Leaf area index, canopy structure and photosynthesis of red clover (Trifolium pratense L.).

SUMMARYYield, critical LAI and apparent photosynthetic rate per unit leaf area were measured in four families selected from L. perenne S. 321. Differences in yield were attributable to differences in canopy structure producing differing critical LAI. The most productive family, which was 33% more productive than the base population, produced the largest critical LAI but had the lowest photosynthetic rate.

Download Full-text

Seasonal Variation in Canopy Aerodynamics and the Sensitivity of Transpiration Estimates to Wind Velocity in Broadleaved Deciduous Species

Journal of Hydrometeorology ◽

10.1175/jhm-d-16-0049.1 ◽

2016 ◽

Vol 17 (12) ◽

pp. 3029-3043 ◽

Cited By ~ 4

Author(s):

D. M. Barnard ◽

W. L. Bauerle

Keyword(s):

Seasonal Variation ◽

Wind Speed ◽

Leaf Area Index ◽

Leaf Area ◽

Canopy Structure ◽

Biophysical Model ◽

Structure Model ◽

Area Index ◽

Wind Speeds ◽

The Impact

Abstract Characterization of seasonal dynamics in wind speed attenuation within a plant canopy α is necessary for modeling leaf boundary layer conductance , canopy–atmosphere coupling Ω, and transpiration at multiple scales. The goals of this study were to characterize seasonal variation in α in four tree species with canopy wind profiles and a canopy-structure model, to quantify the impact of α on estimates of and Ω, and to determine the influence of variable wind speed on transpiration estimates from a biophysical model [Multi-Array Evaporation Stand Tree Radiation Assemblage (MAESTRA)]. Among species, α varied significantly with above-canopy wind speed and seasonal canopy development. At the mean above-canopy wind speed (1.5 m s−1), α could be predicted using a linear model with leaf area index as the input variable (coefficient of determination R2 = 0.78). However, the canopy-structure model yielded improved predictions (R2 = 0.92) by including canopy height and leaf width. By midseason, increasing canopy leaf area and α resulted in lower within-canopy wind speeds, a decrease in by 20%–50%, and a peak in Ω. Testing a discrete increase in wind speed (0.6–2.4 m s−1; seasonal mean plus/minus one standard deviation) had variable influence on transpiration estimates (from −30% to +20%), which correlated strongly with vapor pressure deficit (R2 = 0.83). Given the importance of α in accurate representation of , Ω, and transpiration, it is concluded that α needs to be given special attention in plant canopies that undergo substantial seasonal changes, especially densely foliated canopies (i.e., leaf area index >1) and in areas with lower native wind speeds (i.e., <2 m s−1).

Download Full-text

Daily leaf area index from photosynthetically active radiation for long term records of canopy structure and leaf phenology

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2021.108407 ◽

2021 ◽

Vol 304-305 ◽

pp. 108407

Author(s):

Cheryl Rogers ◽

Jing M. Chen ◽

Holly Croft ◽

Alemu Gonsamo ◽

Xiangzhong Luo ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Photosynthetically Active Radiation ◽

Canopy Structure ◽

Leaf Phenology ◽

Area Index ◽

Active Radiation

Download Full-text

Co-varying effects of vegetation structure and terrain attributes are responsible for soil respiration spatial patterns in a sandy forest–steppe transition zone

Web Ecology ◽

10.5194/we-21-95-2021 ◽

2021 ◽

Vol 21 (2) ◽

pp. 95-107

Author(s):

Gabriella Süle ◽

Szilvia Fóti ◽

László Körmöczi ◽

Dóra Petrás ◽

Levente Kardos ◽

...

Keyword(s):

Soil Respiration ◽

Leaf Area Index ◽

Leaf Area ◽

Vegetation Structure ◽

Canopy Structure ◽

Spatiotemporal Variability ◽

Ecosystem Functions ◽

Forest Steppe ◽

Area Index ◽

Terrain Features

Abstract. Forest–steppe habitats in central Hungary have contrasting canopy structure with strong influence on the spatiotemporal variability of ecosystem functions. Canopy differences also co-vary with terrain feature effects, hampering the detection of key drivers of carbon cycling in this threatened habitat. We carried out seasonal measurements of ecosystem functions (soil respiration and leaf area index), microclimate and soil variables as well as terrain features along transects for 3 years in poplar groves and the surrounding grasslands. We found that the terrain features and the canopy differences co-varyingly affected the abiotic and biotic factors of this habitat. Topography had an effect on the spatial distribution of soil organic carbon content. Canopy structure had a strong modifying effect through allocation patterns and microclimatic conditions, both affecting soil respiration rates. Due to the vegetation structure difference between the groves and grasslands, spatial functional diversity was observed. We found notably different conditions under the groves with high soil respiration, soil water content and leaf area index; in contrast, on the grasslands (especially in E–SE–S directions from the trees) soil temperature and vapor pressure deficit showed high values. Processes of aridification due to climate change threaten these habitats and may cause reduction in the amount and extent of forest patches and decrease in landscape diversity. Owing to habitat loss, reduction in carbon stock may occur, which in turn has a significant impact on the local and global carbon cycles.

Download Full-text

Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States

Biogeosciences ◽

10.5194/bg-13-239-2016 ◽

2016 ◽

Vol 13 (1) ◽

pp. 239-252 ◽

Cited By ~ 14

Author(s):

H. Tang ◽

S. Ganguly ◽

G. Zhang ◽

M. A. Hofton ◽

R. F. Nelson ◽

...

Keyword(s):

United States ◽

Leaf Area Index ◽

Leaf Area ◽

Canopy Structure ◽

The United States ◽

Data Set ◽

Area Index ◽

Continental Scale ◽

Comparison Results ◽

Waveform Lidar

Abstract. Leaf area index (LAI) and vertical foliage profile (VFP) are among the important canopy structural variables. Recent advances in lidar remote sensing technology have demonstrated the capability of accurately mapping LAI and VFP over large areas. The primary objective of this study was to derive and validate a LAI and VFP product over the contiguous United States (CONUS) using spaceborne waveform lidar data. This product was derived at the footprint level from the Geoscience Laser Altimeter System (GLAS) using a biophysical model. We validated GLAS-derived LAI and VFP across major forest biomes using airborne waveform lidar. The comparison results showed that GLAS retrievals of total LAI were generally accurate with little bias (r2 =  0.67, bias  =  −0.13, RMSE  =  0.75). The derivations of GLAS retrievals of VFP within layers were not as accurate overall (r2 =  0.36, bias  =  −0.04, RMSE  =  0.26), and these varied as a function of height, increasing from understory to overstory – 0 to 5 m layer: r2 =  0.04, bias  =  0.09, RMSE  =  0.31; 10 to 15 m layer: r2 =  0.53, bias  =  −0.08, RMSE  =  0.22; and 15 to 20 m layer: r2 =  0.66, bias  =  −0.05, RMSE  =  0.20. Significant relationships were also found between GLAS LAI products and different environmental factors, in particular elevation and annual precipitation. In summary, our results provide a unique insight into vertical canopy structure distribution across North American ecosystems. This data set is a first step towards a baseline of canopy structure needed for evaluating climate and land use induced forest changes at the continental scale in the future, and should help deepen our understanding of the role of vertical canopy structure in terrestrial ecosystem processes across varying scales.

Download Full-text

Effect of Leaf Occlusion on Leaf Area Index Inversion of Maize Using UAV–LiDAR Data

Remote Sensing ◽

10.3390/rs11091067 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1067 ◽

Cited By ~ 9

Author(s):

Lei Lei ◽

Chunxia Qiu ◽

Zhenhai Li ◽

Dong Han ◽

Liang Han ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Canopy Structure ◽

Laser Scanner ◽

Crop Canopy ◽

Voxel Size ◽

Area Index ◽

Point Distance ◽

Occlusion Effect ◽

The Relationship

The leaf area index (LAI) is a key parameter for describing crop canopy structure, and is of great importance for early nutrition diagnosis and breeding research. Light detection and ranging (LiDAR) is an active remote sensing technology that can detect the vertical distribution of a crop canopy. To quantitatively analyze the influence of the occlusion effect, three flights of multi-route high-density LiDAR dataset were acquired at two time points, using an Unmanned Aerial Vehicle (UAV)-mounted RIEGL VUX-1 laser scanner at an altitude of 15 m, to evaluate the validity of LAI estimation, in different layers, under different planting densities. The result revealed that normalized root-mean-square error (NRMSE) for the upper, middle, and lower layers were 10.8%, 12.4%, 42.8%, for 27,495 plants/ha, respectively. The relationship between the route direction and ridge direction was compared, and found that the direction of flight perpendicular to the maize planting ridge was better than that parallel to the maize planting ridge. The voxel-based method was used to invert the LAI, and we concluded that the optimal voxel size were concentrated on 0.040 m to 0.055 m, which was approximately 1.7 to 2.3 times of the average ground point distance. The detection of the occlusion effect in different layers under different planting densities, the relationship between the route and ridge directions, and the optimal voxel size could provide a guideline for UAV–LiDAR application in the crop canopy structure analysis.

Download Full-text

Comparison of LiDAR-based Models for True Leaf Area Index and Effective Leaf Area Index Estimation in Young Beech Forests

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun202068030559 ◽

2020 ◽

Vol 68 (3) ◽

pp. 559-566

Author(s):

Zdeněk Patočka ◽

Kateřina Novosadová ◽

Pavel Haninec ◽

Radek Pokorný ◽

Tomáš Mikita ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Regression Models ◽

Canopy Structure ◽

Optical Methods ◽

Distribution Model ◽

Area Index ◽

Index Estimation ◽

Effective Leaf Area Index

The leaf area index (LAI) is one of the most common leaf area and canopy structure quantifiers. Direct LAI measurement and determination of canopy characteristics in larger areas is unrealistic due to the large number of measurements required to create the distribution model. This study compares the regression models for the ALS-based calculation of LAI, where the effective leaf area index (eLAI) determined by optical methods and the LAI determined by the direct destructive method and developed by allometric equations were used as response variables. LiDAR metrics and the laser penetration index (LPI) were used as predictor variables. The regression models of LPI and eLAI dependency and the LiDAR metrics and eLAI dependency showed coefficients of determination (R2) of 0.75 and 0.92, respectively; the advantage of using LiDAR metrics for more accurate modelling is demonstrated. The model for true LAI estimation reached a R2 of 0.88.

Download Full-text

Canopy structure and topography effects on snow distribution at a catchment scale: Application of multivariate approaches

Journal of Hydrology and Hydromechanics ◽

10.1515/johh-2017-0027 ◽

2018 ◽

Vol 66 (1) ◽

pp. 43-54 ◽

Cited By ~ 9

Author(s):

Michal Jenicek ◽

Hana Pevna ◽

Ondrej Matejka

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Snow Depth ◽

Forest Canopy ◽

Snow Water Equivalent ◽

Canopy Structure ◽

Catchment Scale ◽

Area Index ◽

Forest Sites ◽

Hemispherical Photographs

Abstract The knowledge of snowpack distribution at a catchment scale is important to predict the snowmelt runoff. The objective of this study is to select and quantify the most important factors governing the snowpack distribution, with special interest in the role of different canopy structure. We applied a simple distributed sampling design with measurement of snow depth and snow water equivalent (SWE) at a catchment scale. We selected eleven predictors related to character of specific localities (such as elevation, slope orientation and leaf area index) and to winter meteorological conditions (such as irradiance, sum of positive air temperature and sum of new snow depth). The forest canopy structure was described using parameters calculated from hemispherical photographs. A degree-day approach was used to calculate melt factors. Principal component analysis, cluster analysis and Spearman rank correlation were applied to reduce the number of predictors and to analyze measured data. The SWE in forest sites was by 40% lower than in open areas, but this value depended on the canopy structure. The snow ablation in large openings was on average almost two times faster compared to forest sites. The snow ablation in the forest was by 18% faster after forest defoliation (due to the bark beetle). The results from multivariate analyses showed that the leaf area index was a better predictor to explain the SWE distribution during accumulation period, while irradiance was better predictor during snowmelt period. Despite some uncertainty, parameters derived from hemispherical photographs may replace measured incoming solar radiation if this meteorological variable is not available.

Download Full-text

Diversity of weed flora, selected biometric characteristics and yielding of Miscanthus spp. cultivated on light and heavy soil

Acta Agrobotanica ◽

10.5586/aa.2014.005 ◽

2014 ◽

Vol 67 (1) ◽

pp. 67-76

Author(s):

Beata Feledyn-Szewczyk ◽

Mariusz Matyka ◽

Mariola Staniak

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Canopy Structure ◽

Weather Conditions ◽

Weed Species ◽

Area Index ◽

State Research Institute ◽

Light Soil ◽

Heavy Soil ◽

Weed Flora

An important issue related to the cultivation of plants for energy purposes and poorly recognized so far is their impact on the environment, including biodiversity. The aim of the work was to assess weed flora diversity, canopy structure and yield of miscanthus cultivated on two types of soil: light and heavy.The study was carried out in the Experimental Station of the Institute of Soil Science and Plant Cultivation – State Research Institute at Osiny, Poland (N:51o28, E:22o4), on two fields of miscanthus (Miscanthus saccharflorus Robustus × M. sinensis– M-115) established in 2004, on light loamy sand and heavy loam. The analysis of weed flora was carried out in 2010 and 2011, in mid-June and mid-August, using two methods: the frame method and phytosociological relevés. Moreover, an analysis of green and dry matter yield of miscanthus, some biometric features and leaf area index (LAI) was carried out.The results showed that weed species diversity in a miscanthus crop was dependent on soil type. A larger number of weed species was found in miscanthus cultivated on heavy soil – 37 – in comparison with miscanthus cultivated on light soil – 33. Sorensen’s indicators showed low similarity between weed communities in miscanthus on light and heavy soil. Weed abundance and percentage of weed cover were lower in miscanthus cultivated on light soil. Weed density decreased during the vegetation season as a result of increasing competitiveness of the miscanthus canopy against weeds. Miscanthus yields were more dependent on weather conditions than the type of soil. Plant height and shoot diameter as well as leaf area index (LAI) were higher in miscanthus grown on heavy soil.

Download Full-text