Canopy Density Research Articles

Macroclimate and canopy characteristics regulate forest understory microclimatic temperature offsets across China

AbstractForest microclimates can contrast substantially from the macroclimate outside forests. These microclimates regulate understory biodiversity and ecosystem functions. Studies have quantified the global patterns and driving factors of forest understory temperature offsets, but data from China were almost missing, making the global assessment incomplete. To fill this knowledge gap, we quantitatively synthesized 494 paired observations from China extracted from 91 publications to quantify mean (Tmean), maximum (Tmax) and minimum temperature offsets (Tmin). Results showed that (1) forest canopies significantly buffered understory Tmean and Tmax against macroclimatic temperature, with average offsets of 1.0 and 1.5°C, respectively, while understory Tmin offsets were not significantly different from zero; (2) forest type (broadleaved, mixed, vs. coniferous) and forest location (rural vs. urban) did not affect Tmean, Tmax or Tmin offsets, but climate zone and season showed significant impacts; and (3) macroclimatic temperature, wind speed, tree height and canopy density also impacted temperature offsets, although their effects varied among Tmean, Tmax and Tmin. Our results complement the global assessment of forest buffering capacity, and reiterate the necessity for incorporating microclimatic variability into future bioclimatic modelling of species demography and distributions.

Evaluating methods for measuring the leaf area index of encroaching shrubs in grasslands: From leaves to optical methods, 3-D scanning, and airborne observation

Leaf area index (LAI) is a key variable describing ecosystem structure and influencing the exchange of carbon, water, and energy. LAI is often evaluated with indirect methods. However, the accuracy of indirect measurements can vary with canopy structure and is not always generalizable across ecosystems. Previous research has characterized the accuracy of indirect methods for woody plants in forest ecosystems, but it is not well established for woody plants in open ecosystems—despite having large differences in canopy structure. In this study, we compared direct LAI measurements in clonal grassland shrub canopies to three indirect methods: a ceptometer, a handheld 3D scanner (processed using EXScanPro-3.6 software), and NEON's LAI product obtained from airborne hyperspectral imaging (derived from SAVI). To our knowledge, this is the first study to assess the accuracy of leaf area data in woody plants using a handheld 3D scanner and one of few studies assessing the accuracy of the National Ecological Observation Network's (NEON) Airborne Observation Platform—our source of airborne hyperspectral imaging. Data were collected in tallgrass prairie undergoing woody encroachment and three treatments: no herbivore disturbance, bison present, and simulated browsing. We found that direct LAI measurements of control and grazed C. drummondii canopies averaged ∼8.0. The ceptometer accurately estimated LAI in non-browsed canopies but overestimated LAI of browsed canopies by 38 %. One-sided leaf area of ramets measured with a handheld 3D scanner was strongly related to direct measurements (r2=0.86), but underestimated leaf area at greater values. LAI estimated from airborne spectral data underestimated LAI by 55 %. We conclude that a ceptometer was adequate for measuring LAI in dense shrub canopies when browsing was not present, the handheld 3D scanner was adequate for measuring leaf area of individual ramets, and the airborne spectral data was not suitable for estimating LAI of dense, grassland shrub canopies.

Sound propagation modeling in forests using the transmission line matrix method: Comparison with experimental in situ measurements

We present efforts to adapt the time-domain Transmission Line Matrix (TLM) method for modeling sound propagation in forests. It is relevant to professionals and researchers in environmental acoustics and to those interested in studying sound propagation in outdoor environments using numerical modeling techniques. The study aims to demonstrate the applicability of the method in complex media where sound waves undergo multiple reflections combined with ground effects during their propagation from a sound source to a receiver point. The TLM method is used to numerically model sound propagation in a 3D forest geometry generated based on a real tree distribution case. Data from an experimental campaign conducted in the rainforest of French Guyana are used as a reference. The results show an encouraging comparison between them and the in situ measurements, even if the hypotheses made to adapt the input data in the model were strong. We find that more measurement points and more specifications (ground impedance measurements, canopy density, etc.) about the experimental site are needed for further simulations, even if obtaining them presents technical difficulties.

Spray performance of flexible shield canopy opener and rotor wind integrated boom-sprayer application in soybean: effects on droplet deposition distribution.

Canopy density is high during mid-to-late soybean growth as a result of dense planting to improve yield, which seriously affects the control of pests and diseases. The dilemmas of difficult droplet penetration, nonuniform deposition, and droplet drift in field spraying remain challenges to the precise control of droplet distribution. This paper proposed a novel spraying application mode combined flexible shield canopy opener (FSCO) with rotor wind. The design of the key components of the new boom-spraying machine are described. The effects of the comparative spraying modes on spray deposition and droplet drift were studied in a field validation test to explore the feasibility of the novel spraying application. The study found that droplet coverage inside the soybean canopy was significantly affected by spraying mode, rotor wind speed and opener depth. The spraying operation that used the FSCO and rotor wind integrated mode was optimal for droplet uniformity on the adaxial and abaxial surfaces of the canopy leaves, with droplet uniformity indices of 0.966 and 0.934, respectively. At a rotor wind speed of 6 m s-1 and opener depth of 15 cm, the soybean canopy droplet coverage uniformity effect achieved the highest composite score of 0.937. The spraying mode used in this study improved droplet coverage uniformity by 82.30% and droplet anti-drift performance improved by 99.73% compared to the conventional boom-spraying mode. The study shows validity of the spraying mode combined FSCO with rotor wind to open dense canopy and improved droplet deposition uniformity in canopy and anti-drift performance. © 2024 Society of Chemical Industry.

A Theory of Maximum Entropy Production and Its Application to Microwave Remote Sensing—Simultaneous Retrieval of Soil Moisture and Vegetation Water Content

AbstractA theory of maximum entropy production (MEP) for electromagnetic wave propagation in dielectric materials is proposed and applied to simultaneously retrieving soil moisture (SM) and vegetation water content (VWC) from L‐band microwave brightness temperature (TB). One representation of the MEP principle states that a non‐equilibrium system corresponds to such a configuration of energy fluxes that minimizes a dissipation function under the constraint of energy conservation. The dissipation function for radiative transfer is formulated as an analogy of that for heat transfer. A new physical parameter, radiative inertia as an analogy of thermal inertia, is introduced to characterize radiative attenuation in dielectric media. The radiative inertia is parameterized in terms of the penetration depth of electromagnetic waves as a function of the complex dielectric constant. The MEP based retrieval algorithm predicts SM and VWC by minimizing the dissipation function under the constraint of the conservation of radiative energy. The retrievals of SM and VWC based on the MEP theory were validated against field observations in tropical and temperate forested regions of the Amazon and North America. The proof‐of‐concept analysis demonstrates the capability of the MEP algorithm for simultaneous retrievals of SM and VWC even for dense canopy (e.g., VWC > 5 kg m−2). The MEP method is a new theoretical framework for developing innovative remote sensing algorithms of the Earth system not limited to microwave observations.

Assessment of the Influence of Canopy Morphology on Leaf Area Density and Drag Coefficient by Means of Wind Tunnel Tests

This paper investigates the aerodynamic behavior of Basil (i.e., Ocimum basilicum) and Mentuccia (i.e., Clinopodium nepeta (L.) Kuntze), emphasizing the impact of plant structure on drag force. In this paper, the drag coefficient is assessed for the two crop species under various configurations, starting from the pressure drop measured through wind tunnel tests. The methodology involves an innovative use of image processing techniques to determine the leaf area density (LAD) for both Basil and Mentuccia. This approach allows for a precise differentiation between leaf areas and crop pores, crucial for accurate aerodynamic analysis. For Basil, LAD values ranged from 2.41 to 5.08 m2 · m−3, while Mentuccia displayed LAD values between 1.17 and 1.93 m2 · m−3, depending on the crop configuration. This study provides the relationship between plant morphology, canopy density, and drag coefficient, highlighting how these aspects are influenced by different wind velocities. These results are fundamental and necessary for the proper definition of crop behavior and the aerodynamic parameters in Computational Fluid Dynamics simulations. This knowledge is not only fundamental to the field of agricultural aerodynamics but also has significant implications for optimizing crop planting and arrangement, leading to more efficient farming practices and better understanding of plant–environment interactions.

Differential Analysis of Island Mountain Plant Community Characteristics: Ecological Sensitivity Perspectives

Island plants form the foundation for maintaining the ecology of an island. With the development of the island’s infrastructure, its ecosystems become damaged to a certain extent. A comprehensive understanding of island habitats and plant community characteristics is crucial for the development of island plant communities. This paper focuses on Pingtan Island in Fujian Province, China, as the research subject. Firstly, considering the significance of the wind environment on the island, this study constructed a wind environment model for the entire island of Pingtan to evaluate the ecological sensitivity from a macro perspective. Subsequently, 33 typical sample plots were selected based on different ecologically sensitive areas to conduct a micro-survey and the characterization of the montane plant communities on Pingtan Island. The findings reveal that (1) Pingtan Island’s ecological sensitivity is dominated by areas with ecological insensitivity (35.72%), moderate ecological sensitivity (33.99%), and high ecological sensitivity (18.02%). The soil texture, wind environment, and land use type are the primary influencing factors in the ecological sensitivity of Pingtan Island. (2) A total of 47 families, 82 genera, and 93 species of plants were investigated in a typical sample site in the mountainous area of Pingtan Island. The plant community structure was dominated by the successional stage of shrubs and herbs. There is some similarity in the plant composition of different ecologically sensitive areas. High ecologically sensitive areas have more species. As sensitivity increases, the dominant species in the three ecologically sensitive areas continue to undergo plant succession from Acacia confusa to Pinus thunbergii to Eurya emarginata. (3) Both community characteristics and species diversity vary between sensitive areas. The canopy density (CD) and the mean height of tree layer (MHTL) are higher in moderate ecologically sensitive areas. The mean tree diameter at breast height (MDBH) and the mean height of shrub layer (MHSL) are higher in high ecologically sensitive areas, while the mean height of herb layer (MHHL) is higher in extreme ecologically sensitive areas. Four diversity indicators increase with increasing sensitivity. In the moderate and high ecologically sensitive areas, Casuarina equisetifolia and A. confusa thrive, with Pinus thunbergii showing the opposite trend. However, species diversity is better characterized by A. confusa and P. thunbergii, with C. equisetifolia being the least diverse. Both the community characteristics and species diversity of P. thunbergii are optimal in extreme ecologically sensitive areas. In this study, the ecological sensitivity of Pingtan Island and the characteristics of montane plant communities were systematically analyzed to explore more stable montane plant communities on the island, aiming to provide a scientific basis and model reference for the ecological restoration and sustainable development of Pingtan Island and other islands.

Tree marking guidelines for northern hardwoods: a review of criteria for assessing vigour and quality

Recent studies have highlighted the need to update hardwood tree marking guides by changing the criteria used to assess vigour and quality, and thus the priority for deciding which trees to remove and retain during selection harvests. However, these studies have recommended different criteria, so it remains uncertain which should be included in the classification systems used to assess vigour and quality. We review these studies with the aim of reducing this uncertainty and identifying potential improvements to the provincial tree marking guides for northern hardwood forests in Canada, particularly the Ontario Tree Marking Guide. We review the differences in methodologies and summarize which defects have been shown to affect vigour and/or quality. The defects that should be used to assess vigour are canopy dieback, cankers, and fungi. Decaying wounds, wounds without decay, canopy density, and bark condition could also be used as secondary criteria for borderline cases in which the primary criteria are not decisive. The defects that should be used to assess quality are cankers, fungi, cracks, cavities, and decay (including black bark and wounds with moisture or soft wood). We present a new classification system based on these results and identify potential challenges to its implementation.

Canopy Structural Changes in Black Pine Trees Affected by Pine Processionary Moth Using Drone-Derived Data

Pine species are a key social and economic component in Mediterranean ecosystems, where insect defoliations can have far-reaching consequences. This study aims to quantify the impact of pine processionary moth (PPM) on canopy structures, examining its evolution over time at the individual tree level using high-density drone LiDAR-derived point clouds. Focusing on 33 individuals of black pine (Pinus nigra)—a species highly susceptible to PPM defoliation in the Mediterranean environment—bitemporal LiDAR scans were conducted to capture the onset and end of the major PPM feeding period in winter. Canopy crown delineation performed manually was compared with LiDAR-based methods. Canopy metrics from point clouds were computed for trees exhibiting contrasting levels of defoliation. The structural differences between non-defoliated and defoliated trees were assessed by employing parametric statistical comparisons, including analysis of variance along with post hoc tests. Our analysis aimed to distinguish structural changes resulting from PPM defoliation during the winter feeding period. Outcomes revealed substantive alterations in canopy cover, with an average reduction of 22.92% in the leaf area index for defoliated trees, accompanied by a significant increase in the number of returns in lower tree crown branches. Evident variations in canopy density were observed throughout the feeding period, enabling the identification of two to three change classes using LiDAR-derived canopy density metrics. Manual and LiDAR-based crown delineations exhibited minimal differences in computed canopy LiDAR metrics, showcasing the potential of LiDAR delineations for broader applications. PPM infestations induced noteworthy modifications in canopy morphology, affecting key structural parameters. Drone LiDAR data emerged as a comprehensive tool for quantifying these transformations. This study underscores the significance of remote sensing approaches in monitoring insect disturbances and their impacts on forest ecosystems.

Twenty years of irrigation acclimation is driven by denser canopies and not by plasticity in twig- and needle-level hydraulics in a Pinus sylvestris forest.

Climate change is predicted to increase atmospheric vapor pressure deficit, exacerbating soil drought, and thus enhancing tree evaporative demand and mortality. Yet, few studies have addressed the longer-term drought acclimation strategy of trees, particularly the importance of morphological versus hydraulic plasticity. Using a long-term (20 years) irrigation experiment in a natural forest, we investigated the acclimation of Scots pine (Pinus sylvestris) morpho-anatomical traits (stomatal anatomy and crown density) and hydraulic traits (leaf water potential, vulnerability to cavitation (Ψ50), specific hydraulic conductivity (Ks), and tree water deficit) to prolonged changes in soil moisture. We found that low water availability reduced twig water potential and increased tree water deficit during the growing season. Still, the trees showed limited adjustments in most branch-level hydraulic traits (Ψ50 and Ks) and needle anatomy. In contrast, trees acclimated to prolonged irrigation by increasing their crown density and hence the canopy water demand. This study demonstrates that despite substantial canopy adjustments, P. sylvestris may be vulnerable to extreme droughts because of limited adjustment potential in its hydraulic system. While sparser canopies reduce water demand, such shifts take decades to occur under chronic water deficits and might not mitigate short-term extreme drought events.

Forest and Natural Vegetation Cover Loss Over 2000 to 2020 in Sri Lanka; A Canopy Density Base Analysis

As one of the most important biodiversity hotspot, forest and natural vegetation areas play an essential role in the global ecosystem. It provides an uncountable number of ecosystem services while controlling the adverse impacts of climatic changes. With the expansion of civilization and fulfilling the infinite needs of man, forests and natural vegetation areas were destroyed, especially for agricultural purposes, development projects and timber. Due to this, the accelerated growth of deforestation and loss of natural vegetation can be observed in Sri Lanka in the past few decades. This study aimed to identify the forest and natural vegetation area loss from 2000 to 2020 with a particular focus on the Canopy Density (CD) of tree cover (>25%, >50% and >75%) in Sri Lanka. The satellite estimated data (30 mx30 m resolution) was downloaded from the 2000 to 2020 time period from the Global Forest Watch (GFW) online platform conducted by the World Resource Institute were used. Spatial and temporal changing patterns of the forest and natural vegetation areas have been identified using descriptive analysis methods (percentage) using MS Excel 2019 software. Results of the study found that in 2000, 61.38 percent of the country was covered with above 25% tree cover CD, while 53.86 percent and 39.76 percent of areas have covered with the tree cover CD above 50% and 75%, respectively. However, when it has come to 2020, these areas have decreased by 52.78 percent (>25% CD), 44.27 percent (>50% CD) and 28.65 percent (>75% CD). During this period, 8.6 percent (>25% CD), 9.59 percent (>50% CD) and 11.11 percent (>75% CD) of the forest and natural vegetation areas of Sri Lanka have lost the country. Throughout this period, 2016 can be identified as a year at risk for deforestation due to its annual deforestation rate (>8.8 percent). The total area of forest cover lost in 2016 is 17799 ha (>25% CD), 15583 ha (>50% CD) and 9865 ha (>75% CD). This is nearly 13 percent of forest cover loss for all three types of CD tree cover areas. According to the calculations of the forest areas that have >75% of CD, Anuradhapura (12.06%), Kurunegala (9.82%), and Monaragala (8.49%) districts are the areas that contributed to forest cover loss in the country during 2000 to 2020. According to the study, the annual deforestation rate is still very high. Hence should be needed to monitor and take action to stop deforestation and achieve sustainability in natural resource management in Sri Lanka. 
 Keywords: Deforestation, Canopy density, Tree cover, Natural resource management, Sri Lanka

Light Spectral Regimes under a Closed and Dense Canopy: Evidence from Mesua ferrea Trees for Human Comfort in Urban Landscape Planning


 
 
 Trees play an important role in urban landscape planning due to their multi-faceted functions including the provision of human comfort through shade and cooling and air pollution abatement. Mesua ferrea is the national tree of Sri Lanka with multi-colored leaves and pyramidal dense canopy architecture, which can be promoted to grow in roadside gardens and parks to gain more attraction and attention. It is important to know how different trees provide human comfort under the canopy. In the present study, we measured the transmittance spectra in the 318-885 nm range using a high-resolution spectroradiometer under the canopy of selected Mesua ferrea trees on bright sunny days. The change in shade casting on the ground during the day was modeled. In addition, the temperature, CO2, and relative humidity were also measured. The light transmittance through the canopy is reduced when moving from the outer edge of the canopy (1,142 μW.cm-2.nm1) to the trunk-base (0.82 μW.cm-2.nm-1) on the horizontal plane. It was obvious that the irradiance received closer to the base of the tree is not sufficient to support the understory plant growth. The irradiance levels of blue (B: 400-500 nm), red (R: 650-680 nm), and far-red (FR: 700-885 nm) components of the transmittance spectra under the canopy were also found significantly low compared to sunlight, with significantly altered R:B, R:FR and B:FR ratios. Importantly, a 14 fold cut down in the UV radiation (318-400 nm) under the canopy beyond half of the canopy diameter towards the trunk was also observed. Under the canopy, there was a temperature reduction of about 1° C on bright sunny days perhaps due to the reduced irradiance and the altered spectrum, and the reduced CO2 concentration (by 5%). We identified that the Mesua trees are suitable for human comfort, and thus can be recommended for roadside planting and for public parks in urban landscape planning.
 Keywords: Shade caste, Radiation spectrum, Mesua ferrea, Landscape planning, Urban planning
 
 

Study of summer microclimate and PM2.5 concentration in campus plant communities

Understanding the influencing effect of meteorological factors and air pollutants in the campus plot and the relationship between them is an important topic in the planning and design of campus green space. The changes of pollutant concentrations and meteorological factors in campus green space have certain patterns and specific influencing factors. In this study, we selected four sample plots in Nanjing Forestry University as the research objects, and collected various environmental parameters of the four plots on July 25, 2022. The results showed that the main influences of meteorological factors are the type of the underlying surface of the site, the degree of plant canopy density and the shade coverage area of the building. These factors mainly have a great influence on the value of temperature and humidity. The comprehensive influencing factors can be concluded that the cooling and humidifying effect of the site is ranked as follows: forest > lawn > asphalt road > concrete Square. The main influencing factors of pollutants are: illumination, wind speed, temperature and relative humidity. Among them, illumination and temperature have a negative correlation with PM2.5, wind speed and relative humidity have a positive correlation with PM2.5. Our research shows that the adjustment of campus green space factors can reduce the concentration of pollutants by changing the meteorological factors.

Quantifying water-use efficiency in plant canopies with varying leaf angle and density distribution.

Variation in architectural traits related to the spatial and angular distribution of leaf area can have considerable impacts on canopy-scale fluxes contributing to water-use efficiency (WUE). These architectural traits are frequent targets for crop improvement and for improving the understanding and predictions of net ecosystem carbon and water fluxes. A three-dimensional, leaf-resolving model along with a range of virtually generated hypothetical canopies were used to quantify interactions between canopy structure and WUE by examining its response to variation of leaf inclination independent of leaf azimuth, canopy heterogeneity, vegetation density and physiological parameters. Overall, increasing leaf area index (LAI), increasing the daily-averaged fraction of leaf area projected in the sun direction (Gavg) via the leaf inclination or azimuth distribution and increasing homogeneity had a similar effect on canopy-scale daily fluxes contributing to WUE. Increasing any of these parameters tended to increase daily light interception, increase daily net photosynthesis at low LAI and decrease it at high LAI, increase daily transpiration and decrease WUE. Isolated spherical crowns could decrease photosynthesis by ~60 % but increase daily WUE ≤130 % relative to a homogeneous canopy with equivalent leaf area density. There was no observed optimum in daily canopy WUE as LAI, leaf angle distribution or heterogeneity was varied. However, when the canopy was dense, a more vertical leaf angle distribution could increase both photosynthesis and WUE simultaneously. Variation in leaf angle and density distributions can have a substantial impact on canopy-level carbon and water fluxes, with potential trade-offs between the two. These traits might therefore be viable target traits for increasing or maintaining crop productivity while using less water, and for improvement of simplified models. Increasing canopy density or decreasing canopy heterogeneity increases the impact of leaf angle on WUE and its dependent processes.

Evaluating shallow mixing layer in partially-distributed canopy flows using DA-LES: bed friction, water shallowness and canopy denseness

ABSTRACT Shallow mixing layers developed in partially-distributed canopy flows (PCFs) are important for water conveyance, sediment transport and solute dispersion. In this paper, we address the response of shallow mixing layers in PCFs to several influential factors associated with bed friction, water shallowness and canopy denseness using depth-averaged Large Eddy Simulation (DA-LES). The results show that under certain canopy denseness, shallow mixing layers in PCFs display asymptotic behaviour for the variation of bed friction and water shallowness, consistent with classic shallow mixing layers. The canopy drag encourages the asymmetric growth of the inner and outer parts of the mixing layer, and this effect decreases when bed friction and water shallowness become pronounced. Characteristic velocity and length scales show similarity well delineated by exponential decay function regarding a stabilization efficiency parameter. The exception happens for the inner length scale of the mixing layer when only changing canopy density. We conclude that changing the canopy denseness can encourage the overall shift of mixing layer scaling regarding a broad range of bed friction and water shallowness. Furthermore, the bed friction parameter thresholding triggering flow instability of mixing layers in PCFs is found about 0.03, lower than 0.09 for splitter-plate induced mixing layers.

TreeDetector: Using Deep Learning for the Localization and Reconstruction of Urban Trees from High-Resolution Remote Sensing Images

There have been considerable efforts in generating tree crown maps from satellite images. However, tree localization in urban environments using satellite imagery remains a challenging task. One of the difficulties in complex urban tree detection tasks lies in the segmentation of dense tree crowns. Currently, methods based on semantic segmentation algorithms have made significant progress. We propose to split the tree localization problem into two parts, dense clusters and single trees, and combine the target detection method with a procedural generation method based on planting rules for the complex urban tree detection task, which improves the accuracy of single tree detection. Specifically, we propose a two-stage urban tree localization pipeline that leverages deep learning and planting strategy algorithms along with region discrimination methods. This approach ensures the precise localization of individual trees while also facilitating distribution inference within dense tree canopies. Additionally, our method estimates the radius and height of trees, which provides significant advantages for three-dimensional reconstruction tasks from remote sensing images. We compare our results with other existing methods, achieving an 82.3% accuracy in individual tree localization. This method can be seamlessly integrated with the three-dimensional reconstruction of urban trees. We visualized the three-dimensional reconstruction of urban trees generated by this method, which demonstrates the diversity of tree heights and provides a more realistic solution for tree distribution generation.

Coloring Outside the Lines: Exploiting Pigment-Protein Synergy for Far-Red Absorption in Plant Light-Harvesting Complexes.

Plants are designed to utilize visible light for photosynthesis. Expanding this light absorption toward the far-red could boost growth in low-light conditions and potentially increase crop productivity in dense canopies. A promising strategy is broadening the absorption of antenna complexes to the far-red. In this study, we investigated the capacity of the photosystem I antenna protein Lhca4 to incorporate far-red absorbing chlorophylls d and f and optimize their spectra. We demonstrate that these pigments can successfully bind to Lhca4, with the protein environment further red-shifting the chlorophyll d absorption, markedly extending the absorption range of this complex above 750 nm. Notably, chlorophyll d substitutes the canonical chlorophyll a red-forms, resulting in the most red-shifted emission observed in a plant light-harvesting complex. Using ultrafast spectroscopy, we show that the introduction of these novel chlorophylls does not interfere with the excited state decay or the energy equilibration processes within the complex. The results demonstrate the feasibility of engineering plant antennae to absorb deeper into the far-red region while preserving their functional and structural integrity, paving the way for innovative strategies to enhance photosynthesis.

Estimation of forest canopy density through Geospatial Technology-a case study on Sathyamangalam Forest, Erode District, Tamil Nadu.

The term forest canopy density (FCD) refers to one of the important criteria used to evaluate forest's ecological health. It plays a significant role in assessing the health of the forest and serves as a key landmark for potential management actions. The canopy coverage or crown cover is referred to the percentage of the forest floor that is covered by the vertical projection of tree crowns and necessary for monitoring the condition of the forest. The present study aims to estimate the forest canopy density (FCD) through Geospatial Techniques for Sathyamangalam Forest for the period between 2016 and 2022 with SENTINEL 2A satellite data. The weighted overlay analysis method was implemented with biophysical parameters, namely, Normalize Difference Vegetation Index (NDVI), Advanced Vegetation Index (AVI), Shadow Index (SI), and Soil Bareness Index (SBI) to analyze the state of the forest and its activity. The results observed significantly that the forest canopy with 158.60 km2 in 2016 which is increased to 190.37 km2 in 2018 (1.14%) then suddenly decreased to 134.85 km2 in 2020 (2.47%). The forest canopy has recovered some of its original area with 168.83 km2 through better environmental conditions during 2021-2022 (1.52%). Therefore, Geospatial Technology plays a significant role in estimating recent changes in regional forest.

A new interpolation method to resolve under-sampling of UAV-lidar snow depth observations in coniferous forests

Obtaining accurate snow depth estimates under dense canopies using airborne lidar (light detection and ranging) techniques is challenging due to the under-sampling of ground and snow surfaces. Existing interpolation techniques do not adequately address this problem and they often result in an overestimation of under-canopy snow depths. To address this issue, we introduce and evaluate a new interpolation method that incorporates intra-canopy snow depth variability to provide more accurate estimations at unsampled locations. Four interpolation methods were tested, considering systematic trends (landscape trend, canopy vs. gap trend, and intra-canopy trend) along with spatial interpolation of the residuals. Our results show that spatial interpolation methods without consideration of trends are sufficient to capture and reconstruct the small-scale variability of snow depths below a separation distance of 1 m between sampled and unsampled locations, (i.e., ground surface point density > 1 pt. m−2). However, beyond a separation distance of 2.5–3 m (point density < 0.33–0.40 pt. m−2), spatial interpolation based on proximity alone becomes unreliable because point separation becomes larger than the snow depth spatial correlation scale. Within these limiting distances, the method that incorporates trends along with spatial interpolation techniques can resolve the small-scale variability and thereby reduce the likely overestimation of snow depths under the canopy.

A planting optimization strategy to improve the carbon sink benefit for urban green-Taking the communal green of Nanjing Forestry University as an example

This research study identified the communal green at Nanjing Forestry University as an example and focused on the carbon sink benefits of the plant communities. Firstly, the representative plant communities in the communal green were investigated, and the parameters of the plant communities were established so that the carbon sink benefits of each plant community could be quantified. Secondly, by applying correlation analysis to study the influence degree of varied plant community factors on the benefits of carbon sink, it was found that the canopy closure, diameter class structure and tree density showed significant positive correlation; the correlation between community density and daily carbon sequestration per unit area was significant; the correlation between community density and carbon storage per unit area showed none significance; and the correlation between the proportion of trees and shrubs and the carbon sink benefits was of no significance. Thirdly, regression analysis was used to study the curve trends of the carbon sink benefits of the plant communities, from which it was concluded that increasing canopy density, average plant height, average crown width and tree density will improve carbon sink benefits. Increasing the average DBH would achieve positive effects for increasing daily carbon sequestration per unit area only at the early stage of the community growth. The plant community density showed positive effects on the increase of the daily carbon sequestration per unit area within a limited range. Since most regression formulas resulted in S-curves, certain threshold bottlenecks were found existed of improving the carbon sinks benefits by increasing the plant community factors. Finally, the characteristics of plant communities with high carbon sink benefit were summarized to provide theoretical references for forming a planting optimization strategy of urban green.