Forest biomass carbon pool dynamics in Tibet Autonomous Region of China: Inventory data 1999-2019

According to the forest resources inventory data for different periods and the latest estimation parameters of forest carbon reserves in China, the carbon reserves and carbon density of forest biomass in the Tibet Autonomous Region from 1999 to 2019 were estimated using the IPCC international carbon reserves estimation model. The results showed that, during the past 20 years, the forest area, forest stock, and biomass carbon storage in Tibet have been steadily increasing, with an average annual increase of 1.85×104 hm2, 0.033×107 m3, and 0.22×107 t, respectively. Influenced by geographical conditions and the natural environment, the forest area and biomass carbon storage gradually increased from the northwest to the southeast, particularly in Linzhi and Changdu, where there are many primitive forests, which serve as important carbon sinks in Tibet. In terms of the composition of tree species, coniferous forests are dominant in Tibet, particularly those containing Abies fabri, Picea asperata, and Pinus densata, which comprise approximately 45% of the total forest area in Tibet. The ecological location of Tibet has resulted in the area being dominated by shelter forest, comprising 68.76% of the total area, 64.72% of the total forest stock, and 66.34% of the total biomass carbon reserves. The biomass carbon storage was observed to first increase and then decrease with increasing forest age, which is primarily caused by tree growth characteristics. In over-mature forests, trees’ photosynthesis decreases along with their accumulation of organic matter, and the trees can die. In addition, this study also observed that the proportion of mature and over-mature forest in Tibet is excessively large, which is not conducive to the sustainable development of forestry in the region. This problem should be addressed in future management and utilization activities.

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Estimating spatial variation in Alberta forest biomass from a combination of forest inventory and remote sensing data

Biogeosciences Discussions ◽

10.5194/bgd-10-19005-2013 ◽

2013 ◽

Vol 10 (12) ◽

pp. 19005-19044 ◽

Cited By ~ 3

Author(s):

J. Zhang ◽

S. Huang ◽

E. H. Hogg ◽

V. Lieffers ◽

Y. Qin ◽

...

Keyword(s):

Carbon Storage ◽

Random Forests ◽

Forest Inventory ◽

Regression Models ◽

Spatial Interpolation ◽

Spatial Regression ◽

Forest Biomass ◽

Biomass Carbon ◽

Inventory Data ◽

Spatial Regression Models

Abstract. Uncertainties in the estimation of tree biomass carbon storage across large areas pose challenges for the study of forest carbon cycling at regional and global scales. In this study, we attempted to estimate the present biomass carbon storage in Alberta, Canada, by taking advantage of a spatially explicit dataset derived from a combination of forest inventory data from 1968 plots and spaceborne light detection and ranging (LiDAR) canopy height data. Ten climatic variables together with elevation, were used for model development and assessment. Four approaches, including spatial interpolation, non-spatial and spatial regression models, and decision-tree based modelling with random forests algorithm (a machine-learning technique), were compared to find the "best" estimates. We found that the random forests approach provided the best accuracy for biomass estimates. Non-spatial and spatial regression models gave estimates similar to random forests, while spatial interpolation greatly overestimated the biomass storage. Using random forests, the total biomass stock in Alberta forests was estimated to be 3.11 × 109 Mg, with the average biomass density of 77.59 Mg ha−1. At the species level, three major tree species, lodgepole pine, trembling aspen and white spruce, stocked about 1.91 × 109 Mg biomass, accounting for 61% of total estimated biomass. Spatial distribution of biomass varied with natural regions, land cover types, and species. And the relative importance of predictor variables on determining biomass distribution varied with species. This study showed that the combination of ground-based inventory data, spaceborne LiDAR data, land cover classification, climatic and environmental variables was an efficient way to estimate the quantity, distribution and variation of forest biomass carbon stocks across large regions.

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Tree height integrated into pantropical forest biomass estimates

Biogeosciences ◽

10.5194/bg-9-3381-2012 ◽

2012 ◽

Vol 9 (8) ◽

pp. 3381-3403 ◽

Cited By ~ 239

Author(s):

T. R. Feldpausch ◽

J. Lloyd ◽

S. L. Lewis ◽

R. J. W. Brienen ◽

M. Gloor ◽

...

Keyword(s):

East Africa ◽

Carbon Storage ◽

Stand Structure ◽

Forest Biomass ◽

Small Diameter ◽

Tree Height ◽

Total Biomass ◽

Guiana Shield ◽

Tree Biomass ◽

Continental Scale

Abstract. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

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Forest Biomass Estimation Based on Forest Inventory Data in Middle and Last Scales

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.183-185.220 ◽

2011 ◽

Vol 183-185 ◽

pp. 220-224

Author(s):

Ming Ze Li ◽

Wen Yi Fan ◽

Ying Yu

Keyword(s):

Tree Species ◽

Forest Inventory ◽

Forest Biomass ◽

Biomass Estimation ◽

Total Biomass ◽

Inventory Data ◽

Biomass Equation ◽

Tree Species Composition ◽

Forest Inventory Data ◽

Ecosystem Carbon

The forest biomass (which is referred to the arbor aboveground biomass in this research) is one of the most primary factors to determine the forest ecosystem carbon storages. There are many kinds of estimating methods adapted to various scales. It is a suitable method to estimate forest biomass of the farm or the forestry bureau in middle and last scales. First each subcompartment forest biomass should be estimated, and then the farm or the forestry bureau forest biomass was estimated. In this research, based on maoershan farm region, first the single tree biomass equation of main tree species was established or collected. The biomass of each specie was calculated according to the materials of tally, such as height, diameter and so on in the forest inventory data. Secondly, each specie’s biomass and total biomass in subcompartment were calculated according to the tree species composition in forest management investigation data. Thus the forest biomass spatial distribution was obtained by taking subcompartment as a unit. And last the forest total biomass was estimated.

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Carbon storage along altitudes in agrisilviculture system- Case study of Devprayag Block, Tehri District, Uttarakhand, India

International Journal of Current Research in Biosciences and Plant Biology ◽

10.20546/ijcrbp.2020.709.004 ◽

2020 ◽

Vol 7 (9) ◽

pp. 29-38

Author(s):

K.K. Vikrant ◽

D.S. Chauhan ◽

R.H. Rizvi

Keyword(s):

Climate Change ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Carbon Storage ◽

Carbon Stock ◽

Total Carbon ◽

Total Biomass ◽

Biomass Carbon ◽

Total Carbon Stock ◽

Crop Biomass

Climate change is one of the impending problems that have affected the productivity of agroecosystems which calls for urgent action. Carbon sequestration through agroforestry along altitude in mountainous regions is one of the options to contribute to global climate change mitigation. Three altitudes viz. lower (286-1200m), middle (1200-2000m), and upper (2000-2800m) have been selected in Tehri district. Ten Quadrates (10m × 10 m) were randomly selected from each altitude in agrisilviculture system. At every sampling point, one composite soil sample was taken at 30 cm soil depth for soil organic carbon analysis. For the purpose of woody biomass, Non destructive method and for crop biomass assessment destructive method was employed. Finally, aboveground biomass (AGB), belowground biomass carbon (BGB), Total tree Biomass (TTB), Crop biomass (CB), Total Biomass (TB), Total biomass carbon (TBC), soil organic carbon (SOC), and total carbon stock (TC) status were estimated and variables were compared using one-way analysis of variance (ANOVA).The result indicated that AGB, BGB, TTB, CB , TB, TBC, SOC, and TC varied significantly (p < 0.05) across the altitudes. Results showed that total carbon stock followed the order upper altitude Ëƒ middle altitudes Ëƒ lower altitude. The upper altitude (2000-2800 m) AGB, BGB,TTB, TBC,SOC, and TC stock was estimated as 2.11 Mg ha-1 , 0.52 Mg ha-1, 2.63 Mg ha-1, 2.633 Mg ha-1, 1.18 Mg ha-1 , 26.53 Mg ha-1, 38.48 Mg ha-1 respectively, and significantly higher than the other altitudes. It was concluded that agrisilviculture system hold a high potential for carbon storage at temperate zones. Quercus lucotrichophora, Grewia oppositifolia and Melia azadirach contributed maximum carbon storage which may greatly contribute to the climate resilient green economy strategy and their conservation should be promoted.

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The ratio of total to merchantable forest biomass and its application to the global carbon budget

Canadian Journal of Forest Research ◽

10.1139/x83-056 ◽

1983 ◽

Vol 13 (3) ◽

pp. 372-383 ◽

Cited By ~ 53

Author(s):

W. Carter Johnson ◽

David M. Sharpe

Keyword(s):

United States ◽

Carbon Storage ◽

Woody Debris ◽

Forest Biomass ◽

Total Biomass ◽

Global Carbon Budget ◽

The Mean ◽

Carbon Losses ◽

Global Carbon ◽

Level Analysis

Records of merchantable forest volumes can be used to estimate rates of carbon storage or depletion using a ratio to convert merchantable weights to total forest biomass (T/M ratio). We present evidence that the T/M ratio used to estimate carbon storage in midlatitude forests has been seriously underestimated by neglecting carbon in trees of unmerchantable size and quality and in coarse and fine litter. Ratios for forest types and size classes in Virginia based on detailed plot-level analysis ranged from 2.1 to 5.0; the mean weighted ratio of 2.7 was 55% greater than a ratio currently in use. More general analysis indicated that the T/M ratio for Virginia was representative of forests of the East; forests of the western United States were comparable to those of the East when woody debris was included in the estimate of total biomass. Application of the weighted ratio to growth of United States forests during 1952–1977 yielded a per-annum accretion of carbon in biomass (excluding soil carbon) of 0.15 Gt C•year−1, about 10% of the 1.6–1.9 Gt C•year−1 computed for midlatitude forests. More complete studies of counterbalancing carbon losses from forests, particularly losses in litter and soils after forest harvest and conversion to agriculture, are needed before the source or sink nature of midlatitude forests can be determined with confidence.

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Spatiotemporal Distribution and Driving Factors of Forest Biomass Carbon Storage in China: 1977–2013

Forests ◽

10.3390/f8070263 ◽

2017 ◽

Vol 8 (7) ◽

pp. 263 ◽

Cited By ~ 5

Author(s):

Jiameng Yang ◽

Xiaoxia Ji ◽

David Deane ◽

Linyu Wu ◽

Shulin Chen

Keyword(s):

Carbon Storage ◽

Forest Biomass ◽

Driving Factors ◽

Spatiotemporal Distribution ◽

Biomass Carbon

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Carbon Storage and Land-use in Extractive Reserves, Acre, Brazil

Environmental Conservation ◽

10.1017/s0376892900031428 ◽

1992 ◽

Vol 19 (4) ◽

pp. 307-315 ◽

Cited By ~ 27

Author(s):

I. Foster Brown ◽

Daniel C. Nepstad ◽

Ivan de O. Pires ◽

Leda M. Luz ◽

Andréa S. Alechandre

Keyword(s):

Land Use ◽

Carbon Storage ◽

Large Scale ◽

Forest Biomass ◽

Forest Products ◽

Primary Forest ◽

Forest Conversion ◽

Total Biomass ◽

Rubber Tappers ◽

Extractive Reserves

Large-scale forest conversion in Brazil, primarily to cattle pasture, contributes significantly to the global anthropogenic emission of CO2 into the atmosphere. An alternative land-use, namely extractive reserves for forest residents, may serve as one means of using Amazonian forests sustainably and of maintaining carbon in living matter rather than adding it to that in the atmosphere.In the Seringal (former rubber estate) Porongaba (6,800 ha) of the Chico Mendes Extractive Reserve, Acre, Brazil, primary forest still covers more than 90% of the area. Total biomass in primary forest is estimated at 426 tons per ha, equivalent to 213 t C per ha. Rubber tappers effectively maintain about 60,000 tons of carbon per household (family unit) in forest biomass and thus out of the atmosphere. Deforestation of primary forest was less than 0.6% per yr — much less than rates of natural disturbances for other neotropical forests.Slash-and-burn agriculture in the Seringal Porongaba releases carbon at a gross rate of some 200 t C per yr per household. Net releases are much less, as regrowth forests absorb carbon at rates of about 9 t C per ha per yr. The net areal flux of carbon to the atmosphere from land-use in Seringal is much less than one ton of carbon per ha per yr, which is equivalent to less than 0.3% per yr of the carbon stock in forest biomass. If Seringal Porongaba is typical of the three million hectares in extractive reserves in Brazilian Amazonia, then these reserves are calculated to retain 0.6 Gigatons of carbon in the terrestrial biota.Adverse changes in income patterns for rubber tappers could lead to abandonment of extractive reserves or increased deforestation within them. Diversification and improvement of income from non-timber forest products are needed to maintain rubber tappers in extractive reserves. Most beneficiaries of carbon storage in these and other reserves live outside Brazil; devising means of recompensation for these benefits is a challenge for the global society.

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Estimating spatial variation in Alberta forest biomass from a combination of forest inventory and remote sensing data

Biogeosciences ◽

10.5194/bg-11-2793-2014 ◽

2014 ◽

Vol 11 (10) ◽

pp. 2793-2808 ◽

Cited By ~ 30

Author(s):

J. Zhang ◽

S. Huang ◽

E. H. Hogg ◽

V. Lieffers ◽

Y. Qin ◽

...

Keyword(s):

Land Cover ◽

Random Forests ◽

Forest Inventory ◽

Regression Models ◽

Spatial Interpolation ◽

Spatial Regression ◽

Forest Biomass ◽

Biomass Carbon ◽

Inventory Data ◽

Spatial Regression Models

Abstract. Uncertainties in the estimation of tree biomass carbon storage across large areas pose challenges for the study of forest carbon cycling at regional and global scales. In this study, we attempted to estimate the present aboveground biomass (AGB) in Alberta, Canada, by taking advantage of a spatially explicit data set derived from a combination of forest inventory data from 1968 plots and spaceborne light detection and ranging (lidar) canopy height data. Ten climatic variables, together with elevation, were used for model development and assessment. Four approaches, including spatial interpolation, non-spatial and spatial regression models, and decision-tree-based modeling with random forests algorithm (a machine-learning technique), were compared to find the "best" estimates. We found that the random forests approach provided the best accuracy for biomass estimates. Non-spatial and spatial regression models gave estimates similar to random forests, while spatial interpolation greatly overestimated the biomass storage. Using random forests, the total AGB stock in Alberta forests was estimated to be 2.26 × 109 Mg (megagram), with an average AGB density of 56.30 ± 35.94 Mg ha−1. At the species level, three major tree species, lodgepole pine, trembling aspen and white spruce, stocked about 1.39 × 109 Mg biomass, accounting for nearly 62% of total estimated AGB. Spatial distribution of biomass varied with natural regions, land cover types, and species. Furthermore, the relative importance of predictor variables on determining biomass distribution varied with species. This study showed that the combination of ground-based inventory data, spaceborne lidar data, land cover classification, and climatic and environmental variables was an efficient way to estimate the quantity, distribution and variation of forest biomass carbon stocks across large regions.

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Carbon Sequestration in Broad Leaved Forests of Mid-Hills of Nepal: A Case Study from Palpa District

The Initiation ◽

10.3126/init.v3i0.2424 ◽

1970 ◽

Vol 3 ◽

pp. 20-29

Author(s):

Bishnu P Shrestha

Keyword(s):

Carbon Sequestration ◽

Soil Carbon ◽

Forest Biomass ◽

Total Carbon ◽

Total Biomass ◽

Biomass Carbon ◽

Deep Soil ◽

Below Ground ◽

Shallow Soils

This study was carried out to quantify total carbon sequestration in two broad leaved forests (Shorea and Schima-Castanopsis forests) of Palpa district. The inventory for estimating above and below ground biomass of forest was carried out using stratified random sampling. Biomass was calculated using allometric models. Soil samples were taken from soil profile upto 1 m depth for deep soil and up to bed rock for shallow soils at the interval of 20 cm. Walkey and Black method were applied for measuring soil organic carbon. Total biomass carbon in Shorea and Schima-Castanopsis forest was found 101.66 and 44.43 t ha-1 respectively. Soil carbon sequestration in Schima-Castanopsis and Shorea forest was found 130.76 and 126.07 t ha-1 respectively. Total carbon sequestration in Shorea forest was found 1.29 times higher than Schima-Castanopsis forest. The study found that forest types play an important role on total carbon sequestration. Key Words: Carbon sequestration, Shorea forest, Schima-Castanopsis forest, Biomass carbon, Soil carbon DOI: 10.3126/init.v3i0.2424 The Initiation Vol.3 2009 p.20-29

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Seven new species of Phyllocoptes Nalepa from Tibet Autonomous Region, China (Acari: Eriophyidae: Phyllocoptinae)

Zootaxa ◽

10.11646/zootaxa.2313.1.2 ◽

2009 ◽

Vol 2313 (1) ◽

pp. 35-60 ◽

Cited By ~ 1

Author(s):

ZI-WEI SONG ◽

XIAO-FENG XUE ◽

XIAO-YUE HONG

Keyword(s):

New Species ◽

Mite Species ◽

Autonomous Region ◽

Tibet Autonomous Region ◽

Picea Asperata ◽

Eriophyoid Mite

In this paper, seven new species of Phyllocoptes from China are described and illustrated. They are Phyllocoptes cunninghamiae sp. nov. on Cunninghamia sp. (Taxodiaceae); Phyllocoptes stephanocarpae sp. nov. on Lonicera stephanocarpa Franch. (Caprifoliaceae); Phyllocoptes webbianae sp. nov. on Lonicera webbiana Wall. ex DC. (Caprifoliaceae); Phyllocoptes bayisis sp. nov. and Phyllocoptes myrtilloidia sp. nov. on Spiraea myrtilloides Rehd. (Rosaceae); Phyllocoptes graminis sp. nov. on Berberis graminea Ahrendt (Berberidaceae); and Phyllocoptes piceanis sp. nov. on Picea asperata Mast. (Pinaceae). All the eriophyoid mite species described here are vagrants on the undersurface of host leaves. A key to the species of Chinese Phyllocoptes is provided herein.

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