上海翻譯公司完成林業(yè)區(qū)域“區(qū)域林業(yè)碳匯源計量體系”簡介英文翻譯

Regional Forestry Carbon Sink / Source Measurement System

 

Executive Report

 

 

Implementation Units

The Nature Conservancy

Sichuan Forestry Survey and Planning Institute

Institute of Geographic Sciences and Natural Resources Research

Sichuan Academy of Forestry

Chengdu Institute of Biology, Chinese Academy of Scienc

Funding Agencies:

 

 

June 2014, Beijing 

 

Content 

Foreword

Project Objectives and Technical Route

Major Activities

Activity I: carrying out survey of land-use changes and forestry carbon accounting methodologies, parameters, metering system or model, including:

Activity II: assessment of land use changes in Sichuan province and forestry data and its applicability

Activity III: based on the above research activities, the land use changes and forestry data of Sichuan province, the application model and related costs to develop a framework for measuring carbon models the IPCC Third tier methodologies, as well as a carbon measurement framework system.

Activity IV: land use changes and forestry data collection, interpretation, standardization, the confirmation of forestry land use transition matrix of Sichuan province.

Activity V: collecting all the research literature on Chinese biomass and biomass equations and abroad, carrying out comprehensive analysis and establishing a national-scale biomass and litter equations and other carbon accounting parameters. These parameters are used to the measurement of way I in this carbon measurement system.

Activity VI: Sichuan province's forest biomass, shrub biomass, undergrowth shrub and grass, litter supplementary survey, measurement and model establishment. The project's measurement and modeling is used to initialize Method II sample tree in measurement system, carbon measurement in sample place and Method III model.

Activity VII: organic forest soil carbon research, investigation and measurement

Activity VIII: Measurement of 49 kinds of plant physiological and ecological parameters: measurement of the thirty-two categories of field trees, fifteen kinds of shrubs and four kinds of herbaceous plants' photosynthesis A-Ci curve (net photosynthetic rate and CO2 concentration), dark respiration, stomatal conductance, maximum carboxylation rate, maximum electron transport rate, physiological and ecological parameters such as leaf area and nitrogen content of various organs and carbon / nitrogen ratio. Activities IX: collecting and purchasing the 2010 historical climate data, developing, verifying and calibrating the radioactive transfer model, checking the spatial data of climate stations.

Activities X: researching on ecological process model and remote sensing model, developing Sichuan land use change and forestry carbon accounting model.

Activities XI: developing a linking program, carrying out clustering and overlay analysis, determining the minimum 10,540,000 calculating spatial units, improving inputs and outputs of model circulation structures.

Activities XII: running the model, Sichuan carbon sinks for the past twenty years and the results were analyzed, as the methodology of third level in this measurement system.

Activities XII: Development of first methodology based on forest resources statistics and second methodology based on forest resources survey sample place and sample tree statistics including relevant parameters (tree density, biomass expansion equation, root to shoot ratio, carbon content, etc.). Sichuan province's past 20 years of carbon sinks are measured, and the results are analyzed.

Activity XIII: applying a user-friendly interface, developing a software-use system , so that to enable the existing first-level and second-level methodology of computing, as well as the query and output of three levels of long time series methodology results.

Activity XIV: conducting a comprehensive analysis of three methodologies and drafting the project technical reports. ,which includes the technical description reports of three methodologies(more than 400 pages) and the results portfolio.

Activity XV: project research conferences: during the execution of the project, a large number of seminars were held, some important seminar were:

Activity XVI: International training: six project technical staff participated in CBM-CFS3 training held in Pacific Forestry Centre in Victoria, Canada, from February 27 to March 1 in 2012. 21

Activity XVII: during the climate change conference in Bonn, the multi-party forest carbon measurement conference was held on June 6, 2014 , introducing the results of this project.

Activity XVIII: The international jury .

Activity XVIIII: project summary conference

Main Outcomes

Foreword

Regular reporting of greenhouse gas inventories are the basic obligations for countries to fulfill The United Nations Framework Convention on Climate Change(UNFCCC). The Chinese government also asks all provinces and regions to submit regular greenhouse gas inventories. Land use changes and forestry carbon sinks are an important part of the greenhouse gas inventories of all countries and provinces and regions within the country. Changes in land use and forestry are extremely complex and has high uncertainty. China has a vast, complex terrain with a huge geographic span from tropical to cold temperate, from humid areas to the arid and semiarid regions and China has various vegetation types, making the measurement of land use change and forestry carbon sinks extremely complex and difficult.

To improve the accuracy, reliability, transparency and comparability of the countries compilation of national greenhouse gas inventories, the Intergovernmental Panel on Climate Change (IPCC) has published and updated the Compilation Guidelines for National Greenhouse Gas Inventories since 1995 for several times. The greenhouse gas sources are measured according to three tier methodology ranking from low to high. Among which Tier 1 carries out calculation through application of IPCC calculation methods and international parameters, Tier 2 carries out calculation through application of IPCC calculation method and country parameters, the Tire 3 methodology carries out calculation through application of country methods and parameters, including the establishment of a national carbon accounting system or model, and the application of satellite remote sensing and GIS, etc.

Directing at land-use change and forestry, the major developed countries, such as Canada, Australia, USA, UK etc. in whole or in part adopt Tire 3 methodology, especially in Canada, Australia and other countries national carbon accounting system or model are established. China has submitted two national greenhouse gas inventories to UNFCCC, IPCC Tier 2 methodology is mainly used in land-use change and forestry, the conformability can be up to 50%. In compiling the provincial greenhouse gas inventories, similar methods are applied.

In 2009, State Forestry Administration launched the "forestry carbon sink metering and  monitoring system construction". The project was started in 2009 and was listed as one of the first four pilot provinces by the State Forestry Administration. Sichuan has huge forest resources in China, its forest areas accounting for 8.4% of the country's total forest areas and its storage accounting for 12% of the total national amount. Sichuan province has complex terrain, from the plains, hills, low altitude mountains, medium altitude mountains to high altitude mountains, covering China's major ecosystem types. Therefore it has typical meaning to choose  Sichuan province as a demonstration province. The project aims to explore and establish a provincial or regional land-use change and forestry carbon accounting system in compliance with the highest level of IPCC methodology. The project is funded by the German Environment, Nature Conservation, Construction and Nuclear Safety Bureau  (BMUB), National Forestry Administration and Sichuan Forestry Department.

 

Project Objectives and Technical Route

Project objectives: taking Sichuan province as a demonstration province , based on the latest IPCC higher-level Guidelines methodology, to build a internationally recognized regional land-use change and forestry carbon measurement methodology (including the conversion between forest and other land types ) to meet possible future UNFCCC reporting and future intentional reporting requirements obligations, and to meet the information request by Sichuan Forestry to address climate change carbon sink forestry management policies, to improve China's ability to accounting land-use change and forestry carbon sinks.

Technical Route: Based on the survey of forest resources, monitoring systems, integrating multi-source, multi-outcome data on forest resources survey, remote sensing data, climate data, through forest carbon sink metering data base research to establish regional forestry carbon sink/source measurement platform applying to different scales and objects with gradually improved measurement and accuracy. Applying measurement system to carry out quantitative accounting about forestry carbon reserves and the spatial-tempetial trends of carbon sink/source, and comparing and verifying related measurement methods.

First, carrying out research on basic measurement data. ①carrying out informationization and standardization research on the data already have of forest, climate and remote sensing in the past forty years; ②carrying out the special research on the key elements such as biomass, forest soul organic carbon and physiological and ecological parameters.③ carrying out system. Second, carrying out research on measurement methods. ① taking the provincial statistical outcome as measurement, optimizing IPCC methodology recommended Tier 2 as the first level methodology of this measurement system; ② tinning the measurement down to the sample place and tree, carrying out systematic research on biomass, forest soil organic carbon measurement model, developing methodology based on the measurement of sample place and tree, that is the Tier 2 methodology of this measurement; ③ based on Tier 2 methodology ,integrating multi-source, multi-phase data such as remote sensing, climate data, physiological and ecological parameters and further extending to the measurement of spatial units to hill plots, developing Tier 3 methodology based on ecosystem process model.

 

Major Activities

Activity III: (Figure 1).

 

 

Tier 1 method                      tier 2 method                  tier 3 method

Figure 1 Carbon Measurement System Framework

 

Activity IV:

 

Table 1 Land Use Transition Matrix

Transferred out

 transferred in Woodland 非林地

Forest land Open forest land Shrub Land Other Forest Farmland grass land Waters Unused land Construction land

Forest stand Economic Forest Bamboo Forest

Forest stand 10738959 15284 42212 76376 26409 113562 23458 0 0 0 0 

Economic Forest 58114 699096 6814 0 7025 14390 111907 0 6994 0 27977 

Bamboo Forest 15114 4762 319755 7370 13433 13382 0 0 0 0 0 

Open forest land 200919 12135 0 375426 18916 14125 0 0 0 0 0 

Shrub Land 38793 0 18922 15725 6809678 30344 8897 0 710 0 710 

Other Forest 343867 48986 36822 25510 374312 1882915 47021 0 0 5225 7837

Farmland 246963 215096 61496 0 14617 109782 9528775 4862 14585 0 140987 

grass land 4842 0 0 0 4865 24911 8651706 0 0 0 0

Water area 0 0 0 0 4865 0 801133 0 0 0 0

Unused Land 4842 0 0 0 4865 0 5059338 0 0 0 0

Construction Land 0 0 0 0 0 0 815708 0 0 0 0

 

Figure 4  Land Use Change Figure

 

 

 

Table 2 Models for Single Plant Biomass

Species Position Form of the Equation

(B = single forest plant biomass, kg d.m.) Parameter Values Number of Samples Scope Modeling Location Literature Sources

a b c DBH (cm) Tree Height H (m) Forest Age (years)

Kashiwagi Aboveground 0.12703 0.79975 6~20 Dejiang,Guizhou province An Heping et al, 1991

Aboveground 0.1789 0.7406 16 - Yanting,Sichuan Shi Peili et al ,1996

Fujian Cypress Whole Forest 0.0614 0.9119 17 10~37 Anxi,Fujian Yang Zongwu et al, 2000

Whole Forest 0.13059 2.20446 28 4.4~14.8 4.4~9.3 6~15 Zhuzhou,Hunan Xue Xiukang et al, 1993

Arborvitae Aboveground 2.57097 0.03172 75 3.9~15.2 3.16~10.35 Yixian,Hebei Ma ZengWang et al, 2006

Thunbergii Whole Forest 0.1425 0.9181 18 33 Mouping,Shandong Xu Jingwei et al, 2005

Korean Pine Whole Forest 0.30891 0.79746 53 2.8~32.8 2.80~20.71 Liaoning Province Jia Yun et al, 1985

Aboveground 0.0615 0.3815 15 Baihe Forestry Bureau Chen ZhuanGuo et al, 1984

Armandi Whole Forest -2.9132 0.9302 86 4.0~38.3 3.0~20.1 14~57 Mt.Xiaolong, Gansu Cheng Tongren et al, 2007

Pinus Taiwanensis Whole Forest 0.02193 1.04658 6.0~17.95 5.75~9.15 Shangchen,Henan Zhao Tishun et al, 1989

Loblolly Whole Forest -2.77631 2.52444 50 9~17 Jurong,Jiangsu Kong Fanbin et al, 2003

Abies Aboveground 0.0387 0.9293 6.2~29.1 7.7~15.8 Ebian,Sichuan Su Ming et al, 2000

Fir Aboveground 0.0323 0.9294 20 Baihe Forestry Bureau Chen Zhuanguo et al, 1984

Spruce-fir Whole Forest -3.2999 0.9501 57 5.5~45.7 6.0~20.5 10~69 Mt.Xiaolong, Gansu Cheng Tongren et al, 2007

Redskins Spruce Aboveground 5.2883 -2.3268 0.5775 17 6~37 Suileng,Heilongjiang Mu Liqiang et al, 1995

.............

 

Bamboo Type Bamboo Species (group) Equation

(Kg d.m. plant -1) Modeling Location Literature

Large Diameter Scattered Bamboos Phyllostachys (bamboo)

Changning,Sichuan He Yaping et al, 2007

  

Northern Fujian Chen Hui et al, 1998

 

  

Northern Guizhou Wu  Qixin, 1983

 

Dagang Mountain, Jiangxi Wu Qixin

 

Nie Daoping, 1994

 

Zhejiang Zhou Guomo, 2006

W aboveground = -11.497 +3.0465 DBH +0.111 7DBH2 Jiangxi, southern Zhejiang Chen Shuanglin et al, 2004

W aboveground = -11.497 +3.0465 DBH +0.111 7DBH2 Southern Jiangxi Li Xi et al, 2007

Phyllostachys (bamboo)   

Xu DaoWang et al, 2004

Phyllostachys (Taiwan Makino)

 

Eastern Fujian Zheng Yushan et al, 1997

W aboveground = -11.497 +3.0465 DBH +0.111 7DBH2

W total = 0.000721DBH2.8382H-0.3078 Eastern Fujian Zheng Yushan and Liang Hongshen, 1998

Large Diameter Scattered Bamboos Dendrocalamus(Dendrocalamus Latiflorus) W aboveground=0.540093DBH1.9305

W aboveground=0.172139DBH1.5684H0.3916 Fujian, Hainan Liang Hongshen and Chen Xuekui, 1998

Dendrocalamopsis(bamboo)

 

Fujian Province Zheng Yushan et al, 1997

..... ..... ....... ..... .....

 

Table 3 Aboveground Biomass - Related Accumulation Equation

Species (group)

 

 

 

 

Spruce, Fir 4.165749 0.653489

Larch 1.641699 0.801589

Korean Pine 2.783807 0.695848

Pinus Sylvestris 2.844362 0.677522

Chinese Pine 2.632238 0.696978

Armandi 4.573398 0.583726

Mason Pine 1.827539 0.792975

Slash Pine 2.053735 0.772233

Other Pines(including Simao pine, Yunnan pine,Taiwan pine , red pine, black pine, mountain pine, Changbai pine, loblolly pine, etc.) 2.403794 0.723530

Kashiwagi 1.985272 0.794173

Chinese Fir 2.536998 0.674639

Other fir (metasequoia, cedar, redwood, Keteleeria, Taxodium) 2.694643 0.665671

Quercus 1.340549 0.896018

Birch 1.075562 0.902351

Sweetgum, Schima superba, ashtree, walnut, yellow pineapple 2.685404 0.741345

Camphor, Phoebe 4.292969 0.613426

Other hardwood class 3.322268 0.687013

Poplar 0.942576 0.871034

Eucalyptus 1.221362 0.869172

Achacia 2.969276 0.706251

Casuarina 6.932459 0.595017

Other soft broad categories (linden, sassafras, willow, paulownia, neem, etc.) 1.142254 0.876051

Mixed Coniferous 3.211378 0.6466

Mixed Conifer 2.208249 0.7437

 

Table 4 Litter— Aboveground Biomass  Related Accumulation Equation

Species (group)

 

 

 

 

Spruce Fir 20.7385 -0.0102

Larch 67.413 -0.0141

Chinese Pine 24.2749 -0.0217

Mason Pine 7.2175 -0.0067

Other Pines (including Simao pine, Yunnan pine, Taiwan pine , red pine, black pine, mountain pine, Changbai pine, loblolly pine, red pine, Pinus sylvestris, pine, slash pine, etc.) 13.1198 -0.009

Kashiwagi 3.7595 -0.0047

Fir and other fir 4.9897 -0.0025

Quercus 7.7325 -0.0048

Birch, sweet gum, lotus wood, Shui Hu Huang, camphor, phoebe, and other hardwood class 6.9779 -0.0043

Poplar 12.3106 -0.0069

Eucalyptus 24.697 -0.014

Achacia 9.5338 -0.0004

Other soft broadleaf categories (linden, sassafras, willow, paulownia, neem, etc.) 8.1286 -0.0046

Mixed Coniferous 31.4239 -0.0257

Broadleaf Mixed Forest 10.7653 -0.0057

Mixed Conifer 9.7816 -0.0063

 

Activity VI: carrying out supplementary survey, measurement and model establishment of Sichuan province's forest biomass, shrub biomass, undergrowth shrub and grass, litter. The project's measurement and modeling is used to initialize Method II sample wood in measurement system, carbon measurement in sample place and Method III model.

Forest biomass measurement adopting systematic sampling and typical sampling methods, gathering 1477 plants of  15 categories major forest tree types in field ,measuring ) biomass of various organs (trunks, branches, leaves, roots).

 

 

Establishing an interaction term (D2H) regression model of 15 species' (group) biomass in each plant organ of single plant and test factor of trees in the following Table 5.

Table 5 Biomass in each organ of single plant and tree test factor interaction term (D2H) regression model

Model Form: y = a (D2H) + b

Dominant Species (group)

Trunk Branch Leaf Root

a b a b a b a b

Spruce 0.0114 37.5626 0.0665 0.7169 0.0430 0.6821 0.0345 0.7994

Yunnan Pine 0.0120 6.9646 0.0349 0.7164 0.0578 0.5700 0.0723 0.5810

Kashiwagi 0.0187 2.4597 0.1317 0.5290 0.2205 0.4404 0.1011 0.5461

Chinese Fir 0.0101 5.0111 0.0728 0.5699 0.1656 0.4384 0.0577 0.6238

Mason Pine 0.0134 13.0579 0.015 0.8166 0.0263 0.6604 0.0525 0.7136

Larch 0.0111 4.7674 0.0474 0.618 0.0310 0.5661 0.0140 0.8206

Other pines 0.0206 1.6156 0.0047 0.9834 0.0051 0.9249 0.0048 1.0287

Other Birch 0.0121 30.3463 0.0114 0.8854 0.0076 0.7340 0.0184 0.8186

Quercus 0.0178 20.5873 0.0271 0.7687 0.0465 0.5449 0.0773 0.7186

Other Camphora 0.0168 6.7421 0.0257 0.7968 0.0312 0.6505 0.0086 0.9625

Phoebe Species 0.0174 6.1856 0.0207 0.7735 0.0271 0.6093 0.1408 0.6558

Populus 0.0093 25.8334 0.0423 0.7713 0.1318 0.4315 0.1157 0.6272

Eucalyptus 0.0169 -0.5333 0.0638 0.5490 0.2170 0.2665 0.0342 0.7237

Hard Broadleaf 0.0217 7.4214 0.0079 0.9124 0.0164 0.7005 0.0051 1.0082

Soft Broadleaf 0.0169 4.0108 0.0373 0.7287 0.0889 0.4166 0.0876 0.6115

 

Using forest resource to carry out survey on measurement data of sample place; through stepwise regression analysis, establishing the regression equation of thirty groups' tree measurement data D2H and geographical factors (lon, (lon) 2, (lat), (lat ) 2, (elev), (elev) 2) (Figure 6), and by fusing the above-described biomass (D2H) allometric equation of biomass, realizing biomass equations spatial extension.

Table 6 (D2H) and geographical factors related equation

Dominant Species (group)

(Group) Model Form: f（D2H）=aD2+bD+c（lon）2+d（lon）+e（lat）2+f（lat）+g（elev）2+h（elev）+K

A b c d e f g h K

Spruce 43.54 -926.04 -274.34 55283.76 / / / / -2772311.75

Fir 35.75 -636.49 -5.25 / 224.59 -13302 / / 256096.84

Hemlock 54.22 -1516.6 / / / / / / 11052.41

Yunnan Pine 32.84 -523.99 -181.87 36855.05 78.51 -4464.19 / / -1801214.28

Mason Pine 22.76 -199.65 16.19 -3492.23 / / - E +00 / 188793.11

High Moutain Cedar 19.62 -266.53 -89.94 18608.54 / / / 10.26 -978330.72

Low, High Mountain Cedar 20.61 -158.16 / / -0.3 / / -0.34 875.79

Larch 30.6 -524.14 / -1152.39 / / / / 128038.05

Chinese Fir 26.35 -295.47 -0.16 / / 30.81 / / 1835.8

Slash Pine 21.69 -170.02 -5502.2 1155200.23 10689.55 -620167.84 / / -51639309.06

Cedar 22.13 -180.92 / / / / / 1.68 -173.53

Armandi 36.78 -659.8 115.9 -24689.17 3.65 / / / 1315417.89

Mountain Pine 30.62 -446.9 441.97 -89058.57 / / / -2.12 4495223.28

Chinese Pine 66.65 -1835.12 / 3564.17 1541.2 -100688.81 / 5.03 1274255.21

Keteleeria 27.66 -485.65 3952.86 -803800.14 -8.68 / / -4.5 40875436.88

Camphor 19.77 -187.59 / / 1.83 / / -0.14 -815.57

Phoebe 24.3 -263.16 / / / / / 1.4 183.02

Eucalyptus 18.18 -71.54 -44.41 9369.41 -72.28 4411.34 / -- -561336.58

High mountain Poplar 25.21 -242.97 / / -13.93 847.31 / -3.89 -5704.95

Low, High Mountain Populus 18.95 / / / / / / / -871.2

High Mountain Cedar 27.77 -369.61 -159.31 32406.41 / / / / -1646180.34

Low, High Moutain Cedar 22.37 -211.5 -35.91 7566.31 / / / 1.21 -398222.42

High Moutain Cedar 24.42 -362.14 -181.65 36742.67 115.51 -6768.48 / 4.08 -1763119.14

Low, High Mountain Cedar 23.13 -301.38 / -87.77 -60.85 3753.21 / / -47019.16

High mountain hard broadleaf 13.92 / 29621.07 -6118458.23 -24173.58 1579478.62 / / 290152586

Medium-height mountain hard broadleaf 18.08 -150.63 / / 85.21 / / / -2059.66

Low mountain hard broadleaf 19.7 -133.28 / / / / / -1.68 751.98

High mountain soft broadleaf 31.99 -559.93 / / / / -0.01 34.39 -55578.55

Medium-height mountain soft broadleaf 32.87 -580.84 / / 0.96 / / 1.81 804.53

Low mountain soft broadleaf 38.35 -583.95 -0.37 / / 94.36 / 1.09 3354.75

 

measuring the biomass of shrubs and herbaceous in nearby 122 continuous forest inventory sample plot. fitting and screening the biomass model of undergrowth shrubs and herbs;

undergrowth shrubs: Leaf 

Branch： 

Underground： 

Total： 

 

Under forest plantation：aboveground： 

Underground： 

Total： 

 

Under forest brush and grasses：aboveground： 

Branch： 

Underground： 

 

The Y in the equation stands for biomass（t/ha）； is the plantation average coverage（%）； is the product of brush average altitude (cm) and coverage。

 

（e） Measuring the litter amount of 214 continuous forest inventory sample place, and collecting sample of litter, analyzing the carbon and nitrogen content. Fitting and screening the litter model：

Coniferous forest： 

Mixed Forest 

Deciduous forest ： 

Evergreen broadleaf forests： 

Bamboo forests： 

In the equation, Y stands for litter amount(t/ha)； 、 、 、  seperately stand for the thickness(cm)of litter layer, stand volume（m3/ha）,stand density(plant/ha）and dominate species average（m）。 、 、  seperately stand for longitude, latitude and altitude.

（f） Choosing 21 moso bamboo continuous survey sample place and  37 mixed sample plots，measuring the biomass of each organ of different diameter（taking one to two plants of each sample place in each diameter level with a total of 78 plants and biomass in mixed bamboo sample place. Fitting and screening the best single plant moso bamboo model：

Bamboo pole：  (D stands for diameter)

Bamboo branch： 

Bamboo leaf： 

Bamboo root： 

Since in the forest inventory carried out before 2007, only the number of moso bamboo plants were surveyed and thus there were no single plant measurement data. In the mixed bamboo sample place there were only plants number surveys. Thus we establishing and screening the best regression model of the biomass of bamboo and mixed bamboo Y（t/ha） and the number of plants N（plant/ha）in unit area:

Moso bamboo： 

Mixed bamboo： 

（g） Choosing 8 typical brush species of Sichuan, setting 27 survey sample plots，measuring the biomass and litter amount of each organ，fitting and screening the best regression model of biomass , litter amount (Y) and brush coverage degree(X)：

Brush biomass： 

Brush litter amount： 

（h） While measuring the biomass, litter amount of all standing forests ,bamboo forest, under forest brush and grass, brush, gathering more than 1000 plant sample of different organs, including over 400 tree samples, moso bamboo, 84 moso bamboo samples, some mixed bamboo samples，276 under forest brush samples,186 under forest plantation samples，over 100 brush forest samples，221 litter sample. Carrying out measurement of carbon content.

 

Major Outcome

This project produced a lot of parameters, such as biomass equation, biomass accumulation default equation and litter equation and are directly applied foresting planting carbon sink project methodology approved by National Development and Reform Commission and forests operation carbon sink project methodology adopts also these. Following picture is the screenshot of the methodology of outcomes of this project.