Reconstruction of above-ground biomass and net primary productivity of dominant tree species in Guizhou forests over past five decades based on tree-ring data

2020 ◽  
Vol 40 (10) ◽  
Author(s):  
刘立斌,许海洋,郭银明,梁辉,芦晓明,张慧,梁尔源,倪健 LIU Libin
2008 ◽  
Vol 24 (4) ◽  
pp. 355-366 ◽  
Author(s):  
Jérôme Chave ◽  
Jean Olivier ◽  
Frans Bongers ◽  
Patrick Châtelet ◽  
Pierre-Michel Forget ◽  
...  

AbstractThe dynamics of tropical forest woody plants was studied at the Nouragues Field Station, central French Guiana. Stem density, basal area, above-ground biomass and above-ground net primary productivity, including the contribution of litterfall, were estimated from two large permanent census plots of 12 and 10 ha, established on contrasting soil types, and censused twice, first in 1992–1994, then again in 2000–2002. Mean stem density was 512 stems ha−1 and basal area, 30 m2 ha−1. Stem mortality rate ranged between 1.51% and 2.06% y−1. In both plots, stem density decreased over the study period. Using a correlation between wood density and wood hardness directly measured by a Pilodyn wood tester, we found that the mean wood density was 0.63 g cm−3, 12% smaller than the mean of wood density estimated from the literature values for the species occurring in our plot. Above-ground biomass ranged from 356 to 398 Mg ha−1 (oven-dry mass), and it increased over the census period. Leaf biomass was 6.47 Mg ha−1. Our total estimate of aboveground net primary productivity was 8.81 MgC ha−1 y−1 (in carbon units), not accounting for loss to herbivory, branchfalls, or biogenic volatile organic compounds, which may altogether account for an additional 1 MgC ha−1 y−1. Coarse wood productivity (stem growth plus recruitment) contributed to 4.16 MgC ha−1 y−1. Litterfall contributed to 4.65 MgC ha−1 y−1 with 3.16 MgC ha−1 y−1 due to leaves, 1.10 MgC ha−1 y−1 to twigs, and 0.39 MgC ha−1 y−1 to fruits and flowers. The increase in above-ground biomass for both trees and lianas is consistent with the hypothesis of a shift in the functioning of Amazonian rain forests driven by environmental changes, although alternative hypotheses such as a recovery from past disturbances cannot be ruled out at our site, as suggested by the observed decrease in stem density.


2016 ◽  
Vol 8 (1) ◽  
pp. 125-133 ◽  
Author(s):  
Sudam Charan SAHU ◽  
H.S. SURESH ◽  
N.H. RAVINDRANATH

The study of biomass, structure and composition of tropical forests implies also the investigation of forest productivity, protection of biodiversity and removal of CO2 from the atmosphere via C-stocks. The hereby study aimed at understanding the forest structure, composition and above ground biomass (AGB) of tropical dry deciduous forests of Eastern Ghats, India, where as a total of 128 sample plots (20 x 20 meters) were laid. The study showed the presence of 71 tree species belonging to 57 genera and 30 families. Dominant tree species was Shorea robusta with an importance value index (IVI) of 40.72, while Combretaceae had the highest family importance value (FIV) of 39.01. Mean stand density was 479 trees ha-1 and a basal area of 15.20 m2 ha-1. Shannon’s diversity index was 2.01 ± 0.22 and Simpson’s index was 0.85 ± 0.03. About 54% individuals were in the size between 10 and 20 cm DBH, indicating growing forests. Mean above ground biomass value was 98.87 ± 68.8 Mg ha-1. Some of the dominant species that contributed to above ground biomass were Shorea robusta (17.2%), Madhuca indica (7.9%), Mangifera indica (6.9%), Terminalia alata (6.9%) and Diospyros melanoxylon (4.4%), warranting extra efforts for their conservation. The results suggested that C-stocks of tropical dry forests can be enhanced by in-situ conserving the high C-density species and also by selecting these species for afforestation and stand improvement programs. Correlations were computed to understand the relationship between above ground biomass, diversity indices, density and basal area, which may be helpful for implementation of REDD+ (reduce emissions from deforestation and forest degradation, and foster conservation, sustainable management of forests and enhancement of forest carbon stocks) scheme.


2015 ◽  
Vol 166 (6) ◽  
pp. 389-398 ◽  
Author(s):  
Brigitte Rohner ◽  
Esther Thürig

Development of climate-dependent growth functions for the scenario model “Massimo” Tree growth is substantially influenced by climatic factors. In the face of climate change, climate effects should therefore be included in estimations of Switzerland's future forest productivity. In order to include climate effects in the growth functions of the “Massimo” model, which is typically applied to project forest resources in Switzerland, we statistically modelled climate effects on tree growth representatively for Switzerland by simultaneously considering further growth-influencing factors. First, we used tree ring data to evaluate how climate variables should be defined. This analyses showed that for modelling multi-year tree growth we should use averages of whole-year variables. Second, we fitted nonlinear mixed-effects models separately for the main tree species to individual-tree growth data from the Swiss National Forest Inventory. In these models, we combined climate variables defined according to the results of the tree ring study with various further variables that characterize sites, stands and individual trees. The quantified effects were generally plausible and explained convincingly the physiological differences between the species. The statistical growth models for the main tree species will now be included in the forest scenario model “Massimo”. This will allow for founded analyses of scenarios which assume changing climatic conditions.


2008 ◽  
Vol 24 (3) ◽  
pp. 347-350 ◽  
Author(s):  
Luke P. Shoo ◽  
Jeremy VanDerWal

An important deficiency of the tropical forest data set on above-ground net primary productivity (ANPP) is the paucity of studies where requisite components of forest productivity have been measured at the same location. Missing data on above-ground biomass increment (ABI, which refers to the incremental growth of trees) and fine-litter production (leaves, fruit, flowers, small twigs, but excluding coarse woody debris) is particularly problematic as these are the two major components of ANPP. The fragmentary nature of the data is reflected by the fact that only 13 of 39 (33%) plots reviewed by Clark et al. (2001) and 8 of 104 (8%) plots reviewed by Malhi et al. (2004) had data on both major components of productivity. In an attempt to retain the geographic coverage and replication of data in analyses, researchers have proposed ways to infer missing data. Typically ratios or (more recently) fitted relationships between ABI and litter production have been used for this purpose (Bray & Gorham 1964, Clark et al. 2001, Murphy 1975).


2013 ◽  
Vol 10 (4) ◽  
pp. 2255-2272 ◽  
Author(s):  
A. D. A. Castanho ◽  
M. T. Coe ◽  
M. H. Costa ◽  
Y. Malhi ◽  
D. Galbraith ◽  
...  

Abstract. Dynamic vegetation models forced with spatially homogeneous biophysical parameters are capable of producing average productivity and biomass values for the Amazon basin forest biome that are close to the observed estimates, but these models are unable to reproduce observed spatial variability. Recent observational studies have shown substantial regional spatial variability of above-ground productivity and biomass across the Amazon basin, which is believed to be primarily driven by a combination of soil physical and chemical properties. In this study, spatial heterogeneity of vegetation properties is added to the Integrated Biosphere Simulator (IBIS) land surface model, and the simulated productivity and biomass of the Amazon basin are compared to observations from undisturbed forest. The maximum RuBiCo carboxylation capacity (Vcmax) and the woody biomass residence time (τw) were found to be the most important properties determining the modeled spatial variation of above-ground woody net primary productivity and biomass, respectively. Spatial heterogeneity of these properties may lead to simulated spatial variability of 1.8 times in the woody net primary productivity (NPPw) and 2.8 times in the woody above-ground biomass (AGBw). The coefficient of correlation between the modeled and observed woody productivity improved from 0.10 with homogeneous parameters to 0.73 with spatially heterogeneous parameters, while the coefficient of correlation between the simulated and observed woody above-ground biomass improved from 0.33 to 0.88. The results from our analyses with the IBIS dynamic vegetation model demonstrated that using single values for key ecological parameters in the tropical forest biome severely limits simulation accuracy. Clearer understanding of the biophysical mechanisms that drive the spatial variability of carbon allocation, τw and Vcmax is necessary to achieve further improvements to simulation accuracy.


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