scholarly journals Leaf area index estimation of even-aged oak (Quercus petraea) forests using in situ stand dendrometric parameters

2021 ◽  
Author(s):  
Briere Maxime ◽  
Christophe Francois ◽  
Francois Lebourgeois ◽  
Ingrid Seynave ◽  
Francois Ningre ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Basal Area ◽  
Quercus Petraea ◽  
Forest Stand ◽  
Stand Age ◽  
Estimation Errors ◽  
Data Set ◽  
Area Index ◽  
Net Productivity

The leaf area index (LAI) is a key characteristic of forest stand aboveground net productivity (ANP), and many methods have been developed to estimate the LAI. However, every method has flaws, e.g., methods may be destructive, require means or time and/or show intrinsic bias and estimation errors. A relationship using basal area (G) and stand age to estimate LAI was proposed by Sonohat et al. (2004). We used literature data in addition to data form measurements campaign made in the northern half of France to build a data set with large ranges of pedoclimatic conditions, stand age and measured LAI. We validated the Sonohat et al. (2004) relationship and attempted to improve or modify it using other stand/dendrometric characteristics that could be predictors of the LAI. The result is a series of three models using the G, age and/or quadratic mean diameter (Dg), and the models were able to estimate the LAI of an oak only even-aged forest stand with good confidence (root mean square error, RMSE < 0.75) While G is the main predictor here, age and Dg could be used conjointly or exclusively given the available data, with variable precision in the estimations. Although these models could not, by construction, relate to the interannual variability of the LAI, they may provide the theoretical LAI of an untouched forest (no meteorological, biotic or anthropogenic perturbation) in recent years. additionally, the use of this model may be more interesting than an LAI measurement campaign, depending on the means to be invested in such a campaign.

scholarly journals Algorithm for assessing forest stand productivity index using leaf area index

2019 ◽  
Vol 16 (3) ◽  
pp. 1311
Author(s):  
Faid Abdul Manan ◽  
Muhammad Buce Saleh ◽  
I Nengah Surati Jaya ◽  
Uus Saepul Mukarom
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Basal Area ◽  
Forest Stand ◽  
Productivity Index ◽  
Estimation Model ◽  
Area Index ◽  
Study Objective ◽  
Stand Productivity ◽  
Variable Combination

This paper describes a development of an algorithm for assessing stand productivity by considering the stand variables. Forest stand productivity is one of the crucial information that required to establish the business plan for unit management at the beginning of forest planning activity. The main study objective is to find out the most significant and accurate variable combination to be used for assessing the forest stand productivity, as well as to develop productivity estimation model based on leaf area index. The study found the best stand variable combination in assessing stand productivity were density of poles (X2), volume of commercial tree having diameter at breast height (dbh) 20-40 cm (X16), basal area of commercial tree of dbh &gt;40 cm (X20) with Kappa Accuracy of 90.56% for classifying into 5 stand productivity classes. It was recognized that the examined algorithm provides excellent accuracy of 100% when the stand productivity was classified into only 3 classes. The best model for assessing the stand productivity index with leaf area index is y = 0.6214x - 0.9928 with R2= 0.71, where y is productivity index and x is leaf area index.

scholarly journals A PROPOSED METHODOLOGY FOR THE CORRECTION OF THE LEAF AREA INDEX MEASURED WITH A CEPTOMETER FOR PINUS AND EUCALYPTUS FORESTS

2016 ◽  
Vol 40 (5) ◽  
pp. 845-854 ◽  
Author(s):  
Domingos Mendes Lopes ◽  
Nigel Walford ◽  
Helder Viana ◽  
Carlos Roberto Sette Junior
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Correction Factor ◽  
Basal Area ◽  
Allometric Equations ◽  
Nutrient Cycle ◽  
Area Index ◽  
Physiological Processes ◽  
The Difference ◽  
Non Destructive

ABSTRACT Leaf area index (LAI) is an important parameter controlling many biological and physiological processes associated with vegetation on the Earth's surface, such as photosynthesis, respiration, transpiration, carbon and nutrient cycle and rainfall interception. LAI can be measured indirectly by sunfleck ceptometers in an easy and non-destructive way but this practical methodology tends to underestimated when measured by these instruments. Trying to correct this underestimation, some previous studies heave proposed the multiplication of the observed LAI value by a constant correction factor. The assumption of this work is LAI obtained from the allometric equations are not so problematic and can be used as a reference LAI to develop a new methodology to correct the ceptometer one. This new methodology indicates that the bias (the difference between the ceptometer and the reference LAI) is estimated as a function of the basal area per unit ground area and that bias is summed to the measured value. This study has proved that while the measured Pinus LAI needs a correction, there is no need for that correction for the Eucalyptus LAI. However, even for this last specie the proposed methodology gives closer estimations to the real LAI values.

scholarly journals Spatial and seasonal variations of leaf area index (LAI) in subtropical secondary forests related to floristic composition and stand characters

2016 ◽  
Author(s):  
Wenjuan Zhu ◽  
Wenhua Xiang ◽  
Qiong Pan ◽  
Yelin Zeng ◽  
Shuai Ouyang ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Seasonal Variations ◽  
Basal Area ◽  
Floristic Composition ◽  
Controlling Factors ◽  
Forest Types ◽  
Area Index ◽  
Subtropical Forests

Abstract. Leaf area index (LAI) is an important parameter related to carbon, water and energy exchange between canopy and atmosphere, and is widely applied in the process models to simulate production and hydrological cycle in forest ecosystems. However, fine-scale spatial heterogeneity of LAI and its controlling factors have not been fully understood in Chinese subtropical forests. We used hemispherical photography to measure LAI values in three subtropical forests (i.e. Pinus massoniana – Lithocarpus glaber coniferous and evergreen broadleaved mixed forests, Choerospondias axillaris deciduous broadleaved forests, and L. glaber – Cyclobalanopsis glauca evergreen broadleaved forests) during period from April, 2014 to January, 2015. Spatial heterogeneity of LAI and its controlling factors were analysed by using geostatistics method the generalised additive models (GAMs), respectively. Our results showed that LAI values differed greatly in the three forests and their seasonal variations were consistent with plant phenology. LAI values exhibited strong spatial autocorrelation for three forests measured in January and for the L. glaber – C. glauca forest in April, July and October. Obvious patch distribution pattern of LAI values occurred in three forests during the non-growing period and this pattern gradually dwindled in the growing season. Stand basal area, crown coverage, crown width, proportion of deciduous species on basal area basis and forest types affected the spatial variations in LAI values in January, while species richness, crown coverage, stem number and forest types affected the spatial variations in LAI values in July. Floristic composition, spatial heterogeneity and seasonal variations should be considered for sampling strategy in indirect LAI measurement and application of LAI to simulate functional processes in subtropical forests.

scholarly journals A leaf area index data set acquired in Sahelian rangelands of Gourma in Mali over the 2005–2017 period

2019 ◽  
Vol 11 (2) ◽  
pp. 675-686
Author(s):  
Eric Mougin ◽  
Mamadou Oumar Diawara ◽  
Nogmana Soumaguel ◽  
Ali Amadou Maïga ◽  
Valérie Demarez ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Model Development ◽  
Land Surface Model ◽  
Product Evaluation ◽  
Tree Canopy ◽  
Surface Model ◽  
Data Set ◽  
Area Index

Abstract. The leaf area index of Sahelian rangelands and related variables such as the vegetation cover fraction, the fraction of absorbed photosynthetically active radiation and the clumping index were measured between 2005 and 2017 in the Gourma region of northern Mali. These variables, known as climate essential variables, were derived from the acquisition and the processing of hemispherical photographs taken along 1 km linear sampling transects for five contrasted canopies and one millet field. The same sampling protocol was applied in a seasonally inundated Acacia open forest, along a 0.5 km transect, by taking photographs of the understorey and the tree canopy. These observations collected over more than a decade, in a remote and not very accessible region, provide a relevant and unique data set that can be used for a better understanding of the Sahelian vegetation response to the current rainfall changes. The collected data can also be used for satellite product evaluation and land surface model development and validation. This paper aims to present the field work that was carried out during 13 successive rainy seasons, the measured vegetation variables, and the associated open database. Finally, a few examples of data use are shown. DOI of the referenced data set: https://doi.org/10.17178/AMMA-CATCH.CE.Veg_Gh.

scholarly journals Influence of phytotechnology on growth, production and leaf area index of black walnut (Juglans nigra L.) monocultures in Slovakia

2012 ◽  
Vol 51 (No. 5) ◽  
pp. 213-224
Author(s):  
F. Tokár ◽  
E. Krekulová
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Matter ◽  
Basal Area ◽  
Black Walnut ◽  
Juglans Nigra ◽  
Total Production ◽  
Area Index ◽  
Growth Production ◽  
Crown Thinning

In the paper we evaluate the influence of crown thinning with positive selection, different intensity (moderate PRP III and heavy PRP IV) and 5-year frequency on development of growth, production, quality and leaf area index of black walnut (Juglans nigra L.) monocultures growing on the series of three permanent research plots (PRP) Sikenica (Levice Forest Enterprise, Levice Forest District) as observed in 1978&ndash;2003. The trends of development of mean stem, basal area, standing volume and aboveground dendromass (in dry matter) were mainly influenced by heavy crown thinning. The index of growth was as follows: basal area 169.01%, standing volume 262.12%, aboveground dendromass (in dry matter) 324.48%. At the age of 64 years the black walnut monocultures tended by heavy crown thinning had the following parameters: basal area 31.03 m<sup>2</sup>/ha, standing volume 463.88 m<sup>3</sup>/ha and aboveground dendromass 194.98 t/ha. Mean periodic increment reached the values: basal area 0.51 m<sup>2</sup>/ha/year, standing volume 11.48 m<sup>3</sup>/ha/year and dendromass 5.39 t/ha/year. The index of increment percent growth was: basal area + 31.75%, growing stock + 30.85% and dendromass + 0.79%, compared to the control. The total production was also significantly influenced by heavy thinning. At the stand age of 64 years the tended stands had the total basal area of 4.92 m<sup>2</sup>/ha, total volume production of 572.77 m<sup>3</sup>/ha and total weight production of 246.04 t/ha. The total mean increment of basal area is 0.67 m<sup>2</sup>/ha/year, of volume 8.95 m<sup>3</sup>/ha/year and of weight 3.84 t/ha/year, which is by 24.07%, 23.96% and 16.01% more than on the control plot. The leaf area index at the age of 64 years ranges from 6.54 ha/ha (PRP III) to 7.82 ha/ha (PRP V). Dendrochronological analyses revealed minimum widths of annual rings in the years 1952, 1961, 1968, 1971, 1975, 1981, 1983, 1985, 1993, 2000, maximum ones in 1951, 1957, 1959, 1967, 1974, 1979, 1982, 1984, 1989, 1999.

scholarly journals Supplementary material to "A leaf area index, LAI, data set acquired in Sahelian rangelands (Gourma, Mali) over the 2005–2017 period"

2018 ◽  
Author(s):  
Eric Mougin ◽  
Mamadou Oumar Diawara ◽  
Nogmana Soumaguel ◽  
Ali Amadou Maiga ◽  
Valerie Demarez ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Data Set ◽  
Area Index ◽  
Supplementary Material
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