Canopy Modelling Research Articles

Modelling urban canopy with object-based porosity model

We present a novel approach to modelling urban canopies based on the porosity model. The impact of objects in the canopy layer is implicitly accounted for by applying a high-value drag force in the parts of the canopy layer that objects would occupy. This effectively halts fluid flow in the defined space of the objects, mimicking the impact of solid objects in the canopy layer. The model addresses two common issues in urban canopy modelling: the definition of the drag coefficient and the loss of canopy morphology, which significantly affect flow and turbulence fields. The model is assessed for three cases: two idealised urban-like canopies with realistic urban flow conditions and one benchmark case based on the measurements of Hilderman and Chong (2007). The benchmark results, where the explicitly modelled objects are reduced from 109 to 9, show that the new model exhibits a level of accuracy similar to explicit modelling. We also computed the commonly used zone-based porosity and roughness models for the two idealised urban-like canopies. The new model produced results comparable to the results of explicit modelling and superior to those of the alternative approaches. All cases were computed in unsteady mode using a hybrid RANS/LES model based on elliptic-relaxation eddy-viscosity RANS and the dynamic Smagorinsky model. The simulations were performed using the open-source computational fluid dynamics code T-Flows, available on Github.

A Comparison of UAV-Derived Dense Point Clouds Using LiDAR and NIR Photogrammetry in an Australian Eucalypt Forest

Light detection and ranging (LiDAR) has been a tool of choice for 3D dense point cloud reconstructions of forest canopy over the past two decades, but advances in computer vision techniques, such as structure from motion (SfM) photogrammetry, have transformed 2D digital aerial imagery into a powerful, inexpensive and highly available alternative. Canopy modelling is complex and affected by a wide range of inputs. While studies have found dense point cloud reconstructions to be accurate, there is no standard approach to comparing outputs or assessing accuracy. Modelling is particularly challenging in native eucalypt forests, where the canopy displays abrupt vertical changes and highly varied relief. This study first investigated whether a remotely sensed LiDAR dense point cloud reconstruction of a native eucalypt forest completely reproduced canopy cover and accurately predicted tree heights. A further comparison was made with a photogrammetric reconstruction based solely on near-infrared (NIR) imagery to gain some insight into the contribution of the NIR spectral band to the 3D SfM reconstruction of native dry eucalypt open forest. The reconstructions did not produce comparable canopy height models and neither reconstruction completely reproduced canopy cover nor accurately predicted tree heights. Nonetheless, the LiDAR product was more representative of the eucalypt canopy than SfM-NIR. The SfM-NIR results were strongly affected by an absence of data in many locations, which was related to low canopy penetration by the passive optical sensor and sub-optimal feature matching in the photogrammetric pre-processing pipeline. To further investigate the contribution of NIR, future studies could combine NIR imagery captured at multiple solar elevations. A variety of photogrammetric pre-processing settings should continue to be explored in an effort to optimise image feature matching.

Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review

The potential of precision viticulture has been highlighted since the first studies performed in the context of viticulture, but especially in the last decade there have been excellent results have been achieved in terms of innovation and simple application. The deployment of new sensors for vineyard monitoring is set to increase in the coming years, enabling large amounts of information to be obtained. However, the large number of sensors developed and the great amount of data that can be collected are not always easy to manage, as it requires cross-sectoral expertise. The preliminary section of the review presents the scenario of precision viticulture, highlighting its potential and possible applications. This review illustrates the types of sensors and their operating principles. Remote platforms such as satellites, unmanned aerial vehicles (UAV) and proximal platforms are also presented. Some supervised and unsupervised algorithms used for object-based image segmentation and classification (OBIA) are then discussed, as well as a description of some vegetation indices (VI) used in viticulture. Photogrammetric algorithms for 3D canopy modelling using dense point clouds are illustrated. Finally, some machine learning and deep learning algorithms are illustrated for processing and interpreting big data to understand the vineyard agronomic and physiological status. This review shows that to perform accurate vineyard surveys and evaluations, it is important to select the appropriate sensor or platform, so the algorithms used in post-processing depend on the type of data collected. Several aspects discussed are fundamental to the understanding and implementation of vineyard variability monitoring techniques. However, it is evident that in the future, artificial intelligence and new equipment will become increasingly relevant for the detection and management of spatial variability through an autonomous approach.

Socioeconomic and Environmental Benefits of Expanding Urban Green Areas: A Joint Application of i-Tree and LCA Approaches

Green infrastructures deliver countless functions for counteracting climate change, air pollution, floods, and heat islands, contributing at the same time to water and carbon recycling as well as to renewable energies and feedstock provisioning. Properly addressing such environmental problems would require huge investments that could be decreased thanks to the further implementation of urban forests. Local administrations are designing participative projects to improve territories and their living conditions. The i-Tree Canopy modelling tool and the life cycle assessment method are jointly applied to evaluate the potential benefits of increasing tree coverage within the boundaries of the Metropolitan City of Naples, Southern Italy. Results highlighted that tree coverage could increase by about 2.4 million trees, thus generating 51% more benefits in pollutants removal, carbon sequestration and stormwater management. The benefits are also explored and confirmed by means of the life cycle assessment method. The potential tree cover is expected to provide a total annual economic benefit of USD 55 million, purchasing power parity value adjusted, representing USD 18 per citizen and USD 99,117 per square kilometre of implemented urban forest. These results can support a potential replication elsewhere and provide a reference for the sustainable improvement of cities by expanding urban green areas.

Oil palm (Elaeis guineensis) plantation on tropical peatland in South East Asia: Photosynthetic response to soil drainage level for mitigation of soil carbon emissions

While existing moratoria in Indonesia and Malaysia should preclude continued large-scale expansion of palm oil production into new areas of South-East Asian tropical peatland, existing plantations in the region remain a globally significant source of atmospheric carbon due to drainage driven decomposition of peatland soils. Previous studies have made clear the direct link between drainage depth and peat carbon decomposition and significant reductions in the emission rate of CO2 can be made by raising water tables nearer to the soil surface. However, the impact of such changes on palm fruit yield is not well understood and will be a critical consideration for plantation managers. Here we take advantage of very high frequency, long-term monitoring of canopy-scale carbon exchange at a mature oil palm plantation in Malaysian Borneo to investigate the relationship between drainage level and photosynthetic uptake and consider the confounding effects of light quality and atmospheric vapour pressure deficit. Canopy modelling from our dataset demonstrated that palms were exerting significantly greater stomatal control at deeper water table depths (WTD) and the optimum WTD for photosynthesis was found to be between 0.3 and 0.4 m below the soil surface. Raising WTD to this level, from the industry typical drainage level of 0.6 m, could increase photosynthetic uptake by 3.6 % and reduce soil surface emission of CO2 by 11 %. Our study site further showed that despite being poorly drained compared to other planting blocks at the same plantation, monthly fruit bunch yield was, on average, 14 % greater. While these results are encouraging, and at least suggest that raising WTD closer to the soil surface to reduce emissions is unlikely to produce significant yield penalties, our results are limited to a single study site and more work is urgently needed to confirm these results at other plantations.

CanopyShotNoise – An individual-based tree canopy modelling framework for projecting remote-sensing data and ecological sensitivity analysis

ABSTRACT Very few spatially explicit tree models have so far been constructed with a view to project remote-sensing data directly. To fill this gap, we introduced the prototype of the CanopyShotNoise model, an individual-based model specifically designed for projecting airborne laser scanning (ALS) data. Given the nature of ALS data, the model focuses on the dynamics of individual-tree canopies in forest ecosystems, that is, spatial tree interaction and resulting growth, birth and death processes. In this study, CanopyShotNoise was used to analyse the long-term effects of the processes crown plasticity (C) and superorganism formation (S) on spatial tree canopy patterns that are likely to play an important role in ongoing climate change. We designed a replicated computer experiment involving the four scenarios C0S0, C1S0, C0S1 and C1S1 where 0 and 1 imply that the preceding process was switched off and on, respectively. We hypothesized that C and S are antagonistic processes, specifically that C would lead to increasing regularity of tree locations and S would result in clustering. Our simulation results confirmed that in the long run intertree distances decreased and canopy gap size increased when superorganisms were encouraged to form. At the same time, the overlap and packing of tree crowns increased. The long-term effect of crown plasticity increased the regularity of tree locations; however, this effect was much weaker than that of superorganism formation. As a result, gap patterns remained more or less unaffected by crown plasticity. In scenario C1S1, both processes interestingly interacted in such a way that crown plasticity even increased the effect of superorganism formation. Our simulation results are likely to prove helpful in recognizing patterns of facilitation with ongoing climate change.

Virtual Singapore integration with energy simulation and canopy modelling for climate assessment

Urban heat island (UHI) can be described as characteristics of warmth for both the atmospheres and surfaces in cities compared to rural surroundings. The attention on UHI has helped to advance the development of urban cooling strategies in Singapore. However, these strategies are often implemented at different levels with different mechanisms, and studies on the environmental implications of these strategies are often segregated. Therefore, understanding on how the urban canopy works is vital to analyse the energy performance, because canopy modelling is significant in estimating urban weather conditions, which affects the heat gain intake for buildings. It is thus become imperative to develop an integrated model for accurate prediction of weather conditions at different scales. By utilizing the Virtual Singapore (VSg) database, this study explores the development an integrated simulation platform, named BESCAM, for climate assessment and district energy demand. It focuses on urban canopy modelling and building energy simulation. The approach is to use CityGML from VSg as input, which comprises converted Building Information Modelling (BIM) buildings. Then, an urban canopy modelling (UCM) is developed to assess the microclimate condition with urban morphology consideration. Afterwards, building energy simulation can be conducted consecutively using EnergyPlus by integrating microclimate and building information. Hence, the BESCAM platform would offer a unique opportunity to architects, engineers, and scientists to use the same source of information, using VSg database, for conducting their own analysis and compare their conclusions.

Multilayer urban canopy modelling and mapping for traffic pollutant dispersion at high density urban areas

A semi-empirical multilayer urban canopy model is developed to estimate the vertical dispersion of traffic emissions in high density urban areas. It is motivated by the heterogeneity of urban morphology in real urban cities and the need of quick urban design and planning. The urban canopy is divided into multiple layers, to include the impact of building height variance on pollutant dispersion. The model is derived by mass conservation within each layer through adopting a box model. To validate the model, results in several cases with uniform and non-uniform building height distributions are compared with CFD simulations. The validation study indicates that the assumption of zero pollutant concentration over the modeled canopy and no horizontal pollutant transfer has increasingly negligible influence with increasing urban densities. The new multilayer model performs well to model the vertical pollutant transport, and modelling results can mostly follow the trend of the CFD simulations. The present paper conducts two case studies in metropolitan areas in Singapore and Hong Kong to illustrate how to implement this multilayer urban canopy model in the planning practice. With an in-house GIS team using available data, the multilayer model provides planners a way to understand air pollutant dispersion in high-density urban areas.

Advancing retrievals of surface reflectance and vegetation indices over forest ecosystems by combining imaging spectroscopy, digital object models, and 3D canopy modelling

Imaging spectroscopy based methods offer unique capabilities for retrieving narrow-band vegetation indices which can be empirically related to functional traits of plants. However, in areas with complex topography, illumination effects affect the retrieval of such indices from high spatial resolution airborne or satellite data. Irradiance components at the pixel level are determined by atmospheric composition, as well as instantaneous illumination-surface-sensor geometries. An accurate pixel-wise description of direct and diffuse irradiance components is necessary to perform atmospheric corrections, finally resulting in improved surface reflectances and hence products. We assess three atmospheric correction strategies, differing in their approaches to simulate instantaneous as well as pixel-wise abundances of diffuse and direct irradiance. We use physically-based approaches in combination with either digital elevation models (DEM), fine resolution digital object models (DOM), or 3D modelling output from the Discrete Anisotropic Radiative Transfer (DART) model. The such obtained top-of-canopy reflectances at the Laegern test-site in Switzerland, are used to assess retrieval improvement for a set of indices (Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), as well as chlorophyll and carotenoid indices). We demonstrate that both, the DOM and the DART based approach, improve the retrievals for flat cast-shadows by ≤71% compared to using a DEM. In dense forest areas, improvements are less significant. Remaining key issues are related to overestimating surface reflectance under extreme illumination conditions.

Elevated CO2 concentration affects vertical distribution of photosynthetic activity in Calamagrostis arundinacea (L.) Roth

An understanding of photosynthetic responses to elevated CO2 concentration (EC) across the entire vertical canopy profile will help to achieve more proper simulation of ecosystem responses to expected climate change. Accordingly, we studied changes in vertical gradients of photosynthetic parameters in the grass species Calamagrostis arundinacea under EC at the time of anthesis. Plants were transplanted and grown for 3 years under ambient (385 ppm; AC) and elevated (700 ppm; EC) atmospheric CO2 concentrations in experimental glass domes. In general, EC reduced the variability of photosynthetic activity within the vertical profile of plants. Such changes also altered the differences between AC and EC in the vertical profile. While EC led to greater accumulation of chlorophylls, CO2 assimilation rate, and efficiency of photochemical processes in lower leaves, EC primarily reduced stomatal conductance and transpiration rate in upper leaves. These changes resulted in higher water-use efficiency in lower leaves. On the other hand, we found slightly greater down-regulation of photosynthesis under EC in lower leaves indicated as the A700/A385 ratio. Such knowledge may be important in upscaling EC effects from leaves to the canopy level and modelling impacts of expected climate change on grassland ecosystems.

Calibration of the APSIM-Lucerne model for ‘Grasslands Kaituna’ lucerne crops grown in New Zealand

This study used results from field experiments to calibrate the Agricultural Production Systems Simulator (APSIM) model for ‘Grasslands Kaituna’ lucerne (Medicago sativa L.) crops grown in the cool temperate climate of New Zealand. The field data allowed refinement of functions related to the seasonality of crop phenology and above- and below-ground growth. The model structure was adequate to accommodate the calibration of reproductive development in response to temperature and photoperiod in both release and calibrated versions (root mean squared deviation [RMSD] from 14% to 3% of the mean, respectively). Similarly, vegetative development, characterised by the rate of appearance of main-stem nodes, was simulated with acceptable accuracy (RMSD from 28% to 25% of the mean). Analysis showed a lack of current field data to accurately represent the number of main-stem nodes at the beginning of each regrowth cycle, which is required to further improve the accuracy of leaf appearance simulations. The simulation of leaf area index (LAI) was slightly more accurate when using a site-specific empirical canopy modelling approach for ‘Grassland Kaituna’ (RMSD = 34% of the mean) than with the more mechanistic approach in the release version used for Australian cultivars (RMSD = 40% of the mean). This is particularly important before canopy closure, when LAI has the greatest influence on light interception and biomass accumulation. ‘Grassland Kaituna’ showed a seasonal pattern of change in leaf size and specific leaf area that could not be parameterised using the approach in the release version. Finally, the model structure of the calibrated version was adapted to explicitly simulate the seasonal flow of biomass to shoots and roots. For that, the ‘shoot’ radiation use efficiency (RUE) was modified to a ‘whole plant’ RUE of 1.6 g/MJ total solar radiation and a seasonal rate of below-ground biomass turnover (i.e. respiration plus senescence) was incorporated to correct for the initial offset observed between simulated and observed root biomass. These changes improved the RMSD from 53% to 38% for shoot biomass and 29% to 18% of the mean for roots. This calibration illustrates the heuristic aspect of applying crop models to identify knowledge gaps for guiding future experimentation, including time of node appearance on basal buds and leaf area index dynamics of contrasting lucerne cultivars.

Simplifying data acquisition in plant canopies‐ Measurements of leaf angles with a cell phone

Summary Canopies are complex multilayered structures comprising individual plant crowns exposing a multifaceted surface area to sunlight. Foliage arrangement and properties are the main mediators of canopy functions. The leaves act as light traps whose exposure to sunlight varies with time of the day, date and latitude in a trade‐off between photosynthetic light harvesting and excessive or photoinhibitory light avoidance. To date, ecological research based upon leaf sampling has been limited by the available technology, with which data acquisition becomes labour intensive and time‐consuming, given the overwhelming number of leaves involved. In the present study, our goal involved developing a tool capable of measuring a sufficient number of leaves to enable analysis of leaf populations, tree crowns and canopies. We specifically tested whether a cell phone working as a 3D pointer could yield reliable, repeatable and valid leaf angle measurements with a simple gesture. We evaluated the accuracy of this method under controlled conditions, using a 3D digitizer, and we compared performance in the field with the methods commonly used. We presented an equation to estimate the potential proportion of the leaf exposed to direct sunlight (SAL) at any given time and compared the results with those obtained by means of a graphical method. We found a strong and highly significant correlation between the graphical methods and the equation presented. The calibration process showed a strong correlation between the results derived from the two methods with a mean relative difference below 10%. The mean relative difference in calculation of instantaneous exposure was below 5%. Our device performed equally well in diverse locations, in which we characterized over 700 leaves in a single day. The new method, involving the use of a cell phone, is much more effective than the traditional methods or digitizers when the goal is to scale up from leaf position to performance of leaf populations, tree crowns or canopies. Our methodology constitutes an affordable and valuable tool within which to frame a wide range of ecological hypotheses and to support canopy modelling approaches.

Modelling leaf chlorophyll content in broadleaf and needle leaf canopies from ground, CASI, Landsat TM 5 and MERIS reflectance data

Foliar chlorophyll content in forested ecosystems plays a fundamental role in plant photosynthesis and can indicate vegetation stress and disturbance. However, leaf chlorophyll retrieval is complicated as canopy reflectance in the visible and near-infrared wavelengths is affected by confounding effects not only from leaf pigment concentration but also leaf area index (LAI), canopy architecture, illumination and viewing geometry and understory vegetation. Unlike empirical indices, which are often developed at leaf-level and can be species, site and time specific, a process modelling approach can account for the variation of other variables affecting canopy reflectance; therefore providing a more accurate estimate of chlorophyll content over multiple vegetation species, time-frames and across broader spatial extents. This study used a linked canopy (4-Scale) and leaf (PROSPECT) modelling approach to investigate the ability of radiative transfer models to estimate foliar chemistry for different vegetation types (broadleaf and needle leaf) from optical remote sensing data. Coniferous and deciduous sites were selected in Ontario, Canada, representing different dominant vegetation species, including black spruce (Picea mariana), sugar maple (Acer saccharum) and trembling aspen (Populus tremuloides), and a variety of canopy closures and structures. These sites were sampled over multiple time-frames to collect ground data including leaf area index, leaf reflectance spectra (400–2500nm) and laboratory leaf chlorophyll content. Canopy reflectance data were acquired from the Compact Airborne Spectrographic Imager (CASI), Landsat 5 TM and Medium Resolution Imaging Spectrometer (MERIS). The model results show that leaf chlorophyll content derived from satellite images demonstrates a good relationship with measured leaf chlorophyll content, with validation results of R2=0.62; p<0.001 (MERIS) and R2=0.65; p<0.001 (Landsat 5 TM), and a strong linearity with negligible systematic bias. CASI data gave a regression coefficient of R2=0.41 (p<0.05) on a reduced dataset. This research provides theoretical and operational bases for the future retrieval of leaf chlorophyll content across different vegetation species, canopy structures and over broad spatial extents; crucial characteristics for inclusion in photosynthesis and carbon cycle models.

Optimal crop canopy architecture to maximise canopy photosynthetic CO2 uptake under elevated CO2 - a theoretical study using a mechanistic model of canopy photosynthesis.

Canopy architecture has been a major target in crop breeding for improved yields. Whether crop architectures in current elite crop cultivars can be modified for increased canopy CO2 uptake rate (Ac) under elevated atmospheric CO2 concentrations (Ca) is currently unknown. To study this question, we developed a new model of canopy photosynthesis, which includes three components: (i) a canopy architectural model; (ii) a forward ray tracing algorithm; and (iii) a steady-state biochemical model of C3 photosynthesis. With this model, we demonstrated that the Ac estimated from 'average' canopy light conditions is ~25% higher than that from light conditions at individual points in the canopy. We also evaluated theoretically the influence of canopy architectural on Ac under current and future Ca in rice. Simulation results suggest that to gain an optimal Ac for the examined rice cultivar, the stem height, leaf width and leaf angles can be manipulated to enhance canopy photosynthesis. This model provides a framework for designing ideal crop architectures to gain optimal Ac under future changing climate conditions. A close linkage between canopy photosynthesis modelling and canopy photosynthesis measurements is required to fully realise the potential of such modelling approaches in guiding crop improvements.

A Review of Optical Imagery and Airborne LiDAR Data Registration Methods

Representing a scene completely from remote sensing data requires both spectral and 3-D-surface information. Integration of spectral information from optical images and 3-D-surface information from LiDAR is important in a number of remote sensing applications such as feature extraction, image classification, image analysis, building extraction, 3-D city modelling, canopy modelling etc. Therefore, numerous methods have been developed in the last decade to align both data sets into a common reference frame to effectively utilize their complementary characteristics. However, due to the significantly different characteristics between optical image and LiDAR data, there are a number of technical challenges in the alignment of both data sets. Different research papers introduced different strategy or methodology to overcome the challenges, reaching different alignment/registration results. This paper presents a review of classical and up to date optical-LiDAR registration methods with the emphasis on control point detection and matching. The aim of this paper is to provide readers with an overview of existing methods, identify their advantages and limitations, and give readers the overall information on what will be useful for researchers and practitioners to realistically select proper method for their application.

Accuracy Assessment of Digital Surface Models Based on WorldView-2 and ADS80 Stereo Remote Sensing Data

Digital surface models (DSMs) are widely used in forest science to model the forest canopy. Stereo pairs of very high resolution satellite and digital aerial images are relatively new and their absolute accuracy for DSM generation is largely unknown. For an assessment of these input data two DSMs based on a WorldView-2 stereo pair and a ADS80 DSM were generated with photogrammetric instruments. Rational polynomial coefficients (RPCs) are defining the orientation of the WorldView-2 satellite images, which can be enhanced with ground control points (GCPs). Thus two WorldView-2 DSMs were distinguished: a WorldView-2 RPCs-only DSM and a WorldView-2 GCP-enhanced RPCs DSM. The accuracy of the three DSMs was estimated with GPS measurements, manual stereo-measurements, and airborne laser scanning data (ALS). With GCP-enhanced RPCs the WorldView-2 image orientation could be optimised to a root mean square error (RMSE) of 0.56 m in planimetry and 0.32 m in height. This improvement in orientation allowed for a vertical median error of −0.24 m for the WorldView-2 GCP-enhanced RPCs DSM in flat terrain. Overall, the DSM based on ADS80 images showed the highest accuracy of the three models with a median error of 0.08 m over bare ground. As the accuracy of a DSM varies with land cover three classes were distinguished: herb and grass, forests, and artificial areas. The study suggested the ADS80 DSM to best model actual surface height in all three land cover classes, with median errors <1.1 m. The WorldView-2 GCP-enhanced RPCs model achieved good accuracy, too, with median errors of −0.43 m for the herb and grass vegetation and −0.26 m for artificial areas. Forested areas emerged as the most difficult land cover type for height modelling; still, with median errors of −1.85 m for the WorldView-2 GCP-enhanced RPCs model and −1.12 m for the ADS80 model, the input data sets evaluated here are quite promising for forest canopy modelling.

Mathematical Derivation of Spatially-Averaged Momentum Equations for an Urban Canopy Model Using Underlying Concepts of the Immersed Boundary Method

We propose a new approach to derive spatially-averaged momentum equations for an urban canopy model that resolves buildings vertically and not horizontally. First, in order to mathematically describe the actual momentum field as a completely continuous field, the underling concepts of the immersed boundary method are employed, where we assume that (i) the entire simulation space, including that occupied by buildings, is filled with a fluid, and (ii) an external body force field exists that reduces the wind speed to zero at all positions coinciding with the space occupied by the buildings. Then, in order to obtain the required spatially-averaged momentum equations in a self-consistent manner, a spatial-averaging operation is applied to the Navier–Stokes equations that include a term representing the external force field. The applied spatial-averaging operation is equivalent to the conventional spatial filtering operation used in large-eddy simulations. To examine the significance of the subgrid-scale (SGS) stresses of the spatially-averaged momentum equations, a numerical simulation is performed for a flow around a regular array of cubical blocks with a grid resolution that is sufficient to resolve the blocks. By estimating the individual terms in the spatially-averaged momentum equations using the simulation results, we show that the SGS stresses contribute significantly to the spatially-averaged momentum budget, and therefore they should not be neglected in urban canopy modelling.

Leaf and canopy conductance in aspen and aspen-birch forests under free-air enrichment of carbon dioxide and ozone

Increasing concentrations of atmospheric carbon dioxide (CO2) and tropospheric ozone (O3) have the potential to affect tree physiology and structure, and hence forest feedbacks on climate. Here, we investigated how elevated concentrations of CO2 (+45%) and O3 (+35%), alone and in combination, affected conductance for mass transfer at the leaf and canopy levels in pure aspen (Populus tremuloides Michx.) and in mixed aspen and birch (Betula papyrifera Marsh.) forests in the free-air CO2-O3 enrichment experiment near Rhinelander, Wisconsin (Aspen FACE). The study was conducted during two growing seasons, when steady-state leaf area index (L) had been reached after > 6 years of exposure to CO2- and O3-enrichment treatments. Canopy conductance (g(c)) was estimated from stand sap flux, while leaf-level conductance of sun leaves in the upper canopy was derived by three different and independent methods: sap flux and L in combination with vertical canopy modelling, leaf 13C discrimination methodology in combination with photosynthesis modelling and leaf-level gas exchange. Regardless of the method used, the mean values of leaf-level conductance were higher in trees growing under elevated CO2 and/or O3 than in trees growing in control plots, causing a CO2 x O3 interaction that was statistically significant (P < or = 0.10) for sap flux- and (for birch) 13C-derived leaf conductance. Canopy conductance was significantly increased by elevated CO2 but not significantly affected by elevated O3. Investigation of a short-term gap in CO2 enrichment demonstrated a +10% effect of transient exposure of elevated CO2-grown trees to ambient CO2 on g(c). All treatment effects were similar in pure aspen and mixed aspen-birch communities. These results demonstrate that short-term primary stomatal closure responses to elevated CO2 and O3 were completely offset by long-term cumulative effects of these trace gases on tree and stand structure in determining canopy- and leaf-level conductance in pure aspen and mixed aspen-birch forests. Our results, together with the findings from other long-term FACE experiments with trees, suggest that model assumptions of large reductions in stomatal conductance under rising atmospheric CO2 are very uncertain for forests.

Influence of trellis system and shoot positioning on light interception and distribution in two grapevine cultivars with different architectures: an original approach based on 3D canopy modelling

Background and Aims: A 3D modelling approach simulating canopy structure was used in combination with a radiative transfer model to simulate light interception, distribution and microclimate in the fruiting zone. Methods and Results: This model was parameterised for four training systems (two vertical shootpositioned systems with one or two pairs of catch wires (VSP-1W, VSP-2W); two non-shoot-positioned systems, gobelet (GOB) and bilateral free cordon (BFC)) and two cultivars (Syrah and Grenache). Light interception and canopy microclimate depended on the interactions between the intrinsic architecture of the cultivars and canopy manipulations. Shoot vigour and leaf area were the main determinants of canopy radiative balance. However, differences in shoot architecture accounted for up to 25% of the difference in light interception between cultivar ¥ trellis system pairs at a given leaf area index (LAI). Light interception efficiencies and the proportion of sunlit leaf area (SLA) were 25‐30% lower for VSP-2W than for BFC for intermediate LAI values. The genotypic differences in the ability to capture light were mostly induced by the ‘procumbent’ habit of the Syrah shoots. For this cultivar, shoot-positioned systems resulted in lower levels of fruit illumination at midday than the BFC and GOB systems, whereas the use of a catch wire in VSP-Grenache canopies made it possible to maintain light penetration in the fruit zone. Conclusions: These results highlight the problem of adapting the training system to both the architectural characteristics of the cultivar and climate. Free-standing systems had greater light interception and SLA than shoot-positioned systems. They may enhance fruit illumination for cultivars with ‘procumbent’ shoots. Significance of the Study: Non-positioned shoot systems offer the possibility of combining a high level of light interception, favourable microclimate and reduced labour-intensive practices for vineyards in conditions of moderate vigour.

Modelling of the OASIS Energy Flux Measurements Using Two Canopy Concepts

Two land surface schemes, SCAM and CSIRO9, were used to model the measured energy fluxes during the OASIS (Observations At Several Interacting Scales) field program. The measurements were taken at six sites along a 100 km rainfall gradient. Two types of simulations were conducted: (1) offline simulations forced with measured atmospheric input data at each of the six sites, and (2) regional simulations with the two land surface schemes coupled to the regional climate model DARLAM. The two land surface schemes employ two different canopy modelling concepts: in SCAM the vegetation is conceptually above the ground surface, while CSIRO9 employs the more commonly used `horizontally tiled' approach in which the vegetation cover is modelled by conceptually placing it beside bare ground. Both schemes utilize the same below-ground components (soil hydrological and thermal models) to reduce the comparison to canopy processes only. However, the ground heat flux, soil evaporation and evapotranspiration are parameterised by the two canopy treatments somewhat differently. Both canopy concepts reproduce the measured energy fluxes. SCAM has a slightly higher root-mean standard error in the model-measurement comparison for the ground heat flux. The mean surface radiative temperature simulated by SCAM is approximately 1K lower than in the CSIRO9 simulations. However, the soil and vegetation temperatures (which contribute to the radiative temperature) varied more in the CSIRO9 simulations. These larger variations are due to the absence of a representation of the aerodynamic interactions between vegetation and ground.