scholarly journals Individual Plant Allometric Equations for Estimating Aboveground Biomass and Its Components for a Common Bamboo Species (Bambusa procera A. Chev. and A. Camus) in Tropical Forests

Forests ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 316 ◽  
Author(s):  
Bao Huy ◽  
Giang Thanh ◽  
Krishna Poudel ◽  
Hailemariam Temesgen
Keyword(s):  
Tropical Forests ◽  
Aboveground Biomass ◽  
Nonlinear Models ◽  
Generalized Least Squares ◽  
Forest Degradation ◽  
Seemingly Unrelated Regression ◽  
Simultaneous Estimation ◽  
Individual Plant ◽  
Bamboo Species ◽  
Species Specific

Bamboo forests play an important role in achieving the objectives of the United Nations program on Reducing Emission from Deforestation and Forest Degradation. We developed and validated a modeling system that simultaneously estimate aboveground biomass and its components for a common bamboo species (Bambusa procera A. Chev. and A. Camus) in tropical forests. Eighty-three bamboo culms were destructively sampled from seventeen 100 m2 sample plots located in different parts of the Central Highlands in Viet Nam to obtain total plant aboveground biomass (AGB) and its components. We examined the performance of weighted nonlinear models fit by maximum likelihood and weighted nonlinear seemingly unrelated regression fit by generalized least squares for predicting bamboo biomass. The simultaneous estimation of AGB and its components produced higher reliability than the models of components and total developed separately. With a large number of bamboo species, it may not be feasible to develop species- specific biomass models, hence genus-specific allometric models may be considered.

scholarly journals Simultaneous estimation as an alternative to young eucalyptus aboveground biomass modeling in ecophysiological experiments

2021 ◽  
Vol 43 ◽  
pp. e52126
Author(s):  
Thiago Wendling Gonçalves de Oliveira ◽  
Rafael Rubilar ◽  
Carlos Roberto Sanquetta ◽  
Ana Paula Dalla Corte ◽  
Alexandre Behling
Keyword(s):  
Least Squares ◽  
Aboveground Biomass ◽  
Forest Biomass ◽  
Seemingly Unrelated Regression ◽  
Biomass Estimation ◽  
Simultaneous Estimation ◽  
Efficiency Gain ◽  
Unrelated Regression ◽  
Biomass Components ◽  
Biomass Modeling

Accurate forest biomass estimates require the selection of appropriate models of individual trees. Thus, two properties are required in tree biomass modeling: (1) additivity of biomass components and (2) estimator efficiency. This study aimed to develop a system of equations to estimate young eucalyptus aboveground biomass and guarantee additivity and estimator efficiency. Aboveground eucalyptus biomass models were calibrated using four methods:  generalized least squares (GLS), weighted least squares (WLS), seemingly unrelated regression (SUR), and weighted seemingly unrelated regression (WSUR). The approaches were compared with regard to performance, additivity, and estimator efficiency. The methods did not differ with regard to the mean biomass estimation; therefore, their performance was similar. The GLS and WLS approaches did not satisfy the additivity principle, as the sum of the biomass components was not equal to total biomass. However, this was not observed with the SUR and WSUR approaches. With regard to estimator efficiency, the WSUR approach resulted in narrow confidence intervals and an efficiency gain of over 20%. The WSUR approach should be used in forest biomass modeling as it resulted in effective estimators while ensuring equation additivity, thus providing an easy and accurate alternative to estimate the initial biomass of eucalyptus stands in ecophysiological models.

Simultaneous estimation of biomass models for 13 tree species: effects of compatible additivity requirements

2017 ◽  
Vol 47 (6) ◽  
pp. 765-776 ◽  
Author(s):  
Thomas Nord-Larsen ◽  
Henrik Meilby ◽  
Jens Peter Skovsgaard
Keyword(s):  
Ordinary Least Squares ◽  
Seemingly Unrelated Regression ◽  
Model Systems ◽  
Simultaneous Estimation ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Biomass Models ◽  
Unrelated Regression ◽  
Biomass Components ◽  
Species Specific

A desirable feature of biomass models distinguishing different tree components is compatible additivity of the component functions. Due to forcing of parameter estimates, such additivity is achieved at an expense of precision of the component functions. This study aimed to analyse the loss of precision incurred by forcing of parameters in tree biomass models due to (i) additivity constraints, (ii) combining global and species-specific parameters, and (iii) estimating component functions simultaneously as a system instead of as individual equations. Based on biomass data from 697 trees including 13 different species, we estimated a set of compatibly additive, nonlinear biomass models using simultaneous estimation and compared these with less restricted model systems. In line with other similar studies, the overall model system explained 88%–99% of the variation in individual biomass components. Compared with the unrestricted model, restricting parameters to obtain compatible additivity resulted in a change in RMSE of –0.6% to 5.4%. When restricting parameter estimates using both species-specific and global parameters, RMSE increased by 1.7%–13.1%. Estimating model parameters using simultaneous estimation (nonlinear iterated seemingly unrelated regression, NSUR) increased model bias compared with ordinary least squares estimation (OLS) for most biomass components. Contrary to expectations, NSUR estimation did not lead to a reduction in the standard error of estimates.

scholarly journals The real potential of current passive satellite data to map aboveground biomass in tropical forests

2021 ◽  
Author(s):  
Nidhi Jha ◽  
Nitin Kumar Tripathi ◽  
Nicolas Barbier ◽  
Salvatore G. P. Virdis ◽  
Wirong Chanthorn ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Satellite Data ◽  
Aboveground Biomass ◽  
Real Potential ◽  
The Real

The distribution of organic carbon in major components of forests located in five life zones of Venezuela

1997 ◽  
Vol 13 (5) ◽  
pp. 697-708 ◽  
Author(s):  
M. Delaney ◽  
S. Brown ◽  
A. E. Lugo ◽  
A. Torres-Lezama ◽  
N. Bello Quintero
Keyword(s):  
Tropical Forests ◽  
Aboveground Biomass ◽  
Dead Wood ◽  
Clear Trend ◽  
Soil C ◽  
Forest Inventories ◽  
Biomass Components ◽  
Life Zone ◽  
Data Gap

ABSTRACTOne of the major uncertainties concerning the role of tropical forests in the global carbon cycle is the lack of adequate data on the carbon content of all their components. The goal of this study was to contribute to filling this data gap by estimating the quantity of carbon in the biomass, soil and necromass for 23 long-term permanent forest plots in five life zones of Venezuela to determine how C was partitioned among these components across a range of environments. Aboveground biomass C ranged from 70 to 179 Mg ha−1 and soil C from 125 to 257 Mg ha−1, and they represented the two largest C components in all plots. The C in fine litter (2.4 to 5.2 Mg ha−1), dead wood (2.4 to 21.2 Mg ha−1) and roots (23.6 to 38.0 Mg ha−1) accounted for less than 13% of the total C. The total amount of C among life zones ranged from 302 to 488 Mg ha−1, and showed no clear trend with life zone. In three of the five life zones, more C was found in the dead (soil, litter, dead wood) than in the live (biomass) components (dead to live ratios of 1.3 to 2.3); the lowland moist and moist transition to dry life zones had dead to live ratios of less than one. Results from this research suggest that for most life zones, an amount equivalent to between 20 and 58% of the aboveground biomass is located in necromass and roots. These percentages coupled with reliable estimates of aboveground biomass from forest inventories enable a more complete estimation of the C content of tropical forests to be made.

scholarly journals Effect of disturbance on plant species abundance and density distribution in tropical forest of Sunsari district, Eastern Nepal

2016 ◽  
Vol 6 (1) ◽  
pp. 1-12
Author(s):  
Tilak Prasad Gautam ◽  
Tej Narayan Mandal
Keyword(s):  
Carbon Sequestration ◽  
Species Composition ◽  
Tropical Forest ◽  
Tropical Forests ◽  
Tree Species ◽  
Forest Disturbance ◽  
Species Abundance ◽  
Forest Degradation ◽  
Tree Density ◽  
Shrub Species

The disappearance of global tropical forests due to deforestation and forest degradation has reduced the biodiversity and carbon sequestration capacity. In these contexts, present study was carried out to understand the species composition and density in the undisturbed and disturbed stands of moist tropical forest located in Sunsari district of eastern Nepal. Study revealed that the forest disturbance has reduced the number of tree species by 33% and tree density by 50%. In contrary, both number and density of herb and shrub species have increased with forest disturbance.

scholarly journals Natural and Anthropogenic Variation of Stand Structure and Aboveground Biomass in Niger Delta Mangrove Forests

2021 ◽  
Vol 4 ◽  
Author(s):  
Chukwuebuka J. Nwobi ◽  
Mathew Williams
Keyword(s):  
Aboveground Biomass ◽  
Niger Delta ◽  
Stand Structure ◽  
Oil Pollution ◽  
Negative Impact ◽  
Forest Degradation ◽  
Total Biomass ◽  
Mangrove Forests ◽  
Area Index ◽  
Nipa Palm

Mangrove forests are important coastal wetlands because of the ecosystem services they provide especially their carbon potential. Mangrove forests productivity in the Niger Delta are poorly quantified and at risk of loss from oil pollution, deforestation, and invasive species. Here, we report the most extensive stem girth survey yet of mangrove plots for stand and canopy structure in the Niger Delta, across tidal and disturbance gradients. We established twenty-five geo-referenced 0.25-ha plots across two estuarine basins. We estimated aboveground biomass (AGB) from established allometric equations based on stem surveys. Leaf area index (LAI) was recorded using hemispherical photos. We estimated a mean AGB of 83.7 Mg ha–1 with an order of magnitude range, from 11 to 241 Mg ha–1. We found significantly higher plot biomass in close proximity to a protected site and tidal channels, and the lowest in the sites where urbanization and wood exploitation was actively taking place. The mean LAI was 1.45 and ranged fivefold from 0.46 to 2.41 and there was a significant positive correlation between AGB and LAI (R2 = 0.31). We divided the plots into two disturbance regimes and three nipa palm (Nypa fruticans) invasion levels. Lower stem diameter (5–15 cm) accounted for 70% of the total biomass in disturbed plots, while undisturbed regimes had a more even (∼25%) contribution of different diameter at breast height (DBH) size classes to AGB. Nipa palm invasion also showed a significant link to larger variations in LAI and the proportion of basal area removed from plots. We conclude that mangrove forest degradation and exploitation is removing larger stems (>15 cm DBH), preferentially from these mangroves forests and creates an avenue for nipa palm colonization. This research identifies opportunities to manage the utilization of mangrove resources and reduce any negative impact. Our data can be used with remote sensing to estimate biomass in the Niger Delta and the inclusion of soil, leaf properties and demographic rates can analyze mangrove-nipa competition in the region.

scholarly journals Effects of large aboveground biomass loss events on the deadwood and litter mass dynamics of seasonal tropical forests in Cambodia

Tropics ◽  
2018 ◽  
Vol 27 (2) ◽  
pp. 33-48
Author(s):  
Yoshiyuki Kiyono ◽  
Eriko Ito ◽  
Yukako Monda ◽  
Jumpei Toriyama ◽  
Thy Sum
Keyword(s):  
Tropical Forests ◽  
Aboveground Biomass ◽  
Litter Mass ◽  
Biomass Loss

Partitioning and predicting forage biomass from total aboveground biomass of regenerating tree species using dimensional analyses

2019 ◽  
Vol 49 (3) ◽  
pp. 309-316 ◽  
Author(s):  
Quinn Morgan ◽  
Tamara L. Johnstone-Yellin ◽  
Cornelia C. Pinchot ◽  
Matthew Peters ◽  
Alejandro A. Royo
Keyword(s):  
Aboveground Biomass ◽  
Habitat Structure ◽  
Average Diameter ◽  
Stem Height ◽  
Basal Diameter ◽  
Site Specific ◽  
Species Specific ◽  
And Control ◽  
Forest Renewal ◽  
Sampling Variable

Foresters and wildlife biologists use biomass estimates as proxies of habitat structure, productivity, and carrying capacity. Determining biomass, however, is challenging without destructive harvests. We provide a dimensional analysis approach to partition browse biomass (BB) from total aboveground biomass (AGB) of six regenerating hardwoods in the Allegheny forests of Pennsylvania, USA. First, we determined the average diameter of browsed twigs for each species. Then, we created a subset of potential browsable twig and foliage biomass from total AGB in 439 individuals harvested within paired exclosure (fenced) and control (unfenced) plots at 15 sites. We fit species-specific allometric equations to estimate BB and AGB using basal diameter and height as predictors and tested the effects of fencing. Although overall stem height and BB were greater within exclosures, fencing did not significantly affect relationships between either predictor and BB or AGB, thereby enabling general and robust (R2 ≥ 0.80) equations for most species. Our work provides biomass equations for regionally dominant species and size classes that are underrepresented in the literature, yet critical to forest renewal and wildlife. Moreover, by sampling variable sites and levels of browse pressure, reported equations lessen site-specific biases. Finally, our methodology provides a template to generate forage biomass prediction equations for other plant and ungulate species.

scholarly journals Empirical Analysis of Demand for Real Money Balances in Africa: Panel Evidence from Nigeria and Ghana

2020 ◽  
Vol 19 (4) ◽  
pp. 363-376
Author(s):  
Chigozie Nelson Nkalu
Keyword(s):  
Exchange Rates ◽  
Interest Rates ◽  
Time Series Data ◽  
Generalized Least Squares ◽  
Real Income ◽  
Seemingly Unrelated Regression ◽  
Series Data ◽  
Real Money ◽  
Development Indicators ◽  
Preference Theory

Abstract This study investigates demand for real money balances in Africa using panel time-series data from Nigeria and Ghana between 1970 and 2014. The study employs Levin, Lin, Chu common unit root process and Pedroni Residual Cointegration Test which the results reveal that all the variables in the model are stationary and cointegrated respectively. Data sourced from the World Development Indicators (WDI) were analyzed using Panel Two-Stage Estimated Generalized Least Squares (cross-section Seemingly Unrelated Regression model (SURE)) with Instrumental Variables (IV). The results conform to the liquidity preference theory, with all the variables – inflation, real interest rates, and official exchange rates are statistically significant except real income. It is recommended that the monetary authorities in Africa especially the economies of Nigeria and Ghana should adopt appropriate monetary policies by placing interest rates, inflation and official exchange rates at acceptable levels to boost income through private sector investments.

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