基于蓄积的森林生物量估算方法的对比分析

正森林生物量是指一个森林群落在一定时间内积累的有机质总量,是森林生态系统重要的特征数据,因此世界各国越来越重视对森林生物量的监测与研究[1-3],建立的生物量模型众多[4-6]。大尺度森林生物量监测,是以省、流域、国家乃至全球为对象,在估算方法一致的前提下,对多个时间点的森林生物     

森林生物量的估算方法及其研究进展

总结分析生物量模型(包括相对生长关系和生物量-蓄积量模型)和生物量估算参数这2类常用的生物量估算方法,提出今后我国在森林生物量估算领域的研究重点:1)整合经验相对生长方程;2)系统研究生物量估算参数的规律性及其不确定性;3)构建以传统估算方法和3S技术相结合的生物量估算系统.     

基于GLAS数据的森林生物量估算研究进展

森林生物量是森林生态系统监测的一个重要指标。GLAS波形信息与森林冠层高度、生物量有较强的相关性,在森林冠层高度、生物量等参数估算中具有广阔的应用前景。本文简要介绍了GLAS激光雷达系统及其特点,重点总结归纳了应用GLAS进行森林冠层高度、生物量估算原理及方法,并对森林冠层高度、生物量估算模型作了介绍。     

永平县森林生物量的碳储量初步估算

以云南省永平县的森林资源数据为基础,采用公式:碳储量(C)=林木蓄积湿重×比值×(1-含水率)×含碳率,分别计算林木、林下灌木、林下草本植物、林下凋落物生物量的碳储量,并以2005年为基准年,采用复利公式Cnt=A(1+B)n对永平县2005~2015年森林生物量的碳储量进行了预估.     

河南省杨树人工林生物量研究

利用河南省第7次森林资源连续清查资料,分别采用生物量转换因子法、生物量回归模型法、生物量转换因子连续函数法对河南省杨树人工林生物量进行了估算。经比较模型的适用范围,最终采用生物量转换因子法估算值作为河南省杨树人工林生物量;中、幼林生物量占整个杨树人工林生物量总量的80.47%,表明杨树人工林生物量在各龄组中分布不均衡;河南省杨树人工林生物量总体质量不高,但具有较大发展空间,通过加强杨树人工林的抚育管理措施,对提升整个区域的杨树生物量水平具有重要意义。     

基于森林资源连续清查资料估算的浙江省森林生物量及生产力

基于1994,1999和2004年浙江省森林资源连续清查数据,采用基于生物量与蓄积之间关系的生物量换算因子连续函数法,对浙江省森林生物量和生产力进行估计.结果表明:全省3期森林生物量分别为1.496亿,1.615亿和2.244亿t.林分平均单位面积生产力在1994-1999年间为1.557 t·hm-2a-1,在1999-2004年间为2.060 t·hm-2a-1;浙江省森林资源总量不断增加,但林分质量仍然较低,林分单位面积生物量和生产力都远低于全国平均水平;换算因子连续函数法适合于大尺度森林生物量和生产力估算,但在总体单位蓄积很低的情况下可能导致森林生物量被高估.     

基于森林资源清查资料的盈江县森林生物量和生长量分析

为确定盈江县森林碳储量和碳汇潜力的变化特征及其影响因子,以便更好地分析盈江县森林生物量和生长量。基于盈江县2012年和2017年森林资源清查数据,利用生物量换算因子连续函数法和异速生长方程,评估盈江县森林碳储量和碳汇潜力的变化特征及其影响因子。结果显示：(1)盈江县森林生物量储量丰富,达85.55 t/hm²。其中：栎类林最大,为168.3 t/hm²;核桃林最低,为7.10 t/hm²。(2)不同林龄林分生物量差异较大,近熟林最高,其次分别为中龄林、成熟林、过熟林、幼龄林。(3)常绿阔叶林的林分生长量最大,其次是落叶阔叶林和针叶林。结果表明：盈江县森林生物量储量丰富且以阔叶林为主;林龄和年均气温是影响林分生长和生物量的主要因素。     

黑龙江省西部杨树人工林生物量的估算方法

森林生物量是森林生态系统的最基本数量特征,它既表明森林的经营水平和开发利用的价值,同时也反映森林与其环境在物质循环和能量流动上的复杂关系。生物量数据是研究许多林业问题和环境问题的基础。因而,在当今森林资源监测中,基于全树利用和解决环境问题的需要,将森林生物量作为监测内容已在全球受到普遍关注。因此,森林生物量的测定具有十分重要的理论和实践意义。１　研究方法 本研究所用数据取自大庆市红旗林场的７块标准地。在标准地内每木检尺,测量胸径、树高、冠幅,并按等断面径级标准木法共选取了１４株标准本,以１ｍ区分…     

2060年前我国森林生物量碳库及碳汇潜力预测

【目的】预测研究2060年前我国的森林生物量碳库及碳汇潜力,以期为制定减排增汇政策提供重要依据,为我国获取必要的CO₂排放空间和参与全球气候变化谈判提供参考。【方法】基于全国森林资源清查数据资料,利用Richards生长方程拟合方法,将全国划分为6个区域,每个区域分别建立8～9组主要优势树种（组）的样地公顷蓄积量与林龄的关系模型,并结合我国森林经营规划推算各时期的森林面积,预测2060年前我国的森林（不包括经济林和竹林）蓄积量、生物量碳库和碳汇潜力。【结果】到2030年,我国森林蓄积量将达到204.73亿m³,比2005年增加74.73亿m³; 2060年将达到286.45亿m³。从各区域动态变化来看,西南地区和东南地区是我国未来森林蓄积增长量最快的地方,也是森林质量精准提升潜力最大的地区,分别占2060年全国森林蓄积量的37.68%和21.37%。到2060年,现有森林碳储量将达到12.12 Pg C(Pg=1×10¹⁵g),新造林将再增加碳储量0.92 Pg C,森林生物量...     

基于遥感信息的森林生物量估算研究进展

遥感技术已被广泛应用于植被和生态系统的定量研究中,特别是利用遥感技术快速准确地估算森林生物量已取得了突破性的进展。综述了遥感技术在森林生物量估算中的现状,分析了各种遥感数据源在森林生物量估算中的优缺点,并简要总结了遥感技术在森林生物量估算应用方面的发展趋势。     

Forest biomass and root–shoot allocation in northeast China

Temperate and boreal forests act as major sinks for atmospheric CO₂. To assess the magnitude and distribution of the sinks more precisely, an accurate estimation of forest biomass is required. However, the determinants of large-scale biomass pattern (especially root biomass) are still poorly understood for these forests in China. In this study, we used 515 field measurements of biomass across the northeast part of China, to examine factors affecting large-scale biomass pattern and root–shoot biomass allocation. Our results showed that, Picea & Abies forest and coniferous & broadleaf mixed forest had the highest mean biomass (178–202 Mg/ha), while Pinus sylvestris forest the lowest (78 Mg/ha). The root:shoot (R/S) biomass ratio ranged between 0.09 and 0.67 in northeast China, with an average of 0.27. Forest origin (primary/secondary/planted forest) explained 31–37% of variation in biomass (total, shoot and root), while climate explained only 8–15%, reflecting the strong effect of disturbance on forest biomass. Compared with shoot biomass, root biomass was less limited by precipitation as a result of biomass allocation change. R/S ratio was negatively related to water availability, shoot biomass, stand age, height and volume, suggesting significant effects of climate and ontogeny on biomass allocation. Root–shoot biomass relationships also differed significantly between natural and planted forests, and between broadleaf and coniferous forests. Shoot biomass, climate and forest origin were the most important predictors for root biomass, and together explained 83% of the variation. This model provided a better way for estimating root biomass than the R/S ratio method, which predicted root biomass with a R² of 0.71.     

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.     

Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods

Several studies have reported different estimates for forest biomass carbon (C) stocks in China. The discrepancy among these estimates may be largely attributed to the methods used. In this study, we used three methods [mean biomass density method (MBM), mean ratio method (MRM), and continuous biomass expansion factor (BEF) method (abbreviated as CBM)] applied to forest inventory data to estimate China's forest biomass C stocks and their changes from 1984 to 2003. The three methods generated various estimates of the biomass C stocks: the lowest (4.0–5.9 Pg C) from CBM and the highest (5.7–7.7 Pg C) from MBM, with an intermediate estimate (4.2–6.2 Pg C) from MRM. Forest age class is a major factor responsible for these method-induced differences. MBM overestimates biomass for young-aged forests, but underestimates biomass for old-aged forests; while the reverse is true for MRM. Further, the three methods resulted in different estimates of biomass C stocks for different forest types. For temperate/subtropical mixed forests, MBM generated a 92% higher estimate than CBM and MRM generated a 14% lower than CBM. The degree of the overestimates is closely related with the proportion of young-aged forest within total area of each forest type.     

Estimating forest biomass increment based on permanent sample plots in relation to woodfuel consumption: a case study in Kampong Thom Province,Cambodia

To assess the sustainability of forest use for woodfuel, above ground biomass increment must be examined against woodfuel consumption. However, reliable data on the biomass increment of tropical forests are very limited. In this study, we estimated above ground forest biomass increment in Kampong Thom Province, Cambodia, using two consecutive measurements of 32 permanent sample plots in 1998 and 2000, and forest inventory data of 540 plots collected in 1997. The permanent sampling plot data were used to determine the relationship between initial biomass and subsequent biomass increment over a 2-year period. This relationship was applied to the inventory data to obtain a robust estimate of biomass increment across the major forest types for the entire province. The weighted average annual above ground biomass increment for the whole province was 4.77Mg/ha, or 2.3% of biomass. Woodfuel consumption was estimated to be about 2% of biomass increment for the province, suggesting that deficiency of woodfuel may not occur in this province. However, localized variation needs to be taken into account and there is a need to examine the effects of stand age and factors such as soil type, microtopography, and species composition on biomass increment and to consider woodfuel collection rate in specific forest areas with respect to accessibility for firewood collection.     

中国湿地松立木生物量方程的研建

以我国湿地松154株样木的生物量实测数据为基础,综合利用分段建模方法和非线性误差变量联立方程组方法,建立了与立木材积方程相容的地上生物量方程和生物量转换因子模型,以及与地上生物量方程相容的地下生物量方程和根茎比模型。结果表明:所建地上生物量方程的平均预估误差小于5%,地下生物量方程的平均预估误差小于10%,全树生物量估计的平均预估误差小于3%,完全可满足森林生物量计量的精度要求,从而为我国湿地松林的生物量估计及碳汇能力评估提供了计量依据。     

The realisable potential supply of woody biomass from forests in the European Union

Forests are important for providing wood for products and energy and the demand for wood is expected to increase. Our aim was to estimate the potential supply of woody biomass for all uses from the forests in the European Union (EU), while considering multiple environmental, technical and social constraints.The potential woody biomass supply was estimated for the period 2010-2030 for stemwood, residues (branches and harvest losses), stumps and other biomass (woody biomass from early thinnings in young forests). We estimated the theoretical biomass potential from recent, detailed forest inventory data using the EFISCEN model. Constraints reducing the availability of woody biomass were defined and quantified for three mobilisation scenarios (high, medium, low). Finally, the theoretical potentials from EFISCEN were combined with the constraints to assess the realisable potential from EU forests.The realisable potential from stemwood, residues, stumps and other biomass was estimated at 744 million m³ yr⁻¹ overbark in 2010 and could range from 623 to 895 million m³ yr⁻¹ overbark in 2030, depending on the mobilisation scenario. These potentials represented 50-71% of the theoretical potential. Constraints thus significantly reduced the biomass potentials that could be mobilised. Soil productivity appeared to be an important environmental factor when considering the increased use of biomass from forests. Also the attitude of private forest owners towards increased use of forest biomass can have an important effect, although quantifying this is still rather difficult.The analysis showed that it is possible to increase the availability of forest biomass significantly beyond the current level of resource utilisation. Implementing these ambitious scenarios would imply quite drastic changes in forest resource management across Europe.     

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 for-est 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 spatio-temporal changes of biomass at different spatial scales.The main findings are:(1) the regression relationship between forest biomass and the associated influencing factors at a provincial scale can be applied to estimate biomass at a pixel scale by employing a downscaling method;(2) for-est 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.     

Estimating the quadratic mean diameters of fine woody debris in forests of the United States

Most fine woody debris (FWD) line-intersect sampling protocols and associated estimators require an approximation of the quadratic mean diameter (QMD) of each individual FWD size class. There is a lack of empirically derived QMDs by FWD size class and species/forest type across the U.S. The objective of this study is to evaluate a technique known as the graphical estimation (GE) method for estimating FWD QMDs across forests of the U.S. Results indicate tremendous inter- and intra-specific variation in small FWD diameters. In addition, GE model fitting results demonstrated a lack of substantial difference in FWD QMDs between common forest types. It is postulated that the mixing, fracturing, and decay of both tree and shrub downed woody debris in diverse forest types across the U.S. can homogenate FWD QMDs at state/national levels. In the absence of site-specific empirical measurement of FWD QMDs, it is suggested that a general national set of FWD QMDs derived from the GE method be adopted for large-scale FWD monitoring efforts.     

连云港城市森林分布与优化途径

在深入分析连云港城市森林建设条件与现状特征的基础上,揭示城市发展与城市森林格局和结构的相互关系,针对依山临海和"一市双城"的自然人文特征,依据生态网络理论构建连云港城市森林格局,对照国内外相关研究成果提出城市森林布局优化与建设途径。       

Satellite-based estimation of biomass carbon stocks for northeast China''s forests between 1982 and 1999

Northeast China maintains large areas of primary forest resource and has been experiencing the largest increase in temperature over the past several decades in the country. Therefore, studying its forest biomass carbon (C) stock and the change is important to the sustainable use of forest resources and understanding of the forest C budget in China. In this study, we use forest inventory datasets for three inventory periods of 1984–1988, 1989–1993 and 1994–1998 and NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) data from 1982 to 1999, to estimate forest biomass C stock and its changes in this region over the last two decades. The averaged forest biomass C stock and C density were estimated as 2.10 Pg C (1 Pg = 10¹⁵ g) and 44.65 Mg C ha⁻¹ over the study period. The forest biomass C stock has increased by 7% with an annual rate of 0.0082 Pg C. The largest increase in the C density occurred in two humid mountain areas, Changbai Mountains and northern Xiaoxing’anling Mountains. Climate warming is probably the key driving force for this increase, while anthropogenic activities such as afforestation and deforestation may contribute to variations in the C stocks.