurements. It was found that the effect of a 10% increase in LAI on NIR reflectance can be equal to change caused by translating 50% of leaf area from top to lower layers. As presented, changes in structure did affect vegetation indices associated with LAI and chlorophyll content. Overall, the work demonstrated the ability of terrestrial LiDAR for detailed canopy assessments and revealed the high complexity of the relationship between vertical LAD and reflectance.

Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties

Reliable measurements of the 3D distribution of Leaf Area Density (LAD) in forest canopy are crucial for describing and modelling microclimatic and eco-physiological processes involved in forest ecosystems functioning. To overcome the obvious limitations of direct measurements, several indirect methods have been developed, including methods based on Terrestrial LiDAR scanning (TLS). This work focused on various LAD estimators used in voxel-based approaches. LAD estimates were compared to reference measurements at branch scale in laboratory, which offered the opportunity to investigate in controlled conditions the sensitivity of estimations to various factors such as voxel size, distance to scanner, leaf morphology (species), type of scanner and type of estimator. We found that all approaches to retrieve LAD estimates were highly sensitive to voxel size whatever the species or scanner and to distance to the FARO scanner. We provided evidence that these biases were caused by vegetation heterogeneity and variations in the effective footprint of the scanner. We were able to identify calibration functions that could be readily applied when vegetation and scanner are similar to those of the present study. For different vegetation and scanner, we recommend replicating our method, which can be applied at reasonable cost. While acknowledging that the test conditions in the laboratory were very different from those of the measurements taken in the forest (especially in terms of occlusion), this study revealed existence of strong biases, including spatial biases. Because the distance between scanner and vegetation varies in field scanning, these biases should occur in a similar manner in the field and should be accounted for in voxel-based methods but also in gap-fraction methods.

CFD analyses of the wind drags on Khaya Senegalensis and Eugenia Grandis

The drag coefficients of one mature Khaya Senegalensis tree and one Eugenia Grandis tree in Singapore were analysed using computational fluid dynamics (CFD) modelling and validated with field measurements. For the numerical method, an innovative laser scanning approach was used to generate the tree geometries and to calculate the three-dimensional (3D) leaf area density distribution within the canopies. The canopies were represented by multiple porous domains and the turbulent effect of leaves was simulated by source and sink terms as a function of the calculated leaf area density. Computational fluid dynamics analyses using ANSYS 17.2 software were carried out on both leafless and leafed tree models. Three turbulent models, the Realizable k-ε model, Transition Shear Stress Transport model and Reynolds Stress Model were compared, and it was found that the differences in the drag forces among the turbulent models were negligible when they were meshed appropriately based on the grid independence study. The computed drag coefficient of the Khaya Senegalensis tree and the Eugenia Grandis tree from CFD modelling were similar within the range between 0.6 and 0.7. From field monitoring including the wind velocity and stem strains, the drag coefficients of both trees were calculated to be 0.51 and 0.40. Possible reasons causing the difference and limitations of the numerical method are discussed.

Effect of Vertical Canopy Architecture on Transpiration, Thermoregulation and Carbon Assimilation

Quantifying the impact of natural and anthropogenic disturbances such as deforestation, forest fires and vegetation thinning among others on net ecosystem—atmosphere exchanges of carbon dioxide, water vapor and heat—is an important aspect in the context of modeling global carbon, water and energy cycles. The absence of canopy architectural variation in horizontal and vertical directions is a major source of uncertainty in current climate models attempting to address these issues. This manuscript demonstrates the importance of considering the vertical distribution of foliage density by coupling a leaf level plant biophysics model with analytical solutions of wind flow and light attenuation in a horizontally homogeneous canopy. It is demonstrated that plant physiological response in terms of carbon assimilation, transpiration and canopy surface temperature can be widely different for two canopies with the same leaf area index (LAI) but different leaf area density distributions, under several conditions of wind speed, light availability, soil moisture availability and atmospheric evaporative demand.