scholarly journals Understanding the Impact of Vertical Canopy Position on Leaf Spectra and Traits in an Evergreen Broadleaved Forest

2021 ◽  
Vol 13 (24) ◽  
pp. 5057
Author(s):  
Fangyuan Yu ◽  
Tawanda W. Gara ◽  
Juyu Lian ◽  
Wanhui Ye ◽  
Jian Shen ◽  
...  
Keyword(s):  
Spectral Properties ◽  
Leaf Traits ◽  
Leaf Nitrogen Content ◽  
Canopy Layer ◽  
Evergreen Broadleaved Forest ◽  
Leaf Trait ◽  
Equivalent Water Thickness ◽  
Leaf Chlorophyll ◽  
Canopy Position ◽  
The Impact

Little attention has been paid to the impact of vertical canopy position on the leaf spectral properties of tall trees, and few studies have explored the ability of leaf spectra to characterize the variation of leaf traits across different canopy positions. Using a tower crane, we collected leaf samples from three canopy layers (lower, middle, and upper) and measured eight leaf traits (equivalent water thickness, specific leaf area, leaf carbon content, leaf nitrogen content, leaf phosphorus content, leaf chlorophyll content, flavonoid, and nitrogen balance index) in a subtropical evergreen broadleaved forest. We evaluated the variability of leaf traits and leaf spectral properties, as well as the ability of leaf spectra to track the variation of leaf traits among three canopy layers for six species within the entire reflectance spectrum. The results showed that the eight leaf traits that were moderately or highly correlated with each other showed significant differences along the vertical canopy profile. The three canopy layers of leaf spectra showed contrasting patterns for light-demanding (Castanopsis chinensis, Castanopsis fissa, Schima superba, and Machilus chinensis) and shade-tolerant species (Cryptocarya chinensis and Cryptocarya concinna) along the vertical canopy profile. The spectra at the lower and upper canopy layers were more sensitive than the middle layer for tracking the variation of leaf chlorophyll and flavonoid content. Our results revealed that it is important to choose an appropriate canopy layer for the field sampling of tall trees, and we suggest that flavonoid is an important leaf trait that can be used for mapping and monitoring plant growth with hyperspectral remote sensing.

Interspecific covariation between stomatal density and other functional leaf traits in a local flora

Botany ◽  
2010 ◽  
Vol 88 (1) ◽  
pp. 30-38 ◽  
Author(s):  
Jessy Loranger ◽  
Bill Shipley
Keyword(s):  
Chlorophyll Content ◽  
Stomatal Density ◽  
Leaf Traits ◽  
Functional Ecology ◽  
Leaf Trait ◽  
Leaf Chlorophyll ◽  
Sun And Shade Leaves ◽  
Angiosperm Species ◽  
Sun And Shade ◽  
Shade Leaves

Despite the importance of stomata in leaf functioning, and despite the recent interest in interspecific leaf trait covariation in functional ecology, little is known about how stomatal density relates to other leaf traits in a broad interspecific context. This is especially important because stomatal density has been widely used to deduce temporal variation in atmospheric CO2 concentrations [CO2atm] from fossilized or herbarium leaves. We therefore measured stomatal density, specific leaf area (SLA) and its components, leaf thickness, and leaf chlorophyll content in both sun and shade leaves of 169 individuals from 52 angiosperm species in southwestern Quebec. Using mixed models, we show that stomatal density decreases allometrically with increasing SLA and chlorophyll content, and increases allometrically with increasing lamina thickness. The sun–shade contrast changes the intercepts, but not the slopes, of these relationships. It is important to take into consideration these relations when correlating stomatal density with [CO2], to avoid spurious interpretations.

scholarly journals Evaluation of P-Band SAR Tomography for Mapping Tropical Forest Vertical Backscatter and Tree Height

2021 ◽  
Vol 13 (8) ◽  
pp. 1485
Author(s):  
Naveen Ramachandran ◽  
Sassan Saatchi ◽  
Stefano Tebaldini ◽  
Mauro Mariotti d’Alessandro ◽  
Onkar Dikshit
Keyword(s):  
Tropical Forest ◽  
Vertical Profile ◽  
Mean Squared Error ◽  
Low Frequency ◽  
Tree Height ◽  
Canopy Layer ◽  
Local Maxima ◽  
Slope Correction ◽  
Compensation Approach ◽  
The Impact

Low-frequency tomographic synthetic aperture radar (TomoSAR) techniques provide an opportunity for quantifying the dynamics of dense tropical forest vertical structures. Here, we compare the performance of different TomoSAR processing, Back-projection (BP), Capon beamforming (CB), and MUltiple SIgnal Classification (MUSIC), and compensation techniques for estimating forest height (FH) and forest vertical profile from the backscattered echoes. The study also examines how polarimetric measurements in linear, compact, hybrid, and dual circular modes influence parameter estimation. The tomographic analysis was carried out using P-band data acquired over the Paracou study site in French Guiana, and the quantitative evaluation was performed using LiDAR-based canopy height measurements taken during the 2009 TropiSAR campaign. Our results show that the relative root mean squared error (RMSE) of height was less than 10%, with negligible systematic errors across the range, with Capon and MUSIC performing better for height estimates. Radiometric compensation, such as slope correction, does not improve tree height estimation. Further, we compare and analyze the impact of the compensation approach on forest vertical profiles and tomographic metrics and the integrated backscattered power. It is observed that radiometric compensation increases the backscatter values of the vertical profile with a slight shift in local maxima of the canopy layer for both the Capon and the MUSIC estimators. Our results suggest that applying the proper processing and compensation techniques on P-band TomoSAR observations from space will allow the monitoring of forest vertical structure and biomass dynamics.

scholarly journals Can Architectural Surfaces Capture Atmospheric Particulate Matter Like Trees? A Design Strategy to Mimic Leaf Traits

2021 ◽  
Vol 13 (14) ◽  
pp. 7637
Author(s):  
Taekyoung Lee ◽  
Jieun Cha ◽  
Sohyun Sung
Keyword(s):  
Leaf Traits ◽  
Design Strategy ◽  
Atmospheric Particulate Matter ◽  
Porous Surface ◽  
Base Surface ◽  
Different Types ◽  
Pm2.5 And Pm10 ◽  
Micro Morphology ◽  
The Impact ◽  
Cluster Pattern

Trees’ ability to capture atmospheric Particular Matter (PM) is related to morphological traits (shape, size, and micro-morphology) of the leaves. The objectives of this study were (1) to find out whether cluster pattern of the leaves is also a parameter that affects trees’ PM capturing performance and (2) to apply the cluster patterns of the leaves on architectural surfaces to confirm its impact on PM capturing performance. Two series of chamber experiments were designed to observe the impact of cluster patterns on PM capturing performance whilst other influential variables were controlled. First, we exposed synthetic leaf structures of different cluster patterns (a large and sparsely arranged cluster pattern and a small and densely arranged cluster pattern) to artificially generated PM in a chamber for 60 min and recorded the changing levels of PM2.5 and PM10 every minute. The results confirmed that the small and densely arranged cluster pattern has more significant effect on reducing PM2.5 and PM10 than the large and sparsely arranged cluster pattern. Secondly, we created three different types of architectural surfaces mimicking the cluster patterns of the leaves: a base surface, a folded surface, and a folded and porous surface. The surfaces were also exposed to artificially generated PM in the chamber and the levels of PM2.5 and PM10 were recorded. The results confirmed that the folded and porous surface has a more significant effect on reducing PM2.5 and PM10 than other surfaces. The study has confirmed that the PM capturing performance of architectural surfaces can be improved by mimicking cluster pattern of the leaves.

scholarly journals Many-impurity scattering on the surface of a topological insulator

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Luis Hernando ◽  
Yuriko Baba ◽  
Elena Díaz ◽  
Francisco Domínguez-Adame
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Topological Insulator ◽  
Disordered Systems ◽  
Spectral Properties ◽  
Random Distribution ◽  
Surface States ◽  
Impurity Scattering ◽  
Self Consistent ◽  
The Impact

AbstractWe theoretically address the impact of a random distribution of non-magnetic impurities on the electron states formed at the surface of a topological insulator. The interaction of electrons with the impurities is accounted for by a separable pseudo-potential method that allows us to obtain closed expressions for the density of states. Spectral properties of surface states are assessed by means of the Green’s function averaged over disorder realisations. For comparison purposes, the configurationally averaged Green’s function is calculated by means of two different self-consistent methods, namely the self-consistent Born approximation (SCBA) and the coherent potential approximation (CPA). The latter is often regarded as the best single-site theory for the study of the spectral properties of disordered systems. However, although a large number of works employ the SCBA for the analysis of many-impurity scattering on the surface of a topological insulator, CPA studies of the same problem are scarce in the literature. In this work, we find that the SCBA overestimates the impact of the random distribution of impurities on the spectral properties of surface states compared to the CPA predictions. The difference is more pronounced when increasing the magnitude of the disorder.

scholarly journals Leaf traits and gas exchange in saplings of native tree species in the Central Amazon

2010 ◽  
Vol 67 (6) ◽  
pp. 624-632 ◽  
Author(s):  
Keila Rego Mendes ◽  
Ricardo Antonio Marenco
Keyword(s):  
Gas Exchange ◽  
Nitrogen Content ◽  
Leaf Area ◽  
Tree Species ◽  
Leaf Traits ◽  
Leaf Nitrogen ◽  
Dry Season ◽  
Leaf Thickness ◽  
Rainfall Regime ◽  
Leaf Nitrogen Content

Global climate models predict changes on the length of the dry season in the Amazon which may affect tree physiology. The aims of this work were to determine the effect of the rainfall regime and fraction of sky visible (FSV) at the forest understory on leaf traits and gas exchange of ten rainforest tree species in the Central Amazon, Brazil. We also examined the relationship between specific leaf area (SLA), leaf thickness (LT), and leaf nitrogen content on photosynthetic parameters. Data were collected in January (rainy season) and August (dry season) of 2008. A diurnal pattern was observed for light saturated photosynthesis (Amax) and stomatal conductance (g s), and irrespective of species, Amax was lower in the dry season. However, no effect of the rainfall regime was observed on g s nor on the photosynthetic capacity (Apot, measured at saturating [CO2]). Apot and leaf thickness increased with FSV, the converse was true for the FSV-SLA relationship. Also, a positive relationship was observed between Apot per unit leaf area and leaf nitrogen content, and between Apot per unit mass and SLA. Although the rainfall regime only slightly affects soil moisture, photosynthetic traits seem to be responsive to rainfall-related environmental factors, which eventually lead to an effect on Amax. Finally, we report that little variation in FSV seems to affect leaf physiology (Apot) and leaf anatomy (leaf thickness).

scholarly journals Quantifying Leaf Trait Covariations and Their Relationships with Plant Adaptation Strategies along an Aridity Gradient

Biology ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1066
Author(s):  
Yanzheng Yang ◽  
Le Kang ◽  
Jun Zhao ◽  
Ning Qi ◽  
Ruonan Li ◽  
...  
Keyword(s):  
Dry Mass ◽  
Leaf Nitrogen ◽  
Adaptation Strategies ◽  
Leaf Nitrogen Content ◽  
Moisture Index ◽  
Multivariate Statistical ◽  
Plant Adaptation ◽  
Aridity Gradient ◽  
Leaf Trait ◽  
Leaf Economic Spectrum

A trait-based approach is an effective way to quantify plant adaptation strategies in response to changing environments. Single trait variations have been well depicted before; however, multi-trait covariations and their roles in shaping plant adaptation strategies along aridity gradients remain unclear. The purpose of this study was to reveal multi-trait covariation characteristics, their controls and their relevance to plant adaptation strategies. Using eight relevant plant functional traits and multivariate statistical approaches, we found the following: (1) the eight studied traits show evident covariation characteristics and could be grouped into four functional dimensions linked to plant strategies, namely energy balance, resource acquisition, resource investment and water use efficiency; (2) leaf area (LA) together with traits related to the leaf economic spectrum, including leaf nitrogen content per area (Narea), leaf nitrogen per mass (Nmass) and leaf dry mass per area (LMA), covaried along the aridity gradient (represented by the moisture index, MI) and dominated the trait–environmental change axis; (3) together, climate, soil and family can explain 50.4% of trait covariations; thus, vegetation succession along the aridity gradient cannot be neglected in trait covariations. Our findings provide novel perspectives toward a better understanding of plant adaptations to arid conditions and serve as a reference for vegetation restoration and management programs in arid regions.

scholarly journals Predicting Leaf Trait Variability as a Functional Descriptor of the Effect of Climate Change in Three Perennial Grasses

Diversity ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 233
Author(s):  
Marwa Hamdani ◽  
Khouloud Krichen ◽  
Mohamed Chaieb
Keyword(s):  
Functional Traits ◽  
Leaf Traits ◽  
Perennial Grasses ◽  
Arid Ecosystems ◽  
Leaf Trait ◽  
Grassland Species ◽  
Dimensional Shrinkage ◽  
Potential Link ◽  
Dehydration Avoidance ◽  
Stipa Lagascae

Aims of the study: The most important trends of the current climate variability is the scarcity of rains that affects arid ecosystems. The aim of this study was to explore the variability of leaf functional traits by which grassland species survive and resist drought and to investigate the potential link between resource use efficiency and water scarcity resistance strategies of species. Methods: Three grasses (Cenchrus ciliaris (C4), Stipa parviflora and Stipa lagascae (C3)) were established in a randomized block consisting of eleven replications. The seedlings were kept under increasing levels of water stress. In addition to their functional leaf traits, the rate of water loss and dimensional shrinkage were also measured. Key Results: Thicker and denser leaves, with higher dry matter contents, low specific leaf area and great capacity of water retention are considered among the grasses’ strategies of dehydration avoidance. Significant differences between the means of the functional traits were obtained. Furthermore, strong correlations among leaf traits were also detected (Spearman’s r exceeding 0.8). Conclusions: The results provide evidence that the studied grasses respond differently to drought by exhibiting a range of interspecific functional strategies that may ameliorate the resilience of grassland species communities under extreme drought events.

scholarly journals Leaf Photosynthetic Capacity of Sunlit and Shaded Mature Leaves in a Deciduous Forest

Forests ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 318
Author(s):  
Guangman Song ◽  
Quan Wang ◽  
Jia Jin
Keyword(s):  
Close Relationships ◽  
Deciduous Forest ◽  
Photosynthetic Capacity ◽  
Leaf Gas Exchange ◽  
Nitrogen Concentration ◽  
Leaf Traits ◽  
Leaf Nitrogen ◽  
Leaf Mass Per Area ◽  
Clear Understanding ◽  
Equivalent Water Thickness

A clear understanding of the dynamics of photosynthetic capacity is crucial for accurate modeling of ecosystem carbon uptake. However, such dynamical information is hardly available and has dramatically impeded our understanding of carbon cycles. Although tremendous efforts have been made in coupling the dynamic information of photosynthetic capacity into models, using “proxies” rooted from the close relationships between photosynthetic capacity and other available leaf parameters remains the popular selection. Unfortunately, no consensus has yet been reached on such “proxies”, leading them only applicable to limited cases. In this study, we aim to identify if there are close relationships between the photosynthetic capacity (represented by the maximum carboxylation rate, Vcmax) and leaf traits for mature broadleaves within a cold temperature deciduous forest. This is based on a long-term in situ dataset including leaf chlorophyll content (Chl), leaf nitrogen concentration (Narea, Nmass), leaf carbon concentration (Carea, Cmass), equivalent water thickness (EWT), leaf mass per area (LMA), and leaf gas exchange measurements from which Vcmax was derived, for both sunlit and shaded leaves during leaf mature periods from 2014 to 2019. The results show that the Vcmax values of sunlit and shaded leaves were relatively stable during these periods, and no statistically significant interannual variations occurred (p > 0.05). However, this is not applicable to specific species. Path analysis revealed that Narea was the major contributor to Vcmax for sunlit leaves (0.502), while LMA had the greatest direct relationship with Vcmax for shaded leaves (0.625). The LMA has further been confirmed as a primary proxy if no leaf type information is available. These findings provide a promising way to better understand photosynthesis and to predict carbon and water cycles in temperate deciduous forests.

scholarly journals Leaf Canopy Layers Affect Spectral Reflectance in Silver Birch

2019 ◽  
Vol 11 (24) ◽  
pp. 2884 ◽  
Author(s):  
Maya Deepak ◽  
Sarita Keski-Saari ◽  
Laure Fauch ◽  
Lars Granlund ◽  
Elina Oksanen ◽  
...  
Keyword(s):  
Principal Component ◽  
Common Garden ◽  
Dry Weight ◽  
Leaf Traits ◽  
Tree Canopy ◽  
Canopy Reflectance ◽  
Canopy Layer ◽  
Leaf Reflectance ◽  
Individual Trees ◽  
Reflectance Indices

The availability of light within the tree canopy affects various leaf traits and leaf reflectance. We determined the leaf reflectance variation from 400 nm to 2500 nm among three canopy layers and cardinal directions of three genetically identical cloned silver birches growing at the same common garden site. The variation in the canopy layer was evident in the principal component analysis (PCA), and the influential wavelengths responsible for variation were identified using the variable importance in projection (VIP) based on partial least squares discriminant analysis (PLS-DA). Leaf traits, such as chlorophyll, nitrogen, dry weight, and specific leaf area (SLA), also showed significant variation among the canopy layers. We found a shift in the red edge inflection point (REIP) for the canopy layers. The canopy layers contribute to the variability in the reflectance indices. We conclude that the largest variation was among the canopy layers, whereas the differences among individual trees to the leaf reflectance were relatively small. This implies that within-tree variation due to the canopy layer should be taken into account in the estimation of intraspecific variation in the canopy reflectance.

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