Search

Clumping index (CI), describing the extent of foliage grouping within canopy structures that cause nonrandomness of the leaf spatial distribution within the canopy, is a structural parameter of plant canopies needed in modelling carbon and water cycles of terrestrial ecosystems. CI has been previously retrieved based on an angular index named Normalized Difference between Hotspot and Darkspot (NDHD) derived from multi-angle satellite data. However, since the darkspot reflectance used in NDHD contains shadows influenced by topographical variations, CI retrieved from NDHD is contaminated by topographic effects on multi-angle data. Moreover, the existing global CI products are limited by their spatial resolutions, e.g. 6 km from POLDER and 500 m from Moderate Resolution Imaging Spectroradiometer (MODIS). In this study, we utilized the canopy height (H) metric produced from a spaceborne LiDAR system named Global Ecosystem Dynamic Investigation (GEDI) to implement the mapping for global forest CI at 30 m resolution in the following steps: (1) The H map from GEDI and a CI map from MODIS were employed to establish the relationships between H and CI across flat terrains for different plant functional types (PFT) and vegetation foliage densities characterized using the Simple Ratio (SR); (2) Using the relationships, a new global map of forest CI is derived from the GEDI H and SR maps at 30 m resolution; (3) Field-measured CI values by the Tracing Radiation and Architecture of Canopies (TRAC) instrument at 39 sites over three continents were used to validate the new CI map with satisfactory results at all forest sites: ( R 2 = 0.84, RMSE = 0.0199 for all PTFs; R 2 = 0.42, RMSE = 0.0180 for broadleaf forests, and R 2 = 0.48, RMSE = 0.0206 for needleleaf forests). In the new global high-resolution forest CI map, CI is increased by about 10–15 % and is much less variable with topography over mountainous areas, indicating that topographical effect on CI derivation is greatly reduced. This new map would therefore be highly useful for improving terrestrial carbon and water cycle estimation. [ABSTRACT FROM AUTHOR]

• Euphorbia bupleurifolia populations have undergone a drastic decline. • Bell-shaped size class distribution (SCD) patterns were dominant. • Populations are structured through adult persistence, not high seedling recruitment. • Plants persist in sites with high bare ground cover and minimal overstorey shade. • Harvesting, inappropriate fire frequencies and habitat degradation are threats. Many South African succulent Euphorbia spp. are threatened by anthropogenic activities such as habitat loss and illegal harvesting. However, only a few species have been studied in sufficient detail to aid their conservation through the development of effective management plans. This study documents the distribution, abundance, and population biology of the formerly widespread Euphorbia bupleurifolia , a species endemic to the Eastern Cape and KwaZulu-Natal provinces of South Africa. Until recently, the status of wild populations of this species was largely unknown. Searches for plants in each of the 31 previously recorded localities revealed that only nine populations (29 %) still had plants in 2018, indicating a contraction of the distribution, with the species apparently now ranging from Makhanda to Port Edward. Population size and structure, flowering, microhabitat requirements and various other factors, including potential threats and disturbances, were quantified for the nine populations. Complete counts were conducted, and the diameters of plants were measured and canopy areas calculated. Population sizes varied from one (effectively extinct) to 675 plants (with a total of 1724 plants recorded across all populations). Measurements of cultivated plants at the Walter Sisulu National Botanical Garden established that the onset of reproduction can be expected for a plant with a canopy area of 2.63 cm2, and annual growth rates of 0.55±8.37 cm2 are possible. Bell-shaped size class distribution (SCD) patterns were dominant, which is attributed to an adult persistence population survival strategy. Unsustainable harvesting, inappropriate fire frequencies as well as habitat loss and degradation remain a threat to the species. Euphorbia bupleurifolia persists mostly in sites with low vegetation biomass, high bare ground cover and minimal overstorey shade. This study highlights the drastic decline of a Least Concern species, formally considered widespread (i.e. common), and provides baseline demographic data, which may be employed in future monitoring and management of the remaining populations, to improve the conservation of E. bupleurifolia. Intensified field surveys involving citizen science programmes (e.g. CREW) and subsequent uplisting of the species to a higher Red List threat category is recommended. [ABSTRACT FROM AUTHOR]

Plant area density measurements provide spatially explicit information about the density and distribution of canopy elements. This information is needed for modeling of the forest radiation regime, climate and for other ecological applications. Terrestrial laser scanning (TLS) provides detailed information about canopy structure, but it cannot be used for monitoring large areas. Airborne laser scanning (ALS) uses similar methods to measure plant area density, but due to the larger beam footprints, the scale at which this information can be obtained is coarser than with TLS. The volumetric nature of the ALS measurement poses unique geometric challenges to plant area measurement methods, as assuming an infinitesimal beam size may lead to large errors. Further, the use of voxel grids with ALS measurements may increase errors in plant area measurements, as these grids require discrete spatial allocation of information. In this study, we apply a spatial weighting technique to ray-traced measurements of plant area from ALS data. This spatial weighting scheme allows continuous allocation of trajectory information of ALS pulses, avoiding discontinuity introduced by voxel grids. Our data consisted of high density ALS waveform data (over 40 points/m 2) in 33 plots across two study sites in Finland and Estonia. We compared the plant area index (PAI) obtained through this new measurement method to PAI measurements from hemispheric photography (HP) and TLS, and to ALS with a voxel grid. We found PAI, measured at agrid spacing of 0.6 m, correspond best to HP and TLS measurements. Occlusion severely biased PAI at 0.2 m spacing. With increasing grid spacing, PAI estimates become increasingly biased because of clumping effects at small scales. Continuously sampled PAI measurements corresponded closer to reference values than voxel-based PAIs, indicating that a spatially weighted approach avoids bias from partitioning the volumetric ALS beams into voxels. • We measured plant area density (PAD) from high density ALS waveform data. • We developed a continuous grid sampling method as an alternative to voxels. • Our new continuous grid sampling approach is less biased than voxel grids. [ABSTRACT FROM AUTHOR]

Grazing and precipitation are pivotal factors influencing the productivity and biodiversity of grassland ecosystems, largely through their effects on the growth and reproduction of dominant species. Approximately 50 % of terrestrial ecosystems are concurrently affected by grazing and precipitation addition (PA), yet the interactive effects of these factors remain underexplored. To elucidate the combined impacts of grazing and PA on the growth of dominant species and their influence on community structure and function, we initiated a four-year combined grazing and PA experiment based on a long term of grazing experiment in a typical steppe. The synergistic interaction between PA and grazing enhanced canopy diameter (CD), tiller density (TD), and seedling density (SD) in dominant species, while decreasing reproductive branch density (RB). Conversely, an antagonistic interaction increased plant height (PH) and TD but reduced SD. These responses suggest that dominant species adapt to combined grazing and PA pressures by shifting growth strategies towards lateral growth and asexual reproduction. The growth characteristics of dominant species exhibited four response patterns to grazing and PA interactions: full saturation, sufficient saturation, equal saturation, and deficit saturation, each with three corresponding thresholds: adaptation, optimum, and saturation points. Grazing decreased the precipitation response thresholds for PH, CD, RB, and population density, while increasing the optimal points for TD and SD. These changes in the growth of the dominant species resulted in a 33 % reduction in the aboveground biomass (AGB) of the community and triggered a 18 % increase in the coupling index between AGB and species richness within the community. Our findings highlight the role of dominant species in facilitating community adaptation to increased precipitation and rotational grazing, offering critical insights for developing sustainable grazing strategies under climate change. [Display omitted] • Effects of the interaction of grazing and precipitation addition on population growth. • Contribution of population changes to community structure and functioning. • Grazing and precipitation addition have synergistic effects on growth indicators. • Plant height and population density were the most sensitive to synergistic effects. • Grazing and precipitation addition increase the competitiveness of Stipa bungeana. [ABSTRACT FROM AUTHOR]

Accurate monitoring of leaf area index (LAI) is conducive to timely and targeted management measures. Unmanned aerial vehicle (UAV) remote sensing provides an important way for non-destructive monitoring of crop leaf area index. In this study, visible light (RGB) and multispectral remote sensing data from the UAV and ground-measured LAI data from the Plant Canopy Analyzer LAI-2200 C were used to conduct inversion of maize LAI on a fine scale. To address the problem of spatial scale mismatch between the spatial resolution of UAV images and the ground-measured LAI, the scale difference between UAV image data and ground-measured data was reduced by removing the outermost ring data measured by the LAI-2200 C instrument, calculating the spatial resolution of the UAV images after resampling based on the height of the plant, and the resampling method based on the circle. Finally, through the above method to resample the UAV images, we extract the vegetation index and canopy height features as the input variables of the random forest model to build the maize LAI inversion model in vegetative stages and reproductive stages respectively, which is referred to as the Vis_H+RF method. The Vis_H+RF method of Tongliao experimental station has an R2 of 0.96 in the vegetative stages and a R2 of 0.61 in the reproductive stages, both of which perform well and have certain migration capabilities. The LAI inversion model constructed based on the method in this study is basically consistent with the actual situation and can provide data support for maize growth monitoring. [Display omitted] • This paper proposes a UAV image resampling method based on plant height and ground-measured data for fine-scale maize LAI inversion. • In this paper, a circular convolution kernel is used to resample UAV images based on the ground data measurement approach. • Removing the LAI-2200 C's fifth ring data can slightly reduce the influence of adjacent plots with large growth differences on the ground-measured LAI. • Vegetative indices features and canopy height features as model input variables improved the LAI inversion model performance. [ABSTRACT FROM AUTHOR]

• Designed a hyperspectral imaging spectrometer for observing solar-induced chlorophyll fluorescence of vegetation. • Full transmission optical design based on prism-grating structure. • High imaging quality and high-precision spectral data acquisition capabilities. As a plant functional optical signal, the Solar Induced Chlorophyll Fluorescence (SIF) has a unique advantage in evaluating plant photosynthesis. In recent years, high-quality research results have been achieved with SIF data as the core. However, how to evaluate SIF accurately and quantitatively itself is a huge challenge. We propose a novel transmissive hyperspectral imaging spectrometer specifically designed for SIF observation named HSIS-SIF. It works in the full fluorescence emission band of 650–800 nm, with a field of view of 20 °, Spectral resolution better than 0.3 nm and spatial resolution of 1mrad, and the key Prism-Grating dispersion element composed of the prism and volume phase holographic transmission grating enables the spectrometer to achieve higher energy collection ability and light transmission efficiency while ensuring the excellent optical performance mentioned above. At the weakest SIF signals, the Signal-to-Noise Ratio of the system is still better than 100. High-resolution imaging experiments with the prototype were conducted for mapping the plant canopy SIF, Normalized Difference Vegetation Index, and Near Infrared reflected radiation. The results indicate that our design has excellent optical performance and can perform high-precision SIF detection tasks, as well as providing additional vegetation indices, which has enormous application potential. [ABSTRACT FROM AUTHOR]

Terrestrial LiDAR scanning (TLS) data can be used to efficiently estimate plant canopy structural variables including leaf area density (LAD). This is done by estimating the transmission probability of LiDAR beams through a canopy, which is directly related to the local LAD. Advancements in TLS technology have enabled instruments that can record multiple object intersection points along a single laser pulse path, but whether this additional information can improve LAD estimation from TLS is not fully understood. Several methods for incorporating multiple returns per beam into transmission probability and LAD estimations have been previously suggested, including the use of corrected relative intensity to weight multiple returns more precisely. Intensity-based weighting is complicated by unknown variation in surface reflectance and orientation. Synthetic multiple-return TLS simulations were performed for virtual homogeneous voxels and heterogeneous tree cases with known properties (LAD, leaf angle distribution, reflectivity) in order to evaluate LAD estimates using intensity-based weighting in comparison to first-hits and equal-weighting approaches. An idealized intensity-based weighting, where the fraction of beam energy hitting every surface is known, and an exact weighting, where the impact of partial misses is also accounted for were also analyzed. Intensity-based weighting of multiple-return TLS data did not necessarily improve transmission probability and LAD estimates compared with the more simple equal-weighting method. Both methods had relatively similar performance, with the intensity-weighting method tending towards slightly lower transmission and higher LAD. There could be significant errors for all methods, including when weighting of hit points was exact. The error in LAD caused by choice of weighting method was therefore sometimes overshadowed by a combination of other errors due to clumping, partial misses, voxel occlusion, and limitations of Beer's law for dense canopies, which could have substantial impacts. Given the small, but inconsistent potential improvements in accuracy of the intensity-based methods that were tested in this work, the equal-weighting method appears an acceptable choice. • Methods for weighting multiple-return terrestrial LiDAR data were tested. • Methods were evaluated with LiDAR simulations and known canopy geometry. • Weighting multiple returns equally or by intensity produced similar LAD estimates. • Partial misses and clumping may have a greater impact than return-weighting method. [ABSTRACT FROM AUTHOR]

• A two-stage CFD simulation method is proposed for droplets deposition in air-assisted spraying. • The influence of leaves deformation on droplet movement and deposition is considered. • 3D point cloud scanning technique is used to assist in establishing plant geometric models. • The two-stage simulation method is a tool for optimizing air-assisted spraying parameters. In air-assisted spraying, assisted airflow leads to flexible leaf deformation and affects distribution of droplet deposition in canopies. However, analyzing droplet deposition behavior during dynamic changes in canopies is challenging. To address this issue, a method was developed, called two-stage simulation, with one stage involving a fluid–structure interaction of assisted airflow with plant leaves and the other stage involving a discrete particle tracking simulation of droplet deposition within deformed plant canopies under the air–liquid interaction of assisted airflow and droplets. First, a representative three-dimensional (3D) plant model is developed through 3D point cloud scanning, agricultural planting parameters in the field, and plant growth characteristics. Subsequently, the deformed plant model is derived from the results of the fluid–structure interaction simulation. Finally, discrete particle tracking simulations of droplet deposition in canopies of deformed plants under air–liquid interaction are conducted. The accuracy of the simulation is verified by examining airflow distribution in the canopy and the deposition of droplet particles. The airflow verification results indicate accuracy, with a coefficient of determination of 0.8684 and a root mean squared error of 0.1463 for the linear fitted equation between the simulated and measured values. The normalized mean absolute error between the simulated and measured values is 17.2 %, indicating a favorable match between the two. The variance analysis results indicated that there is no significant difference (P > 0.05) between the simulated and measured values of droplet deposition density in the upper, middle, and lower layers. Utilizing the validated computational fluid dynamics (CFD) model, we analyze the deposition characteristics of droplets under varying airflow velocities and spray flow rates. The results highlight a direct correlation between the liquid distribution and generated airflow pattern with increased droplet deposition and drift risk observed under strong airflow and high spray flow rates. This study offers a novel approach to uncovering droplet deposition patterns through CFD simulation. [ABSTRACT FROM AUTHOR]

• A software application was developed to simulate sprinkler water distribution on undulating hilly terrain. • A water application rate conversion from flat to hilly terrain was deduced by the principle of water volume conservation. • An indoor experimental platform was set up to replicate the sprinkler arrangement on a hill, devoid of plant canopy. The hilly terrain modifies the droplet landing positions in comparison to flat ground, complicating the prediction of sprinkler water distribution on such uneven regions. Utilizing a digital elevation model combined with droplet dynamics and evaporation models, droplet landing positions were calculated on both flat and uneven terrains. From the droplet landing positions and the corresponding water application rates on flat terrain, the water application rate on hilly terrains was deduced using the principle of water volume conservation. Subsequently, a software application was developed to assist in this prediction. Using the radial water distribution data from an individual sprinkler under various operating pressures and the elevation data of a hill, the software predicts the water distribution for either an individual sprinkler or an entire solid-set sprinkler irrigation system on the hill. This allows for the calculation of the average water application rate (h ¯) and distribution uniformity (UCS) for combined sprinklers. The simulated water application rate on hilly terrains was validated using an experimental platform that replicates the sprinkler arrangement on a hill, devoid of plant canopy. Our findings indicate that the simulated water application rate for a sprinkler on hilly terrain aligns closely with the observed values, achieving a confidence coefficient (c) of 0.96. The developed software reliably predicts sprinkler water distribution on hilly terrains with significant accuracy for the conditions studied. We compared the UCS of the flat, hilly slope, and homogeneous slope terrains and found that the hilly slope better reflects the uneven water distribution owing to the undulating characteristics of the hilly terrain. [ABSTRACT FROM AUTHOR]

• Spectral point cloud was obtained from a low-cost fusion method. • Quantifying the spatial distribution of plant disease using spectral point cloud. • Disease levels obtained from fused data performed better than visual assessment. • Disease rates obtained from fused data were in agreement with the measured rates. • Cercospora leaf spot on sugar beet has notable spatial heterogeneity. Cercospora leaf spot (CLS) disease, triggered by the fungus Cercospora beticola, represents the most severe foliar disease affecting sugar beets globally. The significant vertical heterogeneity of the plant canopy makes traditional 2D spectral imaging insufficient to accurately determining the CLS disease ratio. Integrating 3D and spectral imaging from dual sensors to form a plant spectral point cloud faces challenges due to alignment issues and high costs. An approach combining multi-view spectral images with the Structure from Motion (SfM) algorithm was introduced to generate a detailed multispectral 3D point cloud of plant structure. This technique was employed to assess the CLS disease ratio and its spatial heterogeneity. Specifically, a discriminant-based model was developed to differentiate healthy and diseased leaves using various ratio-based or normalized vegetation indices at the leaf scale. This model was then utilized to extract 3D CLS point clouds from the multispectral point clouds reconstructed by the new method at both plant and plot levels. Three-dimensional spatial heterogeneity analysis explored the vertical and horizontal distribution patterns of CLS in sugar beets. The findings revealed that disease levels determined by the 3D CLS model surpassed those of expert visual assessments (75 % vs. 58.3 %). The estimated disease ratio closely matched the measured values (RMSE = 8.4 %). Additionally, plot-scale CLS distribution maps aligned well with RGB image distributions. The analysis indicated that CLS initially spread from lower leaves upwards and displayed a pattern moving from the periphery to the interior. The introduced method offers a cost-effective, convenient alternative for generating detailed multispectral 3D point clouds. This study emphasizes the potential of spectral point clouds in monitoring plant canopy health and physiological activities. [ABSTRACT FROM AUTHOR]

• Plants may opportunistically colonize new habitats and could evolve into epiphytes. • It is hypothesized that epiphytes originated in open vs. umbrophilous environments. • Accidental epiphytes indicate the early step in the evolution of epiphytes. • We did not find accidental epiphytes associated with an umbrophilous environment. • We found accidental epiphytes associated with an open environment. Approximately 10 % of vascular plants can grow as epiphytes, but the impact of epiphytism is more remarkable because there is an unknown percentage of re-terrestrialized taxa that evolved from epiphytic ancestors. Two main hypotheses have been proposed to explain the evolution of epiphytes: one suggests that they evolved from humid, umbrophilous environments (i.e., forest understory; Schimper hypothesis), and the other that they came from an open-infertile environment (Tietze-Pittendrigh hypothesis). The core evidence supporting these hypotheses is the frequency of terrestrial plants that accidentally grow as epiphytes (i.e., accidental epiphytes), because these plants should be abundant in the habitats that promote the colonization of the canopy by the terrestrial plants (i.e., the early state of epiphyte evolution). In a landscape with both environments (humid and umbrophilous vs. open and infertile), we tested the affinity of the flora to the epiphytic habitat and the association of the accidental epiphytes with each environment. We found 71 plant species. Forty-one percent were terrestrial; among the rest, 39 %, 3 %, and 17 % were accidental, facultative (growing equally as terrestrial or arboreal), and true epiphytes (preferentially living as arboreal), respectively. Discounting plants that exclusively grow terrestrially in the sample, in this landscape, a large proportion of the species living in tree crowns are accidental epiphytes (28), and 16 species belong to Asteranae and Rosanae, superorders where epiphytism is infrequent. Nine accidental epiphytes were associated with the open environment and none with the forest, supporting only the Tietze-Pittendrigh hypothesis. Our results support the idea that species from open environments could be preadapted to grow as epiphytes, and landscapes combining forested areas with open environments (e.g., xerophytic scrub, savanna) could promote the colonization of the canopies from terrestrial plants. [ABSTRACT FROM AUTHOR]

• Positive and negative species interactions influence plant community assembly. • Regenerating communities showed phylogenetic and functionally random structure. • Adults of Joannesia princeps and Senna multijuga facilitated community regeneration. • All species had allelopathic effects on seed germination, especially Bixa atlantica. Plant phylogeny, diversity, and production of germination inhibiting chemicals can be used as patterns for inferring key drivers of plant community construction and assembly. We conducted the study in a restoration area of Atlantic Rainforest from Southeast Brazil. In this context, we aimed to investigate community assembly rules by simultaneously evaluating the relationships of species with a phylogenetic, functional, and ecophysiological (allelopathy) approach and multifaceted β diversity (taxonomic, phylogenetic, and functional). We measured the plant canopy height and diameter at soil height for all individuals and determined successional group and dispersal syndrome for all species regenerating in open areas and below 18 adult individuals of each tree species Bixa atlantica Antar & Sano, Inga laurina (Sw.) Willd., Joannesia princeps Vell. and Senna multijuga subsp. multijuga var. verrucosa (Vogel) H.S.Irwin & Barneby. Phylogenetic and functional indexes of community structure were calculated with the net relatedness index and the nearest taxon index. Taxonomic, phylogenetic, and functional diversities (respectively, TD, PD, and FD) for the regenerating community in each area were calculated and pairwise comparisons were made for TD, FD, and PD components of β diversity. Tests of tree species allelopathy derived from leaf extract were performed with seeds of Lactuca sativa L. (Asteraceae). The effects of diversity and extracts on seed germination were analyzed using generalized linear models. The phylogenetic and functional structure of the regenerating communities under the four tree species did not differ from random for the four studied tree species. The PD was significantly higher for the communities that regenerated under Joannesia , while the FD was higher under both Joannesia and Senna , compared to communities from open sites, evidencing a facilitation mechanism for these two species. Only Senna and Inga differed from random in relation to β TD and β FD, suggesting possible environmental changes in these areas. Seeds irrigated with the extracts of Inga, Joannesia, and Senna inhibited germination in an intermediate way, whereas seeds irrigated with Bixa extract had only 1 % germination, indicating allelopathic effects. In this way, the planted species directly influence the organization of communities that regenerate below their canopies. It is therefore important to choose species that can contribute to improving diversity, and thus favor the success of restoration projects. [ABSTRACT FROM AUTHOR]

• The physical basis of dew formation in canopies is theoretically summarized. • The critical relative humidity for dew formation depends on effective radiation. • Condensation rate largely varies with relative humidity and effective radiation. • Condensation rate also depends on air temperature and exchange velocity of canopy. • Two physical indices for assessing leaf wetness duration and amount are proposed. Dew formation on leaves plays an important role in plant growth and water use, but it also contributes to the development of a variety of plant diseases. However, the quantitative relationship between dew formation in plant canopies and meteorological conditions has not been fully elucidated. In the present study, a one-layer energy-balance model (1L-model) of a plant canopy was developed to systematically investigate this relationship, obtaining the following results: (1) Dew formation (condensation rate) on leaves is highly dependent on four parameters: effective radiation, relative humidity, air temperature, and exchange velocity (k L) of the plant canopy. (2) Dew formation occurs when relative humidity (rh) exceeds the critical value (rh cr), wherein rh cr decreases with a decrease in effective radiation and is lower at lower air temperatures. (3) Under conditions where rh > rh cr , the condensation rate reaches a maximum at a specific exchange velocity; however, condensation does not occur when k L is greater than the critical value. (4) The maximum condensation rate increases with decreasing effective radiation, but rapidly decreases with decreasing relative humidity, and increases with increasing air temperature under humid conditions. Given these theoretical considerations, we proposed two physical indices (reference dew amount, W 0, and potential dew amount, W p) calculated from meteorological conditions using the 1L-model. Here, W p is the maximum dew amount for given meteorological conditions, excluding wind speed. The efficacy of W 0 and W p in assessing leaf wetness duration (LWD) and dew amount in plant canopies was confirmed through actual measurements in a rice paddy and numerical simulations using a more comprehensive multilayer energy-balance model. This study contributes to a better understanding of the nature of dew formation on plants and improves the accuracy of LWD and dew amount estimation in plant canopies for the prevention of various plant diseases. [Display omitted] [ABSTRACT FROM AUTHOR]

The Normalized Difference Vegetation Index (NDVI) is a valuable indicator of plant vigor that is frequently used in agronomic practices to make timely and targeted decisions with the aim of increasing the productivity of the system. NDVI measurements of large-scale fields are typically performed using remote sensing from satellite and aerial imaging devices. However, due to their low spatial and temporal resolution, these technologies may have limitations in precision viticulture. This paper investigates the potential of a proximal sensing system to characterize the vine foliage that makes use of data collected by a farmer robot equipped with an Intel RealSense D435 camera. The camera includes two infrared (IR) sensors in stereoscopic configuration and one RGB sensor, which provide, for each observation, both infrared and visible red channel information, thus making possible pixel-per-pixel NDVI calculation. Solutions to IR filtering and radiometric calibration issues are proposed that significantly improve measurement accuracy and reliability. Since the camera also provides stereo-based 3D scene reconstruction, depth information can be used to separate the plant canopy from the background before NDVI measurement. At the same time, range data can be employed to extract geometric properties of the crop, such as plant height and/or volume. The system is validated in the field in a commercial vineyard at different phenological stages, from the formation of the berries to leaf discoloration and fall. Experimental results show good agreement compared with ground truth provided by a GreenSeeker, with a mean absolute percentage error in the NDVI estimation of 4.6% and a R 2 of 0.87 tested over the whole grapevine cycle. Therefore, the proposed sensing system could be a feasible solution to automated NDVI estimation at plant-scale. [Display omitted] • Consumer-grade imaging system using a RealSense RGB-D camera for NDVI estimation. • Robotic platform for automated in-field monitoring at plant scale in viticulture. • Proximal sensing system to characterize the vine foliage. • Solutions to IR filtering and radiometric calibration issues under natural light. • Validation in the field in a commercial vineyard at different phenological stages. [ABSTRACT FROM AUTHOR]

• This is the first comprehensive report highlighting the potential of inter-specific hybrid Fremont mandarin under hot arid region of India which found promising to enable early harvesting than Kinnow mandarin. • Karna khatta rootstock found best for growth and yield traits, whereas Pectinifera rootstock delivered superior fruit quality with high stionic effects. • Pectinifera rootstock induced dwarfism in Fremont mandarin with high rate of scion-rootstock compatibility which enabled high density orcharding and leads to microclimate effect on crop management in arid climate. Performance of an inter-specific hybrid Fremont mandarin was assessed on different rootstocks in the hot arid regions of India as a potential scion species to expand citrus fruit availability in an arid region. Fremont scion attained superior growth and yield characteristics on Karna khatta rootstock by displaying the greatest plant canopy parameters followed by Rough lemon rootstock. However, the Pectinifera as well as the Troyer citrange resulted in dwarfness of the scion. The scion-rootstock compatibility indicators such as scion rootstock ratio, stionic difference and TCSA which were greatest in the Fremont/Pectinifera combination, confirm that the inhibited tree growth on Pectinifera rootstock was caused by intrinsic features of the rootstock rather than an incompatibility reaction. Furthermore, Karna khatta rootstock resulted in highest fruit yield and related traits followed by Rough lemon and Pectinifera rootstocks. The Pectinifera rootstock resulted in a similar response to all fruit physical attributes i.e., fruit weight, fruit diameter, fruit index and fruiting density, except fruit number. The fruit maturity of Fremont was obtained earliest on Pectinifera, while it was most delayed on Karna khatta and Rough lemon rootstocks. Fruit quality parameters on Pectinifera rootstock were superior to those of common rootstock species (Rough lemon or Karna khatta) including fruit juice content as well as its nutritional constituents like TSS, ascorbic acid, pH, total sugar, organoleptic taste, ripening index, lower content of acidity and rind thickness. The total AAE, total flavonoids, total phenol contents were also noticeably higher than those obtained on other rootstocks, except Troyer citrange. Overall, Fremont mandarin can be considered a promising scion in arid regions to extend the harvesting period of superior quality fruits, especially on dwarfing Pectinifera rootstock. It would further ease harvesting operations vis-a-vis possible attainment of a better micro-climate due to small tree stature and high-density orcharding. [ABSTRACT FROM AUTHOR]

While it is well documented that insects exploit polarized sky light for navigation, their use of reflected polarized light for object detection has been less well studied. Recently, we have shown that the small white butterfly, Pieris rapae, distinguishes between host and non-host plants based on the degree of linear polarization (DoLP) of light reflected from their leaves. To determine how polarized light cues affect host plant foraging by female P. rapae across their entire visual range including the ultraviolet (300-650 nm), we applied photo polarimetry demonstrating large differences in the DoLP of leaf-reflected light among plant species generally and between host and non-host plants specifically. As polarized light cues are directionally dependent, we also tested, and modelled, the effect of approach trajectory on the polarization of plant-reflected light and the resulting attractiveness to P. rapae. Using photo polarimetry measurements of plants under a range of light source and observer positions, we reveal several distinct effects when polarized reflections are examined on a whole-plant basis rather than at the scale of pixels or plant canopies. Most notably from our modeling, certain approach trajectories are optimal for foraging butterflies, or insects generally, to discriminate between plant species on the basis of the DoLP of leaf-reflected light. [ABSTRACT FROM AUTHOR]

Many plant species have dorsiventral leaves that have significant differences in optical properties from one side to the other. Several studies have revealed that ignoring this asymmetry induces significant errors in plant canopy reflectance, and current leaf models simulating leaf dorsiventrality are limited to the 0.4–2.5 μ m wavelength range. This article, partly based on two recently collected datasets in the 2.5–14 μ m wavelength range, demonstrates that ignoring leaf dorsiventrality induces significant errors in brightness temperature and effective emissivity at the canopy scale. The PROLIB model, which inherits from the PROSPECT-VISIR and LIBERTY models, is the first radiative transfer model to simulate the reflectance and transmittance of both leaf sides from 0.4 to 5.7 μ m. The palisade and spongy mesophylls are represented as plate and sphere layers, respectively, to account for the structural asymmetry of leaf cells. The sieve effect that explains the differences in transmittance between the adaxial and abaxial sides of the leaf is successfully incorporated into PROLIB. Evaluation of the model on several leaf datasets shows that: (1) It reproduces well the adaxial and abaxial optical properties of the leaves, with a root mean square error (RMSE) of 0.0109 for reflectance and transmittance. (2) It can be inversed to retrieve leaf traits, with RMSE values for leaf chlorophyll, carotenoid, anthocyanin, water, and dry matter content of 5.519 μ g/cm2, 2.344 μ g/cm2, 4.219 μ g/cm2, 0.0022 g/cm2, and 0.0017 g/cm2, respectively (corresponding normalized RMSE values of 22.0%, 34.0%, 49.4%, 19.6%, and 24.7%). However, better and more complete leaf datasets are needed for leaf dorsiventrality analysis and model calibration. • Adaxial and abaxial leaf surfaces have different spectral properties in 2.5–14 μ m. • A leaf model called PROLIB is developed to simulate leaf dorsiventrality. • PROLIB takes into account the sieve effect. • PROLIB reconstructs leaf spectra well from multiple datasets, with an RMSE of 0.0109. [ABSTRACT FROM AUTHOR]

• Broomrape infection in carrots is detectable using hyperspectral data. • Agglomerative clustering with spectral angle mapper can isolate symptomatic pixels. • PROSPECT applied exclusively to symptomatic pixels allows distinct evaluations. • Alterations in macro elements and pigments shape the unique symptomatic spectra. In this study, we explore spectral heterogeneity within plant canopies, a characteristic often observed in stressed plants where certain leaves or intra-leaf regions exhibit stress symptoms while others remain unaffected. Considering this variability in spectral signatures holds promise for enhancing remote sensing methodologies aimed at plant stress detection. Typically, remote sensing techniques analyze the plant as a whole, potentially overlooking stress-related spectral signatures due to the inclusion of unaffected pixels. We used a clustering-based technique, which incorporates semi-supervised learning elements for tuning hyper-parameters, to differentiate spectral patterns associated with and unique to pixels from broomrape-infected (Orobanche spp. and Phelipanche spp.) carrots from unrelated patterns. Ground-based hyperspectral (400–1000 nm) images of broomrape-infected and non-infected carrot canopies were used in an agglomerative clustering procedure followed by spectral angle mapper (SAM) analysis to identify a spectral endmember indicative of broomrape infection symptoms. Pixels from this cluster constituted an average of 8.5–11.5 % from the canopies of infected plants. Subsequently, we: (a) examined the relationship between carrot leaf mineral content and the percentage of symptomatic pixels to explore stress-induced alterations creating the unique spectral signatures of infected plants; and (b) utilized the inverse mode of PROSPECT, a radiative transfer model (RTM), to derive primary plant traits from the distinct spectral data of each cluster. We found that deficits in two macro elements, phosphorous and potassium, along with two pigments, chlorophyll and carotenoid, were correlated with the symptomatic cluster in infected plants. The methodology presented in this study paves the way for further research into broomrape detection in various crop species, as well as other plant stressors. [ABSTRACT FROM AUTHOR]

• We theoretically propose angular resistant spectral indices (ARSIs). • A three-step band selection method for ARSI from multi-angular spectra is developed. • ARSIs are insensitive to angular variation but sensitive to biochemical parameters. • ARSIs obtain high spatial-resolution maps of canopy leaf biochemical parameters. Spectral indices are popular and simple mathematical methods for estimating leaf biochemical parameters from spectral reflectance information. However, the estimation accuracy of most spectral indices decreases in high spatial-resolution data. This is primarily because leaf reflectance exhibits multi-angular effects that are controlled by specular reflection and vary with illumination and viewing angles. Therefore, there is a need for robust spectral indices whose predictions of leaf biochemistry are resistant to measurement angles and configurations. The commonly used wavelength optimization method of reducing angular effects by iterating all the possible band combinations is time-consuming and lacks a sound theoretical basis. In this study, we developed an efficient and defensible three-step wavelength selection method for Angular Resistant Spectral Indices (ARSIs) with difference ratio format based on the multi-angular spectral reflection. Firstly, a cumulative R2 increase within the leaf biochemistry-significant wavelength range is used to identify a specular wavelength (λ spec) as the wavelength with the highest contribution of specular reflection to total reflection. The impact of specular reflection on the estimation of the biochemical parameters is reduced by subtracting the reflection at λ spec from the total reflection. Secondly, a reference wavelength (λ ref) that is insensitive to biochemical variations is selected from the valley bottom of the R2 spectrum near its maximal peak. Thirdly, the optimal ARSIs are developed based on the combination of λ spe c , λ ref , and a biochemistry-indicative wavelength (λ indi). These ARSIs show strong relationships to leaf chlorophyll content (LCC, R2 = 0.94), leaf carotenoid content (CAR, R2 = 0.61), and equivalent water thickness (EWT, R2=0.89). Validation using several independent datasets and accurate LCC and CAR estimations based on close-range hyperspectral images of plant canopies confirmed that ARSIs outperformed most existing indices. The three-step wavelength selection method for ARSIs is valuable and convenient for plant science, and crop management assessments that need accurate estimates of leaf biochemical parameters. [Display omitted] [ABSTRACT FROM AUTHOR]

• Chemometric quantification of macronutrient concentrations in medical cannabis. • Hyperspectral images were taken during lighting period under greenhouse conditions. • PLSR models were applied at single-leaf and canopy level. • Data was collected from a wide range of growing conditions and growth stages. The cultivation of medicinal cannabis (Cannabis sativa L.) indoors is mainly aimed at the homogeneity of the chemical profile produced in flowers and leaves. Nutrient supply in different stages of development highly affects the chemical profile and yield. This study describes a novel approach using hyperspectral imaging as an in situ monitoring system for the nutritional status of cannabis plants under greenhouse conditions. Specifically, the quantification of nitrogen (N), phosphorus (P), and potassium (K) in individual leaves and at canopy level was investigated. Hyperspectral images of whole plants and individual leaves of a phytocannabinoid-rich genotype, grown under different environmental conditions, were acquired in the wavelength range of 400–1000 nm at different growth stages under natural daylight conditions with supplementary greenhouse light. A wide variation of nutrient levels was created by the use of different growth substrates, fertilizer levels, and vegetation lengths for plant cultivation. Pixels of single leaves were filtered out from the background using the normalized difference red edge index, while pixels of plant canopy were separated from the background using a supervised classification algorithm. Mean reflectance per leaf/plant was calculated. Partial least squares regression (PLSR) was able to predict N concentration with a root mean square error (RMSE) of 0.47 % (R2 = 0.9) and 0.6 % (R2 = 0.86) in plant canopy and single leaves, respectively. Satisfactory models could be obtained for P with RMSE of 0.07 % (R2 = 0.74) and 0.08 % (R2 = 0.73) in plant canopy and single leaves, respectively. An R2 of 0.57 (RMSE = 0.48) was obtained for the prediction of K concentration at the plant canopy level, presumably based on the high correlation between K and N. In contrast, the prediction accuracy was insufficient for K at single-leaf level (R2 = 0.13). After wavelength selection, PLSR achieved better model performance than full spectrum PLSR in all cases and significantly reduced the model size for N concentration in plant canopy. This study is a proof of concept, that hyperspectral imaging can be used as real-time sensing technique for nutrient quantification in cannabis greenhouse production, without interfering with growing conditions. [ABSTRACT FROM AUTHOR]

The crop canopy structure has a significant impact on greenhouse microclimate, in return, the intercepted solar radiation and thermal properties of the plant canopy under greenhouse microclimate directly affect plant photosynthesis and so yield. However, in practice, it is very difficult and time-consuming to accurately measure how plants interact with microclimate over time. In this study, a new method was developed to evaluate micro-light climate and thermal performance on the example of Liaoshen-type Solar Greenhouses (LSG) including a detailed 3D tomato canopy structure, simulated using a functional–structural plant model (FSPM). The detailed surface temperature of each greenhouse component and the tomato crop on organ level down to the leaflets were simulated using advanced light modelling techniques. Taking the simulated light absorptions as input, the thermal conditions were obtained using specific energy balance equations. The simulated greenhouse temperature of the cover, roof, inside air, wall, canopy, and soil showed an overall good correlation to the observed values. The presented model can be seen as the first step towards a realistic 3D greenhouse/canopy simulation including extended energy balance computation based on physical-based light simulation, which can be directly transferred to other types of greenhouses and plant species. • Developed a new method to evaluate light climate and thermal performance inside a planting greenhouse. • Extended-energy balance equations were developed to simulate the temperature. • 3D solar greenhouse and tomato canopy structure was built. • Detailed surface radiation and temperature of greenhouse and the tomato crop at leaflet level were simulated. • This work provides a base for further investigations into planting greenhouse microclimate modelling. [ABSTRACT FROM AUTHOR]

Optimum energy consumption and renewable energy utilization reduce environmental impacts and are cost-effective. They are the key aspects of achieving sustainable energy management, such as in the agricultural industry. The contribution of the horticultural section in the global energy demand is approximately 2%, and among its various sections, greenhouses are one of the main systems in modern agriculture that have a great share on energy consumption. In this study, a rose greenhouse is examined and modeled in EnergyPlus as a greenhouse reference (GR). Validation of the developed greenhouse model is carried out with a site experimental measurement. Using the GR as the basic model, 14 various configurations of greenhouses have been assessed by considering a solar photovoltaic blind system (SPBS) in checkerboard arrays 1 m above the greenhouse roof. These modified greenhouses called solar-blind greenhouses (SBGs) have different shading rates and SPBS sizes. To perform a Thermo-environomic assessment, the effects of various parameters, including temperature, relative humidity, natural gas consumption, electricity consumption, and carbon dioxide (CO 2) emission reduction, are studied. Results indicate that covering 19.2% of the roof, with no significant change in the illumination level on the plant canopy, will annually reduce natural gas consumption, electricity demand, and CO 2 emission by 3.57%, 45.5%, and 30.56 kg/m2, respectively. Moreover, with the SPBS, the annual electricity production is approximated at 42.7 kWh/m2. • Greenhouses with various solar photovoltaic blind system (SPBS) were studied. • Illumination on the plant's canopy and growth investigated and precisely controlled. • The SPBS generated electricity and its contribution to energy demand was assessed. • Annual CO 2 emission reduction by covering 19.2% of the roof estimated at 30.6 kg/m2. • Covering 19.2% of the greenhouse roof reduces electricity demand by 45.5% annually. [ABSTRACT FROM AUTHOR]

• Leaf lipids respond to seasonality in temperature and light. • Fatty acid unsaturation correlated with temperature. • n -Alkanol chain lengths correlated with light in the deciduous tree canopy. • Sterol ratios respond to temperature and light thresholds for both species. • Multi-lipid models aid in the reconstruction of seasonal temperature and light. Forest canopy structure is a fundamental ecosystem attribute affecting regional and global climate through primary production by CO 2 drawdown and evapotranspirative feedback. Environmental changes in temperature and light affect leaf physiology and thus canopy functioning. Leaf physiological changes may be reflected in expressed chemical compounds (e.g., leaf lipid biomarkers), that offer opportunities to characterize and quantify climatic effects on plant canopies in the present and the past. To assess this possibility, we systematically investigated the lipids from leaves of deciduous angiosperm (Quercus buckleyi, April–October 2019) and evergreen gymnosperm (Juniperus ashei, April–October 2019 and January 2020) tree species at monthly sampling intervals over one growing season in a natural sub-humid ecosystem of central Texas. Fatty acid unsaturation in Q. buckleyi and J. ashei leaves was negatively correlated with air temperature. The average chain lengths of leaf wax n -alkanols of Q. buckleyi were strongly correlated with leaf area index (LAI) and absorbed photosynthetically active radiation (APAR) (r2 > 0.5). The stigmasterol/β-sitosterol ratio was correlated with light transmittance in the canopy of Q. buckleyi , with values of the sterol ratio three-fold higher in shaded leaves than in sparse canopies. The observed seasonal changes in leaf lipid molecular composition and chain-lengths might be related to their biosynthetic responses to temperature and light stresses. Finally, we developed multi-lipid regression models resolving seasonal differences in temperature, LAI, and APAR. We posit that the specific lipid biosynthetic responses to variations in temperature and light are a basis for reconstructing terrestrial paleoenvironmental changes. [ABSTRACT FROM AUTHOR]

• Grassland had a greater soil water gain and loss than abandoned crop and shrubland. • Hot spots with great deep soil water gain and loss were in layered soils and grassland. • Silt and SOC content primarily controlled the spatial pattern of soil water dynamics. • Plant and soil profile properties secondly controlled the spatial pattern of soil water dynamics. The increase in the extreme drought trend, reduction in soil erosion, and acceleration of deep soil desiccation are renewing interests in soil water dynamics and its environmental controls after long-term (>30 years) grass and shrub revegetation on the Chinese Loess Plateau (CLP). However, inconsistent findings have been reported on soil water dynamics in these typical land uses due to the multi-dependent environmental controls. The objectives of this study are to identify the spatial variability of soil water dynamics and its controls in a small watershed. For this purpose, spatiotemporal soil water storage in 1 m interval to a depth of 5 m was decomposed into a temporal mean (i.e., time-stable pattern) and temporal anomaly (A tn ), which varies over time and is related to soil water dynamics. A tn was then decomposed into a space-invariant temporal anomaly (i.e., spatial mean of A tn ) and a space-variant temporal anomaly (R tn ) , which reflects the spatial variability of soil water dynamics. The R tn was further decomposed using the empirical orthogonal function (E O F) to identify its major controls. Results showed that soil water dynamics (gain and loss) decreased from grassland to abandoned cropland followed by shrubland after long-term revegetation. The hot spots in deep soil water dynamics (2–5 m) were identified in layered soils with an overlying sand layer and underlying silt layer, and grassland with the coexistence of tree-shrub-grass and high deep soil organic carbon (SOC) content. 50–70% of the total variations of R tn were explained by the first two spatial patterns ( E O F s). Silt and SOC content controlled E O F 1 of R tn at 0–2 and 2–5 m, respectively. Plant canopy and soil profile properties (e.g., layered soils with an overlying sand layer and underlying silt layer) controlled E O F 2 of R tn at 0–1 and 2–5 m, respectively. The E O F analysis suggests that silt and SOC dominated soil water storage capacity, plant canopy regulated water flux, and variations of hydraulic properties in soil profiles may jointly drive spatial variability of soil water dynamics. [ABSTRACT FROM AUTHOR]

The influence of coherent vortices on the turbulence structure above and below a dense plant canopy is investigated using turbulence measurements collected at five levels on top and inside a coniferous forest on an Alpine Plateau. Five different stability regimes, from free convection to very stable stratification, were identified and considered in the analysis. Coherent structures are detected by fitting the vertical velocity auto-correlation functions with a theoretical oscillating function. This allowed to evaluate the coherent vortices characteristic timescales and to discriminate between turbulent data subsets characterized by fine-scale turbulence and subsets in which turbulence is dominated by coherent structures generated at the canopy top. An original methodology to fit cross-correlation function and to single out the most energetic frequency in presence of periodic behaviour is presented and applied to the turbulent momentum flux. The analysis shows how not far from neutral conditions the dominant time scale of the momentum flux is mainly determined by the longitudinal wind velocity component, rather than vertical one, while in free convection and very stable conditions coherent vortices do not seem to influence the momentum transport, dominated by large-scale structures. This is confirmed by the fine-scale turbulence and coherent structures efficiency in turbulence transport throughout the stability regimes. • An original methodology to fit the cross-correlation functions is presented. • The methodology singles out the most energetic frequency of coherent vortices. • The coherent structures contribution to the turbulent fluxes is assessed. [ABSTRACT FROM AUTHOR]

• Light extinction coefficient (C) change pattern was studied in different orchards. • A new method was proposed to capture C dynamics in transpiration (T) estimation. • T model with dynamic C scheme was compared with that with fixed C scheme. • Model with dynamic C scheme yielded more accurate results with smaller uncertainty. • Model performance improved better in sites with more sever environmental stresses. The light extinction coefficient (C) describes the efficiency of light interception by a plant canopy, and is a key parameter commonly used to partition radiant energy between a vegetation canopy and the soil surface in several important transpiration models. The C has been observed to vary considerably in the field, but is often parametrized as a fixed constant value, resulting in large potential uncertainty in transpiration estimation. We hypothesized that C changes with leaf area index (LAI) and environments, and that accurate characterization of the C variation pattern would improve transpiration modelling. To test these hypotheses, the relationships between measured C and potential influencing factors were explored for three different fruit plantations in different climate zones in China. Based on these relationships, a new method was proposed to capture C dynamics that considered both LAI and environmental factors. Additionally, 16 C schemes (15 dynamic C schemes and one fixed C scheme) were individually embedded in the Penman-Monteith model, and comprehensive comparisons were made to determine the most effective C scheme for simulating transpiration based on a Bayesian framework. Results showed that C displayed clear variations across all sites, and that there were significant relationships of C with LAI and environmental factors. Compared with the model using a fixed C scheme, the model using the best dynamic C scheme significantly improved model performance by increasing estimation accuracy and decreasing model uncertainty. Specifically, the average coefficients of determination (R2) increased from 0.35 to 0.76, 0.82 to 0.85, and 0.90 to 0.93 for the orange orchard, the jujube orchard, and the grape greenhouse, respectively. Additionally, the average mean relative errors (MRE) decreased by 54.99%, 26.62%, and 13.95%, respectively, and the average uncertainty band widths (B) decreased by 46.81%, 21.74%, and 11.43%, respectively. Model performance improvement was more significant at sites with more serious environmental stresses. The results of our study emphasize the necessity for considering dynamic C patterns in water consumption estimation, particularly for regions facing severe abiotic stresses that are likely to occur in many regions under future climate conditions. [ABSTRACT FROM AUTHOR]

• Explore a novel approach for canopy reconstruction with occluded structure recovery. • Propose a Generative Adversarial Net to complete the occluded leaves. • Propose a point–cloud reconstruction algorithm to recover fragmental point-clouds. • Verify the proposed approach with several canopy reconstruction tests. The inner leaves of crop canopies are obscured by outer branches and leaves, leading to information loss and observation difficulty of the occluded canopy structure using modern crop monitoring techniques. It has restricted the development of phenotypic analysis and precision agriculture. In this paper, we propose a neural network approach to reconstruct the occluded structure of crop canopies with an RGB-D sensor. Taking the cotton plant as the object of study, we propose a novel Cascade Leaf Segmentation and Completion Network (CLSCN) to reconstruct the occluded leaf images and propose a Fragmental Leaf Point–cloud Reconstruction Algorithm (FLPRA) to complete the missing point clouds. By combining the Instance Segmentation Network (ISN), Generative Adversarial Network (GAN) and Point-cloud Reconstruction Algorithm (PRA), the three-dimensional models of cotton plants with both completed internal and external structures of the canopy are smoothly reconstructed. Firstly, we collect a large number of leaf images and point clouds of cotton plants using an RGB-D sensor with the top view and construct a manually labeled cotton leaf dataset for training and evaluation. Secondly, a network named CLSCN is cascading constructed with an Instance Segmentation Network (ISN) and a Generative Adversarial Network (GAN), and the two parts of CLSCN are separately trained with our constructed dataset to output complete cotton leaves. Thirdly, with the fusion of the completed RGB images output by cascaded network segmentation and the point clouds captured by RGB-D sensor, the proposed FLPRA is used to filter, reconstruct, fuse and register the cotton canopy leaf point clouds, and to obtain the whole cotton canopy point-clouds with inner occluded structure recovery. Finally, the CLSCN and FLPRA are validated using the validation dataset of cotton leaf. The test results indicate that the front-end ISN of the proposed CLSCN can generate high-quality cotton leaf masks, with FID scores less than 35 and mIoU up to 84.65%. Additionally, the back-end GAN of CLSCN can complete the occluded leaves with an accuracy of over 94%. The reconstruction accuracy of the final three-dimensional model of the cotton canopy is as high as 82.70%. Therefore, the proposed neural network and algorithm effectively solve the problem of incomplete canopy point cloud caused by the occlusion of outer leaves and provide an effective way to recover the complete three-dimensional structure of crop canopy with internal occlusion. It is a meaningful theoretical and technical support to realize real-time crop status observation and precise field management in agriculture production. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) deposited on canopy surfaces could be washed off and carried in throughfall to the ground. This would help plants recapture airborne PM on their canopy surfaces and then develop a PM purification capacity. Sixteen commonly greening plant species in north China (including 13 arbor species and 3 shrub species) were selected to investigate the washing process of plant-deposited PM during precipitation events. We measured the PM wash-off mass in throughfall under canopies of 16 plant species and in atmospheric precipitation during 14 precipitation events through field positioning experiments in 2015, compared the seasonal changes and species differences in PM wash-off mass, and discussed the predominant factors resulting in the variation. The results showed that plant-deposited PM was largely washed off by precipitation. The average wash-off mass of total suspended particulate (TSP) in throughfall was 1.3 times higher than that in precipitation, at 18.3 ± 0.7 kg hm−2 and 7.9 ± 0.9 kg hm−2, respectively. There were significant seasonal differences in TSP wash-off mass. The value was higher in summer at 22.3 ± 1.0 kg hm−2, followed by that of winter (10.8 ± 0.6 kg hm−2) and spring (8.9 ± 1.0 kg hm−2). TSP wash-off mass in throughfall greatly varied among plant species (F = 9.542, n = 627, p < 0.001). Of the 16 selected species, Platanus acerifoli a (38.0 ± 5.8 kg hm−2) showed the largest difference from that of Liriodendron chinese (8.9 ± 0.6 kg hm−2) (n = 80, p < 0.001). PM wash-off mass of different particle sizes in throughfall increased with the increase of event-based precipitation. This study enhanced the quantitative understanding of plant-deposited PM washed-off by natural precipitation among plant species and seasons. The results could provide significant guidelines for the selection and allocation of plant species to improve the PM retention capacity of urban greening plants. Image 1 • The total PM wash-off mass from plant species averaged 18.25 ± 0.74 kg hm−2. • PM wash-off mass in throughfall greatly varied among plant species and seasons. • PM wash-off mass was higher in summer compared to winter or spring. • Deciduous species had almost twice higher PM 3-10 wash-off mass than the evergreen. • PM 0.4-3 wash-off mass from arbor species was 1.4 times larger than that of shrubs. PM wash-off mass in throughfall varied markedly with both plant species and seasons, and the variation occurred because of precipitation, canopy characteristics, and dry deposition of PM. [ABSTRACT FROM AUTHOR]

• AGC estimates proved comparable to previous estimates using more cumbersome models. • Degraded subtropical thicket can recover 22–27 t C ha−1 AGC through restoration. • Large canopy dominant species contributed the largest AGC portion. • AGC pools are higher to the northeast, consistent with higher summer rainfall. Accurate biomass and carbon flux estimations are essential for global carbon cycle modeling and are useful for setting and evaluating ecological restoration goals. Estimates derived from remote sensing can only be as good as the field data with which they are calibrated. Biomass estimates derived from allometric models are widely used to extrapolate from a plot to a landscape or regional scale, but both species- and/or site- specific models are scarce, and the model development procedure destructive and labour-intensive. Here we present allometric models that estimate biomass for 40 species common in Spekboom Thicket (ST), an arid South African Subtropical Thicket type, and its ecotones. Portulacaria afra (spekboom) is a canopy cover dominant in intact states of ST. Using these simple regression models, based on plant height and canopy diameter parameters, we estimate the aboveground biomass carbon (ABC) and with litter, the total aboveground carbon (AGC) of five sites situated across the Subtropical Thicket biome in South Africa. On each site, adjacent stands were selected that compared two management histories, intact and livestock-degraded, divided by a fence line boundary. Our estimates compared well with results from other studies. The highest AGC for stands in both intact and degraded states were estimated at 43.0 t C ha−1 and 13.0 t C ha−1 respectively, and the lowest at 26.3 t C ha−1 and 2.5 t C ha−1. Large canopy dominant (LCD) species contributed the largest AGC portion at three intact stands. The second largest portion was recorded for spekboom. Overall, the sites to the northeast of the biome recorded the highest AGC pools, consistent with a higher incidence of rainfall, especially in the summer months. In contrast, sites to the west of the biome showed higher mean litter carbon pools. Should intact sites be applied as reference, livestock-degraded subtropical thicket can potentially recover 22 – 27 t C ha−1 in AGC through restoration action. [ABSTRACT FROM AUTHOR]

• Errors in Beer's law due to canopy heterogeneity and anisotropy were evaluated. • As plant spacing approached the canopy height, errors became significant. • Heterogeneity caused errors in daily light interception of up to 115%. • Errors due to anisotropy were usually small except for in the vineyard case. Light interception in plant canopies is most commonly estimated using a simple one-dimensional turbid medium model (i.e., Beer's law). Inherent in this class of models are assumptions that vegetation is uniformly distributed in space (homogeneous) and in many cases that vegetation orientation is uniformly distributed (isotropic). It is known that these assumptions are violated in a wide range of canopies, as real canopies commonly have heterogeneity at multiple scales and almost always have highly anisotropic leaf angle distributions. However, it is not quantitatively known under what conditions these assumptions become problematic given the difficulty of robustly evaluating model results for a range of canopy architectures. In this study, assumptions of vegetation homogeneity and isotropy were evaluated under clear sky conditions for a range of virtually-generated crop canopies with the aid of a detailed three-dimensional, leaf-resolving radiation model. Results showed that Beer's law consistently over predicted light interception for all canopy configurations. For canopies where the plant spacing was comparable to the plant height, Beer's law performed poorly, and over predicted daily intercepted sunlight by up to ∼115%. For vegetation with a highly anisotropic leaf inclination distribution but a relatively isotropic leaf azimuth distribution, the assumption of canopy isotropy (i.e., G = 0.5) resulted in relatively small errors. However, if leaf elevation and azimuth were both highly anisotropic, the assumption of canopy isotropy could introduce significant errors depending on the orientation of the azimuthal anisotropy with respect to the sun's path. [ABSTRACT FROM AUTHOR]

• We assess aboveground carbon, forest patch size and plant species richness to 2030. • Errors from the land use change model are propagated to the impact assessment. • Hereby, we can test if policy instruments (scenarios) significantly reduce impacts. • Limiting development results in the most sustainable pathway for East-Kalimantan. • Under unlimited development, zoning is effective; under limited development not. Large-scale land use and land cover (LULC) changes can have strong impacts on natural ecosystems, such as losses of biodiversity and carbon. Future impacts, under one or multiple future scenarios, can be estimated with the use of LULC projections from land use change models. Our aim is to quantify LULC change impacts on carbon stocks and biodiversity in the West Kutai and Mahakam Ulu districts in East Kalimantan, Indonesia. Hereto, we used LULC data from 1990 to 2009 and land use change model projections up to 2030 under four contrasting LULC change scenarios differing along two axes: land development (limited vs. unlimited) and zoning (restricted vs. unrestricted), explicitly considering the uncertainties in the land use change model. For the LULC change impact calculations, three quantitative indicators were evaluated: aboveground biomass (AGB) (for carbon stocks), closed-canopy forest patch size distribution and plant species richness (for biodiversity). Subsequently, we statistically assessed whether the motivation to opt for a specific scenario was conclusive given the uncertainty in the indicator values. We found that under the limited development scenarios the projected AGB decrease towards 2030 was insignificant, plant species richness was projected to decrease significantly by ∼3%, and closed-canopy forest patches mainly of 100–1000 ha were projected to become fragmented. The effect of zoning was insignificant under these scenarios. The difference between the limited and unlimited development scenarios was significant, with the projected impacts under the unlimited development scenarios being much higher: AGB was projected to decrease 4–30%, plant species richness 10–40%, and the closed-canopy forest was projected to completely loose its typical patch size distribution. The effect of zoning on these scenarios was positive and significant. These results suggest that the most sustainable pathway for East Kalimantan, given our indicators, would be to limit land development, mainly large-scale cash-crop cultivation. If land development cannot be limited, the implementation of restricted development zones is advised. The methodologic novelty of our approach is that we propagate uncertainties from a land use change model to the impact assessment and test the significance of differences between future scenarios, in other words we test if a potential policy instrument has a significant (positive) effect on the studied indicators and may thus be worth implementing. [ABSTRACT FROM AUTHOR]

• Photographic estimate of direct and total light performed better than LAI-2000. • An overcast midday light estimate gave poor characterization of light gradient. • Sunny day light measurement at 3-different time provided the strongest correlation. • Either sunny or overcast midday light estimate underperformed. A knowledge of how light varies within gaps is fundamental to understanding variation in survival and growth of regenerating trees. Simple indices based on a small number of instantaneous measurements by portable sensors or cameras are widely used for this purpose. But the effectiveness of these indices for estimating growing season transmittance is influenced by stand characteristics and local weather conditions. This study was conducted in two small (50 m × 150 m) clearings in a mixed stand of the interior cedar hemlock zone of southern British Columbia to evaluate several commonly used light estimation techniques, including: (1) hemispherical photography; (2) LAI-2000 plant canopy analyzer; and, (3) midday measurements of % photosynthetic photon flux density (hourly average PPFD) under sunny and overcast skies in a strip-shelterwood system. While diffuse indices from hemispherical methods (LAI-2000 and photograph) performed poorly, their direct and total indices (photograph) gave lower variability (lower rmse) and stronger correlations (higher r2) with growing season transmittance. Sky conditions under which light measurements were recorded by photosynthetically active radiation (PAR) sensors influenced the relationships between PAR sensor indices and growing season transmittance. For example, measuring light around midday on a sunny day provided stronger correlation with growing season transmittance than overcast day measurements. Moreover, rather than using one midday light measurement on a sunny or an overcast day, an average of two measurements increased r2 and reduced bias while measuring light three times on a sunny day (morning, noon and afternoon) gave the highest r2 and the lowest variability. Several indices also correlated strongly with monthly light levels, measured from May – September. Based on the finding that indices that accounted for direct beam contribution gave the best outcomes, we suggest that canopy conditions (degree of heterogeneity), stand orientation and gap sizes should be considered in selecting an instantaneous light index for studies in high latitude forests. [ABSTRACT FROM AUTHOR]

• Radiation transmission of vertical canopies is distinct from horizontal canopies. • The extinction coefficient increases following the increasing of incident angle. • South vertical canopy transmission is the highest among the 4 orientations. • Transmission decreases with smaller leaf inclination angle or larger LAI. • Lower transmission reduces solar gain and building energy load. Living wall systems attached to building facades act as energy barriers by blocking solar radiation. Light goes through the plant canopy and reaches the substrate surface instead of the building wall. The amount of solar radiation that reaches the substrate surface dictates the amount of heat transferred indoors, which affects the energy efficiency of the building envelope. The leaf inclination and leaf area index (LAI) describe the structural features of the canopy, which affects transmittance of radiation. The fraction of radiation intercepted by a canopy and the fraction transmitted to the substrate surface can be modeled based on the geometric parameters of the plants and the canopy's relative position to the sun. By modifying Campbell's ellipsoidal model, a new living-wall solar radiation (LWSR) model that computes solar transmission in vertical canopies was established. The model's accuracy was evaluated against experimental measurements of a living wall in Wuhan, China, through spring, summer, and fall. The simulated values were closer to the actual value and the accuracy was higher in comparison with Campbell's ellipsoidal model. The LWSR model can simulate living walls with different orientations and canopy structures. The simulation results reflect different magnitudes of radiation attenuation by living wall canopies as a function of leaf inclination and LAI. Image, graphical abstract [ABSTRACT FROM AUTHOR]

The flow dynamics within and immediately above an artificial plastic vegetation canopy are measured in the field and wind tunnel. Artificial plants created from wooden dowels and cable (zip) ties were arranged in a variety of arrays on pegboards where plant cover (or lateral cover) could be accurately controlled. Plant covers examined ranged from ~12% to 60%. Wind velocity profiles and the bedforms (incipient dunes) that developed within and beyond the vegetation in a few hours were measured. The results indicate that flow deceleration and drag increases within the canopy as plant density increases. In general, there is a marked reduction and inflection in velocity at the canopy top, and a second major inflection in the velocity profiles occurs immediately below the base of the four arrays equal or >23% density. Tall vegetation allows flow to sweep under the canopy and local high speed maxima flows may develop leading to minimal sedimentation in those canopies, but deposition downwind beyond the canopies. Short vegetation, where the leaves fill the canopy close to the ground, display significantly greater drag and rapid rates of sand deposition. Flow velocities above the canopy increase as plant cover or density increases due to flow compression and acceleration. Bedform development is strongly correlated with plant cover, density or lateral cover and short plants such that shorter length, higher bedforms develop in higher density and/or shorter plants. The relationship between plant cover, density or lateral cover and within canopy velocity is non-linear, and a new tentative flow regime is proposed, canopy flow, which may occur between wake interference flow and skimming flow. This study further confirms that plant density plays a defining role in determining bedform and dune morphology. The results also apply to flow in semi-arid grasslands. Development of velocity profiles downwind in high (50%) and low (12%) density plants. The profiles are shown for the upwind edge of vegetation (right side), and at 50 cm and 100 cm downwind. Unlabelled Image [ABSTRACT FROM AUTHOR]

The composition of the plant canopy is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. Terrestrial ecosystem and biosphere models, which are used to predict how ecosystems are expected to respond to changes in climate, atmospheric CO 2 , and land-use change, require accurate representations of plant canopy composition at large spatial scales. The ability to accurately specify plant canopy composition is important because it determines the physiological and ecological properties of plants (such as leaf photosynthetic capacity, patterns of plant carbon allocation and tissue turnover, and the resulting dynamics of plant demography) that govern the biophysical and biogeochemical functioning of ecosystems. Traditionally, plant canopy composition has been represented in a coarse-grained manner within terrestrial biosphere models, with ecosystems being comprised of a single plant functional type (PFT). However, models are increasingly seeking to represent fine-scale spatial variation in plant functional diversity. In this study, we show how imaging spectrometry measurements can provide spatially-comprehensive estimates of within-biome heterogeneity in PFT composition across a functionally diverse and topographically heterogeneous ~710 km2 area in the Southern Sierra Mountains of California. AVIRIS (Airborne Visible Infrared Imaging Spectrometer) data at 18 m resolution from the recent HyspIRI Preparatory Mission (Hyperspectral InfraRed Imager) were used to estimate the sub-pixel fractions of seven PFTs represented in the ED2 terrestrial biosphere model: Shrub, Oak, Western Hardwood, Western Pine, Cedar/Fir, and High-elevation Pine, plus a Grass/NPV (Non-Photosynthetic Vegetation) fraction using Multiple Endmember Spectral Mixture Analysis (MESMA). ED2 is an individual-based terrestrial biosphere model capable of representing fine-scale sub-pixel ecosystem heterogeneity. Our results show that this methodology captures important elevation-related shifts in canopy composition that occur within the study area that are not resolved by existing multi-spectral land-cover products. These estimates modestly improved when the putative PFT endmembers considered in the mixture analysis were constrained using available geospatial data about the presence and absence of the PFTs in particular areas: the average RMSEs (root-mean-square errors) with the geospatially-constrained versus conventional method were 11.3% and 11.9% respectively, with larger reductions in the bias (i.e. mean error) in the abundances of Oak, Cedar/Fir, and Western Hardwood PFTs (ranging from 2.0% to 7.8%). At the hectare scale around four flux towers in the Southern Sierra Mountains, the overall composition improved from an RMSE of 18.2% (5.0–24.2% for individual PFTs) to an RMSE of 9.5% (3.3–13.2% for individual PFTs). Downgrading AVIRIS to 30 m resolution resulted in a reduction in accuracy of the constrained method to an RMSE of 12.7% (0–23.7%) with <1% change in the bias for all tree and shrub PFTs. Our results demonstrate that imaging spectrometry measurements from planned satellite missions such as HyspIRI, EnMAP (Environmental Mapping and Analysis Program), and HISUI (Hyper-spectral Imager SUIte) can provide important and much-needed information about fine-scale heterogeneity in the composition of plant canopies for constraining and improving terrestrial ecosystem and biosphere model simulations of regional- and global-scale vegetation dynamics and function. • Imaging spectrometry used to estimate fine-scale terrestrial ecosystem composition • Analysis conducted over an ecologically diverse California landscape • Sub-pixel PFT abundances accurate to an average RMSE of 11.3% and Bias −2.4 to 3.1%. • Method provides a framework for improved terrestrial biosphere model simulations. [ABSTRACT FROM AUTHOR]

• The uWUE method was cross–compared with three traditional methods. • Daily T partitioned by the uWUE method well agreed with the SW model. • G c had more significant seasonal variations than G s. • The Jarvis model parameterized with G c performed better than those with G s. • The uWUE method can exclude influences of nonstomatal conductances. Canopy conductance (G c) largely regulates carbon/water cycling and land–atmosphere interactions, but quantifying G c using eddy flux data is limited by the difficulty of partitioning plant transpiration (T) and surface evaporation (E). We introduced an underlying water use efficiency (uWUE) method to partition evapotranspiration (ET) in an oasis maize ecosystem, and cross–compared with the Shuttleworth and Wallace (SW) model, the lysimeter and isotope measurements. We then estimated surface conductance (G s) by ET and G c by T partitioned using the uWUE method, followed by a performance evaluation on the Jarvis model parameterized with both G s and G c. The results showed that T/ET estimated by the uWUE method was close to the isotope method in the peak growing season of 2012, it showed similar seasonal variations with the lysimeter/eddy covariance method and the SW model throughout this growing season. Daily T partitioned by the uWUE method was in good agreement with the SW model from 2012 to 2015 (r2 = 0.91). Additionally, G c had more significant seasonal variations than G s. The Jarvis model parameterized with G c exhibited superior performance than those with G s. Our study suggests that the uWUE method can exclude influences of nonstomatal conductances, and will have great potential to provide more reasonable parameterization for simulation of plant stomata. [ABSTRACT FROM AUTHOR]

Abstract In Washington State, half of all pesticide-related illnesses in agriculture result from drift, the off-target movement of pesticides. Of these, a significant proportion involve workers on another farm and orchard airblast applications. We compared the spray drift exposure reduction potential of two modern tower sprayers – directed air tower (DAT) and multi-headed fan tower (MFT), in relation to a traditional axial fan airblast (AFA) sprayer. We employed real-time particle monitors (Dylos DC1100) during a randomized control trial of orchard spray applications. Sections of a field were randomly sprayed by three alternating spray technologies – AFA, DAT and MFT – while monitors sampled particulate matter above and below the canopy at various downwind locations in a neighboring field. Geometric mean particle mass concentrations (PMC) outside the intended spray area were elevated during all applications at all of our sampling distances (16–74 m, 51–244 ft). After adjusting for wind speed and sampling height, the 75th percentile (95% confidence interval) PMC level was significantly greater during spray events than background levels by 105 (93, 120) μg/m3, 49 (45, 54) μg/m3 and 26 (22, 31) μg/m3 during AFA, DAT and MFT applications, respectively. Adjusted PMC levels were significantly different between all three sprayers. In this study, tower sprayers significantly reduced spray drift exposures in a neighboring orchard field when compared to the AFA sprayer, with the MFT sprayer producing the least drift; however these tower sprayers did do not fully eliminate drift. Highlights • Elevated particle levels at all sampling locations 16–74 m from spray applications. • Significantly lower particle levels during tower than airblast sprayer applications. • Significantly higher particle levels at closer distances and below the canopy. • The EPA's application exclusion zone is likely not fully protective of drift. • Real-time monitoring may be an effective, novel method of drift characterization. [ABSTRACT FROM AUTHOR]

Highlights • RGB scans were used to evaluate field crops' canopy cover and irrigation uniformity. • A green-red vegetation index (GRVI) was found suitable to evaluate vegetation cover. • GRVI successfully recognized crop changes and heterogeneity in field irrigation. • Low-cost technique for in-field ET coefficients and irrigation uniformity evaluation. Abstract Canopy cover (or vegetation cover) maps serve in irrigation management mainly to determine the primary evapotranspiration (ET) coefficient, as radiation interception and evaporative surface area are directly related to canopy cover. Crop size and development with time depends on water supply; therefore, crop canopy maps are tools for the detection of the spatial uniformity of irrigation systems. Several aerial scan campaigns were deployed in the Upper Galilee of Israel in the 2017 and 2018 growing seasons to follow up and evaluate the irrigation uniformity and crop coefficients of peanuts and cotton by RGB scans of a Phantom 4 multirotor unmanned aerial vehicle (UAV) and DJI Mavic-Pro UAV equipped with RGB and near-infrared (NIR) sensors. Foliage intensity and coverage were enhanced by a green-red vegetation index (GRVI), which is a normalized difference vegetation index (NDVI)-like process where the green channel replaced the NIR. The results demonstrated that the GRVI is suitable for the purpose of determining the vegetation cover. Furthermore, the GRVI yielded better results than the NDVI in recognizing phenological crop changes (especially senescence) and in detecting heterogeneity in field irrigation. Therefore, this research proves the applicability of a low-cost digital camera mounted on an easily accessible UAV for crop cover and actual, in-field, ET coefficients determination and irrigation uniformity evaluation. [ABSTRACT FROM AUTHOR]

Highlights • Water consumption by jujube can be regulated by the canopy size. • Pruning effectively decreases water consumption and improves the water use efficiency in jujube. • Pruning can reduce soil water consumption and relieve deep soil drying. • Pruning level should be determined based on water consumption and average rainfall. Abstract Aims Soil drying has occurred widely in artificial plantations in the semiarid loess region because the water consumption exceeds the rainfall. Jujube (Ziziphus jujube Mill. CV. Lizao) plantations have been planted to improve the economic income since 2000. In order to prevent soil drying and sustain artificial plantation development, we examined the relationships between the canopy size, water consumption, and water use efficiency in a dry land jujube plantation. Methods Seven treatments were tested comprising native jujube with no pruning and dwarfing jujube under different pruning levels ranging from 1 to 6. Jujube is a popular dwarfing canopy type in this region with a tree height of 2.2 m and this comprised level 1. Jujube received increased intensities of pruning as well as decreases in tree height and canopy size for levels 2–4. Jujube received severe pruning to a tree height of only 1.1 m at level 5, and the canopy was removed with only 30–40 cm of the trunk left for level 6. Soil water was detected using CNC100 neutron tubes. A thermal diffusion probe was used to monitor the sap flow in jujube trees throughout the whole growth period. Results During our study period, 2014 was a wet year with rainfall of 460.4 mm and 2015 was a dry year with rainfall of only 380.8 mm. Transpiration and water consumption by jujube decreased significantly whereas the soil water content increased as the pruning intensity increased in these two years. Compared with 15-year-old native jujube, the annual soil water consumption by 15-year-old dwarfing jujube (pruned at level 1) was 6.54 mm less and the soil water consumption depth moved upward by 2.2 m. The soil water recovered faster for jujube at level 6 and the soil water restoration depth reached 4.6 m after 3 years, with an annual restoration depth of 153.3 cm. Compared with level 1 jujube, at level 5, the height was halved, the transpiration was about 22.1%, and the water use efficiency was significantly improved by 1.1 times, thereby demonstrating that the water consumption could be regulated by the canopy size. Level 2 jujube had the highest water use efficiency with the optimal pruning level in the local region. Conclusions We found that pruning could effectively decrease water consumption, relieve deep soil drying, and improve the water use efficiency in jujube. The pruning level should be determined based on the water consumption rate and average rainfall to obtain high yields. [ABSTRACT FROM AUTHOR]

Abstract Row crops such as grapevine are particularly vulnerable to heat stress under hot and dry conditions due to the combined effect of soil heat fluxes and of limited capacity for leaf/canopy evaporative cooling via transpiration. Therefore, a better understanding of grapevine responses to variations in air and soil temperature and of related heat fluxes are required in Mediterranean-type viticulture in order to optimize canopy and soil management practices, while saving irrigation water. Ground based thermography was used to monitor canopy (T C) and soil (T S) temperature patterns in a vineyard trained in a vertical shoot positioning trellis system. Measurements of heat exchanges in the vineyard were done along the day and throughout the season to predict vine's water status and heat stress risks. Field trials were carried out in 2014 and 2015 in Alentejo winegrowing region (South Portugal) using two V. vinifera red varieties (Aragonez, syn. Tempranillo and Touriga Nacional) subjected to two deficit irrigation strategies. T C and T S measurements were complemented by punctual leaf and berry temperature measurements with thermocouples. Soil water content, leaf water potential and leaf gas exchange were also measured. T C was above the optimal temperature for leaf photosynthesis during a large part of the day (11:00-17:00 h), particularly under stressful atmospheric conditions (high VPD and irradiance) combined with lower soil water availability. The highest T C was measured at mid-late afternoon (17:00 h) indicating a delay relative to the highest T air conditions. The basal part of the canopy (cluster zone) presented a temperature 1–2 °C higher than the upper part, whereas T S was on average 10–15 °C higher than T C. Variation in T S was coupled to sun radiation and T C correlated negatively with leaf water potential and stomatal conductance to water vapour. Our results suggest that T C can be used as a simple indicator of grapevine performance and as a parameter to feed grapevine growth models to estimate heat and water fluxes in irrigated vineyards. T S emerges as a thermal variable with potential use to manage heat and drought stress in vineyards. [ABSTRACT FROM AUTHOR]

• Patterns of plant trait responses to environmental gradients are still under debate. • For three species pairs trait changes were analysed along a precipitation gradient. • Trait values did not reflect replacement of congeneric species along the gradient. • Patterns in trait–abundance relationships varied between species and traits. • Environmental filtering did hardly affect populations' trait variability. Moisture availability is the main limiting factor of plant growth and biomass production in arid and semi-arid grasslands. The question whether plant responses to changing precipitation are species-specific, or change over entire plant communities is still controversial. Our study focussed on intraspecific changes in the plant traits canopy height, plant width, specific leaf area, chlorophyll fluorescence, performance index, and individual biomass of three congeneric species pairs with changing precipitation in Mongolian rangelands, covering a gradient from the desert to the forest steppes. Using this trait data set, we focussed on three questions: (i) Is the replacement of congeneric species along an environmental gradient also reflected in their trait values? (ii) Can intraspecific trait variation patterns be derived from patterns in species abundances, i.e., are trait values optimal where species are most abundant? (iii) Is the within-population trait variability lowest in populations growing under very dry conditions, i.e., under highest environmental stress, caused by stronger filtering? We tested the responses of the six traits to changing precipitation according to species' identity and abundance. We found unimodal relationships between most of the species' traits and precipitation, and strong associations between species abundances and trait values, but not for all investigated species. Trait variability did not significantly differ between populations from different positions along the precipitation gradient. Our results highlight that species show multiple or even opposite trait responses along the precipitation gradient. It thus remains challenging to predict how plant distributions will shift under changing environmental conditions based on their trait composition. [ABSTRACT FROM AUTHOR]

Highlights • We developed an algorithm to estimate evapotranspiration based solely on satellite data. • Our model is able to track the seasonal changes in the flux tower observations. • The errors in the model ET output were lower than the MODIS ET product. • The modeled and observed ET strong relationship implies that our model has the potential to be applied to different ecosystems. Abstract We introduce a different operational approach to estimate 8-day average daily evapotranspiration (ET) using both routinely available data and the Penman-Monteith (P-M) equation for canopy transpiration and evaporation of intercepted water and Priestley and Taylor for soil evaporation. Our algorithm considered the environmental constraints on canopy resistance and ET by (1) including vapor pressure deficit (VPD), incoming solar radiation, soil moisture, and temperature constraints on stomatal conductance; (2) using leaf area index (LAI) to scale from the leaf to canopy conductance; and (3) calculating canopy resistance as a function of environmental variables such as net radiation and VPD. Remote sensing data from the Moderate Resolution Spectroradiometer (MODIS) and satellite soil moisture data were used to derive the ET model. The algorithm was calibrated and evaluated using measured ET data from 20 AmeriFlux Eddy covariance flux sites for the period of 2003–2012. We found good agreements between our 8-day ET estimates and observations with mean absolute error (MAE) ranges from 0.17 mm/day to 0.94 mm/day compared with MAE ranging from 0.28 mm/day to 1.50 mm/day for MODIS ET. Compared to MODIS ET, our proposed algorithm has higher correlations and higher Willmott's index of agreement with observations for the majority of the Ameriflux sites. The strong relationship between the model estimated ET and the flux tower observations implies that our model has the potential to be applied to different ecosystems and at different temporal scales. [ABSTRACT FROM AUTHOR]

Abstract A comprehensive understanding of field ammonia (NH 3) emissions and canopy ammonia fluxes in agriculture is beneficial for controlling ammonia pollution and achieving cleaner production. However, there is little consensus about ammonia emissions and fluxes in field conditions due to a lack of simple methods suitable for measuring field ammonia emissions and canopy ammonia fluxes. The study aimed to determine the feasibility of using portable ammonia detector (PAD) method for detecting ammonia emissions in rice and wheat fields, and elucidate related factors affecting ammonia emissions and fluxes. Four chamber methods were compared, i.e., closed static chamber (CSC), semi-open static chamber (SSC), dynamic flow-through chamber (DFC), and PAD method. Field ammonia emissions and canopy ammonia fluxes were determined using PAD method during two rice (2016 and 2017) and two wheat growing seasons (2016–2017 and 2017–2018). The contributions of soil ammonium (NH 4 +) concentration, soil temperature, and leaf area index to ammonia emissions and fluxes were assessed. The results showed that the PAD method was suitable for monitoring ammonia in field conditions, due to its great precision, accuracy, and sensitivity. During 2016, 2017 rice growing seasons, cumulative ammonia emissions from field surface was 12.31 and 13.48 kg N ha−1, cumulative ammonia fluxes in canopy was −0.340 and −0.379 kg N ha−1, and cumulative ammonia emissions above canopy was 11.97 and 13.10 kg N ha−1, respectively. During 2016–2017 and 2017–2018 wheat growing seasons, cumulative ammonia emissions from field surface was 9.71 and 9.29 kg N ha−1, cumulative ammonia fluxes in canopy was −0.506 and −0.423 kg N ha−1, and cumulative ammonia emissions above canopy was 9.20 and 8.87 kg N ha−1, respectively. Ammonia emissions were highly dependent on soil ammonium concentration. Greater ammonia emissions from field surface tended to increase net ammonia absorption by canopy. Overall, the PAD method is a promising method for measuring field ammonia emission and canopy ammonia flux in agriculture; ammonia emission from rice fields was greater than that from wheat fields, but net ammonia absorption by wheat canopy was greater than that by rice canopy. Highlights • Four chamber methods for measuring ammonia (NH 3) were compared. • Portable ammonia detector method is suitable for assessing NH 3 emissions in fields. • Field NH 3 emissions and canopy NH 3 fluxes in rice and wheat fields were compared. • Greater NH 3 emissions from field surface increased net NH 3 absorption by canopy. • Net NH 3 absorption by wheat canopy was greater than that by rice canopy. [ABSTRACT FROM AUTHOR]

Abstract The thermal domain (TIR; 2.5–15 μm) delivers unique measurements of plant characteristics that are not possible in other parts of the electromagnetic spectrum. However, these TIR measurements have largely been restricted to laboratory leaf level or coarse spatial resolutions due to the lack of suitable data from airborne and spaceborne instruments. The airborne Hyperspectral Thermal Emission Spectrometer (HyTES) provides an opportunity to retrieve high spectral resolution emissivity and land surface temperature (LST) that can be exploited for canopy level vegetation research. This study is a high spatial resolution analysis of plant species' emissivity and LST using HyTES imagery acquired in the Huntington Botanical Gardens on 2014 July 5 and 2016 Jan 25. Leaf and canopy emissivity variation was identified among 24 plant species and used to determine leaf to canopy scaling capabilities. HyTES LST patterns among species and dates were quantified and correlated to LiDAR derived tree canopy attributes. At the leaf scale, one third of the species showed distinct spectral separation from other species. However, at the canopy scale most species were not spectrally separable. Random forest classification demonstrates the high level of confusion between species with overall accuracies <40%. LST data, derived from TIR measurements, showed that species exhibited significantly different distributions between dates and species. These distributions were largely explained by canopy structure (e.g. tree height and canopy density) and composition of neighboring pixels (e.g. presence of pavement versus trees). While species do not exhibit unique emissivity signatures at the canopy level, the LST variation among species provides a stronger understanding of LST variability in coarser resolution TIR imagery. This study represents the analysis of vegetation characteristics using the NASA's HyTES TIR sensor, opening the door for future remote sensing vegetation studies that include using the recently launched ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission. Highlights • Used HyTES to retrieve canopy high spectral emissivity and temperature. • One third of species showed distinct spectral separation with leaf emissivity. • The majority of species were not spectrally separable with canopy emissivity. • Canopy temperature was significantly different between dates and species. • Temperature patterns linked to canopy structure and neighbors derived from LiDAR. [ABSTRACT FROM AUTHOR]

Highlights • AquaCrop simulated soybean canopy cover, growth and yield reasonably well under dryland conditions. • Eddy covariance residual ET was comparable to modelled ET but was under-estimated for some growth stages. • Single crop coefficient values derived from AquaCrop ET compared well with those derived from eddy covariance residual ET. Abstract Simpler crop models simulating evaporation are needed to provide information to farmers, policy makers and decision makers on how to maximise crop yield responses to water. This is becoming important as the frequency and severity of droughts in South Africa is increasing. In this regard, prediction of yield, determination of water productivity and total evaporation (ET) are increasingly becoming essential in water resource management. The overall objective of the study was to compare the FAO AquaCrop daily model output of ET to the residual ET for non-stressed dryland soybean in a sub-humid climate. Energy balance residual ET estimates using an eddy covariance (EC) system and modelled ET using AquaCrop obtained from Glycine max (L.) Merrill grown in the midlands of KwaZulu-Natal, South Africa during the 2012/13 growing season are compared. The modelled and observed yield showed good agreement, while the residual ET was 21.6% less than the modelled. The energy balance closure computed using the daily sums of sensible heat and latent energy fluxes against daily available energy flux for unstable atmospheric conditions was 0.77. A closure of 0.99 was achieved when the EC latent energy flux was replaced with residual latent energy flux. A good fit between the modelled and observed percentage green canopy cover was observed (slope = 0.86, intercept = 15.46%, root mean square error = 10.50% and R2 = 0.83). Season-long daily residual ET values were consistently low for most of the growth stages compared to the modelled, except for the maturity stage. However, the residual ET comparisons with the AquaCrop model improved after gap-filling was applied to discarded data and for when the EC system failed. [ABSTRACT FROM AUTHOR]

Abstract In this study, we revised a two source energy balance model (G c -TSEB) that is based on canopy conductance and soil moisture in evapotranspiration (ET) estimation. We estimate soil evaporation (E) using the complementary concept and soil surface temperature, therefore, the revised G c -TSEB requires no soil moisture as input. We tested G c -TSEB at 10 flux sites under various land cover and climate conditions. The flux-calibrated G c -TSEB performed well in ET predictions, with determinant coefficients (R2) larger than 0.9 at most of the sites. The modeled transpiration was highly correlated with the Gross Primary Production, indicating the usefulness of the model in ET partitioning. More importantly, G c -TSEB can be calibrated against the land surface temperature (LST), which is operationally available using remote sensing technique. Overall, daily ET that was predicted by the LST-calibrated G c -TSEB generally matched the trends of the ET measurements at most of the sites, and R2 range from 0.63 to 0.93, with a median of 0.80, at all sites. Transpiration estimation was highly consistent with the simulations from the flux-calibrated model. Moreover, in vegetated surfaces, soil evaporation was estimated reasonably well using the LST-calibrated G c -TSEB. However, positive biases are prevalent when vegetated fraction is smaller than 0.2, especially in cold regions because of the dramatic differences in evaporation process between summer and winter. To improve model performances, calibrating G c -TSEB model in separated periods and using prior knowledge as constraints proved to be useful. Highlights • A two-source ET model is revised and evaluated under various climate conditions • Soil surface temperature instead of soil moisture is used to model soil evaporation • The model can be calibrated by remotely sensed LST [ABSTRACT FROM AUTHOR]

Abstract Rational design and management of the crop strips structure within fruit orchards are essential to make use of the economic and ecological advantages of intercropping but avoid the negative effects of resource competition on the fruit production. A better understanding of the light transmission processes could provide basis for quantifying resource competition and growth dynamics in the agroforestry system. Modeling work was combined with field experiment in this study to investigate light transmission in an apple tree (Malus pumila M.) and cocksfoot (Dactylis glomerata L.) intercropping system. The experiment was conducted in 2016 and 2017 in a plantation of apple at a spacing of 4 m × 4 m on the Loess Plateau of China. Three floor managing patterns were applied: clean tillage (CT), 2.4-meter-wide cocksfoot strips set up between tree rows that harvested more frequently to maintain a low coverage (LC), and cocksfoot strips with a greater coverage (GC). The light model simulates light transmission in the tree crown with a geometrical model that considering the canopy spatial heterogeneity, and describes light extinction in the crop strips with a strip-path radiation transmission model which is suitable for strip-path canopy structures. Results showed that the model well predicted fraction of incident light over and transmitted through the cocksfoot strips with determination coefficient of 0.707 and 0.892 respectively and root mean square error of 0.096 and 0.037. Averaged over the two seasons, light interception by cocksfoot were 439.1 and 504.7 MJ m−2 in LC and GC respectively, accounted for 23.1% and 26.5% of the total incoming light. Light use efficiency of cocksfoot in LC was far greater than that in the GC in both seasons. Planting cocksfoot showed no significant adverse effects on apple production, 6.32 and 5.67 t ha−1 additional dry forage were produced in the LC and GC plots respectively in 2016, the production were only 3.02 and 2.07 t ha−1 in 2017 as limited by water availability. Simulations with information on apple tree orchards of different age showed that seasonal mean fraction of light interception by cocksfoot under 3–10 years old apple trees varied from 0.41 to 0.29 for GC and from 0.36 to 0.25 for LC treatments, but the fraction became <0.15 for 15 years and older orchards. This study provides basics for quantifying light and other resource competition in tree and crop intercropping systems and gives insights into floor management for rain-fed apple orchards on the Loess Plateau area of China. Highlights • A model to calculate radiation capture by crop strips on orchard floor was developed. • 23.1% to 26.5% of the incoming PAR was intercepted by understorey cocksfoot strips. • Frequent cutting can improve RUE and biomass production of cocksfoot. • 2.07–6.57 t ha−1 grass dry biomass was harvested with no reduction in apple yield. [ABSTRACT FROM AUTHOR]

Highlights • The N-Jarvis model was constructed considering the effects of soil mineral nitrogen content on canopy resistance. • The N-Jarvis model is more accurate than the Jarvis model in predicting canopy resistance. • The transpiration estimated by the P–M model with the N-Jarvis model is more accurate than with the Jarvis model. Abstract Nitrogen partially regulates stomatal conductance and crop transpiration. We conducted greenhouse experiments into the effects of different nitrogen applications on the transpiration (T) of greenhouse pot-grown tomato plants with plastic film mulch in 2016–2017. We modeled the relationship between soil mineral nitrogen content and canopy resistance (r c) and incorporated our model into the Jarvis canopy resistance model to create the nitrogen modified Jarvis (N-Jarvis) model. We calculated transpiration under three nitrogen application levels, each with four irrigation programs using the Penman–Monteith (P–M) model with the Jarvis model and with the N-Jarvis model. Canopy resistance estimated by the Jarvis model differed greatly from observed canopy resistance, which was calculated by reformulating the P–M model and using the measured transpiration by sap flow system (T SF). The N-Jarvis model is more accurate than the Jarvis model in predicting r c. Similarly, the transpiration estimated by the P–M model with N-Jarvis model is more accurate than with the Jarvis model when compared to T SF , with higher values for the coefficient of determination and the modified efficiency coefficient, and lower values for the root mean square error and the Akaike information criterion. Including predictions from the N-Jarvis model improves the accuracy of the P–M model in estimating tomato transpiration under different nitrogen application levels. [ABSTRACT FROM AUTHOR]

Highlights • Delayed sowing can improve photosynthetic N use efficiency of winter wheat leaf. • High grain yield is maintained under late sowing. • Delayed sowing can optimize biomass and N allocation at plant and cell level. • Optimized CO2 diffusion capacity improves net photosynthetic rate at late sowing. • Late sowing promoted the expression of photosynthesis enzymes. Abstract Improvement in photosynthetic nitrogen (N)-use efficiency (PNUE , defined as the ratio between photosynthetic rate and N concentration) at the canopy level may maintain or even increase grain yield with reduced N input. Optimal N allocation maximises canopy carbon assimilation. A better understanding of the relationship between PNUE and N allocation may provide insight into the mechanism underlying canopy PNUE improvement. In this study, Tainong 18, a widely planted winter wheat cultivar, was sown at normal (8 October) and late dates (22 October) during two successive growing seasons. We investigated differences in PNUE and associated photosynthetic traits, as well as N allocation at the canopy, whole-plant, leaf, and cellular levels in normal-sown and late-sown wheat plants. At the canopy level, the N content per unit land area (g m–2) of all green organs, the flag leaf, and leaf 2 increased while those of the ear and leaf 3 remained constant, and those of leaf 4, stem, and sheath decreased. At the whole-plant level, with increased N content of individual plants, late-sown wheat plant allocated higher fractions of N at anthesis to the ear, flag leaf, and leaf 2. The proportion of N allocated to leaf 3 remained constant, and the fraction of N allocated to leaf 4, stem, and sheath decreased. At the leaf level, the leaf mass per area (LMA) and specific green leaf area nitrogen (SLN) of the upper leaves, including the flag leaf and leaf 2, increased; meanwhile, those of the lower leaves including leaves 3 and 4 remained unchanged or decreased. At the cellular level, larger proportions of N were allocated to ribulose-1, 5-bisphosphate carboxylase/oxygenase (Rubisco) in the upper leaves. Unchanged or reduced proportions of N were allocated to Rubisco in the lower leaves. Reduced fractions of N were allocated to the cell wall in all leaves. As a result, the maximum carboxylation rate (V cmax) of the upper leaves increased and that of the lower leaves remained constant or decreased. Both stomatal conductance (g s) and mesophyll conductance (g m) of all leaves increased. Improved V cmax coupled with enhanced CO 2 diffusion capacity led to an improved light-saturated net photosynthetic rate (P max) in the upper leaves. Enhanced CO 2 supply capacity accounted for the improvement in P max in lower leaves. The better performance of P max over SLN led to improved PNUE in upper leaves. The combination of enhanced P max with unchanged or decreased SLN resulted in improved PNUE in lower leaves. Canopy PNUE was improved because enhanced PNUE at the whole plant level compensated for reduced numbers of individual plants per unit area. In summary, optimised N allocation accounted for the improvement in canopy PNUE while maintaining a high grain yield. [ABSTRACT FROM AUTHOR]

Highlights • Integrated was a 3D light detection and ranging canopy mapping system. • Methods were developed to extract canopy attributes for apples trees and grapevines. • System was tested in mapping grapevine canopy changes due to direct root-zone deficit irrigation treatments. Abstract In this study, 3D light detection and ranging (LiDAR) and an inertial measurement unit (IMU) were integrated on a ground vehicle for mapping tree fruit crops. A custom interface was developed in robot operating system for synchronous communication with hardware modules and for continuous field data collection. Point cloud data processing methods were developed for reconstruction and estimation of canopy parameters including height, voxel grid and convex hull methods-based volume and gap fractions in the canopy. The system was tested in apple tree and grapevine canopies. Overall, the mobile 3D LiDAR mapping system provided realistic representation of the canopy compared to the manual methods. For apple trees, the manual canopy volume measurements were strongly correlated to volume derived from the mobile 3D LiDAR mapping system (Convex hull: r = 0.81, Voxel grid: r = 0.51). The voxel grid method adequately considered gaps in the canopy during volume estimation and performed better than the convex hull method. The system was also evaluated for estimating canopy growth in grapevines with different rates of subsurface irrigation treatments. Deficit irrigation treatments did not show any significant effect on the canopy growth due to a high moisture content in the soil, resulting from high winter snowpack prior to that particular season. Nonetheless, the 3D LiDAR mapping system was able to aid in visualization of the temporal changes in canopy growth during the growing season. Change in vine canopy volume for the treatments followed a similar trend to the area ratio estimated from normalized differential vegetation index images derived from small unmanned aerial system based multispectral imagery. Overall, the 3D LiDAR based canopy mapping system and pertinent data mining algorithms can be the useful tool to the growers in rapid assessment of perennial fruit crop canopies for real-time management decision making. [ABSTRACT FROM AUTHOR]