Developing allometric equations to estimate forest biomass for tree species categories based on phylogenetic relationships

The development of allometric biomass models is important process in biomass estimation because the reliability of forest biomass and carbon estimations largely depends on the accuracy and precision of such models.National Forest Inventories(NFI)are detailed assessments of forest resources at national and regional levels that provide valuable data for forest biomass estimation.However,the lack of biomass allometric equations for each tree species in the NFI currently hampers the estimation of national-scale forest biomass.The main objective of this study was to develop allometric biomass regression equations for each tree species in the NFI of China based on limited biomass observations.These equations optimally grouped NFI and biomass observation species according to their phylogenetic relationships.Significant phylogenetic signals demonstrated phylogenetic conservation of the crown-to-stem biomass ratio.Based on phylogenetic relationships,we grouped and matched NFI and biomass observation species into 22 categories.Allometric biomass regression models were developed for each of these 22 species categories,and the models performed successfully(R^(2)=0.97,root mean square error(RMSE)=12.9​t·ha^(–1),relative RMSE=11.5%).Furthermore,we found that phylogeny-based models performed more effectively than wood density-based models.The results suggest that grouping species based on their phylogenetic relationships is a reliable approach for the development and selection of accurate allometric equations.

Estimating and mapping forest biomass in northeast China using joint forest resources inventory and remote sensing data

Being able to accurately estimate and map forest biomass at large scales is important for a better understanding of the terrestrial carbon cycle and for improving the effectiveness of forest management. In this study, forest plot sample data, forest resources inventory(FRI) data, and SPOT Vegetation(SPOT-VGT) normalized difference vegetation index(NDVI) data were used to estimate total forest biomass and spatial distribution of forest biomass in northeast China(with 1 km resolution). Total forest biomass at both county and provincial scales was estimated using FRI data of 11 different forest types obtained by sampling 1156 forest plots, and newly-created volume to biomass conversion models. The biomass density at the county scale and SPOT-VGT NDVI data were used to estimate the spatial distribution of forest biomass. The results suggest that the total forest biomass was 2.4 Pg(1 Pg = 10g), with an average of 77.2 Mg ha, during the study period. Forests having greater biomass density were located in the middle mountain ranges in the study area. Human activities affected forest biomass at different elevations, slopes and aspects. The results suggest that the volume to biomass conversion models that could be developed using more plot samples and more detailed forest type classifications would be better suited for the study area and would provide more accurate biomass estimates. Use of both FRI and remote sensing data allowed the down-scaling of regional forest biomass statistics to forest cover pixels to produce a relatively fineresolution biomass map.

Dynamics of forest biomass carbon stocks from 1949 to 2008 in Henan Province,east-central China

We estimated forest biomass carbon storage and carbon density from 1949 to 2008 based on nine consecutive forest inventories in Henan Province,China.According to the definitions of the forest inventory,Henan forests were categorized into five groups: forest stands,economic forests,bamboo forests,open forests,and shrub forests.We estimated biomass carbon in forest stands for each inventory period by using the continuous biomass expansion factor method.We used the mean biomass density method to estimate carbon stocks in economic,bamboo,open and shrub forests.Over the 60-year period,total forest vegetation carbon storage increased from34.6 Tg(1 Tg = 1×10;g) in 1949 to 80.4 Tg in 2008,a net vegetation carbon increase of 45.8 Tg.By stand type,increases were 39.8 Tg in forest stands,5.5 Tg in economic forests,0.6 Tg in bamboo forests,and-0.1 Tg in open forests combine shrub forests.Carbon storageincreased at an average annual rate of 0.8 Tg carbon over the study period.Carbon was mainly stored in young and middle-aged forests,which together accounted for 70–88%of the total forest carbon storage in different inventory periods.Broad-leaved forest was the main contributor to forest carbon sequestration.From 1998 to 2008,during implementation of national afforestation and reforestation programs,the carbon storage of planted forest increased sharply from 3.9 to 37.9 Tg.Our results show that with the growth of young planted forest,Henan Province forests realized large gains in carbon sequestration over a 60-year period that was characterized in part by a nation-wide tree planting program.

Spatial variation and prediction of forest biomass in a heterogeneous landscape

Large areas assessments of forest bioinass distribution are a challenge in heterogeneous landscapes, where variations in tree growth and species composition occur over short distances. In this study, we use statistical and geospatial modeling on densely sample.d forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur, California. We estimated biomass in 280 forest Plots （one plot per 2.85 km2） and meas- ured an array of ecological （vegetation community type, distance to edge, amount of surrounding non-forest vegetation, soil properties, fire history） and physiographic drivers （elevation, potential soil moisture and solar radiation, proximity to the coast） of tree growth at each plot location. Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 kin. Regression tree （RT） models showed that both physiographic and ecological factors influenced bio- mass distribution. Across randomly selected sample densities （sample size 112 to 280）, ecological effects of vegetation community type and distance to forest edge, and physiographic effects of elevation, potential soil moisture and solar radiation were the most consistent predictors of biomass. Topographic moisture index and potential solar radiation had apositive effect on biomass, indicating the importance of topographically- mediated energy and moisture on plant growth and biomass accumula- tion. RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals. Regression kriging model, developed from RT combined with kriging of regression residuals, was used to map biomass across the Big Sur. This study dem- onstrates how statistical and geospatial modeling can be used to dis- criminate the relative importance of physiographic and ecologic effects on forest biomass and develop spatial models to predict and map biomass distribution across a heterogeneous landscape.

A model to estimate available timber and forest biomass and reforestation expenses in a mountainous region in Japan

We developed a model to estimate supply potentials and available amounts of timber and forest biomass resources from profitable sub-compartments of thinning and final felling operations. Economic balances were estimated while considering not only harvesting expenses but also reforestation expenses after final felling, which should be considered for sustainable forest management. Harvesting expenses were estimated based on two types of timber harvesting systems and three types of forest biomass harvesting systems in each sub-compartment. Then, the model was applied to Nasushiobara city of Tochigi prefecture, Japan. Reforestation expenses had large negative impacts on the financial balances of final felling operations. Few sub-compartments were profitable after considering reforestation expenses. Most profitable sub-compartments were those with mechanized operation systems and landing sales. These accounted for 17.19% of all sub-compartments, while only 5.75% of the sub-compartments were profitable based on their current operation systems and landing sales. Although the overall supply potentials of timber and forest biomass resources were 380,000 m3 and 210,000 Mg, respectively, and 15 times the planned harvest of coniferous tree volume of 25,000 m3year-1 and 50 times the annual demand for the woody gasification power generation of 4,000 Mg year-1 in Nasushiobara, available amounts of timber and forest biomass resources were only49,429 m3 and 33,333 Mg, which were 13.0% and 15.7% of supply potentials for landing sales with mechanized operation systems.

Seasonal Effects of Backscattering Intensity of ALOS-2 PALSAR-2 (L-Band) on Retrieval Forest Biomass in the Tropics

This research has used the L-band radar from ALOS-2 PALSAR-2 and field work data for evaluation of seasonal effects of backscattering intensity on retrieval forest biomass in the tropics. The effects of seasonality and HH, and HV polarizations of the SAR data on the biomass were analyzed. The dry season HV polarization could explain 61% of the biomass in this study region. The dry season HV backscattering intensity was highly sensitive to the biomass compared to the rainy season backscattering intensity. The SAR data acquired in the rainy season with humid and wet canopies were not very sensitive to the in situ biomass. Strong dependence of the biomass estimates with season of SAR data acquisition confirmed that the choice of right season SAR data is very important for improving the satellite based estimates of the biomass. This research expects that the results obtained in this research will contribute to monitoring of the quantity and quality of forest biomass in Vietnam and other tropical countries.

Changes in forest biomass carbon stock in the Pearl River Delta between 1989 and 2003

Forest ecosystems play a significant role in maintaining climate stability at the regional and global scales as an important carbon sink.Regional forest carbon storage and its dynamic changes in the Pearl River Delta have been estimated using the continuous biomass expansion factor(BEF)method based on field measurements of forests plots in different age classes and forest inventory data of three periods(1989–1993,1994–1998,1999–2003).The results show that regional carbon storage increased by 16.76%,from 48....

Disentangling the factors that contribute to variation in forest biomass increments in the mid-subtropical forests of China

Mid-subtropical forests are the main vegetation type of global terrestrial biomes, and are critical for maintaining the global carbon balance. However, estimates of forest biomass increment in mid-subtropical forests remain highly uncertain. It is critically important to determine the relative importance of different biotic and abiotic factors between plants and soil, particularly with respect to their influence on plant regrowth. Consequently,it is necessary to quantitatively characterize the dynamicspatiotemporal distribution of forest carbon sinks at a regional scale. This study used a large, long-term dataset in a boosted regression tree（BRT） model to determine the major components that quantitatively control forest biomass increments in a mid-subtropical forested region（Wuyishan National Nature Reserve, China）. Long-term,stand-level data were used to derive the forest biomass increment, with the BRT model being applied to quantify the relative contributions of various biotic and abiotic variables to forest biomass increment. Our data show that total biomass（t） increased from 4.62 9 106 to 5.30 9 106 t between 1988 and 2010, and that the mean biomass increased from 80.19 ± 0.39 t ha-1（mean ± standard error） to 94.33 ± 0.41 t ha-1in the study region. The major factors that controlled biomass（in decreasing order of importance） were the stand, topography, and soil. Stand density was initially the most important stand factor, while elevation was the most important topographic factor. Soil factors were important for forest biomass increment but have a much weaker influence compared to the other two controlling factors. These results provide baseline information about the practical utility of spatial interpolationmethods for mapping forest biomass increments at regional scales.

Spatial distribution of the potential forest biomass availability in Europe

Background: European forests are considered a crucial resource for supplying biomass to a growing bio-economy in Europe. This study aimed to assess the potential availability of forest biomass from European forests and its spatial distribution. We tried to answer the questions(i) how is the potential forest biomass availability spatially distributed across Europe and(ii) where are hotspots of potential forest biomass availability located?Methods: The spatial distribution of woody biomass potentials was assessed for 2020 for stemwood, residues(branches and harvest losses) and stumps for 39 European countries. Using the European Forest Information SCENario(EFISCEN) model and international forest statistics, we estimated the theoretical amount of biomass that could be available based on the current and future development of the forest age-structure, growing stock and increment and forest management regimes. We combined these estimates with a set of environmental(site productivity, soil and water protection and biodiversity protection) and technical(recovery rate, soil bearing capacity) constraints, which reduced the amount of woody biomass that could potentially be available. We mapped the potential biomass availability at the level of administrative units and at the 10 km × 10 km grid level to gain insight into the spatial distribution of the woody biomass potentials.Results: According to our results, the total availability of forest biomass ranges between 357 and 551 Tg dry matter per year. The largest potential supply of woody biomass per unit of land can be found in northern Europe(southern Finland and Sweden, Estonia and Latvia), central Europe(Austria, Czech Republic, and southern Germany),Slovenia, southwest France and Portugal. However, large parts of these potentials are already used to produce materials and energy. The distribution of biomass potentials that are currently unused only partially coincides with regions that currently have high levels of wood production.Conclusions: Our study shows how the forest biomass potentials are spatially distributed across the European continent, thereby providing insight into where policies could focus on an increase of the supply of woody biomass from forests. Future research on potential biomass availability from European forests should also consider to what extent forest owners would be willing to mobilise additional biomass from their forests and at what costs the estimated potentials could be mobilised.

Assessing current stocks and future sequestration potential of forest biomass carbon in Daqing Mountain Nature Reserve of Inner Mongolia, China

Assessment of regional forest carbon stocks and underlying controls is critical for guiding forest management in the context of carbon sequestration. We investigated the variations in tree biomass carbon stocks relating to forest types, and estimated the total tree biomass carbon stocks and projected gains through natural stand development by 2020 and 2050 in the Daqing Mountain Nature Reserve based on Category II data of the Forest Inventory of Inner Mongolia for the period ending 2008. Over a total area of 388,577 ha,this nature reserve currently stores an estimated 2221 Gg C in tree aboveground biomass alone, with potential to grow by more than 30 % to reach 2938 Gg C by 2020 and nearly double to 4092 Gg C by 2050 through natural development of the existing forest stands. The tree biomass carbon density and potential gain in tree biomass carbon stocks vary markedly among forest types and with stand development.The variations in the potential change of tree biomass carbon density for the periods 2008–2020 and 2008–2050 among forest types partly reflect the varying relationships of tree biomass carbon density with stand age for different tree species, and partly are attributable to variations in the stand age structure among different forest types. Of the major forest types, the ranking of projected changes in tree biomass carbon density are not consistent with variations in the relationship between tree biomass carbon density and stand age, neither are they explainable by variations in stand age structures, implying the interactive effect between forest type and stand dynamics on temporal changes in tree biomass carbon density. Birch rank highest for future biomass carbon sequestration because of its dominance in cover area and better age structure for potential gain in tree biomass carbon stocks. Poplar and larch were out-performers compared to other forest types given their greater contribution to total tree biomass carbon stocks relative to their distributional areas. Findings in this study illustrate that protection and proper management of under-aged forests can deliver marked gains in biomass carbon sequestration. This is of great importance to policy-makers as well as to scientific communities in seeking effective solutions for adaptive forest management and mitigation of anthropogenic greenhouse gases emissions using forest ecosystems.

Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years

Background: In recent decades the future of global forests has been a matter of increasing concern, particularly in relation to the threat of forest ecosystem responses under potential climate change. To the future predictions of these responses, the current forest biomass carbon storage(FCS) should first be clarified as much as possible,especially at national scales. However, few studies have introduced how to verify an FCS estimate by delimiting the reasonable ranges. This paper addresses an estimation of national FCS and its verification using two-step process to narrow the uncertainty. Our study focuses on a methodology for reducing the uncertainty resulted by converting from growing stock volume to above-and below-ground biomass(AB biomass), so as to eliminate the significant bias in national scale estimations.Methods: We recommend splitting the estimation into two parts, one part for stem and the other part for AB biomass to preclude possible significant bias. Our method estimates the stem biomass from volume and wood density(WD), and converts the AB biomass from stem biomass by using allometric relationships.Results: Based on the presented two-step process, the estimation of China’s FCS is performed as an example to explicate how to infer the ranges of national FCS. The experimental results demonstrate a national FCS estimation within the reasonable ranges(relative errors: + 4.46% and-4.44%), e.g., 5.6–6.1 PgC for China’s forest ecosystem at the beginning of the 2010 s. These ranges are less than 0.52 PgC for confirming each FCS estimate of different periods during the last 40 years. In addition, our results suggest the upper-limits by specifying a highly impractical value of WD(0.7 t·m-3) on the national scale. As a control reference, this value decides what estimate is impossible to achieve for the FCS estimates.Conclusions: Presented methodological analysis highlights the possibility to determine a range that the true value could be located in. The two-step process will help to verify national FCS and also to reduce uncertainty in related studies. While the true value of national FCS is immeasurable, our work should motivate future studies that explore new estimations to approach the true value by narrowing the uncertainty in FCS estimations on national and global scales.

Using nonparametric modeling approaches and remote sensing imagery to estimate ecological welfare forest biomass

The spatial distribution of forest biomass is closely related with carbon cycle, climate change, forest productivity, and biodiversity. Efficient quantification of biomass provides important information about forest quality and health. With the rising awareness of sustainable development, the ecological benefits of forest biomass attract more attention compared to traditional wood supply function. In this study, two nonparametric modeling approaches, random forest（RF） and support vector machine were adopted to estimate above ground biomass（AGB） using widely used Landsat imagery in the region,especially within the ecological forest of Fuyang District in Zhejiang Province, China. Correlation analysis was accomplished and model parameters were optimized during the modeling process. As a result, the best performance modeling method RF was implemented to produce an AGB estimation map. The predicted map of AGB in the study area showed obvious spatial variability and demonstrated that within the current ecological forest zone, as well as the protected areas, the average of AGB were higher than the ordinary forest. The quantification of AGB was proven to have a close relationship with the local forest policy and management pattern, which indicated that combining remote-sensing imagery and forest biophysical property would provide considerable guidance for making beneficial decisions.

Analysis of spatio-temporal changes in forest biomass in China

Forests play a central role in the global carbon cycle.China's forests have a high carbon sequestration potential owing to their wide distribution,young age and relatively low carbon density.Forest biomass is an essential variable for assessing carbon sequestration capacity,thus determining the spatio-temporal changes of forest biomass is critical to the national carbon budget and to contribute to sustainable forest management.Based on Chinese forest inventory data(1999–2013),this study explored spatial patterns of forest biomass at a grid resolution of 1 km by applying a downscaling method and further analyzed spatiotemporal changes of biomass at different spatial scales.The main findings are:(1)the regression relationship between forest biomass and the associated infuencing factors at a provincial scale can be applied to estimate biomass at a pixel scale by employing a downscaling method;(2)forest biomass had a distinct spatial pattern with the greatest biomass occurring in the major mountain ranges;(3)forest biomass changes had a notable spatial distribution pattern;increase(i.e.,carbon sinks)occurred in east and southeast China,decreases(i.e.,carbon sources)were observed in the northeast to southwest,with the largest biomass losses in the Hengduan Mountains,Southern Hainan and Northern Da Hinggan Mountains;and,(4)forest vegetation functioned as a carbon sink during 1999–2013 with a net increase in biomass of 3.71 Pg.

Composition,Property Characterization and Application of Agricultural and Forest Biomass Carbon

We analyzed the compositions and basic properties of agricultural and forest biomass carbon,and used the pot method to study the influence of such element on the remediation of contaminated soils and growth of crops.Results show that agricultural and forest biomass carbon contains various nutrients that are necessary for crop growth,high specific surface area,and pore structure development.Cotton stalk charcoal can reduce bioavailability of Cadmium(Cd) in soil.Under mild Cd pollution,soil treated with cotton stalk charcoal adsorbs Cd at a rapid rate.With increasing extent of Cd pollution,Cd adsorption rate gradually slows down and Cd adsorption amount gradually increases.In soil treated with cotton stalk charcoal,the amount of Cd accumulated in the edible portions and roots of Brassica chinensis significantly decrease.The Cd mass fraction of the edible portions and roots are reduced by 49.43%- 68.29%,64.14%- 77.66% respectively.Appropriately adding carbon cotton stalks increases crop biomass.At a certain range,increasing cotton stalk charcoal also promotes the absorption of major nutrients in Brassica chinensis.

Sensitivity Analysis and Evaluation of Forest Biomass Production Potential Using SWAT Model

Sensitivity analysis of crop parameters and the performance of SWAT (Soil and Water Assessment Tool) model to simulate potential forest biomass production were evaluated for the Upper Pearl River Watershed (UPRW). Local sensitivity analysis of seven crop parameters: radiation use efficiency (kg/ha)/(MJ/m2) (BIOE), potential maximum leaf area index for the plant (BLAI), fraction of growing season at which senescence becomes the dominant growth process (DLAI), fraction of the maximum plant leaf area index corresponding to the 1st point on the optimal leaf area development curve (LAIMX1), fraction of growing season corresponding to the 1st point on the optimal leaf area development curve (FRGRW1), plants potential maximum canopy height (m) (CHTMX), and maximum rooting depth for plant (mm) (RDMX) reveals that only three parameters: DLAI, BIOE and BLAI are sensitive to forest biomass production. Further, results indicate moderate sensitivity of DLAI and BIOE and low sensitivity of BLAI with relative sensitivity index of 0.44, 0.35 and 0.14, respectively. The performance of SWAT to simulate potential forest biomass was evaluated by comparing simulated data against three years of observed data that were obtained from USDA Forest Service website. The results indicate satisfactory performance of SWAT in predicting potential forest biomass, which is shown by the high value of coefficient of determination (R2 = 0.83), small root mean square error (RMSE = 11.11 Mg/ha), and small difference between mean. Results also reveal that the UPRW has the potential to produce approximately 49 Mg/ha of average forest biomass annually, which is approximately 6% less than the observed biomass.

A Comparison of Selected Parametric and Non-Parametric Imputation Methods for Estimating Forest Biomass and Basal Area

Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future management plans. The goal of this study was to compare various imputation methods to predict forest biomass and basal area, at a project planning scale (a combination of ground inventory plots, light detection and ranging (LiDAR) data, satellite imagery, and climate data was analyzed, and their root mean square error (RMSE) and bias were calculated. Results indicate that for biomass prediction, the k-nn (k = 5) had the lowest RMSE and least amount of bias. The second most accurate method consisted of the k-nn (k = 3), followed by the GWR model, and the random forest imputation. For basal area prediction, the GWR model had the lowest RMSE and least amount of bias. The second most accurate method was k-nn (k = 5), followed by k-nn (k = 3), and the random forest method. For both metrics, the GNN method was the least accurate based on the ranking of RMSE and bias.

Supply and Demand of a Forest Biomass in Application to the Region of South-East Finland

In Finland it is estimated that forest biomass will be the main source of bioenergy when meeting the national target: 38% renewable from total energy consumption by 2020. This target must become concrete for regional and local level participators of a forest industry and actions should take place in large combined heat and power generation (CHP) plants, district heating plants and independent heating systems. In energy production replacing fossil fuels with renewa-ble energy is reasonable in many cases. However, there are usually doubts about the availability and security of supply of forest biomass. The aim of this study is to introduce a systematical method for analyzing the availability and demand of forest biomass in regional and local level. This study introduces an objective method for analyzing local possibilities on where and how much the use of forest biomass could be increased. By replacing use of fossil fuels with renewable and domestic energy sources carbon dioxide (CO2) emissions and dependency on imported fossil fuels can be reduced. Utilization of biomass creates also local employment on energy sector.

Long-term response of living forest biomass to extensive logging in subtropical China

Forest disturbance and recovery are critical ecosystem processes,but the temporal patterns of disturbance have not been studied in subtropical China.Using a tree-ring analysis approach,we studied post-logging above-ground(ABG)biomass recovery dynamics over a 26-year period in four plots with different degrees of logging disturbance.Before logging,the ABG biomass ranged from 291 to 309 t ha-1.Soon after logging,the plots in primary forest,secondary forest,mixed forest and singlespecies forest had lost 33,91,90 and 100%of their initial ABG biomass,respectively.Twenty-six years after logging,the plots had regained 147,62,80 and 92%of their original ABG biomass,respectively.Over the 26 years following logging,the mean CAI(Current annual increment)were 10.1,5.5,6.4 and 10.8 t ha^-1 a^-1 and the average MAI(Mean annual increment)8.7,2.5,5.6 and 7.8 t ha^-1 a^-1 for the four forest types,respectively.The results indicate that subtropical forests subjected to moderate logging or disturbances do not require intensive management and single-species plantings can rapidly restore the above-ground biomass to levels prior to heavy logging.

Forest Biomass Management challenges in Commercially Exotic Tree Plantations Areas. A case study from the Rungwe Volcanic Province (Southern Highlands of Tanzania)

The carbon (C) stored in the living biomass of trees is typically the largest C pool of the forest ecosystem which is directly impacted by deforestation and degradation (Ensslin et al, 2015). The relationships between diversity, biomass and C stocks at varied altitudes can have crucial implications for the management and conservation of C sinks. The study was conducted at Mbeya One ward lying between Mporoto and Rungwe forest reserves in Mbeya rural district, in the Southern highlands of Tanzania. The main objective was (1) to assess the indigenous tree biomass variation between Mporoto and Rungwe forest reserves (2) to assess the exotic tree biomass variation between the two forest reserves and (3) to assess the human implication on aboveground biomass variation between the two forest reserves. The findings indicated the significant decreased in indigenous trees biomass in residential and crop land areas with a hasty increase in biomass when reaching Mporoto forest reserve indicating little human encroachment in the forest reserve. There was the same trend towards Rungwe forest reserve however in that side, there was a slight increase in indigenous tree biomass when reaching forest reserve which is the sign of human encroachment in the forest reserve. The main human activities encroaching the reserve were;timber harvesting and commercial exotic trees planting (especially the commercial trees, Pinus patula sp). However, the trend was opposite for the exotic trees especially for Pinus patula and Eucalyptus sp in the study area. Hence the study concludes that there is a significant variation between indigenous and exotic trees in the study area, hence the variation in the tree biomass (fig 2&3). There is also a massive human encroachment for indigenous trees clearance in expense of exotic trees plantations towards and in Rungwe forest reserve. Therefore, the study would like to call for an urgent intervention especially in the east side of the study area (Rungwe forest reserve) stopping exotic tree plantation penetrating into the forest reserve which intensify cutting down of indigenous trees in the forest reserves plummeting aboveground biomass and escalating carbon emissions in the atmosphere while jeopardizing the natural forest ecosystem services to the communities. Conservation education should be emphasized in the study area to local communities, exotic trees plantations owners and other relevant stakeholders.

Biomass carbon stocks in China's forests between 2000 and 2050:A prediction based on forest biomass-age relationships

China's forests are characterized by young forest age,low carbon density and a large area of planted forests,and thus have high potential to act as carbon sinks in the future.Using China's national forest inventory data during 1994-1998 and 1999-2003,and direct field measurements,we investigated the relationships between forest biomass density and forest age for 36 major forest types.Statistical approaches and the predicted future forest area from the national forestry development plan were applied to estimate the potential of forest biomass carbon storage in China during 2000-2050.Under an assumption of continuous natural forest growth,China's existing forest biomass carbon(C) stock would increase from 5.86 Pg C(1 Pg=1015 g) in 1999-2003 to 10.23 Pg C in 2050,resulting in a total increase of 4.37 Pg C.Newly planted forests through afforestation and reforestation will sequestrate an additional 2.86 Pg C in biomass.Overall,China's forests will potentially act as a carbon sink for 7.23 Pg C during the period 2000-2050,with an average carbon sink of 0.14 Pg C yr-1.This suggests that China's forests will be a significant carbon sink in the next 50 years.