Research On The Forest Biomass And Carbon Storage In Xiaolong Mountains, Gansu Province

Global carbon cycle is one of the core issues in the researches of global climate changes and the carbon cycle in forest ecosystem is an important part of the global carbon cycle. In present studies, there are still a lot of uncertainties in the studies of global carbon cycle and these uncertainties also exist in the estimats of the size of the regional forest ecosystem carbon storage and the exchange flux between the forest ecosystem and CO₂. Therefore to estimate the gross of carbon storage in regional forest ecosystem and its exchange flux with other carbon storages, all the while, is the hot and difficult problem.This paper does investigations on eight forest stands of Xiaolong Mountains, Gansu Province: Quercus aliena var. acuteserrata, Pinus tabulaeformis, Quercus variabilis, Populus sp. and Betula sp., Larix sp., Pinus armandii, Picea sp. and Abies sp., and other broad leaved mixed forest. It focuses on stand biomass estimate, foundation of tree layer biomass model with compatibility, organic carbon ratio measures of tree layer, shrub layer and herb layer, litter fall carbon ratio measures, the evaluation of the density and amount about regional forest ecosystem carbon storage and the allocation. It is aimed to find an appropriate way to exactly estimate the size of carbon storage of the regional forest ecosystem basing on the forest resource inventory data in the hope of supplying some data for researches on carbon sequestration functions of the regional forest ecosystem and carbon circle of the ecological geographic regional forest ecosystem in China, and providing the foundation and reference for the regional environment construction, the regional forest ecosystem carbon storage management policy and the negotiation of the carbon storage trade that China government participated in. After years of extensive studies,we reached the following conclusings:Part 1 Biomass estimates(1) In eight stands in Xiaolong Mountains, there are close relationship among single wood biomass (W) and trunk diameter (D), and diameter-height (D²H). With eleven mathematical models, we simulate regression equations about W-D-D²H correlations and results show that the correlations are prominent, and the simulative effect of Power equation is best.(2) In the sequence of the eight stands: Quercus aliena var. acuteserrata, Pinus tabulaeformis, Quercus variabilis, Populus sp. and Betula sp., Larix sp., Pinus armandii, Picea sp. and Abies sp., and other broad leaved mixed forest:Their tree layer biomass are: 81.8388, 60.6976, 79.7980, 75.3828, 67.3706, 67.9786, 94.3733, 96.5533 t hm^-2 separately.Their shrub layer biomass are: 1.5126, 0.9884, 1.2504, 1.3746, 1.3618, 1.3691, 1.3746, 1.59441 hm^-2 separately.Their herb layer biomass are: 0.1208, 0.2266, 0.1738, 0.2043, 0.2658, 0.196 8, 0.2043, 0.1393 t hm^-2 separately.Their stand biomass are: 84.0472,62.4424, 81.7747,77.4367,68.9982,70.0695, 96.4865, 98.7235 t hm^-2 separately.Part 2 Foundation of Tree Layer Biomass Prediction Model Based on Forest Resource Inventory Data(1) Graphic Analysis, Correlative Analysis and Regression Analysis about eight stands in Xiaolong Mountains show that there exists a prominent linear relationship between species wood biomass (W) and living forest volume (V). With five evaluation indexes, i.e. Correlation index, Correlation coefficient, Residual standard deviation, Average fractional error and Prediction accuracy, by the comprehensive comparsion of the simulative results about regression equations, and basing on forest resourceinventory statistical data for forest biomass estimates (W～V), we build that the optimal model in the form of W=a+bV, and we prove theoretically that the forest biomass linear estimation model can be directly applied to the regional scale.(2) As far as estimate effects as concerned, the linear models with compatibility of W^V can be used to calculate tree layer biomass by using the sample plots data, stand volume and other information directly, so as to avoid the disadvantage about the traditional methods which cause the destruction of forest resources. Therefore this improved approach is of higher theoretical and practical value.(3) Researches of the eight stands in Xiaolong Mountains show that there is a better correlation between average net growth (â–³W_total) and overall biomass (W_total).We make use of this relationship to build several mathematical models about eight stands for â–³W_total ～ W_total , which best model shows that correlations between averagenet increase in the total amount of forest biomass in different stand are different. Those of Quercus aliena var. acuteserrata, Pinus tabulaefonnis, Larix sp., Picea sp. and Abies sp., are Power model related. Those of Quercus variabilis, Populus sp. and Betula sp., Pinus armandii, are linear model related. And other broad leaved mixed forest are Exponential model related.Compared with previous researches, results show that, the correlativity between average stand net growth and volume of stand biomass in different area is different.Part 3 Measures of Carbon content Rate(1) Using high-precision element analytical method (Dry Combustion method) to measure the carbon content rate of different components (stems, branches, leaves, barks, roots) of eight stands of Xiaolong Mountains, we first acquire accurate value of organic carbon content rate of 13 tree species, 14 shrub species, 10 herbaceous plants, and the forest litters of 7 stand types. We also systematically analyze the changing characteristics of carbon content rate of individual tree and stand.(2) The average organic carbon content rate of 13 tree species, the main standtypes of Xiaolong Mountains, separately, Quercus aliena var. acuteserrata, 0.4653; Pinus tabulaeformis, 0.5049; Quercus variabilis, 0.4755; Betula platyphylla, 0.4985; Betula albo-sinensis, 0.4889; Larix leptolepis, 0.4963; Pinus armandii, 0.4962; Picea asperata, 0.4906; Abies chensiensis, 0.4907; Fraxinus mandschurica, 0.4647; Cornus macrophylla, 0.4501, Acer mono, 0.4689; Quercus liaotungensis, 0.4632. The average organic carbon content rate of 14 shrubs is 0.4446. The average organic carbon content rate of 10 herb plants is 0.3270. The average carbon content rate of litter fall of 7 stands is 0.4221. The average carbon content rate of tree layer of 8 stands separately, Quercus aliena var. acuteserrata, 0.4676; Pinus tabulaeformis, 0.4976; Quercus variabilis, 0.4681; Populus sp. and Betula sp., 0.4837; Larix sp., 0.4903; Pinus armandii, 0.4926, Picea sp. and Abies sp., 0.4902; and other broad leaved mixed forest, 0.4682; The average carbon content rate of 5 coniferous forests is 0.4927. The average carbon content rate of broad leaved forests of 8 stands is 0.4719.(3) For the objects studied in this article, the variation coefficient of carbon content rate of components is within 1.55%～4.91%. The variation coefficient between species is within 1.75%～6.59%. The average carbon content rate of broad leaved forest is close to 0.47. The average carbon content rate of coniferous forest is close to 0.49. Compared to domestic and universal application of the two types forest biomass conversion factor of carbon content rate, 0.45 and 0.5, using 0.48 as conversion coefficients to estimate the total forest tree layer of carbon storage may make estimate result in better effects. for more accurate, we should adopt corresponding conversion coefficients of carbon content rate according to different region and different forest style.(4) Carbon content rates of different tree species, at random distribution, do not show regular changing orderliness and are determined by the characteristics of the trees characters. Judged from the morphological characteristics of the species, component carbon content rate of coniferous forest is higher than that of broad leaved forest, shrub forest and herbaceous plants. The average carbon content rate of conifer species composition is generally in the range between 1.47% and 3.40%, higher than that of broad leaved forest. Coniferous forest corresponding rate is also higher thanthe average carbon content rate of broad leaved forest. The average carbon content rate of species (arithmetic mean) and that of stands, (by weighted average of biomass volume) is very close. In the 13 tree species in this research, the margin does not exceed 1.81%.(5) Compared with previous researches, in forest vegetation of Xiaolong Mountains, the carbon content rate of species and stands both are lower than those in North China. We may conclude that there exists different carbon content rate of the same species in different areas. There are also differences in the carbon content rate within the same stand. The estimation accuracy of forest carbon storage is closely related to estimation of the regional scale module. Estimation accuracy based on Regional scale or regional forest ecosystems scale is better. Carbon content rate of tree species may be related with the growth state, i.e. carbon content rate may be related with latitude, altitude, rainfall and other climate-related conditions, all of which affect tree growth.Part 4 Carbon Storage Estimates(1) The total carbon density of forest vegetation about the eight types in Xiaolong mountains weighted by the area in sequence: Picea sp. and Abies sp., 46.7342 t hm^-2 ; other broad leaved mixed forest, 46.1454 t hm^-2 . Quercus aliena var. acuteserrata, 39.2335 t hm^-2; Quercus variabilis, 38.1974 t hm^-2; Populus sp. and Betula sp., 37.3032 t hm^-2. Pinus armandii, 34.4068 t hm^-2. Larix sp., 33.7259 t hm^-2; Pinus tabulaeformis, 30.9395 t hm^-2.(2) Carbon storage of forest vegetation in Xiaolong mountains weighted by the the area in sequence: Quercus aliena var. acuteserrata, 7.0054 Tg, other broad leaved mixed forest, 3.5959 Tg; Pinus tabulaeformis, 1.4466 Tg; Quercus variabilis, 0.6492 Tg; Populus sp. and Betula sp., 0.2642 Tg. Larix sp., 0.2105 Tg; Pinus armandii, 0.1656 Tg; Picea sp. and Abies sp., 0.0208 Tg. The density of carbon storage of forest vegetation in each stand is 39.4254 t hm^-2. The total carbon storage is 13.3579 Tg.(3) Research results show that, the average density of carbon storage in tree layerof 8 stands in Xiaolong Mountains is close to the estimated carbon density of other forests in China and in the world.Part 5 Highlights(1) This dissertation filled the research vacancy on forest biomass and carbon storage of western Qinling Mountain in China.(2) This dissertation provided some basic data for research on carbon cycle of forest ecosystem in west of China.(3) This dissertation made an innovative progress in estimating the forest stands biomass of Xiaolong Mountains with forest resource inventory data, found linear model with regional biomass compatibility in the form of W = a + bV with high accuracy, and we has proved from theory that the model W = a + bV can be directly applied to the regional scale and it has important reference value for the biomass and carbon storage study about regional ecosystem.