Estimating aboveground biomass of Pinus densata-dominated forests using Landsat time series and permanent sample plot data

Southwest China is one of three major forest regions in China and plays an important role in carbon sequestration.Accurate estimations of changes in aboveground biomass are critical for understanding forest carbon cycling and promoting climate change mitigation.Southwest China is characterized by complex topographic features and forest canopy structures,complicating methods for mapping aboveground biomass and its dynamics.The integration of continuous Landsat images and national forest inventory data provides an alternative approach to develop a long-term monitoring program of forest aboveground biomass dynamics.This study explores the development of a methodological framework using historical national forest inventory plot data and Landsat TM timeseries images.This method was formulated by comparing two parametric methods:Linear Regression for Multiple Independent Variables(MLR),and Partial Least Square Regression(PLSR);and two nonparametric methods:Random Forest(RF)and Gradient Boost Regression Tree(GBRT)based on the state of forest aboveground biomass and change models.The methodological framework mapped Pinus densata aboveground biomass and its changes over time in Shangri-la,Yunnan,China.Landsat images and national forest inventory data were acquired for 1987,1992,1997,2002 and 2007.The results show that:(1)correlation and homogeneity texture measures were able to characterize forest canopy structures,aboveground biomass and its dynamics;(2)GBRT and RF predicted Pinus densata aboveground biomass and its changes better than PLSR and MLR;(3)GBRT was the most reliable approach in the estimation of aboveground biomass and its changes;and,(4)the aboveground biomass change models showed a promising improvement of prediction accuracy.This study indicates that the combination of GBRT state and change models developed using temporal Landsat and national forest inventory data provides the potential for developing a methodological framework for the long-term mapping and monitoring program of forest aboveground biomass and its changes in Southwest China.     

Estimation of the carbon storage of forest vegetation and carbon emission from forest fires in Heilongjiang Province,China

The forest resource of Heilongjiang province has important position in china. On the basis of the six times of national forest inventory data （1973-1976, 1977-1981, 1985-1988, 1989-1993, 1994-1998, 1999-2003） surveyed by the Forestry Ministry of P. R. China from 1973 to 2003, the carbon storage of forests in Heilongjiang Province are estimated by using the method of linear relationship of each tree species between biomass and volume. The results show that the carbon storage of Heilongjiang forests in the six periods （1973-1976, 1977-1981, 1985-1988, 1989-1993, 1994-1998, 1999-2003） are 7.164×10^8 t, 4.871×10^8 t, 5.094×10^8 t, 5.292×10^8 t, 5.594×10^8 t and 5.410×10^8 t, respectively., which showed a trend of decreasing in early time and then increasing. It indicated that Heilongjiang forests play an important role as a sink of atmospheric carbon dioxide during past 30 years. Based on the data of forest fires from 1980 to 1999 and ground biomass estimation for some forest types in Heilongjiang Province, it is estimated that the amount of mean annual consumed biomass of forests is 391758.65t-522344.95t, accounting for 6.4%-8.4% of total national consummation from forest fires, and the amount of carbon emission is 176 291.39t-235 055.23t, about 8% of total national emission from forest fires. The emission of CO2, CO, CH4 and NMHC from forest fires in Heilongjiang Province are estimated at 581761.6-775682.25 t, 34892.275-46523.04 t, 14091.11-18788.15 t and 6500-9000 t, respectively, every year.     

Biomass estimations in forests of different disturbance history in the Atlantic Forest of Rio de Janeiro,Brazil

Tropical forests are large reservoirs of biomass and there is a need for information on existing carbon stocks in these ecosystems and especially the effects of logging on these stocks. Reliable estimates of aboveground biomass stocks within the Atlantic Forest are rarely available. Past human disturbance is an important factor affecting forest structure variation and biomass accumulation among tropical forest ecosystems. To support the efforts of improving the quality of estimations of the current and future biomass carbon storage capacity of this disturbed forest region we tested a non-experimental small scale approach to compare the aboveground tree biomass (AGB) of forest sites. Three sites with known disturbance histories have been investigated: complete cut down, selective logging and conservation since 70 years. The woody plant community (dbh ≥ 10 cm) was censused and canopy openness in conjunction with leaf area index has been obtained by hemispherical photographs at each site. Estimates of aboveground tree biomass have been carried out using an allometric equation for moist tropical forests already applied for the study area. Additionally, a FAO standard equation has been employed for crosschecking our results. We identified significant differences in recent AGB of the three compared forest sites. With 313 (±48 Mg ha⁻¹) the highest AGB-values have been found in the preserved forest area within a National Park, followed by 297 (±83) Mg ha⁻¹ at the former clear cut site. Lowest AGB has been calculated for the area with past selective logging: 204 (±38) Mg ha⁻¹. Values calculated with the FAO standard equation showed the same trend but at a lower AGB level. Our results based an a small scale approach suggest that biomass productivity can recover in a forest which was completely cleared 60 years ago to reach AGB values up to a level that almost represents the situation in a preserved forest. Selective logging may slow down AGB accumulation and the effect is measurable after several decades.     

6种地形校正方法对雷竹林地上生物量遥感估算的影响

结合野外调查数据和Landsat 5 TM影像,分析6种地形校正方法(Teillet -回归,Cosine,C,SCS,SCS+C和Minnaert)对雷竹林地上生物量遥感估算的影响.结果表明:1)除Cosine和SCS方法存在校正过度现象,其余4种地形校正方法均具有良好的校正效果;2)6种地形校正方法均可提高TM4,TM5与地上生物量的相关性,且RVI,NDVI和SAVI这3种植被指数与生物量之间的相关性也得到改善;3)与原始影像相比,6种地形校正后的遥感数据都能不同程度地提高雷竹林生物量估算精度,以Teillet -回归校正后所建雷竹林地上部分生物量估算模型精度最高,相关系数从0.441提高到0.687,RMSE降低17％左右;4)尽管Cosine校正最大程度地提高了TM4,TM5与地上生物量的相关关系,但Cosine方法存在校正过度问题,Cosine校正后雷竹林地上生物量遥感估算模型精度反而略低于Teillet -回归校正;5)虽然地形校正可提高植被指数与雷竹林地上生物量之间的相关性,但所选5种植被指数均未入选雷竹林地上生物量遥感估算模型的变量,这与雷竹林较高的密度有关.     

Synergistic use of very high-frequency radar and discrete-return lidar for estimating biomass in temperate hardwood and mixed forests

• Introduction   

Accurate estimation of aboveground biomass is essential to better understand the carbon cycle in forest ecosystems.     

Profiles of carbon stocks in forest, reforestation and agricultural land, Northern Thailand

A study was conducted to assess carbon stocks in various forms and land-use types and reliably estimate the impact of land use on C stocks in the Nam Yao sub-watershed (19°05'10"N, 100°37'02"E), Thailand. The carbon stocks of aboveground, soil organic and fine root within primary forest, reforestation and agricultural land were estimated through field data collection. Results revealed that the amount of total carbon stock of forests (357.62 ± 28.51 Mg·ha-1, simplified expression of Mg (carbon)·ha-1) was significantly greater (P＜ 0.05) than the reforestation (195.25 ±14.38 Mg·ha-1) and the agricultural land (103.10±18.24 Mg·ha-1). Soil organic carbon in the forests (196.24 ±22.81 Mg·ha-1) was also significantly greater (P＜ 0.05) than the reforestation (146.83± 7.22 Mg·ha-1) and the agricultural land (95.09 ± 14.18 Mg·ha-1). The differences in carbon stocks across land-use types are the primary consequence of variations in the vegetation biomass and the soil organic matter. Fine root carbon was a small fraction of carbon stocks in all land-use types. Most of the soil organic carbon and fine root carbon content was found in the upper 40-cm layer and decreased with soil depth. The aboveground carbon(soil organic carbon: fine root carbon ratios (ABGC: SOC: FRC), was 5:8:1, 2:8:1, and 3:50:1 for the forest, reforestation and agricultural land, respectively. These results indicate that a relatively large proportion of the C loss is due to forest conversion to agricultural land. However, the C can be effectively recaptured through reforestation where high levels of C are stored in biomass as carbon sinks, facilitating carbon dioxide mitigation.     

Aboveground biomass of three conifers in the Qianyanzhou plantation, Jiangxi Province, China

Regressive models of the aboveground biomass for three conifers in subtropical China—slash pine (Pinus elliottii), Masson pine (P. massoniana) and Chinese fir (Cunninghamia lanceolata)—were established. Regression analysis of leaf biomass and total biomass of each branch against branch diameter (d), branch length (L), d ³ and d ² L was conducted with functions of linear, power and exponent. A power law equation with a single parameter (d) was proved to be better than the rest for Masson pine and Chinese fir, and a linear equation with parameter (d ³) is better for slash pine. The canopy biomass was derived by adopting the regression equations to all branches of each individual tree. These kinds of equations were also used to fit the relationship between total tree biomass, branch biomass, foliage biomass and tree diameter at breast height (D), tree height (H), D ³ and D ² H, respectively. D ² H was found to be the best parameter for estimating total biomass. However, for foliage biomass and branch biomass, both parameters and equation forms showed some differences among species. Correlations were highly significant (P<0.001) for foliage biomass, branch biomass and total biomass, among which the equation of the total biomass was the highest. With these equations, the aboveground biomass of Masson pine forest, slash pine forest and Chinese fir forest were estimated, in addition to the allocation of aboveground biomass. The above-ground biomass of Masson pine forest, slash pine forest and Chinese fir forest was 83.6, 72.1 and 59 t/hm² respectively, and the stem biomass was more than the foliage biomass and the branch biomass. The underground biomass of these three forests which estimated with others’ research were 10.44, 9.42 and 11.48 t/hm², and the amount of carbon-fixed were 47.94, 45.14 and 37.52 t/hm², respectively. __________ Translated from Chinese Journal of Applied Ecology, 2006, 17(8): 1382–1388 [译自: 应用生态学报]     

Establishment of planted Norway spruce and Scots pine seedlings: effects of light environment,fertilisation, and orientation and distance with respect to shelter trees

The effects of stand stem density (SSD), orientation and distance with respect to shelter trees, and fertilisation on planted Pinus sylvestris and Picea abies seedlings were examined at two sites, one with a southerly aspect (64°14′N, 19°46′E, 225 m a.s.l.) and one with a northerly aspect (64°09′N, 19°36′E, 274 m a.s.l.) in boreal forests in Sweden. The damage and growth were compared at these sites in stands with three SSD’s and different light regimes: uncut forest (SSD 500, ~500 stems/ha), shelterwood (SSD 150,~150 stems/ha), and clear-cut (SSD, 0 stems). Half of the seedlings were irrigated with fertiliser (10 mM N). Fertilisation and SSD affected the height growth of P. abies, since fertilised seedlings in SSD 0 grew the most (22.2 cm). Fertilised seedlings in SSD 0 also generally had the greatest biomass (twigs, leading shoot and needles), even P. sylvestris seedlings on the North slope, where fertilised and unfertilised pine seedlings in SSD 0 had 62.6 and 39.7 g biomass, respectively. P. sylvestris increased about 150% in dry mass of leading shoot of the increase of P. abies with equal height growth, when comparing SSD 150 and SSD 0. The results indicate that the general conditions of the stand have stronger effects on the growth of planted seedlings than their orientation and distance with respect to the nearest tree and that light requirements cannot be moderated by fertilisation. We postulate that a system in which forest gaps are formed under a shelterwood could provide a way to regenerate forests that exploits the beneficial features of both shelter trees and clear-cuts.     

C and N stocks under three plantation forest ecosystems of Chinese fir, Michelia macclurei and their mixture

Chinese fir (Cunninghamia lanceolata), a type of subtropical fast-growing conifer tree, is widely distributed in South China. Its plantation area covers more than 7 × 10⁶ hm², accounting for 24% of the total area of plantation forests in the country. In recent decades, the system of successive plantation of Chinese fir has been widely used in southern China due to anticipated high economic return. However, recent studies have documented that the practice of this system has led to dramatic decreases in soil fertility and forest environment as well as in productivity. Some forest ecologists and managers recognize the ecological role performed by broadleaf trees growing in mixtures with conifers, and a great deal of studies on mixture effects have been conducted, particularly on mixture species of temperate and boreal forests, but these research results were not completely consistent. Possibilities include dependence of the mixture effects in large part to specific site conditions, the interactions among species in mixtures and biological characteristics of species. Although some researchers also studied the effects of mixtures of Chinese fir and broadleaf tree species on soil fertility, forest environment and tree growth status, little information is available about the effects of Chinese fir and its mixtures with broadleaves on carbon and nitrogen stocks. The experimental site is situated at the Huitong Experimental Station of Forest Ecology, Chinese Academy of Sciences, Hunan Province (26°40′–27°09′ N, 109°26′–110°08′ E). It is located at the transition zone from the Yunnan-Guizhou Plateau to the low mountains and hills of the southern bank of the Yangtze River at an altitude of 300–1,100 m above mean sea level. At the same time, the site is also a member of the Chinese Ecosystem Research Network (CERN), sponsored by the Chinese Academy of Sciences (CAS). This region has a humid mid-subtropical monsoon climate with a mean annual precipitation of 1,200–1,400 mm, most of the rain falling between April and August, and a mean temperature of 16.5°C with a mean minimum of 4.9°C in January and a mean maximum of 26.6°C in July. The experimental field has red-yellow soil. After a clear-cutting of the first generation Chinese fir (Cunninghamia lanceolata) plantation forest in 1982, three different plantation forest ecosystems, viz. mixture of Michelia macclurei and Chinese fir (MCM), pure Michelia macclurei stand (PMS) and pure Chinese fir stand (PCS), were established in the spring of 1983. A comparative study on C and N stocks under these three plantation forest ecosystems was conducted in 2004. Results showed that carbon stocks were greater under the mixtures than under the pure Chinese fir forest and the pure broad-leaved forest, and the broadleaves and the mixtures showed higher values in nitrogen stocks compared with the pure Chinese fir forest. The spatial distribution of carbon and nitrogen stocks was basically consistent, the value being greater in soil layer, followed by tree layer, roots, understory and litter layer. The carbon and nitrogen stocks in soil layer were both highly correlated with the biomass in understory and litter layer, indicating that understory and forest litterfall exerted a profound effect on soil carbon and nitrogen stocks under plantation ecosystems. However, correlations among soil carbon, nitrogen stocks and below ground biomass of stand have not been observed in this study. Translated from Acta Ecologica Sinica, 2005, 25(12): 3,146–3,154 [译自: 生态学报]     

Digital Terrain Analysis Based on DEM

The digital elevation model (DEM), an important source of information, is usually used to express a topographic surface in three dimensions and to imitate essential natural geography. DEM has been applied to physical geography, hydrology, ecology, and biology. This study analyzed digital elevation data sources and their structure, the arithmetic of terrain attribute extraction from DEM and its applications, and DEM’s error and uncertainty algorithm. The Hayachinesan mountain area (in northeastern Japan) was chosen as research site, and the focus was on terrain analysis and the impacts of DEM resolution on topographic attributes, analyzed using TNTmips GIS software (MicroImage, Inc., USA) and “Digital Map 25,000” (published by the Geographical Survey Institute of Japan in 1998). The results show that: (1) DEM is a very effective tool for terrain analysis: many terrain attributes (such as slope, aspect, slope type, watershed, and standard flow path) can be derived, and these attributes can be displayed with both image and attribute databases, with the help of GIS; (2) DEM resolution has a great influence on terrain attributes. The following details are shown: (a) DEM resolution has a significant effect on slope estimation: the average slope becomes smaller and the standard deviation becomes larger when DEM resolution changes from fine to coarse, and the different impacts of DEM resolution on different slope ranges can be classified into three gradient classes: 0–10° (underestimated slope), 10–35° (overestimated slope), and >35° (little impact on slope estimation); (b) DEM resolution has little effect on aspect estimation, but flat areas become larger when DEM resolution changes from fine to coarse; and (c) the quantity of hydrologic topography information declines as DEM resolution decreases. Translated from Journal of Beijing Forestry University, 2005, 27(2) (in Chinese)     

Aboveground biomass and carbon stock in the largest sacred grove of Manipur,Northeast India

Aboveground biomass and carbon stock in the largest sacred grove of Manipur was estimated for trees with diameter [10 cm at 1.37 m height.The aboveground biomass,carbon stock,tree density and basal area of the sacred grove ranged from 962.94 to 1130.79 Mg ha~(-1),481.47 to 565.40 Mg ha~(-1) C,1240 to 1320 stem ha~(-1) and79.43 to 90.64 m~2 ha~(-1),respectively.Trees in diameter class of 30–40 cm contributed the highest proportion of aboveground biomass(22.50–33.73%).The aboveground biomass and carbon stock in research area were higher than reported for many tropical and temperate forests,suggesting a role of spiritual forest conservation for carbon sink management.     

Modeling compatible single-tree aboveground biomass equations for masson pine (Pinus massoniana) in southern China

Because of global climate change,it is necessary to add forest biomass estimation to national forest resource monitoring.The biomass equations developed for forest biomass estimation should be compatible with volume equations.Based on the tree volume and aboveground biomass data of Masson pine(Pinus massoniana Lamb.) in southern China,we constructed one-,two-and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations by using error-in-variable simultaneous equations.The prediction precision of aboveground biomass estimates from one variable equation exceeded 95%.The regressions of aboveground biomass equations were improved slightly when tree height and crown width were used together with diameter on breast height,although the contributions to regressions were statistically insignificant.For the biomass conversion function on one variable,the conversion factor decreased with increasing diameter,but for the conversion function on two variables,the conversion factor increased with increasing diameter but decreased with increasing tree height.     

Carbon accumulation in aboveground and belowground biomass and soil of different age native forest plantations in the humid tropical lowlands of Costa Rica

Generic or default values to account for biomass and carbon accumulation in tropical forest ecosystems are generally recognized as a major source of errors, making site and species specific data the best way to achieve precise and reliable estimates. The objective of our study was to determine carbon in various components (leaves, branches, stems, structural roots and soil) of single-species plantations of Vochysia guatemalensis and Hieronyma alchorneoides from 0 to 16 years of age. Carbon fraction in the biomass, mean (±standard deviation), for the different pools varied between 38.5 and 49.7% (±3 and 3.8). Accumulated carbon in the biomass increased with the plantation age, with mean annual increments of 7.1 and 5.3 Mg ha⁻¹ year⁻¹ for forest plantations of V. guatemalensis and H. alchorneoides, respectively. At all ages, 66.3% (±10.6) of total biomass was found within the aboveground tree components, while 18.6% (±20.9) was found in structural roots. The soil (0–30 cm) contained 62.2 (±13) and 71.5% (±17.1) of the total carbon (biomass plus soil) under V. guatemalensis and H. alchorneoides, respectively. Mean annual increment for carbon in the soil was 1.7 and 1.3 Mg ha⁻¹ year⁻¹ in V. guatemalensis and H. alchorneoides. Allometric equations were constructed to estimate total biomass and carbon in the biomass which had an R ²aj (adjusted R square) greater than 94.5%. Finally, we compare our results to those that could have resulted from the use of default values, showing how site and species specific data contribute to the overall goal of improving carbon estimates and providing a more reliable account of the mitigation potential of forestry activities on climate change.     

Object-based forest biomass estimation using Landsat ETM+ in Kampong Thom Province, Cambodia

Information about forest biomass distribution is important for sustainable forest management and monitoring fuelwood supply. The objective of this study is to develop an accurate forest biomass map for Kampong Thom Province, Cambodia. We used a new technique (object-based approach) and a conventional technique (pixel-based approach) for the estimation of forest biomass using Landsat Enhanced Thematic Mapper Plus (ETM+). The object-based approach created segments of images, and calculated statistical and textural attributes. Our results showed that estimation accuracy of the object-based approach, with the use of band 1 and an exponential fit, was the best (R ² = 0.76), and this accuracy was comparable to that of the pixel-based approach (R ² = 0.67). Although several textural variables were related to forest biomass, they did not contribute significantly to improvement of estimation accuracy. However, the object-based method can be used for image segmentation so that the image objects are spectrally more homogeneous within individual regions than with their neighbors. Hence, they can be regarded as management units for policy-related spatial decisions. Therefore, it is possible to select either of the two methods depending upon what the situation demands.     

Restoration and Rebuilding of Forestry Ecological System in Heilongjiang Province

IntroductionHeilongiiangProvinceisoneoftheIargestforestryregionsinChina,whichisnamedaspreciousregionsofforestsdeposits.Greatamountoftimberandrnanykindsofforestproductshavebeenproducedthere.Thedenseforestshaveprovidednaturaldefenseforthesucceedinghighand's…     

Above-Ground Biomass of Mountain Beech (Nothofagus solandri (Hook.f.) Oerst. var. cliffortioides (Hook.f.) Poole) in Different Stand Types Near Timberline in New Zealand

In the alpine timberline ecotone at 1350 m in the CraigieburnRange, New Zealand, four distinct mountain beech stand types(a pole, a coppice, a high forest and a shrublike stand) wereanalysed for stand biomass and leaf area by means of allomet-ricregressions based on stem diameter. Differences between stand types in terms of age, structure,biomass and leaf area are interpreted as development stagesafter stand breakdowns due to external impacts. Vegetative reproduction,mainly coppicing, plays an important part in stand regeneration. The young pole stand had 177 t ha^–1, the coppice stand272 t ha^–1, and the mature high forest stand 323 t ha^–1aboveground dry weight. A low mountain beech shrub stand withgnarled, windshaped dwarf trees had only 135 t ha^–1. Foliageaccounted for only 3–5% in all stands, the leaf area indexwas also low, at 3.0 in the shrub stand and 3.7–7.4 inthe forest stands. The low foliage proportion is consideredto be a response to the harsh environment.     

Aboveground biomass estimation of small diameter woody species of tropical dry forest

Estimation of accurate biomass of different forest components is important to estimate their contribution to total carbon stock. There is lack of allometric equations for biomass estimation of woody species at sapling stage in tropical dry forest (TDF), and therefore, the carbon stored in this forest component is ignored. We harvested 46 woody species at sapling stage in a TDF and developed regression models for the biomass estimation of foliage, branch, bole and the total aboveground part. For foliage and branch biomass, the models with only stem diameter as estimator showed greater R ². For bole and aboveground biomass, the models including wood specific gravity or wood density exhibited higher R ² than those without wood density. Also, the model consisting of wood density, stem diameter and height had the lowest standard error of estimate for bole and aboveground biomass. Moreover, the R ² values are very similar among models for each component. The measurement error of height and the use of a standard value of wood density together may introduce more than 2 % error into the models. Therefore, we suggest using diameter-only model, which may be more practical and equally accurate when applied to stands outside our study area.     

Individual tree aboveground biomass for <Emphasis Type="Italic">Castanopsis indica</Emphasis> in the mid-hills of Nepal

Quantitative information of tree biomass is useful for management planning and monitoring of the changes in carbon stock in both forest and agroforestry systems. An estimate of carbon stored in these systems can be useful for developing climate change mitigation strategies. A precise estimate of forest biomass is also important for other issues ranging from industrial forestry practices to scientific purposes. The individual tree-based biomass models serve as fundamental tools for precise estimates of carbon stock of species of interest in forest and agroforestry systems. We developed individual tree aboveground biomass models for Castanopsis indica using thirty-six destructively sampled tree data covering a wide range of tree size, site quality, growth stage, stand density, and topographic characteristics. We used diameter at breast height (DBH) as a main predictor and height-to-DBH ratio (a measure of tree slenderness) and wood density (a measure of stiffness and cohesiveness of wood fibres) as covariate predictors in modelling. We, hereafter, termed the biomass models with former two predictors as first category models (density independent models) and the models with all three predictors as second category models (density dependent models). Among various functions evaluated, a simple power function of the form \(y_{i} = b_{1} x_{i}^{{b_{2} }}\), in each category, showed the best fits to our data. This formulation, in each category, described most of the biomass variations (\(R_{adj}^{2}\) > 0.98 and RMSE < 72.2) with no significant trend in the residuals. Since both density dependent and density independent models exhibit almost similar fit statistics and graphical features, one of them can be applied for desired accuracy, depending on the access of the input information required by the model. Our biomass models are site-specific, and their applications should therefore be limited to the growth stage, stand density, site quality, stand condition, and species distribution similar to those that formed the basis of this study. Further research is recommended to validate and verify our model using a larger dataset with a wider range of values for site quality, climatic and topographic characteristics, stand density, growth stage, and species distribution across Nepal.     

基于印度遥感卫星IRS—P6的森林生物量估测模型研究

印度遥感卫星IRS—P6的LISS3数据由于其较高的空间分辨率和相对较低的数据价格而受到广泛关注,而利用LISS3数据估测森林生物量的研究报道较少。以高黎贡山自然保护区常绿阔叶林为研究对象,以2006年印度卫星IRS—P6的LISS3影像为主要数据源,利用地面样地胸径每木调查数据,结合生物量相对生长式,得出样地生物量。通过遥感数据提取4个波段的光谱值、6种植被指数,从DEM获取的海拔、坡度、坡向,共13个遥感及地学因子。在此基础上,提取13个因子的主成分,以前5个主成分值作自变量,建立主成分与地面生物量的回归模型,模型经方差分析及相关性检验,达到显著相关水平,相关系数R=0．7129。     

Above- and belowground biomass measurements in an unthinned stand of Sitka spruce (<Emphasis Type="Italic">Picea sitchensis</Emphasis> (Bong) Carr.)

Reporting carbon (C) stocks in tree biomass (above- and belowground) to the United Nations Framework Convention on Climate Change (UNFCCC) should be transparent and verifiable. The development of nationally specific data is considered ‘good practice’ to assist in meeting these reporting requirements. From this study, biomass functions were developed for estimating above- and belowground C stock in a 19-year-old stand of Sitka spruce (Picea sitchensis (Bong) Carr.). Our estimates were then tested against current default values used for reporting in Ireland and literature equations. Ten trees were destructively sampled to develop aboveground and tree component biomass equations. The roots were excavated and a root:shoot (R) ratio developed to estimate belowground biomass. Application of the total aboveground biomass function yielded a C stock estimate for the stand of 74 tonnes C ha⁻¹, with an uncertainty of 7%. The R ratio was determined to be 0.23, with an uncertainty of 10%. The C stock estimate of the belowground biomass component was then calculated to be 17 tonnes C ha⁻¹, with an uncertainty of 12%. The equivalent C stock estimate from the biomass expansion factor (BEF) method, applying Ireland’s currently reported default values for BEF (inclusive of belowground biomass), wood density and C concentration and methods for estimating volume, was found to be 60 tonnes C ha⁻¹, with an uncertainty of 26%. We found that volume tables, currently used for determining merchantable timber volume in Irish forestry conditions, underestimated volume since they did not extend to the yield of the forest under investigation. Mean stock values for belowground biomass compared well with that generated using published models.