scholarly journals DIEBACK, LEAF AREA INDEX AND YIELD OF YOUNG EUCALYPT CLONES PLANTATION IN THE BRAZILIAN SAVANNAH REGION

2018 ◽  
Vol 41 (3) ◽  
Author(s):  
Geraldo Gonçalves dos Reis ◽  
Frederico de Freitas Alves ◽  
Maria das Graças Ferreira Reis ◽  
Felippe Coelho de Souza ◽  
Diogo Sena Baiero ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Water Deficit ◽  
Tree Height ◽  
Low Fertility ◽  
Limiting Factor ◽  
Soil Water Deficit ◽  
Area Index ◽  
Brazilian Savannah

ABSTRACT Eucalypt has been widely planted in Brazil, in the savannah region, which is characterized by high soil water deficit and low fertility. Dieback, leaf area index (LAI) and yield of young stands of 16 eucalypt clones were studied in Vazante, MG, Brazil (17º36’09"S and 46º 42’02"W). It was determined for each clone: a) the proportion of the tree height with dieback symptoms in the apical terminal (HWD%) and the proportion of trees with dieback (NWD%), at 13 months (end of the first dry season); b) the LAI at 13 and 21 months, and c) the yield at the age of 13, 19 and 25 months. HWD% reached 5-9%, and NWD%, 50-80%, for the five most susceptible clones, when the soil water deficit reached 508 mm in the year. LAI varied from 0.61 to 1.56, at 13 months, and from 2.31 to 3.48 at 21 months, presenting inverse relationship with dieback. The least susceptible clones to dieback achieved the highest yield up to 25 months of age. There was interaction between dieback and fertilizer levels only for three clones. There was a positive correlation (p < 0.001) between the LAI at the age of 13 months and the periodic monthly increment from 0 to 11 months, and from 11 to 19 months. The difference in dieback susceptibility among clones allows the selection of genotypes for regions where the soil water deficit is a major limiting factor.

Fast determination of light availability and leaf area index in tropical forests

2002 ◽  
Vol 18 (2) ◽  
pp. 295-302 ◽  
Author(s):  
Laurent Cournac ◽  
Marc-Antoine Dubois ◽  
Jérôme Chave ◽  
Bernard Riéra
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Optical Sensors ◽  
Light Availability ◽  
Tree Height ◽  
Light Transmittance ◽  
Limiting Factor ◽  
Area Index ◽  
Gap Fraction ◽  
Direct Measurements

An important property of plant communities is the Leaf Area Index (LAI), which is the vertically integrated surface of leaves per unit of ground area. Leaves are the primary sites of photosynthesis and transpiration, thus the LAI, which conditions the light interception by the canopy, is directly related to carbon and water exchange with the atmosphere at the stand scale (McNaughton & Jarvis 1983). LAI also has an impact on tree growth through the interception of light. Light availability below canopies is the principal limiting factor of tree recruitment and growth in forests (Denslow et al. 1990). Several methodologies have been used for measuring LAI in the field. These can be classiffed in four categories (Marshall & Waring 1986): (1) direct measurements by litterfall collection or destructive sampling, (2) allometric correlations with variables such as tree height or tree diameter, (3) gap-fraction assessment (e.g. with hemispherical photographs), (4) measurement of light transmittance with optical sensors.

A simulation model of kenaf for assisting fibre industry planning in northern Australia. III. Model description and validation

1992 ◽  
Vol 43 (7) ◽  
pp. 1527 ◽  
Author(s):  
PS Carberry ◽  
RC Muchow
Keyword(s):  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Leaf Growth ◽  
Biomass Accumulation ◽  
Fibre Industry ◽  
Model Description ◽  
Northern Australia ◽  
Area Index ◽  
Extractable Soil

NTKENAF (Version 1.1) is a computer model which simulates the growth of kenaf (Hibiscus cannabinus L.) under rainfed conditions in tropical Australia. In daily time-steps, the model simulates the phenology, leaf area development, biomass accumulation and partitioning, soil water balance and dry matter yields of kenaf plants based on climatic and management inputs. The model assumes adequate nutrition and no effect of pests and diseases. The model uses daily maximum and minimum temperature, solar radiation and rainfall. The duration from sowing to flowering is predicted using temperature and photoperiod. Leaf growth is described as a function of node production (as determined by temperature), leaf area per node and leaf area senescence. Potential daily biomass is predicted from leaf area index, the light extinction coefficient and radiation use efficiency, and partitioned to the economic stem yield. Soil evaporation is predicted using a two-stage evaporation model, and plant transpiration is predicted from the daily biomass accumulation, a transpiration efficiency coefficient and predicted daily vapour pressure deficit. Plant extractable soil water is dependent on the available soil water range for each depth increment, the extraction front velocity, and the extent of water extraction at each depth. Daily transpiration and leaf growth are decreased below potential values once the fraction of available soil water declines below a threshold value. NTKENAF V1.1 has been validated against observed data from kenaf experiments conducted at two sites (lat. 13�48'S. and 14�28'S.) in northern Australia. The predictive accuracy of the model was good over a range in above-ground biomass up to 25 000 kg ha-1 (n = 40, r2 = 0.94, root mean square deviation = 1716 kg ha-1). Validations were also undertaken for predictions of the core and bark stem components, leaf area index and plant extractable soil water contents. The development of NTKENAF has provided a tool which can greatly aid assessment of the feasibility of a fibre industry based on kenaf in northern Australia.

Validate the DSSAT Model on Winter Wheat under Conservation Tillage Treatments in the West Henan, China

2014 ◽  
Vol 522-524 ◽  
pp. 699-708 ◽  
Author(s):  
Xiang Hui Lu ◽  
Hua Bai ◽  
Hui Ying Liu
Keyword(s):  
Water Balance ◽  
Winter Wheat ◽  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Conservation Agriculture ◽  
Soil Water Balance ◽  
The West ◽  
Area Index ◽  
Straw Mulching

Crop growth simulation models can be useful in evaluating the impacts of different tillage and residue management operations on the changes in land productivity and soil-water balance components. They offer a potentially valuable set of tools for examining questions related to performance of conservation agriculture. This can be both to improve our understanding or conceptualization of processes and to improve quantitative predictions for use by agronomists, growers, policy makers or others. We applied the new Decision Support System for Agro-technology Transfer (DSSAT) version 4.5, an improved crop growth simulation model, to three conservation agriculture treatments and one conventional tillage treatment data from a field-scale study in west Henan region of China to predict winter-wheat yield, leaf area index and soil-water balance. The sites average annual precipitation is 632mm and it had a winter wheat-fallow-winter wheat rotation. There winter wheat planting in October and harvesting in next year June. The model was calibrated using 2005-2006 winter-wheat crop data from field experiments of the four treatments. The treatments were: (1) decreased tillage (DT): mulching of 10-15cm height straw and one ploughing operation to 25cm depth on July 1st; (2) zero tillage (ZT): zero tillage with 35-40cm height straw mulching; (3) subsoiling (SS): 35-40cm height straw mulching and subsoil to 40cm depth on July 1st; (4) conventional tillage (CT): 10-15cm height straw mulching and two ploughing operations 20cm deep on July 1st and October 1st. The DSSAT satisfactorily simulated the four treatments variations in winter-wheat yield, leaf area index and soil-water balance. There was better agreement between observed and predicted yields (the error absolute values were less than 3.95% and the error mean absolute values were less than 2.78%). The mean value of root mean square errors (RMSE) for simulated leaf area index (LAI) and soil water storage were 0.41cm2·cm-2 and 0.08cm3·cm-3 for DT, ZT, SS and CT, treatment respectively. The predicted water use efficiency for the four treatments were 15.85, 15.40, 16.58 and 15.81kg·mm-1·ha-1, respectively. These values were close to the values calculated from field measured data (16.82, 14.44, 16.86 and 15.66kg·mm-1·ha-1, respectively). Although the analysis results show us that the DSSAT V4.5 is well suited for simulating winter-wheat growth in the West Henan region of China, these results are preliminary and based on only one year of experimental data and four treatments and further long-term analyses need to be carried out for improving the understanding of the conservation agriculture cropping systems in the west Henan region of China.

scholarly journals Carbon Storage of some Rubber Trees (Hevea brasiliensis) Clones in HEVECAM’s Plantations in South Cameroon

2021 ◽  
Author(s):  
Menoh A Ngon René ◽  
Tsoata Esaïe ◽  
Tsouga Manga Milie Lionelle ◽  
Owona Ndongo Pierre-André
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Carbon Storage ◽  
Rubber Tree ◽  
Tree Height ◽  
Allometric Equation ◽  
Morphological Parameters ◽  
Area Index ◽  
Significant Difference ◽  
Total Tree

The objective of this work was to estimate the quantity of carbon stored by four main clones of rubber tree cultivated in South Cameroon: GT 1, PB 217, PR 107 and RRIC 100. The forest inventory method was used to measure trees morphological parameters, the latter used to calculate carbon storage using the allometric equation of Wauters et al., (2008). The main morphological parameters measured were: leaf area index (LAI), circumference (C), diameter at breast height (DBH) and total tree height (h). Comparing the morphological parameters of clones two by two using a Dunn test, we observe significant differences in the circumference, the diameter and even very significant in the leaf area index, but not in the height. The clones GT 1, PR 107, PB 217, and RRIC 100 stored on average: 111.05 tC / ha, 150.18 tC / ha, 165.25 tC / ha, and 187.25 tC/ha respectively. A significant difference was established between the means of carbon storage of the clones GT 1 and PB 217 (p = 0.0488) on one hand and, that of the clones GT 1 and RRIC 100 (p = 0.0240), on the other hand. These results are an estimation of models, further research can be undertaken for exact measurements.

scholarly journals Rule-based analysis of throughfall kinetic energy to evaluate biotic and abiotic factor thresholds to mitigate erosive power

2016 ◽  
Vol 40 (3) ◽  
pp. 431-449 ◽  
Author(s):  
Philipp Goebes ◽  
Karsten Schmidt ◽  
Werner Härdtle ◽  
Steffen Seitz ◽  
Felix Stumpf ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Kinetic Energy ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Abiotic Factors ◽  
Tree Height ◽  
Abiotic Factor ◽  
Area Index ◽  
Biotic And Abiotic Factors ◽  
Optimal Set

Below vegetation, throughfall kinetic energy (TKE) is an important factor to express the potential of rainfall to detach soil particles and thus for predicting soil erosion rates. TKE is affected by many biotic (e.g. tree height, leaf area index) and abiotic (e.g. throughfall amount) factors because of changes in rain drop size and velocity. However, studies modelling TKE with a high number of those factors are lacking. This study presents a new approach to model TKE. We used 20 biotic and abiotic factors to evaluate thresholds of those factors that can mitigate TKE and thus decrease soil erosion. Using these thresholds, an optimal set of biotic and abiotic factors was identified to minimize TKE. The model approach combined recursive feature elimination, random forest (RF) variable importance and classification and regression trees (CARTs). TKE was determined using 1405 splash cup measurements during five rainfall events in a subtropical Chinese tree plantation with five-year-old trees in 2013. Our results showed that leaf area, tree height, leaf area index and crown area are the most prominent vegetation traits to model TKE. To reduce TKE, the optimal set of biotic and abiotic factors was a leaf area lower than 6700 mm2, a tree height lower than 290 cm combined with a crown base height lower than 60 cm, a leaf area index smaller than 1, more than 47 branches per tree and using single tree species neighbourhoods. Rainfall characteristics, such as amount and duration, further classified high or low TKE. These findings are important for the establishment of forest plantations that aim to minimize soil erosion in young succession stages using TKE modelling.

scholarly journals Environmental control on water vapour and energy exchanges over grasslands in semiarid region of Brazil

2015 ◽  
Vol 19 (1) ◽  
pp. 3-8 ◽  
Author(s):  
Patrícia S. de S. Gondim ◽  
José R. de S. Lima ◽  
Antonio C. D. Antonino ◽  
Claude Hammecker ◽  
Renan A. B. da Silva ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Water Vapour ◽  
Environmental Control ◽  
Abiotic Factors ◽  
Diurnal Variations ◽  
Energy Partitioning ◽  
Area Index ◽  
Seasonal And Diurnal Variations

A micrometeorological experiment was conducted over grasslands in a semi-arid region of north-eastern Brazil (São João, Pernambuco) from January to December 2011, using the Bowen ratio energy balance method, to improve the current understanding of energy partitioning and water vapour exchange over this ecosystem in this region. The objectives of the present study were to quantify the seasonal and diurnal variations in energy and water vapour exchanges over grasslands and understand the biotic and abiotic factors controlling the energy partitioning of this ecosystem. In the dry period, the low stored soil water limited the grass production and leaf area index, and as a consequence of these conditions, most of the annual net radiation (58%) was consumed in sensible heat flux. During the course of the study the evaporative fraction was linearly related to the leaf area index. The total annual evapotranspiration and its daily maximum were 543.8 mm and 3.14 mm d-1. The seasonal and diurnal variations in energy partitioning and evapotranspiration were controlled by soil water availability and leaf area index.

scholarly journals MERIS GPP/NPP product for Estonia: II. Complex meteorological limiting factor and optimum leaf area index / MERIS’e GPP/NPP tulem Eesti jaoks: II. Kompleksne meteoroloogiline piirangutegur ja optimaalne lehepinnaindeks

2014 ◽  
Vol 61 (1) ◽  
pp. 5-26
Author(s):  
Tiit Nilson ◽  
Mattias Rennel ◽  
Mait Lang
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Meteorological Data ◽  
Vegetation Period ◽  
Meteorological Conditions ◽  
Limiting Factors ◽  
Carbon Gain ◽  
Limiting Factor ◽  
Area Index ◽  
Seasonal Course

Abstract. The merits and possible problems of the light use efficiency-concept based GPP/NPP models applied together with satellite images and meteorological data to quantitatively understand the role of different meteorological factors in forest productivity are analysed. A concept of the complex meteorological limiting factor for plant productivity is introduced. The factor includes the effects of incoming photosynthetically active radiation as well as the temperature and water limiting factors. Climatologically averaged seasonal courses of the complex meteorological limiting factor derived from the records of two contrasting meteorological stations in Estonia - inland Tartu/Tõravere and coastal Sõrve - are shown. Leaf phenology, here described via the seasonal course of leaf area index (LAI), is interpreted as a possible means to maximise the carbon gain under particular meteorological conditions. The equations for the optimum seasonal course of LAI as derived from the NPP model are presented. As the daily adjustment of plant LAI to sudden changes in meteorological conditions is not possible, several approximate strategies for LAI seasonal course to maximise the yearly NPP of vegetation are analysed. Typical optimal courses of LAI show some seasonal asymmetry resulting in lower values of LAI in the second half of the vegetation period due to higher air temperatures and respiration costs. Knowledge about optimum LAI courses has a cognitive value, but can also be used as the simulated LAI courses in several models when the measured LAI values are not available. As the considered GPP/NPP models fail to adequately describe the local trends in forest and agricultural productivity in Estonia, the ways to improve the model’s performance are shown.

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