The efficiency of nitrogen retranslocation from leaf biomass in Quercus ilex ecosystems

Vegetatio ◽  
1992 ◽  
Vol 99-100 (1) ◽  
pp. 225-237 ◽  
Author(s):  
A. Escudero ◽  
J. M. Arco ◽  
M. V. Garrido
Keyword(s):  
Quercus Ilex ◽  
Leaf Biomass ◽  
Nitrogen Retranslocation

Seasonal dynamics of night-time stem water recharge of Schima superba and its relation to tree architecture and leaf biomass

2013 ◽  
Vol 37 (3) ◽  
pp. 239-247 ◽  
Author(s):  
Xiao-Wei ZHAO ◽  
Ping ZHAO ◽  
Li-Wei ZHU ◽  
Guang-Yan NI ◽  
Xiao-Ping ZENG ◽  
...  
Keyword(s):  
Seasonal Dynamics ◽  
Tree Architecture ◽  
Leaf Biomass ◽  
Night Time ◽  
Schima Superba ◽  
Water Recharge ◽  
Stem Water

Biomass of understory species of Pinus halepensis Mill. forests in the Kassandra Peninsula - Chalkidiki

1998 ◽  
Vol 63 ◽  
Author(s):  
P. Smiris ◽  
F. Maris ◽  
K. Vitoris ◽  
N. Stamou ◽  
P. Ganatsas
Keyword(s):  
Moisture Content ◽  
Aboveground Biomass ◽  
Quercus Ilex ◽  
Pinus Halepensis ◽  
Biomass Estimation ◽  
Regression Equations ◽  
Pistacia Lentiscus ◽  
Quercus Coccifera ◽  
Understory Species ◽  
Cistus Incanus

This  study deals with the biomass estimation of the understory species of Pinus halepensis    forests in the Kassandra peninsula, Chalkidiki (North Greece). These  species are: Quercus    coccifera, Quercus ilex, Phillyrea media, Pistacia lentiscus, Arbutus  unedo, Erica arborea, Erica    manipuliflora, Smilax aspera, Cistus incanus, Cistus monspeliensis,  Fraxinus ornus. A sample of    30 shrubs per species was taken and the dry and fresh weights and the  moisture content of    every component of each species were measured, all of which were processed  for aboveground    biomass data. Then several regression equations were examined to determine  the key words.

scholarly journals Mass production of metal-doped graphene from the agriculture waste of Quercus ilex leaves for supercapacitors: inclusive DFT study

RSC Advances ◽  
2021 ◽  
Vol 11 (18) ◽  
pp. 10891-10901
Author(s):  
Gaurav Tatrari ◽  
Chetna Tewari ◽  
Manoj Karakoti ◽  
Mayank Pathak ◽  
Ritu Jangra ◽  
...  
Keyword(s):  
Effective Mass ◽  
Mass Production ◽  
Quercus Ilex ◽  
Cost Effective ◽  
Mass Scale ◽  
Graphene Sheets ◽  
Agriculture Waste ◽  
Doped Graphene ◽  
Metal Doped ◽  
Supercapacitor Applications

This work reports a facile, eco-friendly, and cost-effective mass-scale synthesis of metal-doped graphene sheets (MDGs) using agriculture waste of Quercus ilex leaves for supercapacitor applications.

scholarly journals Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices

2021 ◽  
Vol 13 (2) ◽  
pp. 233
Author(s):  
Ilja Vuorinne ◽  
Janne Heiskanen ◽  
Petri K. E. Pellikka
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Fibre Production ◽  
Additive Models ◽  
Leaf Biomass ◽  
Ground Vegetation ◽  
Perennial Crop ◽  
Red Edge ◽  
Agave Sisalana ◽  
Sentinel 2

Biomass is a principal variable in crop monitoring and management and in assessing carbon cycling. Remote sensing combined with field measurements can be used to estimate biomass over large areas. This study assessed leaf biomass of Agave sisalana (sisal), a perennial crop whose leaves are grown for fibre production in tropical and subtropical regions. Furthermore, the residue from fibre production can be used to produce bioenergy through anaerobic digestion. First, biomass was estimated for 58 field plots using an allometric approach. Then, Sentinel-2 multispectral satellite imagery was used to model biomass in an 8851-ha plantation in semi-arid south-eastern Kenya. Generalised Additive Models were employed to explore how well biomass was explained by various spectral vegetation indices (VIs). The highest performance (explained deviance = 76%, RMSE = 5.15 Mg ha−1) was achieved with ratio and normalised difference VIs based on the green (R560), red-edge (R740 and R783), and near-infrared (R865) spectral bands. Heterogeneity of ground vegetation and resulting background effects seemed to limit model performance. The best performing VI (R740/R783) was used to predict plantation biomass that ranged from 0 to 46.7 Mg ha−1 (mean biomass 10.6 Mg ha−1). The modelling showed that multispectral data are suitable for assessing sisal leaf biomass at the plantation level and in individual blocks. Although these results demonstrate the value of Sentinel-2 red-edge bands at 20-m resolution, the difference from the best model based on green and near-infrared bands at 10-m resolution was rather small.

scholarly journals Aboveground Biomass Allocation of Boreal Shrubs and Short-Stature Trees in Northwestern Canada

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 234
Author(s):  
Linda Flade ◽  
Christopher Hopkinson ◽  
Laura Chasmer
Keyword(s):  
Short Stature ◽  
Biomass Allocation ◽  
Aboveground Biomass ◽  
Leaf Biomass ◽  
Sectional Area ◽  
Plant Component ◽  
Cross Sectional ◽  
Allometric Models ◽  
Stem Biomass ◽  
Model Fits

In this follow-on study on aboveground biomass of shrubs and short-stature trees, we provide plant component aboveground biomass (herein ‘AGB’) as well as plant component AGB allometric models for five common boreal shrub and four common boreal short-stature tree genera/species. The analyzed plant components consist of stem, branch, and leaf organs. We found similar ratios of component biomass to total AGB for stems, branches, and leaves amongst shrubs and deciduous tree genera/species across the southern Northwest Territories, while the evergreen Picea genus differed in the biomass allocation to aboveground plant organs compared to the deciduous genera/species. Shrub component AGB allometric models were derived using the three-dimensional variable volume as predictor, determined as the sum of line-intercept cover, upper foliage width, and maximum height above ground. Tree component AGB was modeled using the cross-sectional area of the stem diameter as predictor variable, measured at 0.30 m along the stem length. For shrub component AGB, we achieved better model fits for stem biomass (60.33 g ≤ RMSE ≤ 163.59 g; 0.651 ≤ R2 ≤ 0.885) compared to leaf biomass (12.62 g ≤ RMSE ≤ 35.04 g; 0.380 ≤ R2 ≤ 0.735), as has been reported by others. For short-stature trees, leaf biomass predictions resulted in similar model fits (18.21 g ≤ RMSE ≤ 70.0 g; 0.702 ≤ R2 ≤ 0.882) compared to branch biomass (6.88 g ≤ RMSE ≤ 45.08 g; 0.736 ≤ R2 ≤ 0.923) and only slightly better model fits for stem biomass (30.87 g ≤ RMSE ≤ 11.72 g; 0.887 ≤ R2 ≤ 0.960), which suggests that leaf AGB of short-stature trees (<4.5 m) can be more accurately predicted using cross-sectional area as opposed to diameter at breast height for tall-stature trees. Our multi-species shrub and short-stature tree allometric models showed promising results for predicting plant component AGB, which can be utilized for remote sensing applications where plant functional types cannot always be distinguished. This study provides critical information on plant AGB allocation as well as component AGB modeling, required for understanding boreal AGB and aboveground carbon pools within the dynamic and rapidly changing Taiga Plains and Taiga Shield ecozones. In addition, the structural information and component AGB equations are important for integrating shrubs and short-stature tree AGB into carbon accounting strategies in order to improve our understanding of the rapidly changing boreal ecosystem function.

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